In this research the Hurst exponent H is used for quantifying the fractal features of LANDSAT images. The Hurst exponent is estimated by means of the Detrending Moving Average (DMA), an algorithm based on a generalized high-dimensional variance around a moving average low-pass filter. Hence, for a two-dimensional signal, the algorithm first generates an average response for different subarrays by varying the size of the moving low-pass filter. For each subarray the corresponding variance value is calculated by the difference between the original and the averaged signals. The value of the variance obtained at each subarray is then plotted on log-log axes, with the slope of the regression line corresponding to the Hurst exponent. The application of the algorithm to a set of LANDSAT imagery has allowed us to estimate the Hurst exponent of specific areas on Earth surface at subsequent time instances. According to the presented results, the value of the Hurst exponent is directly related to the changes in land use, showing a decreasing value when the area under study has been modified by natural processes or human intervention. Interestingly, natural areas presenting a gradual growth of man made activities or an increasing degree of pollution have a considerable reduction in their corresponding Hurst exponent.

Accurate regional crop growth monitoring and yield prediction is very critical for the national food security assessment and sustainable development of agriculture, especially for China, which has the largest population in the world. Remote sensing data and crop growth model have been successfully used in the crop production prediction. However, both of them have inherent limitation and uncertainty. The data assimilation method which combines crop growth model and remotely sensed data has been proven to be the most effective method in regional yield estimation. The aim of this paper is to improve the estimation of regional winter wheat yield of crop growth model by using data assimilation schemes with Ensemble Kalman Filter (EnKF) algorithm. WOrld FOod STudies (WOFOST) crop growth model was chosen as the crop growth model which was calibrated and validated by the field measured data. MODIS Leaf Area Index (LAI) values were used as remote sensing observations to adjust the LAI simulated by the WOFOST model based on EnKF. The results illustrate that the EnKF algorithm has significantly improved the regional winter wheat yield estimates over the WOFOST simulation without assimilation in both potential and water-limited modes. Although this study clearly implies that the assimilation of the remotely sensed data into crop growth model with EnKF algorithm has the potential to improve the prediction of regional crop yield and has great potential in agricultural applications, high resolution meteorological data and detailed crop field management are necessary to reach a high accuracy of regional crop yield estimation.

The Soil and Water Assessment Tool (SWAT) is a well established eco-hydrologic model. For the semi-distributed hydrological model, Hydrological Response Units (HRUs) are the basic modeling units, which are defined by land use, soil and slope. Land surface patches within one Hydrological Response Units (HRUs) should bear identical hydrological properties (including land use, soil, slope and management) and thus have similar hydrological responses. However, it is difficult to determinate the spatial locations and to describe the interactions between different HRUs. This study proposed one schema to discretize HRUs for SWAT on the basis of generalized data input. Within a small watershed of Taihu Basin, the data of land use and soil were generalized for discretizing SWAT HRUs. The SWAT model was modified with the discretized HRUs. The resulted showed that the SWAT improved by discretization schema could be more sensitive the runoff lag process and thus achieved better simulation accuracy.

Quantitative investigation of insect activity in their natural habitat is a challenging task for entomologist. It is difficult to address questions such as flight direction, predation strength and overall activities using the current techniques such as traps and sweep nets. A multi-spectral kHz remote detection system using sunlight as an illumination source is presented. We explore possibilities of remote optical classification of insects based on their wing-beat frequencies and iridescence features. It is shown that the wing-beat frequency of the fast insect events can be resolved by implementing high sampling frequency. The iridescence features generated from the change of color in two channels (visible and near infrared) during wing-beat cycle is presented. We show that the shape of the wing-beat trajectory is different for different insects. The flight direction of atmospheric insect is also determined using silicon quadrant detector.

Experimental study of the hydrogen influence on the optical characteristics of plants by Raman spectroscopy was performed. Research revealed the amplitude increase of Raman intensity in wavenumbers 1130 cm^-1 and 1495 cm^-1 for plants under hydrogen influence. The structural changes in the plant leafs were identified by fluorescence confocal microscopy. Experimental study of kinetic processes of plant tissue has shown the emergence of plant reaction to external impact (hydrogen). In turn, the plant response manifested to Raman intensity increase and leads to increase of stem thickness.

The HY-2A, which was launched on 2011/8/16, is the first microwave marine remote sensing satellite developed by China. In this paper, the significant wave height (SWH) data measured by HY-2A satellite altimeter were compared with the data observed by Jason-1/2 satellite altimeter as well as the data measured by buoys. It was found that there was a systematic error of 0.3-0.4 m between SWH obtained from HY-2A and Jason-1/2 altimeters and buoys. The comparison indicated that there was a linear relationship between the data of HY-2A and buoys, which could be used to calibrate SWH measured by HY-2A to better reflect the real marine situation. Comparisons show that the results are good and HY-2A altimetry data work well with Jason-1/2 satellite altimetry data.

We demonstrate a successful combination of several optical methods of remote sensing (coherent fringe projection illumination (CFP), holographic in-line interferometry (HILI), laser induced fluorescence,) for detection, identification, and characterization of crude oil. These methods enable the three-dimensional characterization of oil spills that is important for practical applications. Combined methods of CFP and HILI are described in the frame of coherent superposition of partial interference patterns. We show that in addition to detection/identification of oil, laser illumination in the green-blue region can also degrade oil slicks. We tested these methods on differentsurfaces contaminated by oil , which include: oil on water, oil on flat solid surfaces, and oil on curved surfaces of. We use coherent fiber bundles for the detection and monitoring of the laser-induced oil degradation in pipes.. Both continuouswave (CW) and pulsed lasers are tested using pump-probe schemes. This finding allows us to suggest that properly structured laser clean-up can be an alternative environmental-friendly method of decontamination and cleaning, which can be an alternative to chemical methods, which are dangerous to environmentApplication of holographic amplifier with phase conjugation will allow to increase sensitivity, reduce aberrations from atmospheric distortions and to focus back-reflected amplified beam on the contaminated area thus accelerating laser cleaning.

Lake Mead provides the source of drinking water for over 25 million people in the western United States. Different forest fire events at the northern part of the lake may intensify the concentration of total suspended sediments (TSSs) in water bodies due to the abrupt changes of land covers with accelerated soil erosion. Therefore, it is important to assess the linkage between forest fire events and TSS concentration within the lake. For this purpose, the integrated data fusion and mining (IDFM) techniques were applied in this study to generate TSS concentration maps on a daily basis with the aid of remote sensing imageries. The results of this study confirm the reliability of the IDFM method for nowcasting of TSS concentrations within the lake based on these daily TSS concentration maps. It leads to the investigation of the probable impact of forest fire events on increasing TSS concentrations. Comparing these maps with time of forest fire occurrence showed the potential linkage between increasing TSS concentrations and forest fire events. However, the negative impacts of forest fire events on soil erosion may have lag time to show up.

Although the emissivity behavior of soil moisture has been the subject of numerous research works, making a critical survey of published results, it is possible to find some inconsistencies. The works establish that the effect of increasing soil moisture is principally reduce reflectance and increase emissivity. However, using the direct method for measurement of emissivity, different results were obtained. A dozen of different kinds of soil from the region were analyzed, at different moisture levels and it was found that in all of them, as the moisture content increases, emissivity of the sample decreases.

Aerosol optical depth (AOD) data from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) were inter-compared and validated against ground-based measurements from Aerosol Robotic Network (AERONET) as well as Moderate Resolution Imaging Spectroradiometer (MODIS) over China during June 2006 to December 2012. We have compared the AOD between CALIOP and AERONET site by site using quality control flags to screen the AOD data. In general, CALIOP AOD is lower than AERONET due to cloud effect detected algorithm and retrieval uncertanty. Better agreement is apparent for these sites: XiangHe, Beijing, Xinglong, and SACOL. Low correlations were observed between CALIPSO and ground-based sunphotometer data in in south or east China. Comparison results show that the overall spatio-temporal distribution of CALIPSO AOD and MODIS AOD are basically consistent. As for the spatial distribution, both of the data show several high-value regions and low-value regions in China. CALIPSO is systematically lower than MODIS over China, especially over high AOD value regions for all seasons. As for the temporal variation, both data show a significant seasonal variation: AOD is largest in spring, then less in summer, and smallest in winter and autumn. Statistical frequency analysis show that CALIPSO AOD and MODIS AOD was separated at the cut-off points around 0.2 and 0.8, the frequency distribution curves were almost the same with AOD between 0.2 and 0.8, while AOD was smaller than 0.4, CALIPSO AOD gathered at the low-value region (0-0.2) and the frequency of MODIS AOD was higher than CALIPSO AOD with AOD greater than 0.8. CALIOP AOD values show good correlation with MODIS AOD for all time scales, particularly for yearly AOD with higher correlation coefficient of 0.691. Seasonal scatterplot comparisons suggest the highest correlation coefficient of 0.749 in autumn, followed by winter of 0.665, summer of 0.566, and spring of 0.442. Evaluation of CALIOP AOD retrievals provides prospect application for CALIPSO data.

The aim of this work was to analyze the distribution of NDVI and its correlation with climatic factors in Eastern China during 1998 - 2008. For this purpose, SPOT-VGT images and 143 meteorological data in Eastern China were collected and analyzed. Results showed that the values of Normalized Difference Vegetation Index (NDVI) were generally higher in the southern part than those in the northern part of Eastern China. The NDVI showed a hidden nonlinear trend after wavelet transform, whereas variations existed in the correlation between NDVI and the four climatic factors (i.e., precipitation and relative humidity, temperature, sunshine hours). NDVI data were positively correlated with temperature and sunshine hours, which was opposite to what was observed in precipitation and relative humidity. Furthermore, the same chan1ge cycle was found for NDVI and precipitation, temperature, and sunshine hours, which were nearly 290 days based on normalized wavelet variance. However, the change cycles of relative humidity showed a different spatial distribution. In the north part of Eastern China, about 30 ten-day were detected, which was not the case for the southern part, where the number increased to 186 ten-day.

This paper retrieved the vegetation water content EWT (equivalent water thickness) information and the relevant parameters for the land surface from full-band TM remote sensing data. The effects of surface water heat flux and surface covering on the EWT were analyzed via studies of the regional land cover status and the combined EWT with land surface parameters. This paper also analyzed the roles and limitations of EWT in drought monitoring combined with classification of the regional drought and regional water stress index (RWSI).

This paper further studies the construction, publishing and display of three-dimensional (3D) scenes and their implementation based on Skyline family of software, combining remote sensing images and DEM data. Among them, the SketchUp software is used to build landscape models and the JavaScript programming language is adopted to achieve web browsing of 3D scenes. The study provides a useful exploration for the establishment of Web 3D-GIS combining Web GIS technology and 3D visualization technology.

Built-up area is the result of human activities, which is one of the most important input parameters for the simulation of biogeochemical cycle, and has very important significance for the research of earth system science. Therefore, it is very necessary to map the distribution of built-up area and monitor the changes of it by using new technologies and methods at high spatiotemporal resolution. This article mainly explored the changes of built-up areas at the beginning of the 21^st century in Zhejiang Province, China, based on Geographic Information System (GIS) and Remote Sensing (RS). In the article, we first introduced the mapping processes of built-up areas in the study area based on the method which combined object-oriented method and the mapping precision were high. Then, we analyzed the changes of built-up areas in the study area from 2000 to 2005 and 2005 to 2010. Through the study of this article, we got that most of the changes have distributed at the northeast part of Zhejiang from 2000 to 2005, and all parts of Zhejiang except Lishui have significant changes from 2005 to 2010. There were about 1564.07km² and 1607.73km² non-built-up areas turned into built-up areas from 2000 to 2005 and 2005 to 2010 respectively. Of course, the contrary conversion also exist which accounted for 22.52km² and 96.32 km² respectively. Moreover, the city with the greatest increase of built-up areas from 2000 to 2005 and 2005 to 2010 is Ningbo and Jiaxing respectively.

In this work, a soil moisture data assimilation scheme was developed based on the Community Land Model Version 3.0 (hereafter CLM) and Ensemble Kalman Filter. Soil moisture in the 1st soil layer was assimilated into CLM to evaluate the improvements of land surface process simulation. The results indicated that the assimilation system could improve the model accuracy effectively. It can transfer the variations of shallow soil layer’s moisture to the deep soil and make great improvements to the soil water and heat status in an overall level. The system could improve the soil moisture accuracy from the 1^st soil layer to the 6^th soil layer by 50%. According to this experiment, the transfer depth of soil moisture was from 40 cm to 60 cm. After assimilation, the correlation coefficient of latent heat flux observation and simulation increased from 0.68 to 0.91 and the RMSE dropped from 86.7 W/m² to 45.7 W/m². For the sensible heat flux, the correlation coefficient increased from 0.69 to 0.80 and the RMSE reduced from 105.1 W/m² to 71.3 W/m². It was feasible and significant to assimilate soil moisture remote sensing products.

To improve the access efficiency of geoscience data, efficient data model and storage solutions should be used. Geoscience data is usually classified by format or coordinate system in existing storage solutions. When data is large, it is not conducive to search the geographic features. In this study, a geographical information integration system of Shandong province, China was developed based on the technology of ArcGIS Engine, .NET, and SQL Server. It uses Geodatabase spatial data model and ArcSDE to organize and store spatial and attribute data and establishes geoscience database of Shangdong. Seven function modules were designed: map browse, database and subject management, layer control, map query, spatial analysis and map symbolization. The system’s characteristics of can be browsed and managed by geoscience subjects make the system convenient for geographic researchers and decision-making departments to use the data.

Dynamic variations of suspended sediment (TSM) in extremely turbid waters of Hangzhou Bay (HZB) have been studied using a tower-based high-frequency water-spectrum observing system. We developed a practical data processing method for the high-frequency water-spectrum observation. In addition, the method was validated by the ASD measurement, and the results showed that the tower-measured normalized water-leaving radiance was consistent with it measured by ASD, with the correlation coefficient greater than 0.90 and the mean relative error of 6.48%. Based on the tower-measured water spectrum, the TSM was retrieved further with high frequency, and the results showed that the TSM in the HZB had significant diurnal and seasonal variations. The diurnal dynamics might mainly be caused by tidal induced resuspension, yet the seasonal variations might be derived by winds largely.

The total suspended particulate matter (TSM) in coastal waters has a great impact on the ocean ecosystem. Based on the in situ measurements of the TSM as well as the degree of polarization (DOP) of the upward radiance just above sea surface, the relationships between the TSM and DOP were investigated. The results indicated that the DOP was negatively correlated with the TSM concentration well. Moreover, the regional TSM algorithms were developed using band ratios of DOP at 490nm/570nm and 520nm/570nm, respectively. There were good agreements between the DOPretrieved and in-situ TSM concentrations, with the minimum relative deviation of27.8% and 29.9%, respectively.

With 2 periods of standard false-color images as data sources, using remote sensing and GIS technology, dynamic change information extraction of the coastline and sea reclamation was completed in the region around Bohai through visual interpretation and artificial vectorization, and then this kind of information was studied deeply. The conclusions are as follows: 1) From 2000 to 2010, coastline of the region around Bohai shows an increasing trend, advancing to the sea rapidly; coastline change of the Beijing-Tianjin-Tangshan area is maximum; the advancing of coastlines of Liaoning and Shandong Province to the sea is obvious; human factors are key factors for the above change . 2) From 2000 to 2010, the sea reclamation area of the region around Bohai is rapidly increasing, the increase of Beijing-Tianjin-Tangshan region is the largest relatively and that of Shandong Province is the smallest; from the structure point of view, the area of sea reclamation for building ports is the largest and that of tideland reclamation is the smallest; different regions have different structures; social and natural factors together determine the evolution of sea reclamation. 3) To some extent, sea reclamation contributes to the increase in length of the coastline; different use types of sea reclamation have different influences on the coastline changes.

Nuclear power plants are used as an option to meet the demands for electricity due to the low emission of CO₂ and other contaminants. The accident at the Fukushima nuclear power plant in 2011 has forced the Chinese government to adjust its original plans for nuclear power. The construction of inland nuclear power plants was stopped, and construction is currently only permitted in coastal zones. However, one obstacle of those plants is that the elevation of those plants is notably low, ranging from 2 to 9 meters and a number of the nuclear power plants are located in or near geological fault zones. In addition, the population density is very high in the coastal zones of China. To reduce those risks of nuclear power plants, central government should close the nuclear power plants within the fault zones, evaluate the combined effects of storm surges, inland floods and tidal waves on nuclear power plants and build closed dams around nuclear power plants to prevent damage from storm surges and tidal waves. The areas without fault zones and with low elevation should be considered to be possible sites for future nuclear power plants if the elevation can be increased using soil or civil materials.

This study examined the dynamic changes of the Bohai Sea coastline in recent 20 years through spatial-temporal analysis using combined data from remote sensing and GIS technology. Three standard false color remote sensing images derived from visual interpretation and the vectorization from artificial methods are adopted to complete the extraction of the Bohai Sea coastline information. The results show that the Bohai Sea coastline has an increasing trend from 1990 to 2010, especially with the fastest growth during 2000 to 2010.The coastlines along the Liaoning and Shandong Provinces generally had a growing trend, while the shoreline along the Beijing-Tianjin-Hebei region changes most rapidly. These analyses have suggested that human influence is the key factor in causing the significant changes of the Bohai Sea coastlines in recent years.

This paper presents a new drought assessment method by modifying the NDVI-Ts space, which named NDVI-Ts general space. Based on this method, the general dry side and wet side equation were established for the period of 1981 and 2010 in the Mongolian Plateau. The results showed that: 1) the NDVI-Ts general space was more stable for monitoring drought than that for the single time Remote Sensing data; 2) TVDI was lower in the areas with high latitude, high vegetation cover, well-growing vegetation, which indicated higher soil moisture.3) The dry level area was the largest one, and the normal area was the second largest, the wet level area was the third, the extremely dry and extremely wet area was the least.4)The results showed that the fluctuated area mainly occurred in the normal level and the dry level, the extremely wet level, the wet level and extremely dry level basically remained unchanged. It may be explored that, the aridification became more serious in the 1981 – 2012, the area transformation mainly occurred between the normal level and dry level.

Aerosol optical depth (AOD) is a key indicator of atmospheric environment. Aerosol remote sensing is the most efficient way to obtain the temporal and spatial distributions of AOD. In this paper, the data from Environment Satellite (HJ-1) CCD camera were employed to retrieve AOD by using deep blue algorithm over the Yangtze River Delta. The third band (in blue) was firstly extracted from the MODIS land surface reflectance product (MOD09) and then converted to the first band of CCD/HJ-1. According to the characteristics of the study area and CCD data, a multi-dimension look up table was then built by the Second Simulation of the Satellite Signal in the Solar Spectrum (6S). AOD over the Yangtze River Delta were finally retrieved from the radiance of the first band of CCD/HJ-1. After the retrieved AOD were validated by the MODIS AOD product (MOD04), the correlation coefficient (R) is 0.64 by regression of all cloud screened pixels (1147). The retrieved AOD has a higher spatial resolution than the MODIS AOD and thus can provide more detailed information. Compared with the AERONET ground observation data, the retrieved AOD is closer to the ground-based data than the MODIS AOD.

Phycocyanin (PC) in the blue-green algae is usually used to detect the quantity of the blue-green algae, and it has a special absorption at 620nm waveband. Taihu Lake has become severely turbid and eutrophic in recent years. However, the accuracy of empirical models varies highly. Therefore, it is very useful to find a model which can retrieve PC concentration in a good accuracy. In this work, four models (i.e. single band model, the radio model, the first-derivative model, the three-band model and empirical ratio model) were developed based on remote sending reflectance and measured PC concentration in Taihu Lake in May, 2010 to retrieve PC concentration and then to find out which one is the best. The results show that the 2^nd order polynomial models generally had a better performance than the line models. The three-band model was the most optimal model because it had the highest values of R² and the lowest values of RMSE.

Remote sensing is an effective tool to estimate foliar pigments contents with the analysis of vegetation index. The crucial issue is how to choose the optimal bands-combination to conduct the vegetation index. In this study, RVI, a vegetation index computed by the reflectance of Red and NIR bands, has been used to estimate the contents of chlorophyll and carotenoid. The reflectance of the two bands forming the narrow band RVI was simulated by the PROSPECT model. The possible combinations of narrow band RVI were examined from 400 nm to 800 nm. The results showed that: At the leaf level, estimation of chlorophyll content can be identified in narrow band RVI. Ranges for these bands included: (1) 549-589nm, 616-636nm or 729-735nm combined with 434-454nm; (2) 663-688nm, 710-717nm, 719-728nm or 730- 739nm combined with 549-561nm; (3) 663-688nm combined with 569-615nm. However, no valid narrow-band RVI for the estimation of carotenoid content was successfully identified. Our results also showed that two rules should be followed when choosing optimal bands-combination: (1) the selected bands must have minimal interference from other biochemical constituents; (2) there should be distinct differences between the sensitivities of the bands selected for particular pigments.

The aim of this work is to estimate leaf chlorophyll concentration with 6 different normalized difference vegetation indices (NDVIs) under 4 bandwidths (1, 5, 10 and 20 nm). A popular leaf radiative transfer model(i.e. PROSPECT) was used to simulate the leaf reflectance spectra from 400-800nm under varying chlorophyll concentrations. Then 6 combinations of bands sensitive to chlorophyll concentrations were chosen for the calculation of their NDVIs. Simulated spectral response functions were applied to calculate the synthesis reflectance spectra at the intervals of 5, 10 and 20 nm respectively, and then corresponding NDVIs were calculated. The change of correlation coefficients between the NDVIs and the leaf chlorophyll concentrations were examined. Results showed that some NDVIs had a good performance with increasing bandwidth, whereas response of different NDVIs to the 4 bandwidths were different generally. Our results suggested that the improvement of spectral resolution was not necessary for some NDVIs to estimate leaf chlorophyll.

Recently, aerosol optical depth (AOD) study has become more important in the field of atmosphere sciences. AOD datasets retrieved from satellites are widely used in multiple fields because of their wide coverage and low cost. However, the integrity of AOD spatial coverage can be easily influenced by clouds, rain, haze and other weather phenomena. Fortunately, the full coverage AOD images are producible by employing the data fusion algorithm and ancillary methods. Based on AOD data derived from MODIS and OMI with meteorological parameters on November 18, 2013 over the East China, this study combined the universal kriging with stepwise regression and second-order polynomial fitted to extend the coverage of MODIS AOD at 550 nm. Results showed that stepwise regression method is efficient to infer the MODIS AOD by using the OMI AOD and meteorological parameters. The wind speed, relative humidity, pressure and solar radiation have significant impacts on the spatial and temporal distributions of AOD. The mean prediction error of universal kriging prediction model is 0.0047 in this paper, indicating that the universal kriging is an effective and accurate interpolation method for AOD data fusion. The methods employed in this paper can provide the data source of AOD for studies in climate and other related fields, effectively compensating the non-full coverage shortcoming of satellite AOD datasets.

With the fast development of economy and urbanization, the phenomenon of city construction occupying Cropland often happens. As the contradiction between human and land becomes more prominent, the contradiction between the supply and demand of the cropland are more radical in Yantai City of China. Analysis on the balance between supply and demand of cropland is the main basis to determine land use objectives, and also the basis of editing land use planning. In this paper, the authors firstly calculated the potential of cropland supply in Yantai for 2020 according to its current number of the cropland and the potential quantity of other kinds of land changing to the cropland, and then calculated the demand for cropland in 2020 with the methods of the population prediction and its national economic development planning. Then the balance between the supply and demand of cropland was analyzed. The results were that the cropland in Yantai city in 2020 were lower than those of its demand. At last, to relieve the contradiction, the authors tried to put forward some recommendations like optimizing the structure to coordinate the balance between the supply and demand of the cropland etc. to realize its regional sustainable development.

This paper retrieved the information of cropland and MCI (Multiple Cropping Index) of China in 2000 and 2009 with SPOT NDVI time series data and utilized meteorological data and statistical data released by the state to calculate potential MCI and statistical MCI. Then, the MCI potential of China and grain production potential based on MCI were calculated in order to analyze the potential spatial distribution characteristics of MCI and the potential spatial pattern characteristics. The national mean MCI potentials in 2000 and 2009 are 0.485 and 0.506 respectively calculated with the remote sensing method and statistical method. And the grain productivity potentials of China based on MCI are 51% and 53% respectively. The improvement of MCI potential not only increases hydrothermal utilization rate and the utilization rate of cropland but also enormously enhances the food security degree of China and provides more available cropland area for the economic development.

This paper extracted the spatial distribution of the continental coastline of Bohai Rim utilizing Remote Sensing and GIS spatial analysis techniques, and calculated the fractal dimension of the coastline by boxcounting method, with a time from 1990 to 2010. Moreover, we analyzed the characteristics of spatialtemporal variability of the coastline's length and fractal dimension, the relationship between the large scales length change and fractal dimension change. During the research period, the coastline length of the study area increased progressively and the most significant change in coastline length was found in Tianjin Municipality. Especially after 2000, the coastline length entered a period of rapid growth. In addition, the fractal dimension of the overall coastline of the study area was between the fractal dimensions of the regional coastlines and was close to the maximum fractal dimensions of these regional coastlines. The fractal dimension of the coastline in Bohai Rim was increasing during the research period, large scale project such as ports construction, reduced tortuous degree of the coastline.

FAO56 Penman-Monteith equation, Hargreaves-Samani equation and Priestley-Taylor equation were used to estimate the reference crop evapotranspiration(ETo) in the North China Plain during the summer and winter, using climatology data from 1960 to 2013 including daily mean wind speed, average relative humidity, sunshine percentage, mean, maximum and minimum temperature at 10 weather stations over the North China Plain. By comparing the Hargreaves-Samani equation and Priestley-Taylor equation with FAO56 Penman-Monteith equation, we found that there existed interdependency between ETo derived from the former two equations and FAO56 Penman-Monteith equation. The interdependency in summer is higher than that in winter. In summer, the average pearson’s correlation coefficient between ETo calculated by Hargreaves-Samani equation and FAO56 Penman-Monteith equation is 0.81, and the average pearson’s correlation coefficient of ETo calculated by Priestley-Taylor equation and FAO56 Penman-Monteith equation is 0.87, while the corresponding pearson’s correlation coefficient for them in winter is 0.69 and 0.51. Respectively, for the ETo calculation in summer, interdependency between Priestley-Taylor equation and FAO56 Penman-Monteith equation is higher than that between Hargreaves-Samani equation and FAO56 Penman-Monteith equation, and vice versa for winter.

An online visual analytical system based on Java Web and WebGIS for air quality data for Shanghai Municipality was designed and implemented to quantitatively analyze and qualitatively visualize air quality data. By analyzing the architecture of WebGIS and Java Web, we firstly designed the overall scheme for system architecture, then put forward the software and hardware environment and also determined the main function modules for the system. The visual system was ultimately established with the DIV + CSS layout method combined with JSP, JavaScript, and some other computer programming languages based on the Java programming environment. Moreover, Struts, Spring, and Hibernate frameworks (SSH) were integrated in the system for the purpose of easy maintenance and expansion. To provide mapping service and spatial analysis functions, we selected ArcGIS for Server as the GIS server. We also used Oracle database and ESRI file geodatabase to store spatial data and non-spatial data in order to ensure the data security. In addition, the response data from the Web server are resampled to implement rapid visualization through the browser. The experimental successes indicate that this system can quickly respond to user’s requests, and efficiently return the accurate processing results.

Leaf pigments are key elements for plant photosynthesis and growth. Traditional manual sampling of these pigments is labor-intensive and costly, which also has the difficulty in capturing their temporal and spatial characteristics. The aim of this work is to estimate photosynthetic pigments at large scale by remote sensing. For this purpose, inverse model were proposed with the aid of stepwise multiple linear regression (SMLR) analysis. Furthermore, a leaf radiative transfer model (i.e. PROSPECT model) was employed to simulate the leaf reflectance where wavelength varies from 400 to 780 nm at 1 nm interval, and then these values were treated as the data from remote sensing observations. Meanwhile, simulated chlorophyll concentration (C_ab), carotenoid concentration (C_ar) and their ratio (C_ab/C_ar) were taken as target to build the regression model respectively. In this study, a total of 4000 samples were simulated via PROSPECT with different C_ab, C_ar and leaf mesophyll structures as 70% of these samples were applied for training while the last 30% for model validation. Reflectance (r) and its mathematic transformations (1/r and log (1/r)) were all employed to build regression model respectively. Results showed fair agreements between pigments and simulated reflectance with all adjusted coefficients of determination (R²) larger than 0.8 as 6 wavebands were selected to build the SMLR model. The largest value of R² for Cab, Car and Cab/Car are 0.8845, 0.876 and 0.8765, respectively. Meanwhile, mathematic transformations of reflectance showed little influence on regression accuracy. We concluded that it was feasible to estimate the chlorophyll and carotenoids and their ratio based on statistical model with leaf reflectance data.