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- Front Matter: Volume 7492
- Applications of Data Fusion to Object Recognition, Classification, and Change Detection
- Data Mining and Knowledge Discovery
- Multi-sensor, Multi-resolution, and Multi-mode Data Fusion
- Spatial Analysis Applications
- Spatial Analysis Models
- Spatial Reasoning
- Spatial Simulation Models
- Spatial-Temporal Applications for Mobile, Wireless, and Location-based Service Networks
- Spatial-Temporal Data Capturing
- Spatial-Temporal Data Modeling
- Visualization of Spatial-Temporal Data
- Web-based Spatial-Temporal Model and Applications
Front Matter: Volume 7492
Front Matter: Volume 7492
Show abstract
This PDF file contains the front matter associated with SPIE
Proceedings Volume 7492, including the Title Page, Copyright
information, Table of Contents, Introduction, and the Conference Committee listing.
Applications of Data Fusion to Object Recognition, Classification, and Change Detection
Study on Land Use Cover Change (LUCC) based on remote sensing and GIS
Show abstract
As a key element for land use cover change research, change detection technique is of urgent demands and has great
potential in scientific applications. Conflation is the process of combining the information from two (or more) geodata
sets to make a master data set that is superior to either source data set in either spatial or attribute aspect. The objectives
of conflation include increasing spatial accuracy and consistency, and updating or adding new spatial features into data
sets. Based on the analysis and summarizations of researched home and aboard, the paper focused on Land Use/Cover
Change detection using feature database of basic types based on vector-image data conflation, that is : Combining of
Land use map and RS image, features(grey feature, texture feature and shape feature) are extracted. This methodology
belongs to "Feature class" of LUCC. It should be pointed out that the researches must be focused on the land use span
other then traditional methods of the pixels. Each spans of T2 will be classified according to the minimum Euclidean
distance to the T2 sample span accepted, and the corresponding land use type will be assigned to the current patch,
Change information are extraction automatically based on Boolean operations. The method is tested on the Quick Bird
images of a district in Wuhan and the precision of the results is high as 92.6% (in urbanization).The experimental results
demonstrate that the proposed method can cut down the computational costs and improve the accuracy.
Comparison of multivariate statistical analysis and fuzzy recognition algorithm for quantitative mapping soil organic matter content with hyperspectral data
Show abstract
The soil organic matter is one of the important criterions of soil fertility. Mapping and dating soil organic matter is of
great importance in soil use and evaluation. In this paper we compare two measures of multivariate statistical analysis
(MSA) and fuzzy recognition algorithm (FRA) for quantitative mapping soil organic matter content using Hyperspectral
remote sensing. This study was tested in Henshan County, northern ShanXi Province of China. On the one hand, the
ratio of the reflectivity reciprocal-logarithm's first derivative of 623.6nm against the reflectivity reciprocal-logarithm's
first derivative of 564.4nm was chosen as the sensitive retrieval parameter and build up the retrieval models. Then, the
best quadratic retrieval model was utilized to map the SOM content by calculating each pixel of Hyperion image, the
adjusted R square coefficient is 0.8684. On the other hand, by analyzing the correlation between spectrally reflective data
and SOM concentrate, the first derivative of logarithmic reflectance at sensitive bands of 393nm, 444nm, 502nm,
1455nm and 1937nm were confirmed as the retrieval indicators due to the notable correlation coefficients. Finally, the
most optimized-retrieval model, utilized to the Hyperspectral data for SOM quantitative mapping, was build up by using
the fuzzy recognition theory. The correlation coefficient of the retrieval model is 0.981. It is found that result of fuzzy
recognition algorithm is better than that of traditionally statistical analysis, with the mean predicted error of 8.43% as
compared to 10.42% for quadratic retrieval model. It is concluded that this fuzzy recognition algorithm for
Hyperspectrally quantitative mapping SOM is available and the result map is reliable and significantly correlative with
known stabilization processes throughout the study area. Moreover, the fuzzy recognition algorithm developed in this
paper could be applied to other domain of quantitative remote sensing.
Application of multi-temporal DEM data in calculating the Earth's surface deformation
Qiuping Lan,
Lifan Fei,
Yining Liu,
et al.
Show abstract
This paper suggests a method of calculating the elevation and the volume change of the terrain based on the multitemporal
digital elevation model (DEM) data sets for the same area. Two methods for calculating the surface change are
introduced: One is based on the regular square grids (RSG), another uses the triangulated irregular network (TIN)
generalized from the original source data by the 3D Douglas-Peucker algorithm so that not only the accuracy of
generalization using 3D Douglas-Peucker is verified, but also the kinds of data formats of DEM for this purpose have
been expanded. Finally, the formulae used by these two methods are introduced, and the experimental results calculated
from the same original DEM data acquired in 1971 and 2000 respectively form the area of Bayanbulak in Xinjiang are
compared. The experiments have shown that the results of the two methods are relatively identical even if under the great
generalization degree of DEM for the second method. Therefore, it shows that the second method can greatly heighten
the efficiency of the calculation while insuring its accuracy.
Fusion of remote sensing images and GIS data for land use/cover change detection
Show abstract
Recently land use/cover change detection (LUCC) has become an important aspect in nature resource and environment
monitoring and protection. A data fusion method for LUCC is presented concerning the situation that there are only the
remote sensing (RS) images of updated period and the land use/cover maps of original period. Firstly, multi-spectral and
panchromatic images of SPOT-5 are fused by using principle component analysis (PCA) algorithm on Erdas Imagine
platform. Then, after the co-registration of the land use/cover map and RS image, the RS image of the updated period is
classified by K-means algorithm and the precise classification chart of the land use/cover is obtained. The land use/cover
map is transformed from vector to raster format and the land class code is used as each pixel's value of the transformed
raster image. Finally, land use/cover changes are found by comparing the corresponding land class codes. The study area
is located in Huangpi District of Wuhan City, and experiments demonstrate the proposed data fusion method for land
use/cover change detection is a feasible resolution.
Semi-automatic typical collieries extraction based on remotely sensed imagery using active contour models
Show abstract
Keeping informed of the collieries exploitation is of great importance for the benefit of our country. Currently, with the
high spatial resolution remotely sensed imagery, we are able to monitor the open air collieries directly without in situ
inspections. This paper presents the application of active contour models(snakes) for semi-automatic extraction of the
contour from the typical collieries in remote sensing images. After carefully examined the characteristics of the
collieries, we improved the active contour model. The boundary of the collieries is not very clearly on the images, and
the influence of the random image noise is extremely large. Therefore, improving the image power of Snake model is
necessary. As the Snake model can only work on panchromatic images, we first fused the multi-spectral image to make
full use of the spectral information contained with in the image. Then we used Canny edge detector which is anti-noise to
extract the features. At the same time, a gauss filter is performed to the edge image to enlarge the envelope of the edge.
We found that the image power calculated from the processed image is more efficient than it from the original image. A
software package build in ArcGIS has been made based on this method.
A data integration index-hiberarchy index tree based on urbanization integration system
Show abstract
Urban information is a kind of multi-sources data, and the variety of these data demands that we should set up an
information system. One of the major tasks is to store massive spatial data and non-spatial data and manage these data
effectively. One of the other major tasks of urbanization integration is how to search for spatial data and non-spatial data
what we need into massive information, so we need to establish indexes for spatial data and non-spatial data and construct
the relation between the two kinds of data in order to convenient query. The paper is focused on data indexes
construction, classified indexes for non-spatial data, R-trees index for spatial data and puts forward an area hiberarchy
index tree to build up direct relationship between spatial data and non-spatial data for seamless queries, and the
experiment shows that the hiberarchy index tree is much validated and something useful is obtained.
Watersheds-based segmentation integrated with edge detection
Show abstract
Image segmentation refers to the process of partitioning a digital image into multiple segments. The goal of segmentation
is to simplify and/or change the representation of an image into something that is more meaningful and easier to analysis
[1]. These advantages of this process make it be widely used to find out the interesting objects in high resolution remote
sensing images. Watershed algorithm is based on the topology of the image, although it can easily split images into
homogenous partitions, it also leads to over-segment in practical implementation. Some solutions were proposed to solve
this problem in the past few years [2][3]. Using pre-defined seeds and extracting the pixels clusters which are grown from
these seeds is a reasonable method to overwhelm the obscure of over-segmentation.
In this paper; we present a novel framework to improve the results of watersheds segmentation by using edge detection
to find out the position of seed points. Then the immersion simulations suggested by Vicent has been used to segment the
image. The algorithm consists of four steps: a) Edge detection with embedded confidence, b) Thinning processing on the
previous results, c) Label the seed points on each side of the thinned edges, d) Detection of watersheds on gradient
magnitude image using immersion simulations.
At last, we use high resolution remote sensing image to qualify the framework and the experimental results are presented.
It shows that reasonable results which preserve the edge could be gotten by applying this framework.
Data Mining and Knowledge Discovery
One new method for road data shape change detection
Luliang Tang,
Qingquan Li,
Feng Xu,
et al.
Show abstract
Similarity is a psychological cognition; this paper defines the Difference Distance and puts forward the Similarity
Measuring Model for linear spatial data (SMM-L) based on the integration of the Distance View and the Feature Set
View which are the views for similarity cognition. Based on the study of the relationship between the spatial data change
and the similarity, a change detection algorithm for linear spatial data is developed, and a test on road data change
detection is realized.
Double-line river axis extraction based on Delaunay triangulation
Haiyong Li,
Lihong Shi
Show abstract
In the geospatial data processing and GIS analysis applications, extracting the axis of the double-line river is an
important part of graphic generalization. At first, this paper introduces the principle of Delaunay triangulation and the
extraction principle of the triangulation skeleton line. On the bases of these principles, it puts forward the method which
is about extracting the double-line river axis based on the principle of Delaunay triangulation. The method is different
from other methods of extracting the axis of the double-line river which deal with polygon objects, but adopts the bank
lines as the treatment object. This method uses the simple line objects instead of the polygon objects whose data structure
is more complex. Therefore, in data processing, the procedure complexity is reduced greatly. And it enhances the
operability of the treatment process. The experiments show that the method can extract the double-line river axis
perfectly and quickly. The method is highly effective and easy to maintain the topological relationships.
Study of RS data classification based on rough sets and C4.5 algorithm
Show abstract
The classification by extracting of remote sensing (RS) data is the primary information source for GIS in land
resource application. Automatic and accurate mapping of region LUCC from high spatial resolution satellite image
is still a challenge. The paper discussed remote sensing image data classification techniques based on C4.5
algorithm and rough sets and the combination of C4.5 algorithm and rough sets. On the basis of the theories and
methods of spatial data mining, we improve the classification accuracy. Finally validates its effectiveness taking a
test area as example. We took the outskirts of Fuzhou with complicated land use in Fujian Province as study area.
The classification rules are discovered from the samples through decision tree C4.5 algorithm, Rough Sets and both
with together, which integrates spectral, textural and the topography characters. And the classification test is
performed based on these rules. The traditional maximum likelihood classification is also compared to check the
classification accuracy. The results have shown that the accuracy of classification based on knowledge is markedly
higher than the traditional maximum likelihood classification. Especially the method based on combine Rough Sets
and decision tree C4.5 algorithm is the best.
Registration of multi-view point clouds based on nonlinear correction
Yunlan Guan,
Xiaojun Cheng,
Guigang Shi,
et al.
Show abstract
Terrestrial laser scanning is a new technology uprising in 1990's. Owing to its ability to obtain a large number of 3D
coordinates of points, called point clouds, in real time, it has been attracted attentions of surveying field. To build threedimensional
models, multiple scans from different viewpoints are required due to occluded surfaces and limited field of
view of the scanner. These multi-view point clouds then must be transformed into a common reference frame in order to
describe complete object being researched. This process is called registration of point clouds. Pairwise registration often
is a common method for registration of multi-views point clouds. Owing to characteristics of error accumulation and
propagation, using pairwise registration method will result in severely distortion of researched object. In order to
overcome this shortcoming, we present a new registration method. Firstly, we use pairwise registration method to
calculate transformation parameters of adjacent two scans, and by selecting coordinate system of first scan as a uniform
coordinate system, we connect all point clouds into a loosely network. Secondly, according to condition that common
points between first scan and last scan must have the same coordinates in uniform system, we use nonlinear correction
model to compute the distortion parameters of loosely network and lastly we correct distortion of each single point
clouds and determine the best position of each point. Experiment is carried out and the results show that the registration
error has reduced from 1.7cm to 5mm after correction, which demonstrates correctness of the method.
Grassland change in west Northeast China plain from SPOT-VEGETATION time series data analysis
Fang Huang,
Ping Wang
Show abstract
The grassland ecosystems in west Northeast China plain are sensitive indicators of environmental impacts from both
climate change and direct human activities. NDVI imagery over each ten-day period in the past ten years was calculated
based on the VGT sensor. The Maximum Value Composites method, annual average value, monthly average value and
difference value of two indices were used to analyze the inter-annual changes of vegetation cover. Linear trends could be
detected in the NDVI time series that differ by season. We pointed that grassland cover in this area decreased with an
obvious undulating trend during 1998-2007. The yearly maximum NDVI mean over the study area decreased from 0.644
in 1998 to 0.615 in 2007 indicated the decreasing trend of grassland activity. There was a significant decrease of monthly
maximum NDVI in spring and early summer months, while positive NDVI trends were described for autumn. The
degraded vegetation area occupied about 20.29% of the whole study area, while vegetation in some area was increase
taking up 16.03%. Precipitation and temperature had different effect on yearly maximum NDVI of grassland in this
semi-arid region. Grassland degradation may be explained by the duration and severity of drought.
Automatic detection on LUCC based on SIFT
Show abstract
Land use cover change (LUCC) provide important information for environmental management and planning. It is one of
the most prominent characteristics in globe environment change, and not only limited by natural factor, but also affected
by the factor of social, economics, technique and histories. Traditionally, field surveys of land cover and land use are
time consuming and costly and provide tabular statistics with out geographic location information. Remote sensing and
GIS are the most modern technologies which have been widely used in the field of natural resource management and
monitoring. Change detection in land use and updating information on the distribution and dynamics of land use have
long term significance in policy making and scientific research. In this paper, we use multistpectral images of Spot period
two different of time 2002 and 2007 for detection on LUCC base on Scale Invariant Feature Transform (SIFT) method.
An automatic image matching technique based on SIFT was proposed by using the rotation and scale invariant property
of SIFT. Keypoints are first extracted by searching over all scales and image locations, then the descriptors defined on
the keypoint neighborhood are computed. The proposed algorithm is robust to translation, rotation, noise and scaling.
Experimental results, urban is the most part of Huangpi area which have been changed.
Some critical issues on airborne LIDAR mapping software in coastal survey
Show abstract
Airborne LIDAR is one of the most effective and reliable means of coastal survey. Using LIDAR data for coastal
survey is becoming a standard practice in spatial related areas. However, the effective processing of the raw LIDAR data,
the generation of an efficient and high-quality DEM and feature extraction remain big challenges. This paper reviews
some critical issues on the LIDAR data pre-processing, removing and separating the LIDAR data, mainly including the
following: How to extract and classify the buildings, vegetation, roads and the other objections and afterward having
some discussions on the image registration and multi-source data fusion.
Application potential of differential SAR interferometry in land subsidence spatial-temporal data capturing
Zhaoquan Huang,
Le Yu,
Fan Wang
Show abstract
Three Differential Synthetic Aperture Radar Interferometry (D-InSAR) methods are compared on the capability of
obtaining land subsidence temporal data. These three methods including, Interferograms time-series stacking, Permanent
Scatters D-InSAR(PS-InSAR) and Multi-Baseline D-InSAR are all base on interferometry phase spatial-temporal
analysis to increase reliability. They are used to extract land subsidence mean velocity from time serial SAR images in
nearly two years. Experimental results are compared by data source quality requirement, extracted data density and
precision and then evaluated their applicability. The results show that though these D-InSAR methods limited by sensor
restriction, baseline decorrelation and atmosphere affect, they could get reliable mean velocity distribution of land
subsidence from difficult condition by careful selection of data source and methods.
Application of high-resolution RS image in settlement extraction
Show abstract
Popularity of high resolution image makes it possible to interpret the internal land use condition within settlement. The
categorization of settlement is firstly made as rural (mountain, plain) and urban (city village, living block) areas. Then
object-based and generic network image processing methods are primarily used in the extraction from the merged
Quickbird and SPOT high resolution image. With mathematical as well as geometrical model, indices such as building
density, floor area ratio, green ratio and space ratio are extracted accordingly. Meanwhile, land use map, field survey
and cadastral map are employed for the estimation and accuracy assessment. In the end, analysis and comparison are
made for land use condition within settlement.
Using LIDAR data and airborne spectral images for urban land cover classification based on fuzzy set method
Show abstract
In this paper, we propose an analysis on the combinative effect of high-resolution airborne image and light
detection and ranging (LIDAR) data for the classification of complex urban areas. In greater detail, the proposed
system is composed of three models briefly. Model one includes an advanced kernelized fuzzy c-means
classification method for high-resolution airborne image. The characteristics of LIDAR point cloud are introduced in
model two, membership degree function of buildings, vegetations and naked land have been built. In model three,
high-resolution image and elevation data form LIDAR point cloud are jointed. Experiment carried out on a complex
urban area provide interesting conclusions on the effectiveness and protentialities of the joint use of high-resolution
image and LIDAR data. In particular, the elevation data was very effective for the separation of species with similar
spectral signatures but different elevation information. Experimental results approve that elevation data can improve
classification accuracy in building occupied area obviously.
Construction of aided design system of land consolidation planning on platform extended graph-element
Li Liu,
Fengya Zou,
Yu Zhou
Show abstract
According to the actual situation of aided design system of land consolidation, the shortcomings of the traditional aided
design software of land consolidation are concluded in the paper. And with the development of the technology of the
computer aided design and software, the aided design system of land consolidation on the platform extended
graph-element, which adopts the mature and advanced technologies of extended graph-element as well as parametric
design, and displays geospatial phenomenon to the users by the interactive design technology with CAD, is constructed
to improve the speed and quality of the design. Considering about the main problems of the current land consolidation
aided design, following the practical and systematic design idea, functional modules of the land consolidation aided
design are constructed, and the composition and the working process of each function module is described in details.
Study on the methods of retrieving urban winter LST based on the Landsat TM 6
Jingjing Zhao,
Liang Pei,
HuiPing Huang,
et al.
Show abstract
Presently, there are three methods of retrieving land surface temperature based on TM thermal
infrared band (band 6). These methods are: the Radiative transfer equation (RTE), the Mono-window
algorithm and the General single channel algorithm. Due to the general unavailability of situatmospheric
profile data, the RTE method is seldom applied. Though the other two methods are
relatively widely researched, the fields are almost limited on the urban hot island study by retrieving
hot seasonal temperature. With the increasing emphasis of city energy saving in China and the
increasing heating energy consumption, more researchers are beginning to study the construction of
city buildings and hot diffusion in winter with remote sensing methods. In order to judge which one
of the other two LST retrieval methods is optimal to retrieve cold seasonal temperature, this paper
focuses on the retrieval of cold seasonal LST from the Landsat TM6 data. This data was captured on
4th Jan 2007 over the Xi Cheng District in Beijing by using the Mono-window algorithm and the
General single channel algorithm. The results indicate that, both methods can produce a similar LST
spatial distribution. However, with the higher relative precision, the Mono-window algorithm proved
to be more suitable than the General single channel algorithm to this research area. Furthermore, the
author presents some suggestions on the choice of winter temperature LST methods.
A review of remote-sensing-based spatial/temporal information capturing for water resource studies in Poyang Lake
Show abstract
Remote sensing techniques have been widely applied to capture spatial/temporal information for water resource
studies and they provide great useful information for keeping the managements and sustainable developments of
aquatic ecosystems. Poyang Lake, the largest freshwater lake in China, is located at the southern bank of the middle
Yangtze River, and the high water quality makes it an important international wetland, allowing its ecosystem to
provide significant benefits to the society. This paper aims to review recent applications of remote sensing techniques
on capturing spatial/temporal information for water resource studies in Poyang Lake. The Poyang Lake and remote
sensing techniques are briefly introduced first. Then the applications of remote sensing techniques on the studies of
water level, water area, flooding disaster, water quality (e.g. water clarity and suspended sediment concentration) and
eutrophication of Poyang Lake are reviewed. Finally some potential applications of remote sensing techniques on
Poyang Lake and conclusion are summarized. It is hoped that this paper might provide necessary and integrated
information for the researchers to understand the applications of remote sensing techniques in the water resource studies and to establish foundation for their further studies in Poyang Lake.
Feasibility of estimating heavy metal concentrations in water column using hyperspectral data and partial least squares regression
Yiyun Chen,
Yaolin Liu,
Dun Wang,
et al.
Show abstract
Mining and smelting often produce acidic wastes that can cause severe biogeochemical changes downstream from these
mines. Dexing copper mine, as the largest open cast mine in China, is connected to Poyang Lake by Le An river. Water and
spectra samples were taken from Le An River and two of its branches, and afterward the concentrations of Cd, Cu, Pb and
Zn were measured in the lab. Different spectral pre-processing methods were applied to the spectra, including
Savitzky-Golay spectral smoothing, SNV, first derivative, second derivative spectral transforming. On the purpose of
estimating metal concentrations from differently pre-processed spectra, partial least squares regression was then used in
model calibrations. For deciding the optimal number of PLS factors included in the PLS model, the model with the lowest
root mean square error of validation is chosen. The coefficient of determination (R2v) between the predicted and the
reference values from the test set are used as an evaluation mean. For estimating Pb concentration, R2v = 0.915, which is
acceptable. For Cd concentration, R2v = 0.697 and 0.683 for Zn. PLS model seems to failed in estimating Cu concentration,
for the best R2v for PLS model of Cu is lower than 0.5. From the aspects of spectral pre-processing methods, first derivative
after Savitzky-Golay smoothing performs superior to others. In conclusion, PLS models based on carefully pre-processed
hyperspectral data turn out to be a promising solution for detecting certain heavy metals concentrations in river.
Land use classification and evaluation of RS image based on cloud model
Xiangyun Tang,
Keyun Chen,
Yangfang Liu
Show abstract
The traditional land use classification technology of remote sensing(RS) image is in a low level of automation and
intelligence,land use classification of RS image is an uncertain problem which contains random and fuzziness,the cloud
model integrates fuzziness and random together,constituting mapping between qualitative and quota. According to the
above,this article introduces the cloud theory into land use classification of RS image,establishing a cloud mapping
space based on gradation,aiming to solve the problem of land use classification of RS image. At the same time,this paper
has constituted the result evaluating indicator system in aspect of the homogeneity indexes of the region and the
boundary location,and has carried on the empirical analysis of the SPOT image of Nanhu area of Wuhan,elaborated the
model construction process in depth,explored the serviceability of this method in this domain by the evaluation and the
contrast of the classification results.
Multi-sensor, Multi-resolution, and Multi-mode Data Fusion
A design of context-sensitive web map service
Tao Liu,
Jing Tang,
Qingyun Du,
et al.
Show abstract
Context-Sensitive, also known as context-aware, is a new computing model which taking people as a dominant
factor, it requires the computing devices can detect the user's context information to adjust the system's behavior. Web
Map Service (WMS) is a GIS (Geography information system) specification which is established by the OGC in
accordance with the development of Web Service technology. In order to make the map services more user-friendly and
get better user experience, our works are people-oriented and dynamically provide corresponding map services on the
basis of the user's context information.
In this paper we address an architecture of web map service which concentrates on context-sensitive. It can convert
varies user's context information to different kinds of parameters, about the visualization of geographic data, to get
variable map images in response to the users' context., and finally realizes providing context-sensitive Web Map Service.
Spatio-temporal data dynamic visualization based on temporal tree structure
Show abstract
This paper reviews the characteristics of spatio-temporal data and existing techniques for visualizing them, and then
proposes a temporal tree structure which used to record and manipulates spatio-temporal object's predecessors and
successors for the data source of dynamic visualization by algorithms of multi-temporal vector data correlation. Then,
dynamic visualization methods of geometry shape and thematic were proposed with the support of temporal tree
structure and case study were used to verify the methods proposed. The results and conclusion show that our method of
dynamic visualization is an effective and generic way to implement dynamic modeling and visualization processes of
spatio-temporal objects with various states along time.
Research on scene organization of process simulation in port 3D GIS
Jing Ding,
Wenping Jiang
Show abstract
At present, the application of three-dimensional GIS becomes more and more widespread gradually, but due to the
defect of representing time, four-dimensional GIS based on spatial-temporal expression is facilitated to emerge and
progress. Combined with developing the 3D dynamic demonstration of Tianjin center fishing port, this paper
researches the mass data and animated simulation of building process and provides an approach that the data is dealt
with in the way just as 2D map does such as classification and partition to get clarified data. At the same time, a scene
integration method is proposed by dividing a large-scale 3D scene to several sub-scenes with a number of levels and
various covering areas. And through editing and synthesizing the commentary, time axis and flight routes, the dynamic
simulation and automatic demonstration are achieved. Based on the study above, a system of simulating and
illustrating the port building process is designed and implemented.
A hybrid 3D spatial access method based on quadtrees and R-trees for globe data
Jun Gong,
Shengnan Ke,
Xiaomin Li,
et al.
Show abstract
3D spatial access method for globe data is very crucial technique for virtual earth. This paper presents a brand-new
maintenance method to index 3d objects distributed on the whole surface of the earth, which integrates the 1:1,000,000-
scale topographic map tiles, Quad-tree and R-tree. Furthermore, when traditional methods are extended into 3d space, the
performance of spatial index deteriorates badly, for example 3D R-tree. In order to effectively solve this difficult
problem, a new algorithm of dynamic R-tree is put forward, which includes two sub-procedures, namely node-choosing
and node-split. In the node-choosing algorithm, a new strategy is adopted, not like the traditional mode which is from top
to bottom, but firstly from bottom to top then from top to bottom. This strategy can effectively solve the negative
influence of node overlap. In the node-split algorithm, 2-to-3 split mode substitutes the traditional 1-to-2 mode, which
can better concern the shape and size of nodes. Because of the rational tree shape, this R-tree method can easily integrate
the concept of LOD. Therefore, it will be later implemented in commercial DBMS and adopted in time-crucial 3d GIS
system.
Research on visualization of main tourist areas in Hubei province based on Google Earth
Show abstract
The travel craze in China has become one of the largest sources of expenditure increases. However, the limited
patterns of information demonstration hindered the availability of necessary information to the public as well as the
decision makers. Google Earth provides a useful platform for integrating environmental information with
geospatial data from different sources. Using KML files, various environmental data may be viewed in Google
Earth. In this paper, Google Earth is used as basic GIS platform. Placemarks of main tourist areas of Hubei
Province are made and loaded by KML. The most up-to-date information is released using text, picture and video
in HTML files. This approach transformed the traditional two-dimension travel information system into
multi-dimensional information platform, facilitating data updating and information sharing over the Internet. It
would also help decision making of the government and promote information availability to the public.
Spatial information mining and visualization for Qinghai-Tibet Plateau's literature based on GIS
Show abstract
The subject intersection becomes a hot research topic recently. This paper tried to couple the Bibliometrics and
Geographical Information System (GIS) technologies for studying on the spatial information mining and visualization
from the Qinghai-Tibet Plateau's literature. All the literatures about Qinghai-Tibet Plateau research were indexed in the
ISI Web of Knowledge. The statistical tables about the authors were extracted from the papers by using the method of
bibliometrics. The spatial information of the author's countries was linked with the GIS database. The spatial distribution
was presented by the format of maps based on the GIS technologies. Comparing with the regular presentation forms of
the bibliometrical analysis, the spatial distribution maps can afford more abundant and intuitive senses for the users.
Historical relics visualization by fusing terrestrial laser point-clouds and aerial orthophoto
Li Yan,
Xu Zhao,
Xin Xiang,
et al.
Show abstract
There are many large-scale historical relics in China's stone-desert district, all this sorts relics are threatening by
wind deflation. For documenting the cultural heritage in detail and avoiding a long working time in formidable desert
conditions, we need an accurate and fast way to record the relics' 3D information. Laser scanners offer various
applications on conservation of cultural heritage in recent years, such as static surveying, precise modeling and
visualization for data acquiring purpose. Point clouds generated by terrestrial laser scanner and aerial image both are
valuable data sources for the reconstruction of objects'3D models. This study exploits an approach for recording relic's
datum by long-range terrestrial laser scanner (Optech ILRIS-3D) and fusing the scan data with gray information for
visualization tasks. As a result of obtaining full scene needs several scans, we transform every scan individually into one
global reference frame for decreasing the accumulative errors of point-clouds registration of common ICP approaches,
and build 3D point-clouds model of historical relics by this way. For the purpose to add texture information on the
point-clouds model, we consider using the approach by fussing the corresponding aerial orthophoto with the model
because the objects have very similar texture information in desert. Results show its efficiency and feasible.
Visualization of spatial-temporal data based on 3D virtual scene
Xianghong Wang,
Jiping Liu,
Yong Wang,
et al.
Show abstract
The main purpose of this paper is to realize the expression of the three-dimensional dynamic visualization of spatialtemporal
data based on three-dimensional virtual scene, using three-dimensional visualization technology, and
combining with GIS so that the people's abilities of cognizing time and space are enhanced and improved by designing
dynamic symbol and interactive expression. Using particle systems, three-dimensional simulation, virtual reality and
other visual means, we can simulate the situations produced by changing the spatial location and property information of
geographical entities over time, then explore and analyze its movement and transformation rules by changing the
interactive manner, and also replay history and forecast of future. In this paper, the main research object is the vehicle
track and the typhoon path and spatial-temporal data, through three-dimensional dynamic simulation of its track, and
realize its timely monitoring its trends and historical track replaying; according to visualization techniques of spatialtemporal
data in Three-dimensional virtual scene, providing us with excellent spatial-temporal information cognitive
instrument not only can add clarity to show spatial-temporal information of the changes and developments in the
situation, but also be used for future development and changes in the prediction and deduction.
Virtual-real spatial information visualization registration using affine representations
Show abstract
Virtual-real registration in Outdoor Augmented Reality is committed to enhance user's spatial cognition by overlaying
virtual geographical objects on real scene. According to analyze fiducial detection registration method in indoor AR, for
the purpose of avoiding complex and tedious process of position tracking and camera calibration in traditional
registration methods, it puts forward and practices a virtual-real spatial information visualization registration method
using affine representations. Based on the observation from Koenderink and van Doorn, Ullman and Basri in 1991 which
is given a set of four or more non-coplanar 3D points, the projection of all points in the set can be computed as a linear
combination of the projection of just four of the points, it sets up global affine coordinate system in light of world
coordinates, camera coordinates and virtual coordinates and extracts four feature points from scene image and calculates
the global affine coordinates of key points of virtual objects. Then according to a linear homogeneous coordinates of the
four feature point's projection, it calculates projection pixel coordinates of key points of virtual objects. In addition, it
proposes an approach to obtain pixel relative depth for hidden surface removal. Finally, by a case study, it verifies the
feasibility and efficiency of the registration methods. The method would not only explore a new research direction for
Geographical Information Science, but also would provide location-based information and services for outdoor AR.
Visualization analysis of multivariate spatial-temporal data of the Red Army Long March in China
Ding Ma,
Zhimin Ma,
Lumin Meng,
et al.
Show abstract
Recently, the visualization of spatial-temporal data in historic events is emphasized by more and more people. To provide
an efficient and effective approach to meet this requirement is the duty of Geo-data modeling researchers. The aim of the
paper is to ground on a new perspective to visualize the multivariate spatial-temporal data of the Red Army Long March,
which is one of the most important events of the Chinese modem history. This research focuses on the extraction of
relevant information from a 3-dimensional trajectory, which captures object locations in geographic space at specified
temporal intervals. However, existing visualization methods cannot deal with the multivariate spatial-temporal data
effectively. Thus there is a potential chance to represent and analyze this kind of data in the case study. The thesis
combines two visualization methods, the Space-Time-Cube for spatial temporal data and Parallel Coordinates Plots
(PCPs) for multivariable data, to develop conceptual GIS database model that facilitates the exploration and analysis of
multivariate spatial-temporal data sets in the combination with 3D Space-Time-Path and 2D graphics. The designed
model is supported by the geo-visualization environment and integrates diverse sets of multivariate spatial-temporal data
and built-up the dynamic process and relationships. It is concluded that this way of geo-visualization can effectively
manipulate a large amount of distributed data, realize the high efficient transmission of quantitative and qualitative
information and also provide a new research mode in the field of the History of CPC and military affairs.
Use of Google SketchUp to implement 3D spatio-temporal visualization
Linhai Li,
Lina Qu,
Shen Ying,
et al.
Show abstract
Geovisualization is an important means to understand the geographic features and phenomena. Urban space, especially
buildings, keeps changing with social development. However, traditional 2D visualization can only represent the plane
geometric description, which is unable to support 3D dynamic visualization. Only with 3D dynamic visualization can the
buildings' spatial morphology be exhibited temporally, including buildings' creation, expansion, removing, etc. But these
buildings' changes are impossible to be studied in traditional 2D and 3D static visualization systems. As a result, it
becomes urgent to find an effective solution to implement 3D spatial-temporal visualization of buildings. Inspired by 2D
spatial-temporal visualization methods, like snapshot and event-based spatio-temporal data model(ESTDM), we propose
a new data model called Spatio-Temporal Page Model(STPM) and implement 3D spatial-temporal visualization in
Google SketchUp based on STPM. This paper studies 3D visualization of real estate focusing on its spatio-temporal
characteristics. First of all, 3D models are built for every temporal scenario by the Google SketchUp. And every
Geo-object is identified by a unique and permanent ObjectID, the linkage of Geo-objects between different time spots.
Then, each temporal scenario is represented as page. After having the page series, finally, it is possible to display its
spatial-temporal changes and create an animation. Underlying this solution, we have built a prototype system on part of
real estate data. It is proven that users are able to understand clearly the real estate's changes from our prototype system.
Consequently, we believe our method for 3D spatial-temporal visualization definitely has many merits.
Research for 3D visualization of Digital City based on SketchUp and ArcGIS
Hanwei Xu,
Rami Badawi,
Xiaohu Fan,
et al.
Show abstract
The visualization of 3D city information is the precondition and foundation to construct Digital City and the
uniformity of 2D and 3D GIS platforms to make the Digital City more widely applicable. This article firstly analyzes
some kinds of 3D visualization software. Secondly, using the Google SketchUp and ArcGIS as examples and discuss the
3D visualization of city information and modeling, and lastly, carrying out research on the 3D model construction
process.
Quadtree of TIN: a new algorithm of dynamic LOD
Junfeng Zhang,
Lifan Fei,
Zhen Chen
Show abstract
Currently, Real-time visualization of large-scale digital elevation model mainly employs the regular structure of GRID
based on quadtree and triangle simplification methods based on irregular triangulated network (TIN). TIN is a refined
means to express the terrain surface in the computer science, compared with GRID. However, the data structure of TIN
model is complex, and is difficult to realize view-dependence representation of level of detail (LOD) quickly. GRID is a
simple method to realize the LOD of terrain, but contains more triangle count. A new algorithm, which takes full
advantage of the two methods' merit, is presented in this paper. This algorithm combines TIN with quadtree structure to
realize the view-dependence LOD controlling over the irregular sampling point sets, and holds the details through the
distance of viewpoint and the geometric error of terrain. Experiments indicate that this approach can generate an efficient
quadtree triangulation hierarchy over any irregular sampling point sets and achieve dynamic and visual multi-resolution
performance of large-scale terrain at real-time.
Computation of hillshade values considering diffuse radiation condition
Qingzhou Luo,
Yechao Yan,
Shuping Yue
Show abstract
There is no direct solar irradiance in shadow area. The terrain information of shadow area is often neglected in
preceding researches for that hillshade values are calculated only by direct solar irradiance. In this paper, a model
simulating hillshade values in natural environment based on the total irradiance which consists of direct solar irradiance
and diffuse sky irradiance are developed. According to isotropic model of diffuse sky radiation, the author provides a
formula to calculate the illumination of diffuse sky irradiance. The relative hillshade values can be calculated according
to solar position and the ratio of diffuse irradiance to total irradiance on horizontal surface. This research shows the new
method is more suitable to express topographic information in complex terrain areas.
Spatial-temporal variations of evapotranspiration in the upper Huaihe River basin
Show abstract
Evapotranspiration, which is an important component of water cycle, is a critical variable in determination of
local water resources available. This paper selected the upper Huaihe River as case study site. The daily
reference evapotranspiration was computed by the Penman-Monteith method, and then the mean annual
reference evapotranspiration (ETref), the decadal average values of annual ETref and the decadal average
values of annual seasonal ETref were calculated and mapped. The results revealed that the spatial distribution
of mean annual ETref was uneven with a clearly decreasing gradient in the mean annual ETref from the east to
the west; The spatial and temporal distribution of decadal average values of annual ETref varied with decades
and from 1960s to 1980s , there existed a decreasing trend with an increasing trend from 1980s to 1990s; The
spatial and temporal distribution of decadal averages of annual seasonal ETref varied with seasons and
decades. The decadal average in spring decreased with decades, while the value in summer had a decreasing
trend from 1960s to 1980s with an increasing trend in 1990s compared with 1980s, and the decadal averages
both in autumn and winter increased from 1960s to 1970s then decreased in 1980s with an increasing trend in
1990s compared with 1980s. The output of this paper provides a valuable reference for the forecast of future
water resource available and the sustainable development and utilization of water resources in the Huaihe
river basin.
A 3D data model for fast visualization
Show abstract
3D data model is an indispensable component to any 3D GIS, and forms the basis of 3D spatial analysis and
representation. And now, plenty of representative 3D data models are proposed. However, existing models just take the
theoretic 3D formal representation and the topology between objects into account, and neglect the display result and the
consumption of storage space. Based on the review of existing three-dimensional (3D) GIS data model, a 3D surface
model is proposed for fast visualization in this paper, which is composed of node, segment and triangle. Secondly, data
structure and formal representation of 3D surface model is developed to construct and store data of 3D model. In order
to compare this 3D surface model with other 3D data model, the building models in an experimental area are
reconstructed and stored by the 3D surface model. The result demonstrates that the newly proposed 3D surface model is
superior to the existing data model in terms of data volume, moreover, it can acquire fast visualization speed.
Research on symbolization of urban topographic features in ArcGIS
Xiaolan Xu,
Lianying Li,
Hanwu Li,
et al.
Show abstract
Map symbol is a basic means that represents spatial data. As a significant tool of information representation and transfer,
it has an important role for map display and output. ArcGIS is a GIS platform with strong functions, but its embedding
symbol libraries, ESRI.Style files ,are not conform to Chinese map standard, thus can't meet the demand of map display
and output for Chinese urban fundamental GIS. On the basis of ArcEngine map output modules this article elaborates
classification of topographic feature, design and construction of map symbol library and map symbolization in large
scaled GIS, so as to provide technical experiences for related applications and improve the efficiency of system
developing.
Spatial Analysis Applications
A prototype system based on visual interactive SDM called VGC
Zelu Jia,
Yaolin Liu,
Yanfang Liu
Show abstract
In many application domains, data is collected and referenced by its geo-spatial location. Spatial data
mining, or the discovery of interesting patterns in such databases, is an important capability in the
development of database systems. Spatial data mining recently emerges from a number of real
applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis,
road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and
complicated problems. For spatial data mining of large data sets to be effective, it is also important to
include humans in the data exploration process and combine their flexibility, creativity, and general
knowledge with the enormous storage capacity and computational power of today's computers. Visual
spatial data mining applies human visual perception to the exploration of large data sets. Presenting data
in an interactive, graphical form often fosters new insights, encouraging the information and validation of
new hypotheses to the end of better problem-solving and gaining deeper domain knowledge. In this paper a
visual interactive spatial data mining prototype system (visual geo-classify) based on VC++6.0 and
MapObject2.0 are designed and developed, the basic algorithms of the spatial data mining is used decision
tree and Bayesian networks, and data classify are used training and learning and the integration of the two
to realize. The result indicates it's a practical and extensible visual interactive spatial data mining tool.
Application of data mining in science and technology management information system based on WebGIS
Xiaofang Wu,
Zhiyong Xu,
Shitai Bao,
et al.
Show abstract
With the rapid development of science and technology and the quick increase of information, a great deal of data is
accumulated in the management department of science and technology. Usually, many knowledge and rules are
contained and concealed in the data. Therefore, how to excavate and use the knowledge fully is very important in the
management of science and technology. It will help to examine and approve the project of science and technology more
scientifically and make the achievement transformed as the realistic productive forces easier. Therefore, the data mine
technology will be researched and applied to the science and technology management information system to find and
excavate the knowledge in the paper. According to analyzing the disadvantages of traditional science and technology
management information system, the database technology, data mining and web geographic information systems
(WebGIS) technology will be introduced to develop and construct the science and technology management information
system based on WebGIS. The key problems are researched in detail such as data mining and statistical analysis. What's
more, the prototype system is developed and validated based on the project data of National Natural Science Foundation
Committee. The spatial data mining is done from the axis of time, space and other factors. Then the variety of knowledge
and rules will be excavated by using data mining technology, which helps to provide an effective support for decisionmaking.
Obstacle constraint spatial clustering
Yuan-ni Wang,
Fu-ling Bian
Show abstract
Constraints in the real world must be seriously considered in the process of spatial clustering. In this paper we study
the spatial clustering issue in the presence of obstacles. The cluster algorithm is based on the K-medoid algorithm, and
an improved algorithm Guo Tao is introduced to obtain the distance of spatial objects in the presence of obstacles. It is
more efficient for small and medium-sized data through theoretical analysis. The experiments results prove that the
algorithm is feasible.
Data mining based on spectral and spatial features for hyperspectral classification
Show abstract
Hyperspectral remote sensing technique provides fine and detailed spectral information by contiguous and narrow
spectral channels. For the traditional classification algorithms, most of them are based on spectral information; spatial
information which is useful for the hyperspectral data analysis is paid a little attention to. So, hyperspectral image
classification based on effective combination of spectral and spatial information needs further investigation. In this paper
a new classification method for hyperspectral remote sensing is proposed in order to mine spatial information which
hidden in the image. Firstly, some spectral features which are statistics indexes (MinBand, MaxBand, AvgBand, StdBand,
etc.) are extracted from OMIS image data. Secondly, spatial structure information and spatial information such as Area,
Length, Compact, Convexity, Solidity, Roundness, and so on are extracted. Then the spectral and spatial attributes are
computed and used for the following classification. Lastly, several kernel functions which using joint spectral and spatial
information such as Linear, Polynomial, Radial Basis Function (RBF) and Sigmoid kernel are adopted for SVM
classification model. The experiments proved that the classification algorithm which joint spectral and spatial
information can work more effectively compared to the traditional classification methods, and this new approach is
useful for hyperspectral classification and imaging analysis, and has the potential ability in hyperspectral remote sensed
data processing.
Predicting methods of construction land demand and application in county's general land use planning
Show abstract
China faces a serious problem is that dramatic expansion of construction land cause largely reduction of cultivated
land. To control the scale of construction land is the focus of land use and planning management work, whose core is
land use control, and how to forecast the quantity of construction land scientifically, reasonably and correctly is an
important content in general land use planning. In this paper, based on the field survey and statistic data of land changes
in Changjiang Hainan province during 1996-2005, the gross construction land in this region was simulated and predicted
using trend analysis method, exponent smoothing method, remnant GM(1,1) method, Markov model and multifactor
optimal combination method, respectively. From the compare of the average relative error, GM(1,1) Method is better to
predict, but its parameters c and p indicate this model can't be used to forecast long term data. From the result of Markov
model, the average relative error is small, but its maxerror is 4.15%. By comparison of these models, Multifactor optimal
combination method is more reliable and effective for policymakers of land management, and which is preferable for
predicting construction land demand of county's general land-use planning.
The comparative analysis of various classification models on land evaluation
Jian Tian,
Yueming Hu,
Jianmin Liu,
et al.
Show abstract
Many methods of data mining model were widely applied for land evaluation, and they show different characteristics of
the application for land evaluation. In order to analyze different classification model effect for land evaluation, this paper
took land in Longchuan County as a case study, established three models using decision tree, back propagation neural
network (BP) and logistic regression on land evaluation. The result of study shows that the accuracy of three models
changes remarkably according to 6 groups of training samples. The accuracy of the decision tree and BP model can reach
high level in support of 4000 training samples, but decision tree model is superior to BP model at intelligibility of model
and consuming-time aspects. The overall performance of Logistic regression model is worse than other models at the
massive samples. Moreover, three model have different the characteristic of error distribution by means of confusion
matrix. The error of decision tree distributes evenly, and the error distribution of BP has opposite result of Logistic
regression. Results indicate that the model of decision tree is the best model for evaluating Longchun County land at
comprehensive thought, and it has a good effect on application.
Multisource geological data mining and its utilization of uranium resources exploration
Show abstract
Nuclear energy as one of clear energy sources takes important role in economic development in CHINA, and according
to the national long term development strategy, many more nuclear powers will be built in next few years, so it is a great
challenge for uranium resources exploration. Research and practice on mineral exploration demonstrates that utilizing
the modern Earth Observe System (EOS) technology and developing new multi-source geological data mining methods
are effective approaches to uranium deposits prospecting. Based on data mining and knowledge discovery technology,
this paper uses multi-source geological data to character electromagnetic spectral, geophysical and spatial information of
uranium mineralization factors, and provides the technical support for uranium prospecting integrating with field remote
sensing geological survey. Multi-source geological data used in this paper include satellite hyperspectral image
(Hyperion), high spatial resolution remote sensing data, uranium geological information, airborne radiometric data,
aeromagnetic and gravity data, and related data mining methods have been developed, such as data fusion of optical data
and Radarsat image, information integration of remote sensing and geophysical data, and so on. Based on above
approaches, the multi-geoscience information of uranium mineralization factors including complex polystage rock mass,
mineralization controlling faults and hydrothermal alterations have been identified, the metallogenic potential of uranium
has been evaluated, and some predicting areas have been located.
Measuring the amount of information of national topographic database based on entropy
Hong Wang,
Shanwu Su,
Yuxiang Li,
et al.
Show abstract
Abundant and up-to-date basic geographic information is urgently required by various users. Reasonably measuring the
amount of information can provide technique foundations for describing, evaluating, and choosing products by
producers, quality controllers of information and users. Entropy is a kind of information quantity evaluation based on
information theory and mostly applied to measure of map information. However, measures for topographic features of
information database are absented. In this paper, existing measures for map information are analyzed. An experiment is
conducted by selecting several maps from national topographic database and the assessed feature is road layer. The
authors completely evaluated statistical information, geometric information, topological information and thematic
information entropy. Results show that entirely evaluating the amount of information for features is necessary and
feasible, and it can reflect the distribution and thematic characters for features in topographic database.
Application of binary tree based SVMs approach to land grade evaluation
Show abstract
Support vector machines (SVMs), which are based on statistical learning theory, have recently got considerable potential
in data mining by their good ability of generalization. Land grade evaluation, which provides information for land
planning and decision-making, is a process of evaluating land quality for a particular use. It can be referred to as
multiclass classification problem. As a result of SVMs' binary nature, they can not be directly applied to land grading
process. By integrating SVMs with a binary tree, this paper applied a binary tree based SVMs (BTSVMs) approach into
land grade evaluation. Arable land in Heping County, Guangdong, was chosen as study area and BTSVMs model was
then applied to the data. In addition to BTSVMs, the same data were classified using decision tree (DT) and artificial
neural network (ANN). Compared with DT and ANN, results showed that BTSVMs had better classification accuracy.
While decreasing the size of training data, the accuracy of each approach dropped down positively with BTSVMs
relatively more accurate than others. In general, BTSVMs is potentially feasible in the application of land grade
evaluation with its good performance.
Gross error detection and correction based on wavelet transform and support vector machine
Tingye Tao,
Fei Gao,
Zhaofu Wu
Show abstract
In order to obtain high accuracy results, the gross errors in observations must be correctly detected and repaired. In this
paper, the theory and methods of singularity detection based on wavelet transform, support vector machine regression
model are introduced. The wavelet multi-resolution analysis (MRA) was carried out and the location of the gross errors
can be detected by ascertaining the points of modulus maximal value of the wavelet coefficients since the gross error can
be regarded as the singular point of the observation time series. Then the time series regression model based on support
vector machine (SVM) was established to repair the gross errors. Practical test results indicate that the gross errors can
be validly detected by wavelet method as well as be correctly repaired by the method based on support vector machine.
Indicator mining model for spatial multi-scale degraded land evaluation
Show abstract
At present, no feasible and effective methods meet the requirements of constructing a comprehensive and representative
indicator system for degraded land evaluation, which orients spatial multi-scale and diversity of evaluation objects as
well as integrates experts' judgments and objective information. This paper, tying to solve the problem, firstly proposes
three propositions on evaluation indicator knowledge base (EIKB), universe evaluation indicator set (UEIS), evaluation
indicator subset (EIS) and Mapping Rule of EIS (MREIS), and then constructs an heuristic indicator mining model
(HIMM) based on above theories, variable precision rough set and information entropy. Finally, we applied HIMM to
practical degraded land evaluation and examined the effectiveness of HIMM. The result shows that HIMM is applicable,
especially in the aspect of solving the comprehensive and representative problem in the process of indicator system
construction.
A data skew handling method based on the minimum spatial proximity for parallel spatial database
Show abstract
Data skew is one of most important reasons to deteriorate the performance of parallel spatial database. This paper studies
the issues of handling data skew in shared nothing parallel spatial database system architecture. A novel data skew
handling method is proposed, which fulfill spatial data distribution balancing based on the spatial proximity of data
fragments. The minimum spatial proximity is used to be the principle of moving data fragments among different network
parallel nodes. Our experimental results show that the proposed data skew handling method can achieve dynamic data
load balancing and offer significant improvement for reducing response time of parallel spatial queries.
Harmonic generalization based on the integrated geographic feature retrieval
Lina Huang,
Lifan Fei,
Jing He
Show abstract
Generalization is needed to describe relevant information on an appropriate level of detail. However, the harmony
between different generalized geographic features are always difficult to be ensured even if the data sources come from
the same topographic maps or geographic databases, as the generalization is carried out separately in the context of
computer assisted cartography. This paper introduces a new approach for the harmonic generalization of terrain and
water system based on the integrated geographic feature retrieval using 3D Douglas-Peucker algorithm. The advantage
of the research is two folded: firstly, it focuses on the geographic nature of water system and terrain; secondly, the 3D
Douglas-Peucker algorithm is developed to make this generalization of the two kinds of features possible. The spatial
representation of water system in vector data and that of the terrain in DEMs are unitized into one set of general
character points. Then the 3D Douglas-Peucker algorithm is performed for the features retrieval. After that, the result is
returned to generate the abstracted terrain and the simplified water system. In this way, the harmonic registration
between the generalized terrain and the generalized water system can be ensured. The preliminary experiments show that
this harmonic generalization is a promising way both in cartography and GIS.
Experimental analysis on classification of unmanned aerial vehicle images using the probabilistic latent semantic analysis
Show abstract
In this paper, we present a novel algorithm to classify UAV images through the image annotation which is a
semi-supervised method. During the annotation process, we first divide whole image into different sizes of blocks and
generate suitable visual words which are the K-means clustering centers or just pixels in small size image block. Then,
given a set of image blocks for each semantic concept as training data, learning is based on the Probabilistic Latent
Semantic Analysis (PLSA). The probability distributions of visual words in every document can be learned through the
PLSA model. The labeling of every document (image block) is done by computing the similarity of its feature
distribution to the distribution of the training documents with the Kullback-Leibler (K-L) divergence. Finally, the
classification of the UAV images will be done by combining all the image blocks in every block size. The UAV images
using in our experiments was acquired during Sichuan earthquake in 2008. The results show that smaller size block
image will get better classification results.
Design and implementation of multi-source data mining system for land use
Show abstract
With the development of "3S" technologies, a large quantity of spatial-temporal data related to land use has been
accessed. Being scattered across different departments and lacking of relevant analysis tools made them utilize
insufficiently. Although some experts have applied data mining to solve this problem, most of them have only provided
one method for single task to build the mining systems. However, it is undesirable to use just one method to mine. In
addition, the single function systems can not be used widely and conveniently. Hence, under full investigation on
operations of land use, a multi-source data mining prototype system for land use is proposed by integrating of
technologies of GIS and spatial data mining. According to the general data mining process, aiming at the multi-demands
of land evaluation and land planning and so on, the system is developed by using ArcEngine 9.0 and VB.net. The system
integrates basic geospatial data, land use/cover data, and thematic data as data sources, excavates different knowledge of
land Quality, land use zoning rules, land use patterns and change rules and so on. Based on the types of knowledge, the
system accordingly provides several different mining methods, including decision tree, support vector machine, artificial
neural network, time series, spatial association rules, etc. Wide adaptability of the system is demonstrated by using some
cases. The results of the system can meet multipurpose needs and be used to support decision-making of the land
management department.
Study on the expropriation (requisition) price of cultivated land in China: take Nanyang City, Henan Province as an example
Show abstract
With currently China's farmland transformation for non-agricultural advancement is speeding up, such disadvantages as
low standard and simplified mode of compensation obviously appears in our land expropriation (requisition) system. And
land expropriation (requisition) price has been distorted seriously, which has caused a series of social problems aroused
more attention from many fields. It's high time to establish new criteria of land compensation. This paper presents a new
method to analyze the compensation standard of cultivated-land Expropriation and requisition respectively through
defining and normalize the connotation of tenure system and relevant rights of cultivated land in China, and to explore
the value composition of rights over cultivated land. Methods of logic analysis, comparison and empirical analysis were
applied. The results show that the tenure system of cultivated land is composed of five parts: natural productive price,
social security price, social stabilization price, ecological security price and development right price. The values of all
these rights vary under different socio-economic conditions, and they have to be embodied gradually in the process of
land Expropriation and requisition. Moreover, the new proposed methodology has been applied to a case study of paddy
lands located in Nanyang City, Henan Province in order to demonstrate its goodness. From the results of this work we
can conclude that the approach proposed stands out as a good alternative to current compensation standard of
cultivated-land Expropriation (requisition).
Entropy-theory-based study on the relationship between land use structure and industry system: a case study of the eastern Hubei metropolitan area
Show abstract
During the process of economic growth, the industry structure transforms at different developing sections and that
industrial composition as well as each department interior demand for land resources would reflect on land-use structure
reform. This paper takes Hubei as the research zone, through a consecutive time sequence of 10 years period (1996-2005)
just before and after the 1 plus 8 Eastern Hubei Metropolitan Area project, a quantitative study of the correlation between
the industry structure and land-use structure is made based on the entropy theory. According to the classification of
industrial composition, the land-use structure here is also redefined into four types as Land Use for Primary Industry,
Land Use for Secondary Industry, Land Use for Tertiary Industry, and Land Use for Potential Reserve, in the aim that it
should model new methods for researching the relationship of industry structure and land-use structure, and the instinct
driving force would be presented more evidently at the same time. The outcomes indicate that the change of land-use
structure has close relationship with the structure of industry composition; the trend of information entropy in Hubei
mostly keeps increasing during the past 10 years which predicating the symmetrical degree of land-use structure is
gradually built; and Eastern Hubei Metropolitan Area is of favorable power far superiority other units within province in
promoting regional development, yet land-use structure adjustments are still not stable and a optimal mode of land use
needs further approach.
Knowledge acquisition model of map generalization based on granular computing
Ying Song,
Dongmei Yu,
Chen Shen
Show abstract
The knowledge of automated map generalization mainly derives from map specifications, experience of experts and
spatial data. The representation, acquisition and reasoning of knowledge for cartographic generalization have been
widely recognized as difficulty. In an example with results of cartographic generalization, it is certain that some special
knowledge consist in spatial data, which represent spatial relationship of geographical objects. The meaning of acquiring
the knowledge hided in data lies in that other unknown data can be inferred by the knowledge. In this paper, a model of
knowledge representation and acquisition for automated map generalization based on granular computing is first
proposed. Then, the conceptions concerning knowledge granule and its structure are defined, and intrinsic mechanism
and method of knowledge acquisition are further discussed. Lastly, the model and method mentioned above are
illustrated through a case study. The conclusion is that knowledge acquisition lies on the dependence degree of
decision-making attributes for condition attributes. Each attribute has a different effect on the result of cartographic
generalization. The decision-making rules knowledge acquired by difference of dependence degree is just the
representation condition of cartographic objects, by which other unknown data with similar distribution characters can be
inferred.
Modeling the demand forecast of construction land of county-level
Hai-yuan Dong,
Xiao-yan Wang,
Li-li Jiao,
et al.
Show abstract
During the land-use planning, the demand forecast of construction land is complex. If the number of forecasting is
excessive, the land resources would be wasted. On the contrary, the local economic develop would be restricted for lack
of enough construction land. So it is important to determine an appropriate quantity of land for construction. The demand
of construction land is affected by many factors, so it is difficult to use a simple mathematical model to simulate it.
Therefore, this paper analyzes the important influencing factors on the quantity of land for construction and builds a
model to simulate the demand of construction land using a neural network. After comparison, the forecast result by using
the neural network is better than by the linear regression .The neural network is useful in the land-use planning.
Research on land registration procedure ontology of China
Zhongjun Zhao,
Qingyun Du,
Weiwei Zhang,
et al.
Show abstract
Land registration is public act which is to record the state-owned land use right, collective land ownership, collective
land use right and land mortgage, servitude, as well as other land rights required the registration according to laws and
regulations onto land registering books. Land registration is one of the important government affairs , so it is very
important to standardize, optimize and humanize the process of land registration. The management works of organization
are realized through a variety of workflows. Process knowledge is in essence a kind of methodology knowledge and a
system which including the core and the relational knowledge. In this paper, the ontology is introduced into the field of
land registration and management, trying to optimize the flow of land registration, to promote the automation-building
and intelligent Service of land registration affairs, to provide humanized and intelligent service for multi-types of users .
This paper tries to build land registration procedure ontology by defining the land registration procedure ontology's key
concepts which represent the kinds of processes of land registration and mapping the kinds of processes to OWL-S. The
land registration procedure ontology shall be the start and the basis of the Web service.
Spatial information semantic query based on SPARQL
Zhifeng Xiao,
Lei Huang,
Xiaofang Zhai
Show abstract
How can the efficiency of spatial information inquiries be enhanced in today's fast-growing information age? We
are rich in geospatial data but poor in up-to-date geospatial information and knowledge that are ready to be accessed by
public users. This paper adopts an approach for querying spatial semantic by building an Web Ontology language(OWL)
format ontology and introducing SPARQL Protocol and RDF Query Language(SPARQL) to search spatial semantic
relations. It is important to establish spatial semantics that support for effective spatial reasoning for performing semantic
query. Compared to earlier keyword-based and information retrieval techniques that rely on syntax, we use semantic
approaches in our spatial queries system. Semantic approaches need to be developed by ontology, so we use OWL to
describe spatial information extracted by the large-scale map of Wuhan. Spatial information expressed by ontology with
formal semantics is available to machines for processing and to people for understanding. The approach is illustrated by
introducing a case study for using SPARQL to query geo-spatial ontology instances of Wuhan. The paper shows that
making use of SPARQL to search OWL ontology instances can ensure the result's accuracy and applicability. The result
also indicates constructing a geo-spatial semantic query system has positive efforts on forming spatial query and
retrieval.
Research on uncertainty spatial association rule based on geo-rough space theory
Minshi Liu,
Xiaofeng Hong,
Dongyang Fang
Show abstract
A spatial association rule is a rule indicating certain association relationship among a set of spatial and possibly some
non-spatial predicates. Most spatial data mining methods, including previous study on spatial association rules, use
spatial objects with exactly known location. However, in real situations the extensions of spatial objects can be known
only with a finite accuracy because of limits of measurement technology and uncertainties of objects et al. The
inappropriate data mining methods based on these uncertain data will result in poor, even unaccepted quality of mining
models. How to employ spatial association rule to extract hidden knowledge in uncertain and imprecise data is worth
researching. Hence, in this paper we extend the technique for the discovery of spatial association rules from uncertainty
data, based on geo-rough space theory. According to the concepts of the lower approximation set, the boundary set,
rough topology relationships and rough distance relationships in geo-rough space, rough spatial predicates of
Rough-Near, Rough-Touch, Rough-Overlay and Rough-In are proposed. Then we put forward more reasonable rough
confidence and rough support for excavating spatial association rules from uncertainty data by using the Apriori
algorithm. The result of case indicates the method works well.
Analysis of obstruction reason of urban sewer using spatial association rules
Show abstract
Sewerage network is an important part of municipal infrastructure for a city. Obstruction of sewer causes street flooding
and affects people's daily life directly. To investigate reasons why some sewage pipes are blocked frequently in
Kunming, China, we employ spatial analysis and data mining technology to analyze the data on the basis of a municipal
sewerage geographic information system of the city. In the GIS, all of map layers and attribute tables are organized and
saved in a relational database with Geodatabase model. First, we combined SQL attribute query with spatial location
query to find out the sewage pipes that are blocked frequently. Then, we carried out buffer analysis and intersect analysis
on the layers of the frequently-blocked pipes and buildings along the streets to extract buildings that are close to these
frequently-blocked pipes. Joining the buildings in the buffer scope and the frequently-blocked pipes forms a big table
prepared for spatial data mining. We used Apriori algorithm to mine spatial association rules from the data in the big
table in order to search implicit reasons of obstruction of the pipes. The results from data mining indicate that strong
spatial and non-spatial associate rules exist between the obstruction and restaurants in the buildings, as well as attribute
slopes and diameters of these sewage pipes.
Research on the methods of connecting contour lines' breakpoints
Show abstract
As is well known, the contour line has always been the key unit in such projects of automatic recognition of geographic
maps, but how to handle the contour lines' breakpoints automatically is still not settled thoroughly. This paper first
synthetically analyzes four classical algorithms of the contour lines' breakpoints connecting methods, then presents a
layering-based breakpoints connecting policy. Taking brown plate map as data source, separately recognizing and
extracting the influencing factors such as elevation annotation, dry riverbeds, cliffs symbols which lead to the contour
lines' long-distance break from the map as the reference layers, then judging on the reference layer when connecting the
breakpoints, and according to the different influencing factors, designing the corresponding algorithms to achieve the
true connecting of the contour lines.
Applying fuzzy clustering optimization algorithm to extracting traffic spatial pattern
Chunchun Hu,
Wenzhong Shi,
Lingkui Meng,
et al.
Show abstract
Traditional analytical methods for traffic information can't meet to need of intelligent traffic system. Mining value-add
information can deal with more traffic problems. The paper exploits a new clustering optimization algorithm to extract
useful spatial clustered pattern for predicting long-term traffic flow from macroscopic view. Considering the sensitivity
of initial parameters and easy falling into local extreme in FCM algorithm, the new algorithm applies Particle Swarm
Optimization method, which can discovery the globe optimal result, to the FCM algorithm. And the algorithm exploits
the union of the clustering validity index and objective function of the FCM algorithm as the fitness function of the PSO
algorithm. The experimental result indicates that it is effective and efficient. For fuzzy clustering of road traffic data, it
can produce useful spatial clustered pattern. And the clustered centers represent the locations which have heavy traffic
flow. Moreover, the parameters of the patterns can provide intelligent traffic system with assistant decision support.
Research on determining the weights of urban land grading evaluation factors based on Spearman rank correlation analysis
Show abstract
The multi-factor integrated classification is usually used in urban land grading evaluation. The weights of urban land
grading evaluation factors determine the evaluation results. Therefore, the method used to determine the weights of
evaluation factors is of significant importance for the evaluation result. In this paper, a new method for determining the
weights of urban land grading evaluation factors, i.e., K-means clustering and spearman rank correlation analysis, is
proposed. This method is capable of decreasing human error and enhancing the effectiveness of the automatization
process.
Fuzzy Bayesian network classifier for extraction of rocky desertification
Shui-ming Li,
Ning Shu,
Jian-bin Tao,
et al.
Show abstract
Aiming at the complexity and uncertainty in the interpretation of rocky desertification from multi-source data, this
paper promotes fuzzy Bayesian network embedded Gaussian mixture model(GMM) for extracting rocky desertification
information.This model make a fuzzy quantization for continuous variable through GMM, use the convex function of
multiple Gaussion density functions to fit the "true" distribution of the data better, and avoid variable's discretization in
traditional Bayesian network. All nodes's parameter are then integrated utilizing naïve Bayesian network. Experiments
indicate that this model have high accuracy than hybrid Bayesian network and with research value in data mining of
multi-source data.
Agricultural regionalization based on spatial clustering of mixed data
Long Li,
Wenting Xiang,
Yangge Tian
Show abstract
Agricultural regionalization, which is largly achieved according to the similarity within a certain area and the
difference between this area and other ones, is the foundation of agricultural production. Due to the fact that clustering is
much like regionalization, methods for clustering are also commonly used in regionalization. However, the clustering
algorithms applied are usually for only numerical attributes and large amounts of categorical data with great values
cannot be handled with traditional clustering methods, which largely limits the utilization of clustering in agricultural
regionalization. In this paper, we propose a new spatial clustering algorithm which combines the ROCK algorithm with
fuzzy mathematics, can handle both numerical and categorical data at the same time, to satisfy the actual needs of
agriculture regionalization. The effectiveness of the new algorithm is tested on the agricultural regionalization of
ZengCheng, GuangZhou, China. During the test, we test both the effectiveness of the new spatial clustering algorithm
and some old algorithms. The final result shows that the new algorithm performs better in agricultural regionalization,
and its result is also closer to the artificial agricultural regionalization.
Data mining of synergetic coupling for land use based on extenics
Show abstract
A model of synergistic coupling for land-use data mining based on extension theory is put forward in this paper, which
can mine the relation of synergistic coupling for various land use activity in land use database to guide all kinds of
activity. In order to mine the knowledge of synergistic coupling, some knowledge must be obtained from database of
land use. Changjiang is a county in west of Hainan province, China. The data of land use is studied as a case through the
changes of construction to influence other land use types. The results show that the model can be used for the mining in
the land-use synergistic coupling relations. The knowledge that obtain in this case based on the model of synergistic
coupling for land-use data mining is essential for decision-makers to deal with the paradoxical problem of land-use.
Construction and application of particle swarm optimization algorithm for ecological spatial data mining
Show abstract
The research of the regional ecological environment becomes more important to regional Sustainable Development in
order to achieve the harmonious relationship between the person and the nature. The advent of spatial information
technologies, such as GIS, GPS and RS, have great enhanced our capabilities to collect and capture spatial data. How to
discover potentially useful information and knowledge from massive amounts of spatial data is becoming a crucial
project for spatial analysis and spatial decision making. Particle Swarm Optimization has a powerful ability for reasoning
and semantic representation, which combined with qualitative analysis and quantitative analysis, with prior knowledge
and observed data, and provides an effective way to spatial data mining. This paper focuses on construction and learning
a Particle Swarm Optimization model for spatial data mining. Firstly, the theory of spatial data mining is introduced and
the characteristics of Particle Swarm Optimization are discussed. A framework and process of spatial data mining is
proposed. Then we construct a Particle Swarm Optimization model for spatial data mining with the given dataset. The
research area is focused on the distribution of pollution sources in Wuhan City. The experimental results demonstrate the
feasibility and practical of the proposed approach to spatial data mining. Finally, draw a conclusion and show further
avenues for research. Through the empirical study, it has been proved that Particle Swarm Optimization algorithm is
feasible and the conclusion can provide instruction for local environmental planning.
An adaptive spatial clustering algorithm based on the minimum spanning tree-like
Show abstract
Spatial clustering is an important means for spatial data mining and spatial analysis, and it can be used to discover
the potential rules and outliers among the spatial data. Most existing spatial clustering methods cannot deal with the
uneven density of the data and usually require predefined parameters which are hard to justify. In order to overcome such
limitations, we firstly propose the concept of edge variation factor based upon the definition of distance variation among
the entities in the spatial neighborhood. Then, an approach is presented to construct the minimum spanning tree-like
(MST-L). Further, an adaptive MST-L based spatial clustering algorithm (AMSTLSC) is developed in this paper. The
spatial clustering algorithm only involves the setting of the threshold of edge variation factor as an input parameter,
which is easily made with the support of little priori information. Through this parameter, a series of MST-L can be
automatically generated from the high-density region to the low-density one, where each MST-L represents a cluster. As
a result, the algorithm proposed in this paper can adapt to the change of local density among spatial points. This property
is also called the adaptiveness. Finally, two tests are implemented to demonstrate that the AMSTLSC algorithm is very
robust and suitable to find the clusters with different shapes. Especially the algorithm has good adaptiveness. A
comparative test is made to further prove the AMSTLSC algorithm better than classic DBSCAN algorithm.
Extraction and mining for layered natural disaster information based on GIS
Yi Zhu,
Xiaodong Liu,
Lijian Sun
Show abstract
At present,the request for the rapid response to the various types of emergencies from countries and governments at all
levels are urgently,and most information of the natural disaster is relevant to the spatial location. So we should make full
use of the basis of mapping information,and make a rapid positioning about the location information,then mark the
disasters-event information,and at last achieve the integration of geographical information and multi-layer disaster
information.Based on the above-mentioned,it can offer the comprehensive analysis,statistics and mining to the historical
disaster database which are with the location information.It offers information to support decision-making and resources
platform for the disaster prevention and mitigation of countries and regions.
Spatial Analysis Models
The digital generalization principle of digital elevation model
Hai Hu,
Jun Gao,
Peng Hu
Show abstract
This paper briefly is based on the discussion of three fundamental characteristics of the ground (elevation
accuracy, validity of elevation order, and the preservation of elevation features) and the concept of the model, then
analyses major theoretical and practical shortcomings of the DEM generated in the mechanical model in depth,
finally we proposes and discusses objects for feature modeling and the way of digital generalization, and discusses
the principle of DEM digital generalization. We also give the 1:5 0000 and 1:1 0000 two series of DEM
generalization maps, which achieve the desired results. Experimental results clearly show that: Only with digital
generalization based on reliable DEMs which have expressed all terrain features, we can express DEM of required
terrain feature on designated resolutions. That is no generalizing, there will be no DEM. The excellent consistency of
Theoretical analysis and experimental results, makes this paper believe that objects for feature modeling and digital
generalization will bring qualitative change to DEM, and will be a promising new way to solve hundred-year
problem -combination and generalization of contours and water portfolio.
Ontology for cell-based geographic information
Show abstract
Inter-operability is a key notion in geographic information science (GIS) for the sharing of geographic information (GI).
That requires a seamless translation among different information sources. Ontology is enrolled in GI discovery to settle
the semantic conflicts for its natural language appearance and logical hierarchy structure, which are considered to be able
to provide better context for both human understanding and machine cognition in describing the location and
relationships in the geographic world. However, for the current, most studies on field ontology are deduced from
philosophical theme and not applicable for the raster expression in GIS-which is a kind of field-like phenomenon but
does not physically coincide to the general concept of philosophical field (mostly comes from the physics concepts).
That's why we specifically discuss the cell-based GI ontology in this paper. The discussion starts at the investigation of
the physical characteristics of cell-based raster GI. Then, a unified cell-based GI ontology framework for the recognition
of the raster objects is introduced, from which a conceptual interface for the connection of the human epistemology and
the computer world so called "endurant-occurrant window" is developed for the better raster GI discovery and sharing.
Progressive transmission of road network
Bo Ai,
Tinghua Ai,
Xinming Tang,
et al.
Show abstract
The progressive transmission of vector map data requires efficient multi-scale data model to process the data into
hierarchical structure. This paper presents such a data structure of road network without redundancy of geometry for
progressive transmission. For a given scale, the road network display has to settle two questions. One is which road
objects to be represented and the other is what geometric details to be visualized for the selected roads. This paper
combines the Töpfer law and the BLG-tree structure into a multi-scale representation matrix to answer simultaneously
the above two questions. In the matrix, rows from top to bottom represent the roads in the sequence of descending
classification of traffic and length, which can support the Töpfer law to retrieve the more important roads. In a row,
columns record one road by a linear BLG-tree to provide good line graphics.
The change detection of multi-temporal remote sensing images based on D-S algorithm
Show abstract
Change Detection is one of the most popular topics in the field of Multi-temporal Remote Sensing (RS)
applications. In this paper, a novel approach was introduced for the change detection of the urban area. This
approach adopts the Dempster-Shafer(D-S) algorithm for feature fusion of the multi-temporal RS images. It, in
the first place,,constructs difference images of pixel and context respectively. These two difference images
present the features of changes in different scales. The pixel difference image is obtained by fusing the results
of the subtraction operation and the division operation, while the context difference image is obtained by the
image context. Secondly, by using the difference images, two evidences could be constructed. These
evidences are not certain, but they can give more reliable combination result if considering the average support
of the evidence to different subsets in the assignment framework. And based on these evidences, the
criterion function could be established by the D-S theory. At last, an improved D-S algorithm is applied to fuse
the two different features for detecting the change information of the RS images. An experiment, using the
SPOT and TM images of Wuhan urban area, has compared the accuracy of edge detection by using the new
fusion algorithm and the existent ones. The result shows that the method of improved D-S is solid and
efficacious, which has preferable value in remote sensing applications.
Geographic spatial reasoning strategy based on ontology
Xiaochu Du,
Qingsheng Guo,
Quanfang Wang
Show abstract
Research on geographical spatial reasoning aims at expression of spatial relationships, geo-spatial reasoning rules and
reasoning mechanism that could be used for geo-spatial knowledge discovery and spatial analysis. Spatial reasoning is
intelligent spatial data processing technology in support of geo-spatial decision-making. Geographic ontology is clear
formal definition of geographical concepts, which defines the basic terms and relations of these concepts, and the rules
combining these terms and relationship. Therefore, it can well meet the formal knowledge representation requirement for
geo-spatial reasoning that carry out reasoning by using geographic ontology.
In this paper, methods of creating geographic ontology are discussed, and the rules based on spatial reasoning are
summarized. Furthermore, a path query method based on geographic ontology is proposed, by creating a road ontology
system and the corresponding administrative region ontology system, it can be used to solve large-scale spatial path
query problem.
A research on natural geographical factors based on Chinese urban expansion
Shunguang Hu,
Zengxiang Zhang,
Xianhu Wei,
et al.
Show abstract
To further explore the intrinsic mechanism of urban expansion, this paper was mainly related to natural geographical
factors on urban expansion based on MSS and TM multi-spectral remote sensing image of the 34 provincial capital level
cities in China from 1975 to 2005. With the help of MATLAB, SPSS and ARCGIS, the methods that the principal
component factor analysis, correlation analysis, and meanwhile overlay analysis had been used. And the results showed
that the natural geographical conditions of Chinese cities had a deep effect on their urban expansion. Firstly,
mountainous cities were limited by the terrain that their expansion rate was lower than that of the cities in the plain. At
the same time, with average altitude increasing, urban expansion rate had a tendency of decreasing. The spatial and
temporal changes of urban expansion were bound up with the average slope of the province. And the speed of urban
expansion varied greatly on different levels of slope. Secondly, urban expansion showed distinct characteristics
respectively in different weather conditions. Correspondingly, the temperature, precipitation and sunshine hours were
selected as different grade reference factors to analyze urban expansion characteristics. Thirdly, analysis on the
relationship between the hydrological and urban expansion had been done. In conclusion, this paper had made a try on
the study of natural geographical factors on urban expansion. And it had an important practical significance to classify
different cities with natural environmental indicators.
Study on paddy rice yield estimation based on multisource data and the Grey system theory
Wensheng Deng,
Wei Wang,
Hai Liu,
et al.
Show abstract
The paddy rice is our important crops. In study of the paddy rice yield estimation, compared with the scholars who
usually only take the remote sensing data or meteorology as the influence factors, we combine the remote sensing and
the meteorological data to make the monitoring result closer reality. Although the gray system theory has used in many
aspects, it is applied very little in paddy rice yield estimation. This study introduces it to the paddy rice yield estimation,
and makes the yield estimation model. This can resolve small data sets problem that can not be solved by deterministic
model. It selects some regions in Jianghan plain for the study area. The data includes multi-temporal remote sensing
image, meteorological and statistic data. The remote sensing data is the 16-day composite images (250-m spatial
resolution) of MODIS. The meteorological data includes monthly average temperature, sunshine duration and rain fall
amount. The statistical data is the long-term paddy rice yield of the study area. Firstly, it extracts the paddy rice planting
area from the multi-temporal MODIS images with the help of GIS and RS. Then taking the paddy rice yield as the
reference sequence, MODIS data and meteorological data as the comparative sequence, computing the gray correlative
coefficient, it selects the yield estimation factor based on the grey system theory. Finally, using the factors, it establishes
the yield estimation model and does the result test. The result indicated that the method is feasible and the conclusion is
credible. It can provide the scientific method and reference value to carry on the region paddy rice remote sensing
estimation.
The GIS map coloring support decision-making system based on case-based reasoning and simulated annealing algorithm
Shuang Deng,
Yangge Tian
Show abstract
Map coloring is a hard task even to the experienced map experts. In the GIS project, usually need to
color map according to the customer, which make the work more complex. With the development of GIS,
more and more programmers join the project team, which lack the training of cartology, their coloring map
are harder to meet the requirements of customer.
From the experience, customers with similar background usually have similar tastes for coloring map.
So, we developed a GIS color scheme decision-making system which can select color schemes of similar
customers from case base for customers to select and adjust. The system is a BS/CS mixed system, the client
side use JSP and make it possible for the system developers to go on remote calling of the colors scheme
cases in the database server and communicate with customers.
Different with general case-based reasoning, even the customers are very similar, their selection may
have difference, it is hard to provide a "best" option. So, we select the Simulated Annealing Algorithm
(SAA) to arrange the emergence order of different color schemes. Customers can also dynamically adjust
certain features colors based on existing case. The result shows that the system can facilitate the
communication between the designers and the customers and improve the quality and efficiency of coloring
map.
Study on temporal and spatial variations of urban land use based on land change data
Show abstract
With the rapid development of urbanization, demands of urban land increase in succession, hence, to analyze temporal
and spatial variations of urban land use becomes more and more important. In this paper, the principle of trend surface
analysis and formula of urban land sprawl index ( ULSI) are expatiated at first, and then based on land change data of
Jiayu county, the author fits quadratic trend surface by choosing urban land area as dependent variable and urbanization
and GDP as independent variables from 1996 to 2006, draws isoline of trend surface and residual values; and then urban
land sprawl indexes of towns are calculated on the basis of urban land area of 1996 and 2006 and distribution map of
ULSI is plotted. After analyzing those results, we can conclude that there is consanguineous relationship between urban
land area and urbanization, economic level etc.
Spatial Reasoning
Multi-scale terrain representation and terrain analysis
Xi-lin Ke,
Qing-sheng Guo,
Yue-peng Zhang,
et al.
Show abstract
Multi-scale handling and representation of terrain is one of the key hot topics in GIS. It can meet the demand of different
users on the different scale geo-spatial data. Through multi-scale representation of terrain the non-scale GIS can be
achieved and the users can acquire the info they care about easily by such GIS. This paper analyzes the concept of
multi-scale reprensentation of terrain and the relative researches on multi-scale terrain representation. Also the
construction of multi-scale terrain is discussed, and its application in terrain analysis is described.
Application of multi-source data fusion in navigation satellite autonomous orbit determination
Show abstract
Aiming at the orbit floating or so called constellation rotation in navigation satellite autonomous orbit determination, an
approach based on multi sources data fusion was introduced, that is to introduce angle observation from on board star
sensor toward fixed star to fix the ascending node Ω, one of the six orbit elements so as to avoid constellation rotation.
During data processing, a generalized measurement model based on matrix Cholesky decomposition and the method of
measurement noises de-correlation was adopted. On the foundation of roundly analysis of present theories and methods
of multi sources data fusion, and characteristics of multi sources measurement data fusion taken into account, two sorts
of multi sources data fusion measurement models based on independent same distribution and correlation of
measurement noises were conducted. Theoretical analysis and simulation experiment show that navigation satellite
autonomous orbit determination based on multi sources data fusion can well solve the problem of orbit floating
contrasting against that of only inter-satellite observations used.
Statistics analysis on SPOT 5 classification accuracy of different data fusion methods
Show abstract
In recent years, data fusion has become a very popular method in remote sensing image enhancement. In this paper, a
comparative study was conducted on data fusion methods based upon SPOT5 image. First land types of forest, paddy
field, dry land, water and building was selected through field survey. Then supervised classification and non-supervised
classification were used upon original image and four fusion images (HIS, PCA, high-pass filtering (HPF) and Brovery)
respectively. Land change area, change rate and classification accuracy were calculated. Finally suitable SPOT5 fusion
method for every land types was presented. The result showed: (1) In all four fusing methods PCA held the highest land
change rate, being average 49.0% for non-supervised classification and average 18.9% for supervised classification. So
visual interpretation was a better way for PCA fusion image. (2) HIS produced some distortion to the original spectrum
and made flaky features into pieces. This method was suitable to extract small features in complicated urban areas
because of its high spatial resolution. In the research, building change rate in HIS fusing image under supervised
classification was lowest, only 3.32%. (3) For HPF land change rate was low for no matter non-supervised classification
or supervised classification, being average 16.3% and 11.2% respectively. This fusion method held low distortion and
more high-frequency spectrum. It was suitable to be used as the basic image data for both supervised classification and
non-supervised classification. In our research image classification accuracy of urban areas in HPF fusion image was
93.1%.
Multispectral and SAR image fusion based on wavelet and IHS transform
Ling Liu,
Ning Shu
Show abstract
Multi-spectral images are of narrow-banded and high spectral resolution, however the transmission energy is low,
which result in a large scanning IFOV and a loss of spatial resolution; while SAR (Synthetic Aperture Radar) images, as
the angle reflection of buildings and low backscattering of waters, have excellent performance on texture structure and
water bodies[1]. Therefore, adopting an appropriate fusion algorithm could obtain more accurate and abundant
information than any a single data.
Wavelet and IHS transform are complementary. An improved algorithm based on them applied to multi-source image
fusion is presented, which could overcome the disadvantages that classical algorithms have such as inconspicuous
improvement of space resolution, low level of information integration and serious spectral distortion. Intensity
component is first extracted from the multi-spectral image by IHS transform, and then I component and SAR image are
decomposed respectively by selected wavelet filter and decomposition layer. The modulation factor is gained through
regional energy measurement in sub-windows for the new I-component. Finally the fused image could be acquired
through inverse IHS transform. With different wavelet filters and decomposition layers, parameters are eventually fitted
on Coiflets for four layers with subjective and objective indicator criteria. Through regional energy fusion, we could
divide the smooth areas and marginal areas of the image in frequency domain, which could make a significative feature
measurement in smaller ranges. Experimental results indicate that this model would achieve an excellent effect on the
maintenance of spectral information in multi-spectral images as well as texture and edge in SAR images.
Study on multiscale generalization of DEM based on lifting scheme
Zuqiao Yang,
HuanBin Liu,
Nai Yang,
et al.
Show abstract
Automatic generalization of geographical information is the core content of multi-scale representation of spatial data, but
the scale dependent generalization methods are far from abundance because of its extreme complicacy. Most existing
algorithms about automatic generalization do not relate to scale directly or accurately, not forecast and control the
generalized effects, and cannot assess the global consistency of the generalized results. The rational and quantitative
methods and criterions of measuring the extent of generalization have not still been sought out.
Lifting Scheme is a new branch of Wavelet analysis burgeoning in last decades. It has several noteworthy aspects
comparing with the Binary wavelet Transformation. The fundamentals of Lifting Scheme and the three constructing steps,
which include Split step, Predict step and Merge step, are presented detailed in this paper. DEM can be represented in
multi-scale model by the methods of The Lifting Scheme and The Binary Wavelet Transform. Compare with two
methods, the Lifting Scheme has several superiorities by analyzing the experimental results: Firstly, the trend of relief
could be preserved in course of transforming; secondly, the Lifting Scheme can process the points of boundary of DEM
efficiently and the spatial data precision can also be maintained, and at last the calculation process of Lifting Scheme is
more speedy.
Uniform color processing of scanned topographic maps based on SSR
Zhongliang Fu,
Chunya Tong,
Lu Liu,
et al.
Show abstract
Nowadays, large amount of paper-based topographic maps are still existed in many government department. The scanned
maps of them are very useful for research on city history migration, city planning and so on. However, the brightness of
these maps is not uniform, and creases are existed, so uniform color process is always needed. If the classical Retinex
algorithm is used, the map would have a low brightness and contrast ratio. Therefore, a normal intercepting SSR
algorithm of linear extending is presented in this paper. This algorithm first uses the classical SSR algorithm to process
the data, and then the average value of image and variance are introduced to do normal intercepting linear extending on
the map. Experiment results show that, the improved SSR can not only efficiently eliminate creases and uniform the map
brightness, but also increase the global brightness and contrast ratio. Moreover, this algorithm can also be used in the
pretreatment of grid image registration, thus to enhance the precision, velocity and accuracy of registration.
An effective method for merging point-cloud model
Guoli Wang,
Yanmin Wang
Show abstract
LIDAR is applied in a variety fields as a reverse engineering technology, such as factory, cultural heritage protection and
Digital City Modeling etc. Point cloud pre-processing has been a research hotspot in recent years, one of the factors
restricts its application is merging point-cloud which affects the quality of data very much. In this paper, an effect
method is proposed to merge point cloud with different point views to one single point cloud model to represent the real
objects. In this method, a base point-cloud model is selected and other models are subtracted according to the missing
data of base model, precise alignment is made to smooth the patched point cloud. The method will merge the different
point cloud views effectively and reduce the redundant data, thus it will be effect for the following processing. It's
proved to be a good method for merging huge point-cloud.
Spatial Simulation Models
Ancient architecture point cloud data triangulation based on algorithm integration with the subdivision of the grid and tangent plane projection
Show abstract
With the development of Terrestrial 3D Laser-scanning technology, as the one of main methods of earth
observing architecture, Terrestrial 3D Laser-scanning technology is increasingly widely applied in the field of
ancient architecture protection. Triangulating a set of scattered 3D points is a common approach but a difficult
problem to surface reconstruction from unorganized point clouds. Because the amount of point cloud data of
ancient architecture is very large and the surface of ancient architecture is very complex comparing to reverse
engineering field, Universal triangulation algorithms are inefficient and ineffective for complex surface. On the
basis of full analysis of the characteristics of the ancient buildings, a modified surface projection-based
triangulation algorithm was proposed in this article, which integrated with the subdivision of the grid by K-D tree
and tangent plane projection triangulation. The algorithm was used in a real project. Experiments show that the
method is more efficient and effective and support for the 3D model reconstruction of ancient buildings is provided.
Automatic modeling of cliff symbol in 3D topographic map
Nai Yang,
Qingsheng Guo,
Dayong Shen
Show abstract
In view of the problem that some relief symbols are difficult to build models in 3D topographic map, we take cliff
symbol as an example to set up an illumination model of it according to the visual sensation rules under the different
illumination conditions, propose a set of automatic modeling principles, educe automatic modeling formulas and
introduce the automatic modeling method of cliff symbol in detail. The experiment proves that it is feasible. The study
will be helpful to build the models of other similar relief symbols automatically.
Process-oriented research on spatio-temporal dynamic semantics
Show abstract
Being short of evolution mechanisms, theories of spatio-temporal representation and modeling have great challenges to
describe and represent the continuity and gradual geographical entities, still less deeper information retrievals and
knowledge mining. The spatio-temporal dynamic semantics, which contains geographical entities, changes of entities
and evolution mechanisms, is presented. According to the intrinsic process characteristics of dynamic entities, a
hierarchical semantics structure and process object sequences included by level are given. This paper describes the
process relationships and behaviors, and formalizes them into evolution operators, which subdivide into the process
recurrence operators and recurrence ones. Based on the object-oriented technologies, the evolution operators are
integrated into process object sequences, and a process-oriented dual representation framework on process objects'
recurrence and recursion (DRF-PORR) is presented as well. And finally, as a case study, the typical oceanographic
phenomena are taken to carry out the case modeling.
Design and implementation of segment oriented spatio-temporal model in urban panoramic maps
Haiting Li,
Lifan Fei,
Qingshan Peng,
et al.
Show abstract
Object-oriented spatio-temporal model is directed by human cognition that each object has what/where/when attributes.
The precise and flexible structure of such models supports multi-semantics of space and time. This paper reviews current
research of spatio-temporal models using object-oriented approach and proposed a new spatio-temporal model based on
segmentation in order to resolve the updating problem of some special GIS system by taking advantages of object-oriented
spatio-temporal model and adopting category theory. Category theory can be used as a unifying framework for
specifying complex systems and it provides rules on how objects may be joined. It characterizes the segments of object
through mappings between them. The segment-oriented spatio-temporal model designed for urban panoramic maps is
described and implemented. We take points and polylines as objects in this model in the management of panoramic map
data. For the randomness of routes which transportation vehicle adopts each time, road objects in this model are split into
some segments by crossing points. The segments still remains polyline type, but the splitting makes it easier to update
the panoramic data when new photos are captured. This model is capable of eliminating redundant data and accelerating
data access when panoramas are unchanged. For evaluation purpose, the data types and operations are designed and
implemented in PostgreSQL and the results of experiments come out to prove that this model is efficient and expedient
in the application of urban panoramic maps.
DEM's digital progressive generalization and multi-scale visualization of contour lines
Peng Hu,
Li Yang
Show abstract
The paper introduces much about the DEM digital progressive generalization based on new DEM theory for
the diversification of demands in applications, at the same tine, gives the algorithm to realize this process. A
number of data experiment results show that we should do the digital generalization to keep the DEM quality.
And only the high fidelity DEM can reserve features well. From the progressive digital DEM generalization, we
can do the multi-scale visualization of contour lines well. These series of research work and data results have
open our minds in DEM thinking.
Study on relationship between vegetation index and meteorological factors in north Hubei
Junqi Zhou,
Jie Ge
Show abstract
Vegetation Index can reflect the growth situation of vegetation. Meteorological factors can reflect climate change
which can act on the growth situation of vegetation.
The paper analyses the relationship between vegetation index and meteorological factors during each January and
May from 2003 to 2005 in north Hubei Province where the majority of plant is wheat. Using the correlation coefficient
of normalized difference vegetation index (NDVI) and precipitation, insolation duration, accumulative temperature to
find out that the accumulative temperature is the most important factor in the relationship between vegetation index and
meteorological factors in this area. The experiment compares correlation coefficients in 9 regions, and find out that the
correlation coefficient is greater where accumulative temperature changes fast.
A multiple representation data model based on state and behavior
JingZhong Li,
Tinghua Ai
Show abstract
The representations of spatial data over scale space have some properties, such as limitation, polymorphism and
hierarchy and so on. Firstly, the spatial data can only be represented on a limted scale range||S0, SE||, which can be
considered as the representation lifespan. Secondly, druing the representaion lifespan, the spatial data may be describled
by different geometry types and semantic structures. Thirdly, the changes between two consecutive representaions may
be abrupt or gradual. Usually the abrupt changes are the cumulations of many gradual changes. We can consider the
representations related to abrupt changes as the key frames, and the others as the general frames. Based on these
properties, this paper presents a multiple representaion data model based on state and behavior, which includes two basic
elements, the key frames and the scale transformation operations, the former sketching the blueprint and the latter
constructing the intermedial states. If we denote the key frames as a state set G, and the scale transformations as a
behavior set F, then the representation at any scale point can be calculated by this formula: Rs=f(g,s), f∈F , g∈G and
s∈[S0, SE].
Representation and application of bus system at the lowest level of detail
Show abstract
Based on spatial data modeling, bus transit features can be represented at different levels of detail, which provides
possibility of more precise estimation of travel impedance. The simple route-stop bus data model is efficient at the macro
level and has been applied in many transport-related applications. However, a more comprehensive data model is needed
to cope with different levels of needs as well as complicated situations existing in heavily bus-oriented cities. For this
purpose, a bus transit data model is developed based on representation of transit features at the detailed spatial level.
With this data model, the impedance between any pair of routes at each transfer junction can be computed. For testing
the data model, an integrated approach is developed to identify optimal bus trips with consideration of both on-board
travel time and transfer time.
A top-down hierarchical spatio-temporal process description method and its data organization
Jiong Xie,
Cunjin Xue
Show abstract
Modeling and representing spatio-temporal process is the key foundation for analyzing geographic phenomenon and
acquiring spatio-temporal high-level knowledge. Spatio-temporal representation methods with bottom-up approach
based on object modeling view lack of explicit definition of geographic phenomenon and finer-grained representation of
spatio-temporal causal relationships. Based on significant advances in data modeling of spatio-temporal object and
event, aimed to represent discrete regional dynamic phenomenon composed with group of spatio-temporal objects, a
regional spatio-temporal process description method using Top-Down Hierarchical approach (STP-TDH) is proposed
and a data organization structure based on relational database is designed and implemented which builds up the data
structure foundation for carrying out advanced data utilization and decision-making. The land use application case
indicated that process modeling with top-down approach was proved to be good with the spatio-temporal cognition
characteristic of our human, and its hierarchical representation framework can depict dynamic evolution characteristic of
regional phenomenon with finer-grained level and can reduce complexity of process description.
Spatial-temporal database model based on geodatabase
Show abstract
Entities in the real world have non-spatial attributes, as well as spatial and temporal features. A spatial-temporal data
model aims at describing appropriately these intrinsic characteristics within the entities and model them on a conceptual
level so that the model can present both static information and dynamic information that occurs over time. In this paper,
we devise a novel spatial-temporal data model which is based on Geodatabase. The model employs object-oriented
analysis method, combining object concept with event. The entity is defined as a feature class encapsulating attributes
and operations. The operations detect change and store the changes automatically in a historic database in Geodatabase.
Furthermore, the model takes advantage of the existing strengths of the relational database at the bottom level of
Geodatabase, such as trigger and constraint, to monitor events on the attributes or locations and respond to the events
correctly. A case of geographic database for Kunming municipal sewerage geographic information system is
implemented by the model. The database reveals excellent performance on managing data and tracking the details of
change. It provides a perfect data platform for querying, recurring history and predicting the trend of future. The instance
demonstrates the spatial-temporal data model is efficient and practicable.
Spatio-temporal statistics for exploratory NDVI image analysis
Show abstract
In this paper, spatio-temporal changes of vegetation in Jilin are explored with MODIS NDVI images time series
from 2000 to 2006. MODIS NDVI images time series are organized into a spatio-temporal data cube. We build a
linear regression model of NDVI time series at each pixel of the MODIS image. The slope of the linear regression
model indicates the change trend of vegetation. Using these change trends data, we further develop three advanced
spatio-temporal statistics of regional statistics, the center of gravity, and spatial autocorrelation for exploring spatiotemporal
changes of Jilin vegetation. Three method results have commonly showed that Jilin vegetation change is
generally stationary and slightly increasing in space. Meanwhile, Jilin vegetation changes are spatially
heterogeneous in local regions. In particular, vegetation change is stationary in eastern Jilin, and is increasing in
western Jilin. Vegetation change is decreasing in southwestern Jilin, northwestern Jilin, riverside and lakeside
regions, and Changchun downtown. Positive spatial autocorrelation of Jilin vegetation changes is significant.
Besides, the regions with a similar vegetation change trend are spatially clustered. Three given methods of
exploratory NDVI image analysis have emphasized separable spatio-temporal interaction modeling, that is, a twophrase
combination of modeling temporal changes firstly and modeling spatial changes secondly.
Building depth images from scattered point cloud
Shuangfeng Wei,
Hong Chen
Show abstract
With the equation of plane and sphere, we fit them with Linear Least Squares. To cylinder datum fitting, firstly
parameterize GQS equation of cylinder from seven parameters to five parameters, then using Local
Paraboloid Construct method based on coordinate translation to get fitting initial values, finally evaluate
results by Levenberg-Marquardt--a Nonlinear Linear Least Squares. Algorithm. However, initial values with
Local Paraboloid Construct method are unstable. So to improve the precision of cylinder fitting ,a robust
cylinder fitting method is put forward, which at first gets initial cylinder parameter values by Gauss Image,
then fits cylinder by Nonlinear Least Squares for parameterized distance function. After getting reference
datums, this paper proposes the methods of creating depth images from scattered point cloud and the
specific steps with reference to different datums. Finally we choose some point cloud data of ancient building
components from laser scanning data of Forbidden City in China as experiment data. Experiment results
demonstrate the stability and high precision of the method of plane, cylinder and sphere fitting as well as the
validity of depth images to represent point cloud of object.
A spatial-temporal covariance model for rainfall analysis
Sha Li,
Hong Shu,
Zhengquan Xu
Show abstract
Many environmental phenomena are regarded as realizations of random functions which possess both spatial and
temporal characteristics. In particular, Geostatistics with an extension of the existing spatial techniques into the
space-time domain offers some kinds of methods to model such processes. Although these methods for the analysis of
spatial-temporal data are becoming more important for many areas of application, they are less developed than those for
the analysis of purely spatial or purely temporal data. In this paper, two kinds of spatial-temporal stationary covariance
models are introduced. And the differences between spatial domain and time domain are examined. A product-sum
covariance model originally given by De Cesare is extended for spatial-temporal analysis on daily rainfall measurements
in the three provinces of Northeast China. Remarkably, this generalized non-separable model does not correspond to the
use of a metric one in space-time. The rainfall measurements used for this experiment are taken at 104 monitoring
stations from January 2000 to December 2005. In the experiment, the product-sum variogram model is employed for
developing ordinary kriging and its application to interpolation of the monthly rainfall data from January 2000 to
December 2004 has been used to predict the monthly rainfall of 2005. The true values and the predicted ones are
compared. The experimental results have shown that this product-sum covariance model is very effective for rainfall
analysis.
A geodatabase-based data model for Poyang Lake watershed comprehensive management modeling
Geying Lai,
Jianxing Lv,
Cui Chen,
et al.
Show abstract
It is clear that the development of an integrated watershed data model (IWDM) that encapsulates the data layers
describing watershed eco-systems will benefit coupling GIS to watershed models. It is desired that integrated
watershed data model will not only store separate layers of information but also provide geographic and temporal,
natural and social-economic connectivity to better represent watershed system and all of the features and
information within it. The objective of this study is to establish an integrated watershed data model to describe the
watershed system and its primary elements in order to support Poyang Lake watershed comprehensive
management modeling (PLWCMM), in which many models are coupled with ArcGIS Engine using Visual Studio
2005. In this paper, the integrating framework of PLWCMM was firstly introduced and the requirement analysis
of the integrated watershed data model was conducted. In addition, the frame structure and detailed features of
each feature datasets in IWDM were described. In the IWDM, the six components of Hydro, LandScape,
Weather, Social-Economy, Simulation and TimeSeries were contained, and there are different feature classes in
each model component. This data model can connect natural spatial unit in watershed to administration unit by
the relationship between their spatial features and also connect spatial data to temporal data.
Remote satellite sensor modeling design and implementation based on the sensor modeling language
Show abstract
Various sensors play a very important role in our everyday life. Sensor model language is a vital part of the OGC for the
description of the common sensor. SensorML not only describe properties of the sensor itself, but also the process about
the sensor. Based on the SensorML which is coding with XML schema, we need an efficient way for modeling a sensor
or a system. In this paper, firstly, the SensorML model is introduced, in which the SensorML schema is analyzed, and a
common procedure for sensor modeling is defined. Secondly, the establishment of a common sensor model platform
comes true using the dynamic generation, reflex, XML DOM in the .NET Framework 3.5. At last, the BJ-1 satellite was
used as an example for the SensorML modeling. For the non-physical process chain, the red band and near infrared band
of the BJ-1 satellite were as inputs for the NDVI calculation. After all, we validate the BJ-1 satellite SensorML instance.
Sphere target fitting of point cloud data based on TLS
Show abstract
Sphere target is an important toolbox in terrestrial laser scanning. With the sphere target, multiple point clouds data
obtained from different views can be transformed into the same coordinate frame. Determination of the sphere target
center is key to complete the task mentioned above. A usual approach to determine the coordinates of the center of the
sphere is the Less Squares (LS) method. In this paper, a new method using Total Least Squares (TLS) to determine the
center of the sphere target is investigated. For the new method, a special model is assumed that the design matrix
contains the linearization, and errors in both the residuals vector and the design matrix can be minimized simultaneously.
Various experiments are conducted using the real point clouds data, and it is shown that the proposed TLS approach
works effectively and achieves better results than the usual LS method.
Chaos analysis of groundwater depth time series using surrogate data method
Show abstract
The investigation of chaos in time series is the basis of prediction with chaos theory. Though the science of chaos is
a burgeoning field and the available methods to investigate the existence of chaos in a time series are in the state of
infancy, a wide variety of methods are available. Among these methods, the correlation dimension method is the most
popular one. According to this method, a finite correlation dimension is a sign of deterministic chaos, which is
understood as the principal. However, a finite correlation dimension may also be observed from a linear stochastic
process. Therefore, it is necessary to confirm the absence of linearity in the data to verify the results with application of
the correlation dimension method. In this paper, after the reconstruction of phase space, the correlation dimension
method was employed to analyze the chaotic characteristics for groundwater depth time series in Hetao Irrigation District
of Yellow River in China. Considering that a finite correlation dimension is only the necessary condition of chaotic
behavior, the surrogate data method which can distinguish nonlinear characteristics of time series was employed to
analyze the chaotic characteristics for the groundwater depth series. As a comparison, classic Lorenz chaos time series
and stochastic white noises were analyzed using the surrogate data method at the same time. The results show that there
is somewhat chaos in the groundwater depth time series in Hetao District in Yellow River Basin. Meanwhile, the
surrogate data method is the necessary complementarity of the correlation method to investigate the chaotic behavior for
time series.
Construction of geographical names knowledge base with ontology and production rule
Gang Cheng,
Qingyun Du
Show abstract
With the rapid development of the gazetteers, more and more geographical names databases has been established. Since
the geographical names exit in form of records which provide little qualitative description other than quantitative
information, geographical names are hardly shared and interoperable. In order to solve this problem, we urgently need to
set up knowledge base for geographical names that shall provide qualitative knowledge to describe the essence of the
elements. So, we use ontology and production rules to build geographical name knowledge base, where the geographical
names ontology is regarded as the foundation for reuse and sharing of the geographical names information, and
production rules are used to enhance the expressivity of the ontology. First of all, we analyzed the geographical names
concepts and their semantics, the concepts of space and time and their relationships in geographical names to describe
the knowledge structure for this field, used Web Ontology Language (OWL) to provide formal descriptions to give them
explicit semantics, and proposed a unified semantic framework for description. Secondly, we established the
common-sense rules and spatial relations inference rules coded with Semantic Web Rule Language (SWRL) which laid
the foundation for geographical names knowledge discovery and automatic reasoning. Finally, we established a
geographical name knowledge base combining both the geographical names ontology and rules established above.
Through the analysis of examples we showed that based on the geographical names knowledge base the geographical
names information can be well shared and reused.
An event-version-based spatio-temporal modeling approach and its application in the cadastral management
Show abstract
Spatiality, temporality, legality, accuracy and continuality are characteristic of cadastral information, and the cadastral
management demands that the cadastral data should be accurate, integrated and updated timely. It's a good idea to build
an effective GIS management system to manage the cadastral data which are characterized by spatiality and temporality.
Because no sound spatio-temporal data models have been adopted, however, the spatio-temporal characteristics of
cadastral data are not well expressed in the existing cadastral management systems. An event-version-based
spatio-temporal modeling approach is first proposed from the angle of event and version. Then with the help of it, an
event-version-based spatio-temporal cadastral data model is built to represent spatio-temporal cadastral data. At last, the
previous model is used in the design and implementation of a spatio-temporal cadastral management system. The result
of the application of the system shows that the event-version-based spatio-temporal data model is very suitable for the
representation and organization of cadastral data.
An improved trajectory query on moving objects in a spatio-temporal database
Jing Tang,
Tao Liu
Show abstract
The ideal spatio-temporal database not only has the normal functions essential to every spatial database, but also has
the ability for keeping track of dynamic data changing with time. Some analyses based on spatio-temporal database,
such as spatial network analyses based on different timestamps, should firstly do efficient querying work. With the
convenience and improvement in tracking of moving objects, trajectroy can be easily recorded and many novel
services have been proposed. So we should provide an efficient technique to finish trajectroy query on moving
objects. In this paper, we focus on improving the existing trajectory query. Firstly, this paper states the current
research approaches of dynamic query in spatio-temporal database. Secondly, it gives a classification of current
query methods and a description of the trajectory representation. Based on the foregoing groundworks, we propose
our improved methods and give an example to set forth the advantage of the method in details. Finally, we look
ahead and propose a new vista of research in this area.
Development of a spatio-temporal data model based on events and objects in land reclamation information system
Show abstract
The land resource in the mining area has been destroyed badly, therefore to establish a land reclamation information
system of mining area based on GIS is of great significance. However, mining land reclamation is a complex systemic
project, there are a lot of spatial data and spatial information during the whole reclamation procedure. The spatial
information database of land reclamation is a temporal one due to the change of the land resource within the coal mining
area. The damaged land is always above the corresponding underground working face of the mine, there are many pieces
of destroyed land in the mining area. A piece of reclaiming land area can be acted as one object, On the basis of the
analysis of the changing course of the land object in the subsidence region and the advantage of event-based spatio-temporal
data model, a spatio-temporal data model based on objects and events was proposed in this paper, this model
can be applied to administer land information in the mining area. Meanwhile, the spatial information query and the
analytic method were also studied in this paper. The advantage of this model is to connect surface event and underground
mining event which cause the land information change in the mining area.
A judgment approach to topological relation of regions with a hole
Show abstract
The topological relationship between spatial objects is one of the most important aspects in GIS modeling, and it is the
basis of spatial query and analysis. The description of spatial relationships has been paid more attention in the field of
GIS. At present, the research on topological relation model for spatial objects was usually described simple objects, the
research of a regions with a hole are comparatively fewer, it's research has important theory meaning. First, this paper
analysised existing method for description of regions with holes in the eighth reference literature, based on the point-set
topology theory, redefined the regions with holes. By analyzing the evolution plans of simple area objects' topological
relations, put forward a new method which can describe the special topological relations of regions with a hole, and used
the new method to discussed the topological relations of two regions with a hole. Through the experiment, in thoery, it
has been proved that this method is feasible, can provide a theoretical method for improving the modeling and analysis
capabilities of GIS.
Design of objectified spatial-temporal relation data model for WalkGIS platform
Yongwei Li,
Yu Lou,
Qinjie Jiang
Show abstract
This paper discusses the research and design of spatial-temporal relational model in WalkGIS platform, which complies
to the OpenGIS standards. The paper falls under the context of National High-tech Supporting project2. The
spatial-temporal relational model aims at spatial-temporal objects, and one spatial-temporal relation object corresponds
to several tense instances, comparing to the traditional object relation model for one instance with several tenses. Object
relation model is the special example of spatial-temporal model, which can be defined as single temporal model.
Spatial-temporal relational model establishes and maintains constraints and relationship in spatial objects and
temporal-serial instance relationship, performs the transformation of object-based discreet relationship (object-relation)
to object-based spatial-temporal relationship (object-spatial temporal relation), creates and constraints temporal relation
of instances in different times for one object and instance spatial relationship at different times. This article focuses on
temporal model management and design for the objectified spatial-temporal model. Spatial-temporal model supports multi-user and multi-scene. Firstly, multi-user online editing. Each version can be
edited independently. It checks interactively and coordinates version conflicts while editing and uploading. Secondly,
stream model, multi-version creates the stream model. Thirdly, offline capabilities. Fourthly, version compression.
Frequently altered versions can be combined into one version at the end of the year. Fifthly, version transfer. Any version
can be transferred and stored into another spatial database.
This paper covers spatial-temporal model definitions, model application scenario, model design constraints, version
conflicts and reconciliation, data structure design, version management design, etc...
Dynamic change of landscape patterns of Momoge wetland in the last two decades
Guanglei Hou,
Hongyan Zhang,
Yeqiao Wang,
et al.
Show abstract
Wetland degradation and its negative effect have long been considered as a hot yet complicated topic. Therefore, it has
significance to research landscape patterns and their dynamic changes. Based on Landsat-5 TM data in 1988, 2001, 2007
respectively, the dynamic change of landscape patterns in last two decades is quantitatively analyzed by conversion
matrix, landscape index model and centroid model for Momoge National Natural Reserve. The results are as followed: (1)
the area of farmland increased from 29594.934 hm2 to 34002.354hm2 during 1988-2007, but the wetland area decreased
from 68635.274 hm2 to 59356.598hm2 simultaneously. (2) Human and climate interference caused the change of
landscape patterns. In all three periods, landscape patterns of wetland became more fragmentized and the patch counts
were 160, 88, 91 respectively. The SHDI was 1.932, 1.770, 1.772 and SHEI was 0.879, 0806, 0.807 respectively. The
entironment of Momoge wetland worsened gradually, but the rate of degradation mitigated in some sort since 2001. (3)
Decrease of wetland area resulted in a shift of wetland landscape patterns centroid southeastward by 4454.95 meters.
Spatial index study for multi-dimension vector data based on improved quad-tree encoding
Yuxiang Li,
Hong Wang
Show abstract
Now the geographic information system obtains the widespread application in various fields. These small geographic
application systems, covering small regions, may manage large or medium scale data, but on the other hand in regard to
the large geographic information systems, managing entire national territory geography information, basically take the
small scale data as a foundation. Those system final users not only need to establish the corresponding application in the
entire country or the global spatial data, but they often even more pay more attention to some local data or the details.
Therefore it needs to establish an efficient spatial index for these multi-dimension vector data in the large geographic
information systems. This article introduced a method to improve quad-tree encoding. It is a kind of multi-encoding
system for multi-dimension vector data. It can provide variable resolution ability and make neighboring inquiry directly.
The method proved to have high level efficiency in organization of different origin, different projection and different
scale vector data. It accomplished an integrated information combination between large scale, high resolution maps
(mostly focus on cities) and small scale, wide scope maps including national or international data.
Spatial-Temporal Applications for Mobile, Wireless, and Location-based Service Networks
Analysis on the RINEX observations translated by Ashtech Solutions and TEQC
Caihong Zhang,
Hui Liu,
Rong Zou
Show abstract
Ashtech Solutions and TEQC are the software for GNSS data processing. One common function for both software is
translating binary data received by Ashtech receiver to standard RINEX format. Difference in centimeter between the
RINEX data translated by them is found in this paper. Moreover, the multi-path of the RINEX data translated by TEQC
is much more serious than that by Ashtech Solutions. The reasons caused large differences are analyzed in the paper, and
in our opinion, Ashtech Solutions smoothes the data during translating. Unfortunately, general users not only do not
know the default option of smooth, but also can not modify it. As it is well known, any correction should be avoided
when checking the quality. Otherwise, pseudo-results are obtained. Thus, it is not suitable to check the quality of a site
with the data translated by Ashtech Solutions. Nowadays, as there are so many different GNSS random processing
software, we have to be careful when using them.
Application of RS and GIS in soil erosion load evaluation: case study in Xingzigou basin, Shaanxi Province
Lian-Qi Zhu,
Wen-Bo Zhu
Show abstract
This paper studies the method and technique of soil erosion load estimation with RS and GIS, after analyzing for effects
of landform and vegetation factors on soil erosion, based on studies in the Xingzigou basin, Shaanxi Province. In order to
get property data of landform, DEM was used, which generates gradient, slope aspect, relative elevation, etc. In terms
of collecting data on vegetation coverage, we have analyzed indicating function of vegetation type, which affects change
in land cover with techniques of RS and others. With RUSLE, spatial variation of soil erosion modulus has been
simulated, and calculated total load of soil erosion in small basin, which is significance both in theory and in practice.
Principles of midline method and scale line method employed in ocean delimitation
Peng Hu,
Jiajun Zhou,
Hai Hu
Show abstract
This paper analyses marine delimitation theories of Midline (Mid-axis) and Scale line according to the definition of
midline provided by the United Nations Convention on the Law of the Sea (UNCLS). The authors discuss some faults of
midline method and point out that the tendency of marine delimitation technology will be all-shaped scale line method
on the Earth ellipsoidal surface. In the end of the paper, the authors introduce their foundational researches on midline
and scale line methods based on Map Algebra.
Design and application analysis of prediction system of geo-hazards based on GIS in the Three Gorges Reservoir
Show abstract
Although the project of the Three Gorges Dam across the Yangtze River in China can utilize this huge potential source
of hydroelectric power, and eliminate the loss of life and damage by flood, it also causes environmental problems due to
the big rise and fluctuation of the water, such as geo-hazards. In order to prevent and predict geo-hazards, the
establishment of prediction system of geo-hazards is very necessary. In order to implement functions of hazard
prediction of regional and urban geo-hazard, single geo-hazard prediction, prediction of landslide surge and risk
evaluation, logical layers of the system consist of data capturing layer, data manipulation and processing layer, analysis
and application layer, and information publication layer. Due to the existence of multi-source spatial data, the research
on the multi-source transformation and fusion data should be carried on in the paper. Its applicability of the system was
testified on the spatial prediction of landslide hazard through spatial analysis of GIS in which information value method
have been applied aims to identify susceptible areas that are possible to future landslide, on the basis of historical record
of past landslide, terrain parameter, geology, rainfall and anthropogenic activity. Detailed discussion was carried out on
spatial distribution characteristics of landslide hazard in the new town of Badong. These results can be used for risk
evaluation. The system can be implemented as an early-warning and emergency management tool by the relevant
authorities of the Three Gorges Reservoir in the future.
Research of spatio-temporal analysis of agricultural pest
Changwei Wang,
Deren Li,
Yueming Hu,
et al.
Show abstract
The increase of agricultural pest disasters in recent years has become one of major problems in agriculture harvest; how
to predict and control the disasters of agricultural pest has thus attracted great research interest. Although a series of
works have been done and some achievements have been attained, the knowledge in this area remains limited. The
migration of agricultural pest is not only related to the time variation, but also the space; consequently, the population of
agricultural pest has complex spatio-temporal characteristics. The space factor and the temporal factor must be
considered at the same time in the research of dynamics changes of the pest population. Using plant hoppers as an object
of study, this study employed the biological analogy deviation model to study the distribution of pest population in
different periods of time in Guangdong Province. It is demonstrated that the population distribution of plant hoppers is
not only related to the space location, but also has a certain direction. The result reported here offers help to the monitor,
prevention and control of plant hoppers in Guangdong Provinces.
Quantitative factor analysis of forest resources in Changbai mountain areas
Lingbin Yang,
Xia Zhang,
Jin Wu,
et al.
Show abstract
Nine forest characteristic indicators are developed for differentiating the features and laws of the forest geographical
distribution of the 22 cities (or counties) in Changbai mountain areas by factor analysis. It can be found from the factor
eigenvalue and cumulative contribution rate that the basic characteristics of forest composition can be conveyed by three
main factors, that is, the natural forest, plantations, and near mature forest, which reflect 86.7% of the overall forest
features information. According to the analysis of common degrees, the former three factors have reached more than
90% and the forest coverage and open forest volume features have achieved almost 80% while the over mature forest
area and young growth have got to 70%-75%, which determine the general characteristics of forest composition.
According to orthogonal factor scores, the contour map is plotted to disclose the features and laws of the forest
geographical distribution. In conclusion, there is obvious uniqueness and regionality for the characteristics and
geographical distribution of forest composition in Changbai mountain areas. The main factors restricting the quantity and
quality of forest are natural forest, plantations, and near mature forest. Quantitative factor analysis on the forest resources
in Changbai mountain areas can better reflect the characteristics of forest composition. In addition, the geographical
distribution laws of forest composition characteristics can also be revealed, providing a reliable scientific basis for the
rational exploitation of forest resources, the revitalization of Jilin economy, as well as the ecological environment
protection.
A method for estimating the landing area based on marine dynamic GIS
Lihua Zhang,
Fenzhen Su,
Shujun Li,
et al.
Show abstract
The estimation of a landing area plays an important role in landing decision. Due to the drawbacks and limitations of the
traditional static methods, a method for estimating the landing area based on marine dynamic geographic information
system is developed. Main natural geographic features affecting the landing feasibility are analyzed, visual models of the
features for dynamically estimating the landing area are constructed, and a quantitative and visual estimation for the
landing feasibility is performed. Experimental results indicated that the proposed method could estimate the landing
feasibility of areas digitally and dynamically based on the marine dynamic GIS.
Spatial and temporal variations in residential housing prices in Beijing
Yan Zhang,
Meng Lv,
Zhongdong Yin
Show abstract
During the past 10 years, the real estate industry in Beijing has been manifesting a strongly growing trend. Researching
on the distribution of house prices and their tendencies is helpful to grasp and predict the development of the real estate
industry and could be used as reference to city planning. 120 records of housing price data in 2005 to 2006 and open
prices in 38 developing projects from the first quarter of 2002 to the second quarter of 2008 were used in this study to
analyze the spatial and temporal variations of house price with geostatistical methods and nonlinear regression. Results
show that there was a very strong autocorrelation among the house prices in Beijing within the range of about 11 km in
2005 to 2006, which can be well fitted with the spherical model. The isogram of the house prices formed a group of
homocentric ellipses, with their long axis extending NW-SE, and the house prices decreased from the center to the
periphery. The spatial pattern of house prices in Beijing changed obviously from 2003 to 2006. Although both the spatial
patterns for the two periods were homocentric ellipses, the shapes of the ellipses and the directions of the axes changed
greatly. And there were more imbalances in 2005 to 2006. The house prices in the Huilongguan-Qinghe residential zone,
an example of the typical real estate industry in Beijing, kept growing from 2002 to 2008 and could be fitted with
exponential growth model.
Research on urban land grade adjustment based on digital land price model
Show abstract
In this research, the Digital Land Price Model was proposed to adjust the land grade based on the problem of benchmark
price during rectify the land grade. Chose the reasonable interpolation method and then make grid treatment, the
three-dimension land price model was obtained using the bargaining land price, which supported by the Arcview GIS.
The model provided the structure of land price. The price of each unit was calculated after interpolation, and then the
map of the land grade was estimated that compared with the original to make adjust.
The techniques and implementation of fast collision detection for three-dimension pipeline
Zhongliang Fu,
Shiwei Shao
Show abstract
In the design of engineering pipeline, spatial collision detection is always a necessary process. If the artificial
method is used, a heavy work load is always needed and omissions occasionally happens; if the method of
collision detection algorithm for three dimension object in graphics is used, the computation will increasing
sharply with the increase of pipeline number. Because the data size of three dimension pipeline is extremely
big, the key to solve collision problem is efficiency. In this paper, a new collision detection method for three
dimension pipeline is presented. The new method is composed of two parts: the coarse detection based on
Axis-Aligned Bounding Box and precise detection based on geometry model. The method abstracts the pipeline
to spatial line-segments with semantic information using geometry method. Firstly, an improved Axis-Aligned
Bounding Box algorithm is used to classify the pipelines. Finally, the result of coarse detection is used as initial
value, the geometry location relation is used to classify the pipelines, and then the shortest connecting lines
between pipelines are calculated. The experiment results show that, this method can detect collision
three-dimension pipeline efficiently.
Exploratory research on GIS software testing
Hongyan Wang,
Xinming Tang
Show abstract
To insure the quality of GIS software, and reduce the expense of development and maintenance, the normal and
independent software testing must be introduced into the process of GIS software development. Nevertheless, the whole
GIS community pays little attention to software testing while emphasizing on the signification of software quality and
security on the contrary. In the result, there is a lack of solutions of GIS software testing theoretically and systemically,
and also the technological criteria of software testing in GIS industry. This paper focuses on the methods of software
testing in GIS, especially TGIS and Spatial-Temporal Database. Some exploratory researches have been carried on in this
paper, and devoted the effort to the foundation work of GIS software testing designed based on the testing theory and the
empirical testing.
Zenith angle-based method for pattern recognition of landform elements using feature vector matching
Yanlan Wu,
Yongqiong Liu,
Hai Hu,
et al.
Show abstract
Pattern recognition of landform elements provides fundamental information for landscape research such as landscape
evaluation and hazard prediction. Totally different from the existing methods where surface geometrical forms are
commonly described by local curvatures, this paper uses zenith angle as a basis for pattern recognition in topography.
One property of zenith angle is a regional morphmetrical variable, which has potential to overcoming the lack of a
consideration of the center point a part of the regional terrain in curvature-based methods. Moreover, the zenith angles
are converted and stored in the form of a feature vector so that a feature vector matching approach can be applied to
implement the pattern recognition. The proposed method has been implemented and applied to a 10 m cell size DEM of
GISMAP Terrain (issued by Hokkaido-chizu in Japan) as a test case. Through visual observations, the transparent
composite map of the classification map and the shaded relief of DEM shows that the recognized patterns match the
relief well. The topography profiles also reveals that the results of pattern recognition are compatible with the
concave-convex property of the terrain shape. Moreover, the 3D maps of a local terrain data randomly taken from the
DEM for each of the feature matching cases show that the recognized pattern of the central point is matched well with
the characteristics of the surrounding topography.
A method of constructing geo-object ontology in disaster system for prevention and decrease
Show abstract
A kind of formal system, which can express clearly a certain entity or information, is needed to express geographical
concept. Besides, some rules explaining the interrelationship and action between different components are also required.
Therefore, the conception of geo-object ontology is introduced. It is a shared formalization and display specification of
conceptual knowledge system in the field of concrete application of spatial information science. It can constitute
hierarchy structure, which derives from the concept classification system in the geographical area. Its concepts can be
described by the property. Property sets can form a vector space with multi-dimensional characteristics. Geographic
space is composed of different types of geographic entities. And its concept is formed by a series of geographic entities
with the same properties and actions. Moreover, each of the geographic entities can be mapped to an object, and each
object has its spatial property, time information and topology, semantic relationships associated with other objects. The
biggest difference between ecumenical information ontology and geo-ontology is that the latter has the spatial
characteristics. During the construction process of geo-object ontology, some important components, such as geographic
type, spatial relation, spatial entity type and coordinates, time, should be included to make further research. Here, taking
disaster as an example, by using Protégé and OWL, combined methods used by constructing the geo-object ontology in
the form of being manual made by domanial experts and semi-automatic are investigated oriented to disaster to serve
ultimately geographic information retrieval service driven by ontology.
Application research of rough sets in the multi-elemental cooperative spatial analysis
Show abstract
Multi-elemental cooperative analysis can not only brings a large number of relevant information but fuzz up key
elements, so valid data excavating tools are needed to find element information which influences entities the most. Based
on the sample of bus site setting in a city, this paper employs Rough Sets method to analyze multi-elemental cooperation
which influence bus site grade and calculate importance of each element. Thus, multi-elemental cooperative analysis can
be realized. Compared with conventional multi-parameter analysis, this method based on data self-adapting is intelligent,
high-efficiency and have no use for manual intervention.
Hyperspectral assessment of nitrogen nutrition for winter wheat canopy using continuum-removed method
Show abstract
The hyperspectral reflectance of canopy of winter wheat and data of leaf nitrogen accumulation (LNA) were acquired in
primary growth stages under different nitrogen levels in order to monitor winter wheat status and diagnose nitrogen
using remote sensing method. A new method was developed to estimate the nitrogen nutrition of winter wheat using
continuum-removed method, which generally used in spectra analysis on rock and mineral. The continuum-removed
method was effectively used to magnify the object spectral absorption features, and it could be convenient to extract the
spectral absorption features. Based on the continuum-removed treatment and the correlation between absorption feature
parameters and LNA, results show that LNA increased with increasing the nitrogen fertilization. LNA increased from the
erecting stage to the booting stage and decreases from the booting to the heading stage under all nitrogen levels. It is the
VNIR regions that were sensitive to LNA. By continuum removal operation, it can be found that the method magnify the
subtle difference in spectral absorption characteristics arise from the nitrogen stress on winter wheat. At all stages, total
area of absorption peak, left area of absorption peak, right area of absorption peak increased with increasing the nitrogen
fertilization, whereas the normalized maximal absorption depth by area decreased. The correlation analysis indicated that
all the absorption characteristics parameters of continuum-removed spectra highly correlated with LNA, and the
correlation relationship of the whole growth cycle was stronger than that of any single growth stage. But the booting
stage is the best at the several single growth stages and the NMAD is the best absorption parameter to monitoring the
nitrogen of winter wheat canopy. The range 550 nm to 760 nm are the feature bands for extracting nitrogen information
of canopy. The regression analysis on the whole growth period showed that the all regression models between the
absorption characteristics parameters and LNA were all extremely significant (P<0.001).Therefore, continuum-removed
method is a feasible method for quantificational evaluation of winter wheat LNA.
Study on spatial structure of large scale retail stores based on space syntax: case study in Wuhan
Show abstract
This research analyzes the spatial pattern of large-scale stores based on space syntax theory and explores the correlation
between the variations in syntax accessibility and the spatial pattern of large-scale stores. This research develops a
framework of spatial topology analysis based on the space syntax theory, which includes the following modifications: the
trail to break the traditional long axial line network of space syntax and apply this partitioned network in the topological
analysis; the trail to analyze the bus route network; By taking both the syntax accessibility of road and bus network into
consideration, we produce the scopes of urban syntax centers of city level, local level and sub local level respectively. In
the analysis of the retail distribution pattern, the city level, local level and sub local level urban retail centers are
suggested respectively according to the spatial distributions of the quantity and scale of the retail stores. The spatial
distribution pattern of each retail format is studied as spatial correlations between the retail locations and the urban space
syntax centers based on a case study in Wuhan, China. The Space Syntax can be a useful tool to explain the allocation
logic of urban retail space in large cities. We suggest to apply the partitioned transportation network instead of the
traditional long axial line network.
Extraction method of suitable matching regions in the gravity-aided inertial navigation
Li Yan,
Xudong Ma,
Juan Shi,
et al.
Show abstract
The data organization of gravitational field is based on a form of Grid, which is similar to the data structure of DEM in the
terrain. So this paper proposes a method of gravitational field analysis for extracting features by adopting some spatial
analysis means of topography. First of all, the gravity anomaly data is used to calculate the roughness features of
gravitational field. after comparing and anglicizing the features, roughness features are selected as the feature factor of
gravity. Then, the method of calculating contour lines is applied to calculate region segmentation of roughness features and
extract the vector edge of the larger feature regions, and clustering analysis to these contour of the region. At last, the scope
line for Convex Hull of the region is calculated by the Convex Hull algorithm, and so as to obtain a more prominent region
(matching region) that have significant changes in gravity anomaly, which provide the necessary reference data for the
gravity-aided inertial navigation.
Scheme evaluation of urban design using 3D visual analysis
Xia Zhang,
Qing Zhu
Show abstract
The evaluation of urban landscape and the design of urban space are in need of a scientific visual analysis tool that can
wholly include the qualitative analysis, the quantitative analysis and the orientation analysis. With the outstanding
saving, management, visualization and analytical functions of 3D space information, 3DGIS can exactly provide
powerful technique support for this. Based on the humanistic analysis conception, the concept of visual openness index is
introduced, and some visual analysis functions are designed and implemented based on VGEGIS platform. Finally a case
study for the application of visual analysis is carried out and the results show that the urban design scheme evaluation is
improved distinctively.
Design and implementation of land reservation system
Yurong Gao,
Qingqiang Gao
Show abstract
Land reservation is defined as a land management policy for insuring the government to control primary land market. It
requires the government to obtain the land first, according to plan, by purchase, confiscation and exchanging, and then
exploit and consolidate the land for reservation. Underlying this policy, it is possible for the government to satisfy and
manipulate the needs of land for urban development. The author designs and develops "Land Reservation System for
Eastern Lake Development District" (LRSELDD), which deals with the realistic land requirement problems in Wuhan
Eastern Lake Development Districts. The LRSELDD utilizes modern technologies and solutions of computer science
and GIS to process multiple source data related with land. Based on experiments on the system, this paper will first
analyze workflow land reservation system and design the system structure based on its principles, then illustrate the
approach of organization and management of spatial data, describe the system functions according to the characteristics
of land reservation and consolidation finally. The system is running to serve for current work in Eastern Lake
Development Districts. It is able to scientifically manage both current and planning land information, as well as the
information about land supplying. We use the LRSELDD in our routine work, and with such information, decisions on
land confiscation and allocation will be made wisely and scientifically.
Power lines extraction from aerial images based on Gabor filter
Show abstract
With the development of aerial aircraft, it has been possible that using the small unmanned aerial vehicles (UAV) for
power line corridors surveillance. In Queensland, Australia, the local electric power company used the small UAV loaded
the ordinary digital camera for power line surveillance. In order to extract the power lines automatically from the
cluttered natural background aerial images, we propose a power line detection method for a vision based on UAV
surveillance system. A Gabor filter is developed to remove background noise from the images prior to the Hough
transform being employed to detect straight lines. The experiment on real image data demonstrates that the proposed
approach is effective.
GIS-assisted spatial analysis for urban regulatory detailed planning: designer's dimension in the Chinese code system
Yang Yu,
Zheng Zeng
Show abstract
By discussing the causes behind the high amendments ratio in the implementation of urban regulatory detailed plans in
China despite its law-ensured status, the study aims to reconcile conflict between the legal authority of regulatory
detailed planning and the insufficient scientific support in its decision-making and compilation by introducing into the
process spatial analysis based on GIS technology and 3D modeling thus present a more scientific and flexible approach
to regulatory detailed planning in China. The study first points out that the current compilation process of urban
regulatory detailed plan in China employs mainly an empirical approach which renders it constantly subjected to
amendments; the study then discusses the need and current utilization of GIS in the Chinese system and proposes the
framework of a GIS-assisted 3D spatial analysis process from the designer's perspective which can be regarded as an
alternating processes between the descriptive codes and physical design in the compilation of regulatory detailed
planning. With a case study of the processes and results from the application of the framework, the paper concludes that
the proposed framework can be an effective instrument which provides more rationality, flexibility and thus more
efficiency to the compilation and decision-making process of urban regulatory detailed plan in China.
Public facility planning in urban villagers' community based on Public Participation GIS: a case study of Wuhan new urban areas
Jun Li,
Zheng Zeng,
Yang Yu
Show abstract
As a unique group in China's urbanization, "urban villager" is the concern of various parties of the society. From
"farmers" to "urban residents", urban villagers' means of production and life style change dramatically. At present, public
facility planning in urban villagers' community always fail to meet their particular demands. Taking PPGIS as an
instrument, the paper analyzes the present status of public facilities in urban villagers' community and the new demand
on public facilities from the changing production means and life style. The purpose is to put forward suggestions for
public facility setting in urban villagers' community and offer theoretic guidance and proposal for Wuhan new urban
areas. PPGIS is gradually being applied to social science researches in recent years. Through the integrated platform, it
can achieve the objective of communication, coordination, cooperation and collaboration of different interests. In this
research, ephemeral mapping, sketch mapping, scale mapping and aerial photographs are used to acquire spatial data of
public facilities and attribute data of urban villagers in their community. Through the comparison of data, the research
shows that while urban villagers in Wuhan new urban areas gradually accept city life, they inevitably maintain certain
rural habits and customs. Therefore, the public facility planning in this particular kind of communities can neither be
treated equal as countryside facility planning, nor simply adopt the practice in urban residential areas' planning; rather
the planning system should take into account facilities of different categories at all levels, communities of different types
and residential groups.
The comparison of spatial accessibility measures between non-obstacle and obstacle oriented based on gravity model
Zhi-Gang Han,
Cai-Hui Cui
Show abstract
Spatial accessibility denotes the ease with which activities may be reached from a given location using a particular
transportation system. There are a number of accessibility measures methods and models, such as time of access to city
centre, mean travel costs and opportunity accessibility. But these methods or models ignore the existence of obstacles. In
fact, there are many kinds of obstacles in the world, such as rivers, railways, etc. The paper reviews the progress of
accessibility measures, and introduces the obstacle to the accessibility measures. Meanwhile, through the analysis of A*
algorithm, the advantage of A* algorithm that could avoid obstacles is put forward. Based on the above mentioned, the
obstacle oriented accessibility measures based on simple gravity model is discussed in details. Finally, a case study is
fulfilled by comparison between the obstacle oriented and non-obstacle accessibility measures.
A improved particle swarm optimization based on cloud model with implications for urban land use planning
Show abstract
In order to solve the dependence on the problem of patch technology in the constrained optimization of Particle Swarm
Optimization (PSO), conversion will be achieved on the qualitative and quantitative of feasibility rules of the PSO
algorithm by the uncertain illation and figure characteristics of cloud .The quantification of binding correction factor will
be done in order to realize the common patch methods of different issues. The improved algorithm will be applied to the
urban land use planning of Nanning and Yulin city in Guangxi. Quantifying the land conversion factor and combining
with spatial analyses technology, analyzing and contrasting the land conversion area of the two cities, this improved
algorithm will be proved to settle different problems.
Sustainable development strategy based on GIS
Show abstract
The key problem for implementation of the sustainable development is to design the strategy and policy which
incorporates the environmental impacts. This paper puts forward a new model based on GIS of ecological environment
protection and sustainable development based on estimating and assessment. The environmental carrying capacity and
developing intensity of studied area are analyzed, the ecological security and the level of sustainable development are
evaluated, and also the constraints are discussed. According to this analysis, the range of Lichuan is divided into four
regions. On the foundation of distinctive characteristics of each area, the designation of the industrial development and
environment protection have been ensured; after that, the environmental impact of the given strategies has been
identified and predicted; finally, several mitigation measures are suggested.
Accuracy analysis of exterior orientation elements on vertical parallax in POS-supported aerial photogrammetry
Show abstract
This paper analyzes the effect of exterior orientation elements on vertical parallax, especially using the orientation
parameters of aerial images obtained by a POS (Positioning and Orientation System) after calibration. Firstly, based on
the theory of analytical relative orientation of consecutive photo connection, the exterior orientation elements can be
easily translated to relative orientation elements. Then, the formula of vertical parallax can be deduced. The results of
vertical parallax in left image space coordinate system are compared with the results calculated in the image coordinate
system which are parallel to those of the object coordinate system. The validity and feasibility of the mathematical model
are tested using two sets of actual data at different images scales. Finally, the differences between the effects of exterior
orientation parameters on vertical parallax are compared using exterior orientation parameters obtained by traditional
bundle block adjustment and by a POS after calibrated. And how the single element of exterior orientation effected on
vertical parallax and how they worked together are analyzed. The empirical results indicate that the effects of different
elements of exterior orientation on vertical parallax are different, all exterior orientation parameters can be affected by
each other, so the overall effect of vertical parallax accuracy can be restricted by all exterior orientation parameters.
Pattern analysis of geo-referenced motion processes
Show abstract
Spatial motion is a part of dynamic geographic phenomena which could be directly observed by human on a certain
geographic scale. Most motion processes are generally regulated by external geographical environment, or some social
criterions. A geo-referenced pattern states an argument that the similar motion processes perhaps have homological
motion characteristics, patterns, trends, and etc. Since this paper concentrates on process model of motion phenomena,
firstly we introduce some descriptors for expressing motion process, which include motion trajectory, process area, and
process extent. The second, in order to describe a correlation between motion process and geographical feature, we
introduce an initial concept of constrained geometry, which is consisted of constrained point, constrained line, and
constrained area. Based on definition of constrained geometry, the computing models for three motion patterns named as
location-referenced pattern, path-referenced pattern, and region-referenced pattern are constructed. In the end, we use
historical typhoon data within the past 3 years from 2004 to 2006 for an experiment, in which 75 typhoon activities are
taken as the example for exemplifying the validation of region-referenced motion pattern. The results confirm that the
existent region of typhoon activities in a year is similar enough to other years.
Analysis on influence of non-point source pollution in Fuhe watershed based on the SWAT model and ArcGIS
XianChun Guo,
BaoGui Zhao,
DaJun Li,
et al.
Show abstract
Precipitation and topography are the most important influence factors of non-point source pollution, especially for soil
erosion. Based on the SWAT model and ArcGIS, the Fuhe watershed was divided into 50 sub-basins. Combined with the
standard deviation gradational method, statistical analyses on characteristics of the spatial and temporal variation of
rainfall in Fuhe watershed were carried out1 based on the rainfall observation data from January 1st, 1986 to December
31st, 2005 from 25 stations within the watershed. The results showed that the spatial-temporal distribution of
precipitation was uneven. Spatially, the average annual rainfall was divided into five grades. Temporally, there was great
variation in inter-year precipitation. The inter-year rainfall distribution was extremely uneven, focused on March to June,
which accounted for 56 % of the total. The analysis of topography in Fuhe watershed was carried out by using the
standard deviation gradational method. The slope of the basin was divided into five grades. The basin was divided into
four grades of the NPS risk by using pollution average slope and rainfall to calculate a weighted value of the risk of NPS
pollution. The first and second level district were mainly distributed in the western, the eastern area, and sporadically
distributed in certain areas of the southern in the watershed, which accounted for 55.6% of the basin area; the risk values
were very large in these districts.
Spatio-temporal contextual approaches to mapping land cover change based on remote sensing imagery
Show abstract
This paper explores data-driven methods for quantifying and incorporating spatio-temporal contextual information in the
mapping of land cover change. In remote sensing, area classes of land cover are typically mapped via statistical
manipulation of feature-space measurement, e.g., reflectance data, and other ancillary data. Contextual information has
been known to have the potential of increasing the accuracy of land cover classification and change detection, on the
ground that land cover often exhibits spatial and temporal correlations and, as such, should be properly accommodated.
In Bayesian methods, a priori probabilities of class occurrences can be considered as contextual information, which are
combined with class-conditional probability densities to arrive at discriminant decisions with minimized
misclassification. These prior probabilities may be made to vary locally to honor variability in the strengths of spatial
dependence in class occurrences. For deriving local prior joint probabilities in land cover co-occurrences over time, a
modified Expectation and Maximization (EM) algorithm was developed, in which a local window size can be adjusted in
the light of spatial dependences inferred from class probability densities computed from spectral data. Empirical studies
were performed using bi-temporal Landsat TM image subsets in Wuhan, which confirmed the comparative benefits of
incorporating localized prior probabilities in land cover change detection.
Building MapObjects attribute field in cadastral database based on the method of Jackson system development
Show abstract
ESRI's GIS components MapObjects are applied in many cadastral information system
because of its miniaturization and flexibility. Some cadastral information was saved in cadastral
database directly by MapObjects's Shape file format in this cadastral information system. However,
MapObjects didn't provide the function of building attribute field for map layer's attribute data
file in cadastral database and user cann't save the result of analysis. This present paper designed
and realized the function of building attribute field in MapObjects based on the method of
Jackson's system development.
Managing landscape connectivity for a fragmented area using spatial analysis model at town scale
Shiliang Liu,
Yuhong Dong,
Wei Fu,
et al.
Show abstract
Urban growth has great effect on land uses of its suburbs. The habitat loss and fragmentation in those areas are a main
threat to conservation of biodiversity. Enhancing landscape functional connectivity is usually an effective way to
maintain high biodiversity level in disturbed area. Taking a small town in Beijing as an example, we designed potential
landscape corridors based on identification of landscape element quality and "least-cost" path analysis. We described a
general approach to establish the corridor network in such fragmented area at town scale. The results showed that
landscape elements position has various effects on landscape suitability. Small forest patches and other green lands such
as meadow, shrub, even farmland could be a potential stepping-stone or corridor for animal movements. Also, the
analysis reveals that critical areas should be managed to facilitate the movement of dispersers among habitat patches.
Development of a GIS database for Iraqi marshlands ecosystem studies
Show abstract
One of the World's most famous wetland ecosystems centered on the Euphrates and Tigris river basin and its delta
regions in the Middle East was very nearly destroyed by the actions of government. A high quality database is the
starting point for any GIS application. For Mesopotamian Marshlands, a large amount of spatial data has been
accumulated by numerous ecosystem studies. This study encompasses to introduce a GIS database development in
support of these studies. The study includes the following components: the *establishment of a data server conveniently
accessible to all users; the selection of appropriate RDBMS/GIS software for both attribute data and geographic data; the
development of a general data format and database structure; the formalization of data management procedures,
including input, update, conversion and the implementation of data query and retrieval utilities for end users to search,
display, print or plot. The increasing focus on integrating socio-economic and biological information with remote
sensing and GIS technology can only help to further our understanding and capacity to manage ecosystems in a more
sustainable manner.
Integrating models to predict the reason of unknown-caused grassland fire based on GIS
Zhengxiang Zhang,
Guanglei Hou,
Hongyan Zhang,
et al.
Show abstract
This study predicts the reason of unknown-caused fires that occurred in grassland in the east of Inner Mongolia, China.
GIS and logistic regression are used to build the predicting models. The causes of grassland fires were classified as
vehicle, production, living and lighting. The areas were divided into fired and unfired grid cells (500m*500m) with
spatial analysis, in order to determine the spatial factors and weather factors, such as the nearest distance to villages,
roads, fields etc. Logistic regression was used to build predictive models of the probability for each reason of grassland
fires. Four probabilities of each unknown-caused grassland fire were calculated and the maximum value expresses the
fire reason. The results show that natural fires are less than human-caused grassland fires and they can be used in fire risk
models and to support fire management decision-making. These methods would take advantage to the other grassland
fire studies, such as fire ecology, fire weather, fire cycle, etc.
Direction difference in terrain features extraction
Show abstract
Geographic information obtained from sensors inevitably contains errors for all kinds of signal interference. How to
automatically and effectively process geographic information to build qualified DEM has always been an important topic
in relevant theoretical field. Automatic identification of gross errors is usually based on topographic trend. However, it's
difficult to directly extract topographic trend from original sampling points, and there is contradictory of causal
interoperability. This paper advances a new idea to solve the problem. Firstly, accurate terrain feature planimetric
position is extracted. On this basis, the corresponding elevation is corrected. Then topographic trend is constructed. The
key to exact accurate terrain feature planimetric position is to reduce the impact of errors. Therefore, direction difference
in terrain features extraction is brought forward in this paper. This method equalizes the impact of errors, and terrain
features become marked. The experimental results show that this method can effectively improve robust capacity in
terrain features extraction. Topographic trend constructed by this method is well consistent with the actual terrain,
especially in the region of identical slope as well as the ridge and valley axes.
Urban landscape change analysis using satellite imagery and support vector machines
Show abstract
We used a change detection approach based on support vector machine (SVM) to analyze two remotely sensed images in
order to analyze urban landscape change on high-dense urban use (HDU), medium-dense urban use (MDU) and
low-dense urban use (LDU) in Kunming, China. These two images were subset of a TM image acquired on 16 August
1992 and an ETM+ image acquired on 2 November 2000, respectively. First, we used SVM to classify each subset into
HDU, MDU, and LDU. Then, we compared the label values of classified data pixel by pixel to analyze urban landscape
changes. In order to obtain high quality training data under the circumstance that existing classification products of
sampling area were not available, we proposed a second sampling method to assure obtaining satisfactory training data.
The kernel function of SVM was radial basis function (RBF). Optimal model with the best penalty parameter C and the
kernel parameter gamma was obtained through training samples. We tested the approach in three sites: northern
Kunming, southern Kunming and entire Kunming. Results indicate that the overall urban use has substantially increased
during 1992- 2000, while the substantial growth in high-density urban use was achieved at the cost of low-density urban
use and partially medium- density urban use.
Spatial-Temporal Data Capturing
Massive spatial data network service architecture based on double-cluster
Show abstract
It is the tendency for the development of massive spatial data network service to use cluster to enlarge load capacity of
spatial data server. In this paper, we use the OSD (Object-based Storage Device) storage cluster as the shared storage of
LVS (Linux Virtual Server) server cluster, and use the servers in the server pool of the LVS server cluster as the storage
client of the OSD storage cluster, to build a scalable massive spatial data network service architecture, which uses the
high scalability of the LVS server cluster and the OSD storage cluster to avoid the bottlenecks of massive spatial data
network service bandwidth and storage I/O throughput.
Several load balance scheduling algorithms embedded in the LVS server cluster can satisfy the demand of load balance
in many applications. But those algorithms can't optimize load balance of spatial data servers, regardless of the features
of spatial data. Spatial data in large scale network service application is generally organized according to the global
longitude and latitude, and managed according to the principle "vertical hierarchies and horizontal dividing". According
to the features of spatial data, we optimize the scheduling algorithm to enhance the Cache utilization efficiency for single
spatial data server.
2-D tiles declustering method based on virtual devices
Show abstract
Generally, 2-D spatial data are divided as a series of tiles according to the plane grid. To satisfy the effect of vision, the
tiles in the query window including the view point would be displayed quickly at the screen. Aiming at the performance
difference of real storage devices, we propose a 2-D tiles declustering method based on virtual device. Firstly, we
construct a group of virtual devices which have same storage performance and non-limited capacity, then distribute the
tiles into M virtual devices according to the query window of 2-D tiles. Secondly, we equably map the tiles in M virtual
devices into M equidistant intervals in [0, 1) using pseudo-random number generator. Finally, we devide [0, 1) into M
intervals according to the tiles distribution percentage of every real storage device, and distribute the tiles in each interval
in the corresponding real storage device. We have designed and realized a prototype GlobeSIGht, and give some related
test results. The results show that the average response time of each tile in the query window including the view point
using 2-D tiles declustering method based on virtual device is more efficient than using other methods.
Research on land information web query service for public
Dongdong Liang,
Lin Li,
Pingchao Song,
et al.
Show abstract
With economics developing fast and internet spreading extensively, the public strongly desire to know about land
information. Especially, the policy, Land registration information available to the public inquiry approach, has been
executed since March 1st, 2003, which gives the Land Department with guidance to build land information web query
service for public. Land information web query service for public requires Land Management Department to provide
land registration information which contains attribute and graphics information. When it comes to querying attribute
information, precise and fuzzy query methods are commonly used in realistic applications. To improve the speed and
accuracy of fuzzy query, Chinese word segmentation method is currently used. Especially, there is no previous example
by this method used in cadastre information inquiry. Meanwhile, as for querying lands' spatial information, it is
necessary to query attribute information before retrieving the actual graphics information. Then turning to the map
service, eagle eye can show which part of whole cadastre map the specified cadastre land located in. But it is obvious the
display speed of eagle eye is not as fast as that of cadastre map. Hence, we try to implement the multi-level query with
frame selection on cadastre map and identify the different cadastre land with different colors, as eagle eye's display and
panning speed are also accelerated. The accomplishments of our research have been applied to Land information query
system of Ningbo. It is hoped that the solutions in this system will help to develop and study analogous issues.
WebGIS based on semantic grid model and web services
WangFei Zhang,
CaiRong Yue,
JianGuo Gao
Show abstract
As the combination point of the network technology and GIS technology, WebGIS has got the fast development in
recent years. With the restriction of Web and the characteristics of GIS, traditional WebGIS has some prominent
problems existing in development. For example, it can't accomplish the interoperability of heterogeneous spatial
databases; it can't accomplish the data access of cross-platform. With the appearance of Web Service and Grid
technology, there appeared great change in field of WebGIS. Web Service provided an interface which can give
information of different site the ability of data sharing and inter communication. The goal of Grid technology was to
make the internet to a large and super computer, with this computer we can efficiently implement the overall sharing of
computing resources, storage resource, data resource, information resource, knowledge resources and experts resources.
But to WebGIS, we only implement the physically connection of data and information and these is far from the enough.
Because of the different understanding of the world, following different professional regulations, different policies and
different habits, the experts in different field will get different end when they observed the same geographic phenomenon
and the semantic heterogeneity produced. Since these there are large differences to the same concept in different field. If
we use the WebGIS without considering of the semantic heterogeneity, we will answer the questions users proposed
wrongly or we can't answer the questions users proposed. To solve this problem, this paper put forward and experienced
an effective method of combing semantic grid and Web Services technology to develop WebGIS. In this paper, we
studied the method to construct ontology and the method to combine Grid technology and Web Services and with the
detailed analysis of computing characteristics and application model in the distribution of data, we designed the WebGIS
query system driven by ontology based on Grid technology and Web Services.
Research on intelligent push of spatial information service based on context-sensitive
Show abstract
Spatial information services are complicated and various nowadays, so how to push appropriate services according to
users' real-time spatial context intelligently is a problem needed to be solved urgently. This paper summarizes the context
of geospatial information, and puts forward the features of context-sensitive geospatial information services as well as
formal model. A mechanism of pushing services intelligently was proposed aiming at users' features and personalized
using demands, by studying the key operations of the context sensitive geospatial information services, and the storage,
management as well as user pattern of the geospatial information service.
Research on sharing platform of urban spatial information service
Show abstract
With the development of GIS, intelligent management and networking, sharing the urban spatial information is becoming
more and more important. This paper researches four important aspects of building the sharing platform of urban spatial
information service, such as data organization, platform structure, application modes and key technologies used. Spatial
data, as the dissemination vector of the spatial information, have a very important position in sharing the urban
information services. In this paper, two main spatial data models are used to organize the required data. One is the
multi-scale Pyramid model with sole element to deal with the vector data, the other is the tile Pyramid model to deal with
the raster data. Taking into account the characteristics of the sharing platform such as multi-user, multi-demand,
multi-purpose, and multi-functional, two modes namely Browser/Server (B/S) and Client/Server (C/S) are used to
construct the entire sharing platform structure. The ultimate goal of building this sharing platform is to apply it in the
urban construction to satisfy peoples' needs. So we must to select the suitable application mode. Finally, this paper
introduces some key technologies used and the realized sharing platform of Tianjin urban spatial information service.
Research on models of Digital City geo-information sharing platform
Hanwei Xu,
Zhihui Liu,
Rami Badawi,
et al.
Show abstract
The data related to Digital City has the property of large quantity, isomerous and multiple dimensions. In the
original copy method of data sharing, the application departments can not solve the problem of data updating and data
security in real-time. This paper firstly analyzes various patterns of sharing Digital City information and on this basis the
author provides a new shared mechanism of GIS Services, with which the data producers provide Geographic
Information Services to the application users through Web API, so as to the data producers and the data users can do their
best respectively. Then the author takes the application system in supermarket management as an example to explain the
correctness and effectiveness of the method provided in this paper.
Research on the application of GIS and sensor network in the building settlement observation
Yan Lv,
Yi Zhu
Show abstract
In this paper, it sets up the model of the building's settlement observation and provides the property of the application
about GIS technology and Sensor network. To explore the running system can guarantee the construction quality and the
using safety. To explore the process of setting up the real-time monitoring system who bases on sensor network
technology for the data collection has some certain applications in practical engineering.
A system architecture of GIS middleware support for context-sensitivity
Zhongliang Cai,
Min Weng,
Yayan Li,
et al.
Show abstract
GIS middleware is a mediator between application (or logical level) and basic services (or physical level), which is
a key part of GeoInformation web services, can adapt to the context changes including spatial-temporal data, devices,
situation of user, and services. There are many researches achievements of context-sensitive pervasive computing
middleware existed. But in the GIS Field, it is very little about research on architecture of context-sensitive spatial
information service middleware.
This paper focuses on the system architecture of GIS middleware to support the building of context-sensitive
applications. Four main components of GIS middleware: GIS Core Service, Context Manager, Data Adapter, and GIS
Service Provider, are introduced in detail.GIS middleware is a mediator between application (or logical level) and basic services (or physical level), which is
a key part of GeoInformation web services, can adapt to the context changes including spatial-temporal data, devices,
situation of user, and services. There are many researches achievements of context-sensitive pervasive computing
middleware existed. But in the GIS Field, it is very little about research on architecture of context-sensitive spatial
information service middleware.
This paper focuses on the system architecture of GIS middleware to support the building of context-sensitive
applications. Four main components of GIS middleware: GIS Core Service, Context Manager, Data Adapter, and GIS
Service Provider, are introduced in detail.
A research on spatial information service based on geo-ontology
Show abstract
Geographic Information Services is the services for geographic information, including its geographic data services and
geographic information systems information processing services. Geographic Information Services, its key is to realize
the standardization of geographical information, as well as geographic information processing versatility, just not far
from the conversion of geographic data to share information, only at a higher level of different applications and systems
asked to cooperate with each other to achieve interoperability, in order to achieve the real purpose of geographic
information services.A research on geo-ontology is the important content of Geographic Information Science and Digital
Earth. The ontological foundation for Geographic Information Science is one of four new research fields that were
proposed by UCGIS (University Consortium for Geographic Information Science) in 2000. In 2002 Research Agenda,
the spatial ontology is the first topic of the ten Long-term Research Challenges. By the geo-spatial information semantic
expression and semantic share based on ontology, the concepts of single community are expanded to more wide range
gradually and are linked with Internet. Through the semantic description of service based on ontology, Web services can
be automatic found out, composed, implemented and supervised. In this paper, based on the existing GIS database and
having established geographic information field ontology, we will establish an application ontology database which is
suitable for geographic data. Description Logic designating the corresponding rules knowledge, between the spatial
database and ontology database, the difference ontology database building a definite correlation, the paper will propose a
method on ontology-driven spatial data query. When inquiring a spatial entity, through the logic computation of ontology
database, we can gain the query results, and return the final results. In the last, we will take tobacco planting query of
digital tobacco as an example to test the method whether is feasible and effective.
A SOA-based approach to geographical data sharing
Zonghua Li,
Mingjun Peng,
Wei Fan
Show abstract
In the last few years, large volumes of spatial data have been available in different government departments in China, but
these data are mainly used within these departments. With the e-government project initiated, spatial data sharing
become more and more necessary. Currently, the Web has been used not only for document searching but also for the
provision and use of services, known as Web services, which are published in a directory and may be automatically
discovered by software agents. Particularly in the spatial domain, the possibility of accessing these large spatial datasets
via Web services has motivated research into the new field of Spatial Data Infrastructure (SDI) implemented using
service-oriented architecture. In this paper a Service-Oriented Architecture (SOA) based Geographical Information
Systems (GIS) is proposed, and a prototype system is deployed based on Open Geospatial Consortium (OGC) standard
in Wuhan, China, thus that all the departments authorized can access the spatial data within the government intranet, and
also these spatial data can be easily integrated into kinds of applications.
Spatial-Temporal Data Modeling
Interactive decision-making support model in MOSD
Yang Liu,
Ze-ying Lan,
Yao-lin Liu,
et al.
Show abstract
The Multi-objective spatial optimization problem is common in the word, which usually has a set of
non-dominated resolutions, also called Pareto resolutions, instead of a single ideal one. So, the
Multi-objectives spatial decision support system (MOSDSS) has two vital basements: how to acquire
all the Pareto resolutions by Multi-objective optimization arithmetic, and how to analysis and appraise
the candidates to determinate the final satisfying solution. At present, there are abundant research fruit
for the former problem, however the latter one hasn't attracted abroad attention in the field. Nowadays,
the findings about analyzing and evaluating the Pareto resolutions mainly focus on three aspects: the
visual expression of candidates, appraising the comparability among the solutions, and designing the
prototype system of visual support tools, which are lack of systemic conclusion and summarization.
Hence, this paper emphasizes the latter problem of MOSDSS and puts up an interactive
decision-making support model to largely improve the efficiency of analyzing and evaluating the
Pareto resolutions. This model is composed of 3 pivotal parts: the geographic brush mechanism, the
similarity querying operators as well as the interactive searching method. Then, the paper designs a
prototype system on the base of the model, which is successfully tested in the exam.
The study of noise filtering algorithm experiment on spatial domain and frequency domain of hyperspectral image
Show abstract
The study of hyperspectral remote sensing data noise filtering algorithm is the key to improving data analysis. In
this paper, to remove the stripe noise in spatial domain smooth filtering algorithm by row was used, while the wavelet
threshold denoising method was used to filter random noise in spectral domain. The former was tested on actual data and
got better results comparing with other moment matching methods. Not only was the stripe noise weakened well, but
also the consistency of mean value curve was retained. Through the spectrum domain wavelet de-noising,the image is
more smooth adopting soft threshold denoising method comparing with hard threshold denoising method, this proves
that the soft threshold denoising filters the good effect. Experimental results demonstrated that the quality of the image
was improved and the radiative feature was retained.
A regression-kriging model for estimation of rainfall in the Laohahe basin
Hong Wang,
Li L. Ren,
Gao H. Liu
Show abstract
This paper presents a multivariate geostatistical algorithm called regression-kriging (RK) for predicting the spatial
distribution of rainfall by incorporating five topographic/geographic factors of latitude, longitude, altitude, slope and
aspect. The technique is illustrated using rainfall data collected at 52 rain gauges from the Laohahe basis in northeast
China during 1986-2005 . Rainfall data from 44 stations were selected for modeling and the remaining 8 stations were
used for model validation. To eliminate multicollinearity, the five explanatory factors were first transformed using factor
analysis with three Principal Components (PCs) extracted. The rainfall data were then fitted using step-wise regression
and residuals interpolated using SK. The regression coefficients were estimated by generalized least squares (GLS),
which takes the spatial heteroskedasticity between rainfall and PCs into account. Finally, the rainfall prediction based on
RK was compared with that predicted from ordinary kriging (OK) and ordinary least squares (OLS) multiple regression
(MR). For correlated topographic factors are taken into account, RK improves the efficiency of predictions. RK
achieved a lower relative root mean square error (RMSE) (44.67%) than MR (49.23%) and OK (73.60%) and a lower
bias than MR and OK (23.82 versus 30.89 and 32.15 mm) for annual rainfall. It is much more effective for the wet
season than for the dry season. RK is suitable for estimation of rainfall in areas where there are no stations nearby and
where topography has a major influence on rainfall.
A new practical methodology of the coal bed stability evaluation: the trend and variation method
Yingchun Wei,
Daiyong Cao,
Juemei Deng
Show abstract
The coal bed stability classification is correct or not, which relates to directly the geological exploration type of coal
resources and the correct assessment of the reasonable development and utilization value. Therefore, the study of the coal
bed stability is very important. Based on the knowledge that the coal thickness change has the regional change and the
partial change in the spatial distribution, and the disadvantages of the quantitative mathematical statistics methods, this
article presented the new method of trend surface analysis and mathematical statistics combination, that is, the trend and
variation method, to the quantitative evaluating coal bed stability, established the indicator system, including the minable
index, the mean, the Coefficient of variation, the trend surface times, the trend surface fitting of the coal bed thickness,
and the standard of the coal bed stability types. Took No.2 coal bed of Baie detailed exploration area in Shanxi as an
application example, and it proved that the trend and variation method has obvious advantages on the coal bed stability
evaluation, with making detailed contrasts and analysis of the results, which are evaluated respectively by the newly
presented the trend and variation method and the traditional mathematical statistics method. The trend and variation
method can reflect the discrete degree of the different coal bed thickness change and the spatial distribution and relativity
of these coal thickness points value.
Research on the comparison of extension mechanism of cellular automaton based on hexagon grid and rectangular grid
Show abstract
Historically, cellular automata (CA) is a discrete dynamical mathematical structure defined on spatial grid. Research on
cellular automata system (CAS) has focused on rule sets and initial condition and has not discussed its adjacency. Thus,
the main focus of our study is the effect of adjacency on CA behavior. This paper is to compare rectangular grids with
hexagonal grids on their characteristics, strengths and weaknesses. They have great influence on modeling effects and
other applications including the role of nearest neighborhood in experimental design. Our researches present that
rectangular and hexagonal grids have different characteristics. They are adapted to distinct aspects, and the regular
rectangular or square grid is used more often than the hexagonal grid. But their relative merits have not been widely
discussed. The rectangular grid is generally preferred because of its symmetry, especially in orthogonal co-ordinate
system and the frequent use of raster from Geographic Information System (GIS). However, in terms of complex terrain,
uncertain and multidirectional region, we have preferred hexagonal grids and methods to facilitate and simplify the
problem. Hexagonal grids can overcome directional warp and have some unique characteristics. For example, hexagonal
grids have a simpler and more symmetric nearest neighborhood, which avoids the ambiguities of the rectangular grids.
Movement paths or connectivity, the most compact arrangement of pixels, make hexagonal appear great dominance in
the process of modeling and analysis. The selection of an appropriate grid should be based on the requirements and
objectives of the application. We use rectangular and hexagonal grids respectively for developing city model. At the
same time we make use of remote sensing images and acquire 2002 and 2005 land state of Wuhan. On the base of city
land state in 2002, we make use of CA to simulate reasonable form of city in 2005. Hereby, these results provide a proof
of concept for hexagonal which has great dominance.
Massive spatial data materialization method based on ArcGIS engine
Lihong Shi,
Haiyong Li
Show abstract
With the application of geographic information becoming more extensive, spatial data model based on geographical
entities begins to be built and developed. Spatial data model based on entities is a new generation combining
object-oriented technology with GIS technology. And it is the future trends of the spatial data model development. It
effectively integrates spatial data with attribute data to express the geographic entities which are objective existence.
This method takes great advantages to deal with the complex geographical phenomenon. In this paper, through the
research of the geographical entity data model, the method of massive spatial data entity building based on ArcGIS
Engine is proposed. According to the characteristics of national fundamental geographic information data, we carry out
the materialization operation to the data and establish the geographic entity database of national fundamental
information. And we apply the results in e-government geographic information general platform. The experiment results
show that the spatial entities data is more humanistic in the expression for the objective world and more suitable for the
trend of GIS application to popular.
Dynamic study of land-use in Yining City
Jiangping Wang,
Lu Wei
Show abstract
Based on models of land-use, the paper analyzes urban sprawl from the macroscopic to the micro level, predicts
the demand for construction land in the city expansion, and presents the law between total amount of urban land
demand and urban space expansion. Then by combining the data with current urban land and natural resources round
the city, the paper appraises the rationality of the developed-land which will have changed their use-nature, to
appraisal the feasibility and utilization ratio of the undeveloped land and nature resource which will be developed in
nearly future, find out the irrationality that may appear in the urban space expanding, thus restrain through planning
and policy. With the rapid develop of western regions in recent years, different with the eastern coastal zone; the
western city is beginning its own urbanization process. Yili Prefecture, as the window of the development of western
regions, is expected to see fast development within a few years. Meanwhile, to Yili Prefecture, the topographical
ground form condition is complicated, the natural resources is extremely abundant, once it is destroyed will cause
irretrievable losses. Under this background, how to handle the relation between city's development and natural
environment and resources well, taking the urban development path that can be constant becomes the important subject
that we can't avoid. So this paper uses linear regression mode and dynamics, offer valuable reference for smooth
development of the city.
An improved Voronoi diagram model based on fuzzy interval theory
Beibei Yan,
Zhenfeng Shao,
Yang Zhou,
et al.
Show abstract
Considering that the application of traditional Voronoi diagram in spatial division ignores the impact of road hierarchy,
speed, road-block, one-way and some other influential factors on proximity, an improved Voronoi diagram model based
on fuzzy interval theory is proposed in this paper by introducing different influential factors into the construction of
Voronoi diagram in order to enhance the accuracy of spatial division and to meet application requirements.
The idea of our improved Voronoi diagram model can be summarized as follows: Firstly, initial Voronoi diagram is built
via point by point insertion algorithm. Secondly, fuzzy interval on all Voronoi edges is generated via geometric
algorithm and is further used to represent each edge of Voronoi polygons. The size of fuzzy interval is determined by
taking all influential factors into consideration. Thirdly, an improved Voronoi diagram with fuzzy boundaries is provided
in which the proximity relationships between points in the fuzzy interval and the sites of Voronoi polygons which own a
public edge are all proposed to be the nearest. Finally, the validity and performance of our improved Voronoi diagram is
demonstrated through a typical application in emergency response system, in which the actual path distance is acted as
influential factor. Experimental results show that with our improved Voronoi diagram optimal attendance station can be
localized quickly and emergency response efficiency can be enhanced obviously. Besides, classification accuracy can be
increased more than 20% compared with traditional Voronoi diagram.
Plantation change in Wuhan and its driving force analysis during 1978-2008
Wensheng Deng,
Huanhuan Xiang,
Changzuo Wang,
et al.
Show abstract
This study is the purpose to detect effectively spatial-temporal change of plantation in Wuhan city and its driving force
during 1978-2008. Firstly, according to study area, to acquire 4-phase remotely sensed images, Landsat MSS image of
1978, Landsat TM image of 1992, Landsat ETM image of 2002, HJ1b CCD image of 2008 and corresponding
topography maps. Using remote sensing image processing software ERDAS to register, correct and resample these
images. Applying to remotely sensed imagery classification method, to class images to urban built-up area, plantation,
forest land and water body. Using map algebra arithmetic and spatial model to acquire plantation change map during the
period of 1978~1992,1992~2002, 2002~2008 and 1978~2008. It reflects spatial distribution of plantation change.
Attribute analysis can get quantities and change ratio of plantation. The result is shown that change of plantation area is
divided to two phases. Plantation area decreases from 6560.73km2 to 4262.49km2 during 1978-2002, and increases by
904.59km2 after 2002. Viewing from spatial distribution, plantation area of central city zone decrease rapidly and is
replaced by urban construction use land. In suburban, plantation partly transforms into forest land, water body and
village inhabitancy, increases or decreases. The research finds out that main driving force of plantation change is urban
built-up area increase and plantation policy.
The application of spatial analysis based on rough set theory and hierarchical analysis
Show abstract
As the development of the theory and technology of geographical information, Geographical Information System (GIS)
has been widely applied in variety of industries. It usually refers to the analytical problem of multi-factor in GIS thematic
application. In this field, the determination of factors' weight is a common and important problem. It actually deals the
data when processing the spatial analysis applying GIS, for example, according to the importance of some factor, assign
some value to it then process spatial overlay operation using the values and finally conclude some evaluation or result. In
reality, there are many factors that affect the some kind of evaluation. Usually, we choose several more important factors
as the evaluation criterion in order to make convenient for research. Then we assign some weight values to these factors
and process spatial analysis then conclude some decision or evaluation to make support for decision-making. We can
choose the factors that can make more impaction on the evaluation or decision-making using the method of Analytical
Hierarchy Process (AHP). However, it has strong subjectivity of the factors' weight values assigned by this method.
Rough set theory, which can effectively remove the impaction made by artificial factors, can make up the deficiency. It
can make the spatial analysis more objective and more effective combining the two methods in GIS spatial analysis.
Spatial clustering analysis based on graphics
Show abstract
Most of the traditional clustering methods are based on spatial database, which reach the clustering results by operating
and computing the spatial coordinates and its attribute values in database. So it can not consider such factors of the
clustering objects as the morphological characters, topological relation etc in the process and results of clustering. From
the point of view of spatial geometry, this paper explored to build the basis of clustering analysis on graphics, divided
spatial clustering into eight types, put forward some kinds of methods of model simplification and dimension reduction
based on spatial projection and mapping, and at last demonstrated the graphics-based spatial clustering method by
introduced a fast spatial clustering method based on Graph Theory and Delaunay triangulation, which achieved good
results judged by the experiment data.
Division of urban hierarchical grid based on hierarchical spatial reasoning
Mingjun Peng
Show abstract
In urban management, many spatial limits of urban areas such as administration boundaries, postal zones, urban planning
zones, traffic analysis zones, etc. were designed by different departments for specific purposes, often resulting in an
inconsistent boundary among them. The social statistics data based on these limits are difficult to use by other
departments due to this inconsistency. To address this issue, the concept of urban basic grid was proposed in this paper,
which is defined as the urban basic grid. An algorithm based on hierarchical spatial reasoning is designed to help
delineating urban basic grid, taking into consideration various factors, including land use, geometry compactness, and
major road. By taking Jiangan District, Wuhan as a case study, the research made an experiment to testify whether the
existing urban planning zone, traffic analysis zones can be generated from the aggregation of the defined basic grids. The
result indicated that the urban basic grid can be used to aggregate higher level urban grid, and therefore the social
statistics data collected through these grids can be shared among other departments.
A new interpolation model of convex hull in Delaunay triangulation
Show abstract
Digital elevation model (DEM) based on Delaunay triangulation can better express the feature of the terrain surface and
avoid significantly data redundancy. There is, however, litter research on the surface model of DEM based on Delaunay
triangulation. The main surface model of DEM is linear interpolation function based on triangulated irregular network
(TIN). Many researches show that the effect of smoothness and continuity is not ideal. Aiming at the problem of linear
interpolation based on TIN of DEM that local part is substituted by plane, the whole surface is not smooth and there is
great difference in the actual terrain, this paper put forward a new surface interpolation model based on Convex Hull
(CH) in Delaunay triangulation. This method is that the known reference points can be well-distributed around the
inserting point. The interpolation model is based on the effective dynamic subdivision of CH area of the triangle
influenced set as the weight. This paper combines with the actual alpine terrain data and uses Root Mean Square Error
(RMSE) and Maximum Error (ME) to evaluate and analysis the experimental results. The experiment shows that our
method has more effective in structure and precision.
Concepts and classification of spatial similarity relations in multi-scale map spaces
Show abstract
Spatial similarity relations are put forward with the introduction of automated map generalization in the construction of
multi-scale map databases; then the definition of spatial similarity relations is presented and the concept of spatial
similarity degree is given. Finally a classification system for spatial similarity relations in multi-scale map spaces is
discussed in detail. This research may be useful to automated map generalization, spatial similarity retrieval and spatial
reasoning.
Determination of suitable cell size for grid based digital elevation model
Show abstract
Horizontal resolution, one of dominant variables for grid based Digital Elevation Model (DEM), directly determines
topographic expression, the accuracy of terrain parameters and geosciences simulations based on DEM. Cell size is
determined on relationship between resolution and terrain parameters traditionally, without taking terrain variance
information content of the raw data into account. This paper puts forward two methods for suitable DEM horizontal
resolution by mining the input contour data based on geostatistics. One is a direct method considering internal and
external variance. Regularization variables of serial resolutions are calculated from the sampled data by regularization
theory in geostatistics. After the variance comparison between point and serial resolutions, the grid at which the external
variance between adjacent grids is larger than average internal variance in grid is named suitable resolution. The other
method, which combines macro-topographical variance with micro-topographical variance, is an indirect way. Various
large-scale supports and their regularization variables are made by dividing the sampled data using regularization theory.
In order to ascertain an optimal support size to express macroscopic spatial variance of terrain, semivariograms of
regularization variables are analyzed on various support sizes. Estimation of the optimal bin size that can estimate the
probability density function in non-parametric density estimation is referred to decide the microcosmic appropriate
resolution in the optimal support. Both methods were experimented in practice, and gave relatively consistent results.
The latter was commended considering the computational efficiency.
Formal representation for gradual changes of spatial relations between regional objects
Nina Meng,
Tinghua Ai,
Xiaodong Zhou,
et al.
Show abstract
Studies the regularity for changes of spatial relations based on the gradual changes of spatial location between two
regional objects. Generates the conceptual neighborhood model of spatial relations like concentric circles, and provides
the formal representation for them using graph theory. Based on the idea of "topylogy matters, metric refines"[1], the
model uses topological relations as basic classification and different direction and distance as the refinement of
classification for spatial relations to reflect the levels of spatial relations. In addition, the changes of spatial relations
between the conceptual neighborhoods are divided into six types. These changes are graded and evaluated according to
the constraints degree of a variety of relations for spatial objects that in favor of formalization and computation. Finally,
experiment is provided to illustrate that the conceptual neighborhood model and its formal description can describe the
gradual changes of spatial relations between regional objects and compute the difference degree between spatial
relations.
Study on quantitative model for relationship between displacement and precipitation for Laozaoping landslide
Show abstract
With the technology of GPS, we conduct precise deformation monitoring of the Laozaoping Landslide in
Chongqing for a flood period. By virtue of the precipitation data close to the landslide in the monitoring period,
we researched the quantitative relationship model between the landslide displacement and precipitation. In
addition, we made researches on the impacts of precipitation distribution on displacement and advanced the
Landslide-Causing Index (LCI). The researches show the model for displacement of Laozaoping landslide and
precipitation is statistically significant; the precipitation distribution exerts more significant effect on
displacement than the amount of precipitation; it is very hard to precisely estimate the displacement of landslide
in terms of the precipitation and soil moisture only.
Research on the decision-making model of land-use spatial optimization
Show abstract
Using the optimization result of landscape pattern and land use structure optimization as constraints of CA simulation
results, a decision-making model of land use spatial optimization is established coupled the landscape pattern model with
cellular automata to realize the land use quantitative and spatial optimization simultaneously. And Huangpi district is
taken as a case study to verify the rationality of the model.
Research on the model of land eco-economic suitability evaluation based on niche suitability
Show abstract
The traditional models of land suitability evaluation were short of comprehensive considering land use with natural,
social and economic characters. In this paper, the model of land eco-economic suitability evaluation was constructed
based on niche suitability, which is to say that the evaluation is to match the land resource real niche with the demanding
niche of life. Then a case study is taken to demonstrate the rationality and validity of the model.
Study on cadastral basic attribute data structure based on man-land relationship
Changgen Zhan,
Yaolin Liu
Show abstract
Based on the idea of man-land relationship, the article defines the concept of cadastral basic attribute data structure
applying the theory of data structure; derives cadastral basic attribute data structure by employing the deductive method,
expecting to lay a good foundation for deep research into cadastral general data structure.
Visualization of Spatial-Temporal Data
Research on the key technology of update of land survey spatial data based on embedded GIS and GPS
Show abstract
According to the actual needs of the second land-use survey and the PDA's characteristics of small volume and small
memory, it can be analyzed that the key technology of the data collection system of field survey based on GPS-PDA is
the read speed of the data. In order to enhance the speed and efficiency of the analysis of the spatial data on mobile
devices, we classify the layers of spatial data; get the Layer-Grid Index by getting the different levels and blocks of the
layer of spatial data; then get the R-TREE index of the spatial data objects. Different scale levels of space are used in
different levels management. The grid method is used to do the block management.
The structure of sharing for land information based on MAGIS-P2P
Show abstract
The key of sharing land information is realizing to share the land spatial data. This paper combined the features of
the land spatial data transmission on network and the demand of rapid sharing for it. We bring in some technique ideas,
such as the MAGIS structure and Agent-P2P, and advanced the structure of sharing system based on MAGIS-P2P. Our
experiments show that, with the MAGIS-P2P being used in land management department to issue and share the land
spatial data, it can be not only more convenient for the land management department from different places to transmit
data, but also for other departments to inquire and acquire the land information in theory.
Web-based Spatial-Temporal Model and Applications
Study on drought-stricken and drought-damaged farmland in China during 1982~2001 with remote sensing
Shuhua Qi,
Zhaoliang Li,
Changyao Wang
Show abstract
The water deficit index (WDI) was introduced briefly. And the 10-day WDI images were estimated with the 1982~2001
NOAA AVHRR dataset of NDVI, light temperature of channel 4 and channel 5. Based on the 10-day WDI images, the
pixels that represent the drought-stricken and drought-damaged farmland were picked up for every year. Only when WDI
greater than 0.75 during crop development (March ~ October) happened in more than one decades, the pixel was thought
as drought-stricken. And WDI greater than 0.7 happened in more than two continuous decades, the pixel was treated as
drought-damaged. The remotely sensed acreage of drought-stricken and drought-damaged farmland have similar
dynamics as the statistical results except in early 1980s. I would like to oppugn the statistical results in early 1980s.
Anyway, results showed that remotely sensed WDI is useful in retrieving drought stricken and damaged farmland and it
also verified the rationality of WDI in evaluating regional soil water status.
A new way of modeling 3D entities based on raster technique
Show abstract
In recent years, the study of 3D spatial models has been developed rapidly, but most of the models are applied to 3D
visualization or orebody modeling. They can only provide limited functionality and operations of spatial analysis. To
solve this problem, this paper firstly analyzes the characteristics of 3D entities and their demands of modeling, and
proposes the method of modeling the exterior surfaces instead of the solid entities themselves using regular volume
elements, hence it has offered a new way of modeling 3D entities, which is based on raster technique, in order to make
promising preparations for 3D spatial analyses, such as the sunlight analysis. Through preliminary visualization
experiments taking the entities with common geometric shapes, simpler and complexer buildings as examples, the
feasibility of this modeling method has been proved.
Research on the recovery of the lunar gravity from simulant orbit perturbation data
K. Zeng,
J. C. Li,
Y. Fang
Show abstract
Research on the lunar gravity field helps us to understand its physical characteristics and its inner structure and discern
its origin and evolvement. Detecting the lunar gravity field helps to improve the precision of calculating geodetic and
geodynamic constant, refining lunar coordinate system, and understanding the evolving history and the geologic
structure of the moon. The determining of the lunar gravity field provides us with useful data for studying the lunar geoid
and gravity anomaly. The lunar gravity field restricts the motion of all the other objects. Detectors changing its orbit from
the earth orbit into the moon orbit and landing are mainly influenced by the lunar gravity. Accurate lunar gravity field
model is the prerequisite of landing accurately and one of the key factors to succeed in the plan of manned landing on the
moon.
Flow paths tracing from raster contours using distance transform
Yanlan Wu,
Yongqiong Liu,
Hai Hu,
et al.
Show abstract
Water flow processes operating on the earth's surface play a fundamental role in shaping various landform elements such
as stream networks, valleys and watershed boundaries. In the digital environment, surface flow paths have been
conventionally derived from a grid-based DEM, where flow directions are assigned based on the direction of steepest
descent determined from grid-cell elevations. However, the assigned flow direction pattern often includes problems such
as unrealistic direction of flow paths especially in nearly flat areas and depressions. A new method for tracing flow paths is
proposed to avoid these problems by two means: 1) Instead of grid-based DEMs, raster contour lines are used as input data;
and 2) Not elevation but information derived from the distance transform performed on a contour map is used to assign
flow directions. The proposed method has been implemented using the C++ programming language. The results obtained
by the new method were compared with those from the existing grid-based methods including the most popular D8 method
and its improved algorithms such as Rho8, FD8, FRho8 and DEMON. The new method resulted in better agreement with
the original stream networks shown in topographic maps, especially in gentle areas. The use of contour lines makes the
new method free from digitizing and interpolation errors, which are often caused in generating a grid DEM from a
topographic map. The high availability of contour maps is another advantage of the new method. The method will benefit
various hydrological analyses and applications.
Simulation of spatial-temporal change of urban land use/cover in a short period of time
Show abstract
The objective of this study is to simulate and validate temporal and spatial changes of land use/cover in a short time
period based on the Markov cellular automata (Markov-CA) model that combines Markov chain analysis and cellular
automata models. Aim to this task, this paper first analyzed the land use/cover change (LUCC) of an urban area in 1997
and 2000 and computed transition probabilities using Markov chain. Then Markov-CA model was employed to simulate
urban land use/cover in 2002 and a validation was followed by using actual land use map interpreted from the satellite
image captured in the same year. Experimental result shows this model is reliable with an acceptable overall accuracy
(86.52%) and Kappa coefficient (0.79), which suggests that LUCC in urban within a short time period could be modeled
and predicted by Markov-CA model.
Pedestrian simulation and distribution in urban space based on visibility analysis and agent simulation
Shen Ying,
Lin Li,
Yurong Gao
Show abstract
Spatial visibility analysis is the important direction of pedestrian behaviors because our visual conception in space is the
straight method to get environment information and navigate your actions. Based on the agent modeling and up-tobottom
method, the paper develop the framework about the analysis of the pedestrian flow depended on visibility. We
use viewshed in visibility analysis and impose the parameters on agent simulation to direct their motion in urban space.
We analyze the pedestrian behaviors in micro-scale and macro-scale of urban open space. The individual agent use
visual affordance to determine his direction of motion in micro-scale urban street on district. And we compare the
distribution of pedestrian flow with configuration in macro-scale urban environment, and mine the relationship between
the pedestrian flow and distribution of urban facilities and urban function. The paper first computes the visibility
situations at the vantage point in urban open space, such as street network, quantify the visibility parameters. The
multiple agents use visibility parameters to decide their direction of motion, and finally pedestrian flow reach to a stable
state in urban environment through the simulation of multiple agent system. The paper compare the morphology of
visibility parameters and pedestrian distribution with urban function and facilities layout to confirm the consistence
between them, which can be used to make decision support in urban design.
Spatial simulation model of storm flow process based on cellular automata algorithm
Show abstract
Spatial simulation is very important study field, by which we can forecast or reproduce a phenomenon in computer.
Storm flow may become to flood when the channels or lakes can't hold the surface water, so it is very useful and
significant to simulate the process of storm flow in computer. In past years, simulation on surface water flow has made a
great progress, and many corresponding simulation models have been produced. However, those models are almost
steady-state model, which just focus on the water flow result rather than process, and also they are always very
complicated, inefficient or inaccurate, when Cellular Automata model has been referred to spatial simulation area, the
simulation becomes easier ,and the simulation models become simple and efficient. Strom flow is one kind of surface
water flow, However it has its own special characteristics. In this paper, a spatial simulation model for storm flow
process based on Cellular Automata is proposed, which is an unsteady-state model (real time dynamic model).Using this
model, we can simulate the entire process of the storm flow in computer rather than just the flow result. At last, for
instance, the storm flow process of a small part of Jinsha river watershed has been simulated by the model. The
simulation results show a good agreement with the fact.
Urban land space evolution based on geographical simulation systems
Jian Gong,
Yaolin Liu,
Zhi Zhang,
et al.
Show abstract
The paper presents a method----Geographical Simulation Systems, which can make up the drawbacks of SD (System
Dynamics) and CA (Cellular Automata), just simulating the urban land space individually. The result shows that the new
system can simulate the urban land space evolution with the GSS (Geographical Simulation Systems) combined with the
SD and CA. Urban land space evolution model is composed of SD layer, CA layer and environmental factors. The
purpose of this new methodology is to simulate the process of urban land space evolution, discuss the Urban Land Space
Evolution Mechanism and forecast the trend of urban land space evolution. The proposed model has been applied to the
simulation of urban land space evolution in Wuhan city of Hubei province. The result indicates that the simulation
accuracy is much better than those of the traditional models.
Research on optimal DEM cell size for 3D visualization of loess terraces
Weidong Zhao,
Guo'an Tang,
Bin Ji,
et al.
Show abstract
In order to represent the complex artificial terrains like loess terraces in Shanxi Province in northwest China, a new 3D
visual method namely Terraces Elevation Incremental Visual Method (TEIVM) is put forth by the authors. 406 elevation
points and 14 enclosed constrained lines are sampled according to the TIN-based Sampling Method (TSM) and DEM
Elevation Points and Lines Classification (DEPLC). The elevation points and constrained lines are used to construct
Constrained Delaunay Triangulated Irregular Networks (CD-TINs) of the loess terraces. In order to visualize the loess
terraces well by use of optimal combination of cell size and Elevation Increment Value (EIV), the CD-TINs is converted
to Grid-based DEM (G-DEM) by use of different combination of cell size and EIV with linear interpolating method
called Bilinear Interpolation Method (BIM). Our case study shows that the new visual method can visualize the loess
terraces steps very well when the combination of cell size and EIV is reasonable. The optimal combination is that the cell
size is 1 m and the EIV is 6 m. Results of case study also show that the cell size should be at least smaller than half of
both the terraces average width and the average vertical offset of terraces steps for representing the planar shapes of the
terraces surfaces and steps well, while the EIV also should be larger than 4.6 times of the terraces average height. The
TEIVM and results above is of great significance to the highly refined visualization of artificial terrains like loess
terraces.
Application and comparison of different grid-based hydrological models in the Laoha River basin
Xingze Wang,
Xiumin Song,
Yunhong Xue,
et al.
Show abstract
In order to examine the applicability of different hydrological models in the Laoha River Basin which is located
in a semi-humid and semi-arid region, the Xin'anjiang model and the vertically-mixed rainfall-runoff model were
employed to the Xiquan and the Chutoulang sub-basins in the Laoha River Basin with the same time series of
data from 1970 to 2003, and the simulated results were compared and analyzed. The results revealed that the
simulation accuracy of the vertically-mixed rainfall-runoff model for flood events simulation is higher than that
of the Xin'anjiang model in both sub-basins. Besides, the simulation accuracy of the vertically-mixed
rainfall-runoff model in the Chutoulang sub-basin is higher by a comparison with that in the Xiquan sub-basin.
Developing a web-based cellular automata model for urban growth simulation
Yan Liu,
Jin He
Show abstract
Cellular automata as an emerging technology have been adapted increasingly by geographers and planners to simulate
the spatial and temporal processes of urban growth. While the literature reports many applications of cellular automata
models for urban studies, in practice, the operation of the models as well as the configuration and calibration of relevant
parameters used in the models were only known to the model builders. This is largely due to the constraint that most
cellular automata models were developed based on desktop computer programs, either by incorporating the model within
a desktop GIS environment, or developing the model independent of a desktop GIS. Consequently, there is little input
from the user to test or visualise the actual operation or evaluate the applicability of the model under different conditions.
This paper presents a methodology to implement a fuzzy constrained cellular automata model of urban growth within a
web-based GIS environment, using the actual urban growth of Metropolitan Sydney, Australia from 1976 to 2006 as a
case study. With the web-based cellular automata model, users can visualise and test the operation of the model; they can
also modify or calibrate the model's parameters to evaluate its simulation accuracies, or even feed the model with
various 'what-if' conditions to generate alterative outcomes. Such a web-based modelling platform provides a useful and
effective channel for government authority and stakeholders to evaluate different urban growth scenarios. It also
provides an interactive environment that can foster public participation in urban planning and management.
Dynamic modeling of tourism by stochastic method: a case of the Beijing-Tianjin-Hebei region
Show abstract
As an efficient way to stimulate the growth of economy, tourism is promoted by most counties allover the world, and has
become one of the world's largest and fastest-growing industries. Essentially, tourism is a spatiotemporal system, with
tourist attractions located in different geographic areas and tourist flows exchanging between different geographic
regions. In this paper, we present a dynamic model for the simulation of tourism and tourist's activities in the context of
GIS and stochastic method, using a case of the Beijing-Tianjin-Hebei region. The model is developed on stochastic
method and multiple geospatial data sources. In the model, the spatiotemporal behavior of tourist on the Earth's Surface
is governed by the evolution rules, which are extracted from the researches on tourist's activities and executed via
stochastic method and multiple geospatial data. By means of the model, we simulate the tourism in the Beijing-Tianjin-
Hebei region, and find that there is good correspondence between the tourist arrivals calculated with the model and those
obtained from the tourism statistics. This shows that the animated dynamic modeling of tourism based on geospatial data
can be used as an indicator of the tourism in the realistic world, and is also can be embedded in the GIS applications.
Natural neighbors interpolation method for correcting IDW
Show abstract
Digital Elevation Model (DEM) interpolation is one of basic functions for spatial description and spatial analysis in GIS
and related spatial information fields. Interpolation can be viewed as a function for estimating the heights of unknown
points using a set of proper known data. It is a key problem of DEM. Inverse distance weighting (IDW) interpolation is
the most commonly used in DEM. The reference points selected by IDW might not be well distributed in space. This
leads to the discontinuity problem of interpolated DEM surface and some artifacts might be generated. In order to solve
the problem caused by ill-distribution of the number and position of reference points in searching process, this paper put
forward a new surface interpolation model about first-order natural neighbor interpolation. The use of first-order natural
neighbor interpolation based on TIN can adapt well to poor data distributions because inserting into a point generates a
well-defined set of neighbors. In the fitting process, according to range of influence composed by first-order natural
neighbor points and the triangle area as weight base of the known point, a non-linear fitting equation can be constructed.
Comparative experiments show that this method has higher precision and more practical application value.
Application of generalized regression neural network residual kriging for terrain surface interpolation
Fucheng Liu,
Xuezhao He,
Li Zhou
Show abstract
Spatial interpolation techniques are a powerful tool for generating visually continuous surfaces from scattered point
data, and the accuracy of interpolation determines the practical values of interpolating surfaces. As the variation of
surface elevation is nonlinear, the conventional spatial interpolation models implemented in many GIS packages
sometime cannot provide appreciate interpolation accuracy for certain application due to their nature of linear estimation.
In this paper, a method of generalized regression neural network residual kriging (GRNNRK) was presented for terrain
surface interpolation. The GRNNRK was a two-step algorithm. The first step included estimating the overall nonlinear
spatial structures by generalized regression neural network (GRNN), and the second step was the analysis of the
stationary residuals by ordinary kriging. And the final estimates were produced as a sum of GRNN estimates and
ordinary kriging estimates of residuals. To test performance of GRNNRK, a total of 1089 scattered elevation data got
from 28.86 km2 area were split into independent training data set (200) and validation data set (889), and the training
data set was modeled for terrain surface interpolation using ordinary kriging and GRNNRK, respectively, while the
validation data set was used to test their accuracies. The results showed that GRNNRK could achieve better accuracy
than kriging for interpolating surfaces. Therefore, GRNNRK was an efficient alternative to the conventional spatial
interpolation models usually used for scattered data interpolation in terrain surface interpolation.