A new era of Earth remote sensing began with the launch of the NASA EOS Aqua platform with the Atmospheric InfraRed Sounder (AIRS) in May 2002. The EOS AIRS instrument is the first in a series of high spectral resolution infrared spectrometers that will allow improved characterization of the global atmospheric temperature and water vapor structure. Follow-on operational sensors with similar sounding capability include the Cross-track InfraRed Sounder (CrIS) on the NPP/NPOESS satellites and the Infrared Advanced Sounding Interferometer (IASI) on the European METOP series. These so-called advanced infrared sounders will have a vital role to play in the remote sensing of land ecosystems. This paper describes how the use of Advanced IR Sounder data can be used to improve the accuracy of atmospheric corrections in the thermal IR and provide detailed information on the spectral dependence of the infrared land surface emissivity. Radiance observations from AIRS have been obtained over a large, uniform sandy desert region in the Libyan Desert suitable for evaluation of the 15-km footprints of the NASA AIRS advanced sounder. Analysis of this data indicates a spectral contrast of more than 30% between 12 mm and 9 mm in the surface infrared emissivity due to the presence of the mineral quartz with somewhat smaller contrast at 4 mm. Results of a method for separation of infrared surface emissivity and effective surface skin temperature are presented also.

This study examined the utility of polytomous logistic regression in pixel classification of remotely sensed images by the growth stage of forests. For a population of grouped continuous categories, the assumption of normal distribution of independent variables, which is often required in multivariate classification methods, may not be appropriate. Two types of polytomous logistic regression procedures, multinomial and cumulative logistic regression, were used to classify Landsat TM data by growth stage (regeneration-immature, intermediate, and mature) of loblolly pine (Pinus taeda L.) forest in the east central Mississippi. Multinomial logistic regression is typically used for analysis of unordered categorical data. Cumulative logistic regression is one of the most commonly used methods of ordinal logistic regression which is generally preferred to analyze ordered categorical data, although, it imposes restrictions on the data. Three hundred sample points were located randomly throughout the study site and vectors of pixel values of four bands of Landsat TM data were used to predict growth stage at each sample location. The results were compared to that of parametric and nonparametric discriminant analysis, k-nearest neighbor method. Non-normal distribution of independent variables indicated a violation of the assumptions for parametric discriminant analysis. Classification with cumulative logistic regression using four bands was performed first. However, the assumption of the model was not met. So, the classification was also performed using only band 4 which appeared to meet the assumption. The error rate of cumulative logistic regression was 39.12% with all the bands and 37.70% with band 4 alone. Although error rate with cumulative logistic regression with band 4 alone resulted in the lowest error rate, the improvement over other methods was marginal. The error rate of k-nearest neighbor method varied from 38.68 to 48.06% depending on choice of the value of k.

In this article, a combined application of a segmentation method with a texturing procedure is employed for delimitation of urban areas in a temporal series of Landsat satellite images over the Sintra-Cascais municipalities. The study area is particularly sensitive as it contains the Natural Park of Sintra-Cascais (PNSC) which is subject to intensive anthropogenic pressure. Selected spatial metrics are used for analysing the evolution of urban pattern for the whole study area and also inside and outside the PNSC. Results reveal that built areas have increased almost 30% and that the pattern of urban growth is being made differently inside and outside the natural park between years 1989 and 2001.

The mapping of agricultural-land use systems using single-date information has, in the past, met with limited success. Broad-band multi-spectral sensors have been used primarily for mapping of broad land cover types, but have been less successful for identifying species-level variation. Hyperspectral sensors have had some success for species mapping, but these images often cover a small area and are not appropriate for large-scale land-use assessment. Phenological changes in crop broad-band spectral properties over the growing season offer a promising method of detecting species variation associated with growth rates, plant structure and cropping practices. This paper will present preliminary results of the use of multi-temporal optical imagery for mapping agricultural species. Three SPOT-4 multispectral scenes were acquired during early, middle and late season growth stages over an agricultural region in eastern Ontario, Canada in 2004. Three supervised classification methods were compared: Maximum-Liklihood, Decision Tree and Neural Network approaches. The impact of atmospheric correction was explored to determine if statistical models using multi-sensor, multi-date inputs are sensitive to differences in atmospheric conditions during image acquisition. The success of each method is assessed based on classification accuracies determined using an independent set of ground measurements. Preliminary results indicate that multi-date information is essential to deriving accurate land use information, and that further inputs in addition to remote sensing data may be needed to define specific classes.

Fuel moisture content (FMC) is an important parameter in determining fire risk and fire behavior. Direct measurement of FMC in the field is very costly and time consuming. Therefore, remote sensing becomes the effective method to retrieve FMC at large scale. Short wave infrared (SWIR) band reflectance has been found negatively related to leaf water content and most of the researches are conducted at leaf level. Here SWIR and NIR (Near Infrared) bands of Moderate Resolution Imaging Spectroradiometer (MODIS) are used to retrieve FMC at canopy level in Northeast China forest. The result shows that the combination of MODIS band 7 and 2 presented the best results for FMC estimates. It is also found that forest fires prone to spread along the dryer area.

An integrated hydrological, ecological, and economical model (HEE) was developed at basin scale to evaluate the interactions among resources, agriculture, and rural development. Hydrological module in the integrated model was adapted from SWAT, the Soil and Water Assessment Tool, to simulate the water balance in terms of soil moisture, evapotranspiration, streamflow, and groundwater table change. Ecological module was integrated into the hydrological module to compute the ecosystem production of biomass and yield for different land use types. Economical module estimated the monetary values of crop yield and other ecosystem services. The model was implemented in a holistic approach, and able to produce simulation results at daily time steps with a spatial resolution of hydrological response unit (HRU). The integrated model was calibrated by data for the period of 1983-1991, and run for the period of 1986-1995 with the calibrated parameters for the upper and middle parts of the Yellow River basin, a semi-arid area in northwest China. The average efficiency of the model in simulating monthly streamflow was 0.63 during the calibration period, which indicated an acceptable calibration. Preliminary simulation results revealed that water use in the study area had largely reduced the streamflow in many parts of the area except for that in the riverhead. Spatial distribution of biomass, crop yield, and water productivity showed a strong impact of irrigation on agricultural production. In general, the simulation results from this study indicated that the model was capable of tracking the temporal and spatial variability of pertinent water balance variables, ecosystem dynamics, and regional economy, and provided a useful simulation tool in evaluating long-term water resources management strategies basin scale.

Remote spectral sensing offers an attractive means of mapping river water quality over wide spatial regions. While previous research has focused on development of spectral indices and models to predict river water quality based on remote images, little attention has been paid to subsequent validation of these predictions. To address this oversight, we describe a retrospective analysis of remote, multispectral Compact Airborne Spectrographic Imager (CASI) images of the Ohio River and its Licking River and Little Miami River tributaries. In conjunction with the CASI acquisitions, ground truth measurements of chlorophyll-a concentration and turbidity were made for a small set of locations in the Ohio River. Partial least squares regression models relating the remote river images to ground truth measurements of chlorophyll-a concentration and turbidity for the Ohio River were developed. Employing these multivariate models, chlorophyll-a concentrations and turbidity levels were predicted in river pixels lacking ground truth measurements, generating detailed estimated water quality maps. An important but often neglected step in the regression process is to validate prediction results using a spectral residual statistic. For both the chlorophyll-a and turbidity regression models, a spectral residual value was calculated for each river pixel and compared to the associated statistical confidence limit for the model. These spectral residual statistic results revealed that while the chlorophyll-a and turbidity models could validly be applied to a vast majority of Ohio River and Licking River pixels, application of these models to Little Miami River pixels was inappropriate due to an unmodeled source of spectral variation.

GOSSYM is a comprehensive crop growth model that has been continuously developed since the late 1970s and widely applied to assist cotton growers, crop consultants, and researchers. The state-of-art CWRF (Climate-Weather Research and Forecasting model) demonstrated skillful simulations of regional water and energy cycle processes that are keenly important to cotton growth. This study focuses on coupling GOSSYM and CWRF to study crop-climate interactions. The coupling procedures include (1) recoding the GOSSYM to follow the CWRF F90 modular implementation; (2) replacing the soil dynamic module of the GOSSYM with the CWRF-predicted soil temperature and moisture while integrating the crop field management or cultural practice component (e.g., irrigation, tillage); (3) providing the GOSSYM with surface air temperature, precipitation, and surface solar radiation from the CWRF; (4) constructing crop height and coverage, leaf and stem area indices, greenness and root profile from the GOSSYM as inputs for the CWRF to represent the crop feedback on solar albedo and infrared emissivity, precipitation interception, and evapotranspiration. This study presents the preliminary results of the GOSSYM driven by the CWRF simulated climate conditions and discusses the model performance on cotton yield, leaf area index and height and their responses to water stress under the irrigation and non-irrigation conditions.

Viewing hydropower as a clean energy source and an important part of overall energy strategy in the years ahead, China has put priority on hydroelectric projects as part of its sustainable development strategy to reduce pollution as well as CO2 emission resulting from burning coal. Although China's hydropower exploitation potential ranks first in the world, its utilization ratio is very low at 24% by comparing with as high as 80% in developed countries. Although the economic importance of hydropower plants cannot be underestimated, their construction also has brought inevitable negative effects on the environment. Moreover, because the efficiency of operating hydropower plants is heavily dependent on precipitation condition which is very sensitive to climate variation and climate change, and the reservoirs built for hydropower plants are also discovered as one of greenhouse gases sources, the climate impact on developing mega-hydropower projects needs to be studied.

An action plan for recovering species at risk (SAR) depends on an understanding of the plant community distribution, vegetation structure, quality of the food source and the impact of environmental factors such as climate change at large scale and disturbance at small scale, as these are fundamental factors for SAR habitat. Therefore, it is essential to advance our knowledge of understanding the SAR habitat distribution, habitat quality and dynamics, as well as developing an effective tool for measuring and monitoring SAR habitat changes. Using the advantages of non-destructive, low cost, and high efficient land surface vegetation biophysical parameter characterization, remote sensing is a potential tool for helping SAR recovery action. The main objective of this paper is to assess the most suitable techniques for using hyperspectral remote sensing to quantify grassland biophysical characteristics. The challenge of applying remote sensing in semi-arid and arid regions exists simply due to the lower biomass vegetation and high soil exposure. In conservation grasslands, this problem is enhanced because of the presence of senescent vegetation. Results from this study demonstrated that hyperspectral remote sensing could be the solution for semi-arid grassland remote sensing applications. Narrow band raw data and derived spectral vegetation indices showed stronger relationships with biophysical variables compared to the simulated broad band vegetation indices.

Due to the rapidly process of urbanization, the water consumption is increasing speedily in Beijing, the capital city of China, during recent decades. Despite great efforts have been done, the daily life of residents and economic construction is threatened continuous in the city. Because of the limitation of sound water management in Beijing the water resources exploitation and utilization are not rational, economically efficiency. The water environment has been degraded in vary levels. The aim of this study is improvement of water management in Beijing. An investigation and collection of the data related to the water management was carried out. The study has made appraisal on the amount of water available and water demands in the region. The reasonable policies, feasible alternatives and institutional management measures have been drawn out from the study for the water management strategies. They can be considered as a base of decision making and macroscopic management for the long-term planning of Beijing.

Soil moisture is an inegligible physical variable in agrometeorology, climatology, hydrology, ecology and crop cultivation and predicted normally by use of the Penman formula for meteorological records from a single or a few stations and weather forecasts. This method, however, allows to make the prediction only for a limited number of stations rather than regional gridded predictions. For this reason, we developed a scheme of satellite sensings retrieval, the regional climate model (RegCM2) and a soil water predicting model in combination for moisture in fields of staple crops over the Huang-Huai Plains, by which to establish a drought warning system, of which 1) the soil water predicting model makes use of the soil moisture balance equation applicable to fields of winter wheat and summer corn in the Plains, whose central component is the Penman formula revised by FAO; 2) the needed NWP products are offered by NCAR RegCM2 and 3) the initial field of soil moisture comes from the retrieval of polar-orbiting meteorological satellite data that are corrected through vegetation cover correction and a variational technique. Results show that the proposed scheme is able to improve the precision of the prediction and to better monitor and predict changes in the moisture and the distribution of drought-hit crop areas over the study plains.

The study is focused on the methods for determining the warm edge and cold edge of vegetation temperature condition index (VTCI) drought monitoring approach by using the multi-years' composited LST and NDVI products. The results show the warm edge can be determined by using multi-years' maximum value composited LST and NDVI products at a specific period, While, the cold edge is determined by a maximum-minimum value composited approach. The ground-measured precipitation data in Guanzhong Plain, Shaanxi Province, PR China are employed to validate the edge determining methods and VTCI approach. The correlation coefficients between VTCI and cumulative precipitation at 1 or 2 periods of ten days' interval are the highest. These results indicate that the edge determining methods are suitable for VTCI approach, and VTCI is a near-real time drought monitoring approach.

Sustainable management of water resources requires reliable information on regional evapotranspiration (ET) distribution, which is the largest output component of the hydrological cycle in North China Plain (NCP). In this work, we integrate a popular remote sensing technique with ArcGIS to build a ArcMap tool bar, named rGIS-ET, for estimating regional ET from Landsat TM/ETM+ data. The development of rGIS-ET enables quick processing of large amount of remote sensing and other spatial data. It also provides user-friendly interfaces for modeling, output display and result analyses. We use daily ET measurements from a weighting lysimeter in our experimental station to verify the performance of rGIS-ET. The verification confirms the reliability of ET calculation, whose errors during crop growing season are less than 10 %. We apply rGIS-ET to Luancheng County, a typical agricultural region in NCP, to demonstrate its utility for calculating regional ET and estimating agriculture water needs and ground water usage, both of which are critical to the design of an effective water resources management program for achieving sustainable development.

Accurate estimation of water consumption requires detailed information on vegetation types, including vegetable that is increasingly becoming one of the most important crops in China and many parts of the world. In current paper, a technique for rapid and accurate extraction of vegetable field (both greenhouse and open field) information from Landsat TM image is developed and tested. Through conducting field experiments and analyzing the Landsat TM images, we obtain the spectral characteristics of the film covered greenhouse vegetable and build a model to extract vegetable fields from the Landsat TM images. Applying this technique to Luancheng County of Hebei Province, China, we calculate the total area of the vegetable field being 208 ha. This number compares well with the result of our field survey. Based on the vegetable field area and the vegetable water consumption rate, we arrive at an estimation of the total vegetable water consumption in Luancheng County being 2.6*106 m3. The analyses also show that, in Luancheng County, the vegetable consumes about 4% of the total agricultural water use. The technique developed here provides an effective way for deriving vegetable field area from Landsat TM data and estimating the regional vegetable water consumption.

Debates have persisted on the precise nature and consequence of urbanization on cultivated land in China. The primary goal of this paper is to provide empirical-based evidence on the impacts of urbanization and industrialization on cultivated land. Based on cultivate land data estimated from Landsat Thematic Mapper/Enhanced Thematic Mapper digital images for 1987, 1995 and 2000 and a unique set of county-level socio-economic data, an econometric model on cultivated land change is empirically estimated. The results produce findings that are both expected and those that are fairly surprising. Because of offsetting effects of land expansion in China's northeast and northwest regions, overall there was a small net increase in cultivated land between 1987 and 2000. Although cultivated area decline between 1995 and 2000, the net decline was about 1.2% only. Industrialization and population growth were largely responsible for the fall in 1995-2000. Moreover, contrary to the conventional opinion, after holding constant the effect of industrialization and population growth, regardless of whether urban area expansion occurs in large, medium or small cities or towns, such urbanization is land-saving when compared to leaving rural residents in rural areas. Two of major implications of our analysis are: 1) although the loss of cultivated land imposes a cost on the nation, it appears to be associated with those processes that will lead to the ultimate modernization of China; 2) the nation's policies of town and small city development are not necessarily inefficient in terms of their impact on cultivated land use.

A modeling approach is used to assess the applicability of the derived equations which are capable to predict chlorophyll content of rice leaves at a given view direction. Two radiative transfer models, including PROSPECT model operated at leaf level and FCR model operated at canopy level, are used in the study. The study is consisted of three steps: (1) Simulation of bidirectional reflectance from canopy with different leaf chlorophyll contents, leaf-area-index (LAI) and under storey configurations; (2) Establishment of prediction relations of chlorophyll content by stepwise regression; and (3) Assessment of the applicability of these relations. The result shows that the accuracy of prediction is affected by different under storey configurations and, however, the accuracy tends to be greatly improved with increase of LAI.

PERFECT (Productivity Erosion and Runoff Functions to Evaluate Conservation Techniques), which has been widely used in Australia, is designed to predict runoff, erosion and crop yield under various management pratices including residue, tillage, sequences of plantings, harvesting and stubble managements in dryland cropping areas. The objectives of this study were to modify and calibrate PERFECT to simulate the impacts of tillage, residue and traffic on runoff and soil water balance under conservation tillage of small- to medium-sized machinery, and to assist identifying appropriate conservation practices for sustained crop production in dry land areas of Northern China. The procedure of runoff prediction using USDA Curve Numbers was modified by incorporating the effects of field slope and rainfall intensity. Runoff was calculated daily as a function of rainfall, soil water, residue cover, slope, surface roughness resulted from tillage, and rainfall energy. A simplified Priestley-Taylor equation was employed in the model to calculate potential evapotranspiration, and the effect of residue cover on evapotranspiration was also considered in the model. Input data for the simulation model included daily weather, runoff, soil hydraulic properties, plant available water capacity, cropping systems, and traffic and tillage management. Data were collected from field experiments on Loess Plateau of Northern China. Preliminary results of model calibration and validation showed that the R² between predicted and observed runoff was 0.86~0.90 and R² between predicted and observed available soil moisture was 0.82~0.94.

China is one of the most arid countries in the world and sand storms happen frequently in northern China and severe storms even impact neighbor countries. Numerous measures such as planting trees, growing grass etc are being used to control sand storms, which has effectively improved ecological environment and controlled the occurrence of sand storms. However, as to the farmland, two kinds of methods are carried out basically. One is planting trees and grass, the other still continues to use traditional moldboard plowed bare cultivation, which led to degradation and desertification of the farmland, reduced the productivity and affected the sustainable development. The soil erosion by wind under conservational and traditional tillage systems was investigated in a 3 years period by means of monitoring field sand losses, wind tunnel simulations and marking pole experiments. The results of the study show that the annual amount of the soil eroded by wind was 6 billion tons in northern China, and the losses of N, P, K and organic matter were 6.67, 1.00, 122.00 and 89.35 million tons, respectively. Among them, the annual soil wind erosion in Beijing was 18 million tons. Compared with tradition tillage, conservation tillage including no till with crop stubble and straw coverage reduced 40% of wind erosion. In order to control sand storms in China, more emphasis should be given to conservation tillage due to its great effectiveness in reducing wind erosion from farmland which is a source of dust, in addition to planting more trees and grasses.

Continental aquatic ecosystems are important sources of the protein for human needs. Assessments of potential food provisioned by aquatic ecosystems can help people better understand how aquatic ecosystems can support human well-beings. In this paper, four power regression models based on environment factors, which affect fishery productivity on basal level, are built to estimate the potential productivity of natural fish in fishable paddy fields, rivers and creeks, lakes, reservoirs and ponds respectively. The data for the assessment include the raster data of solar radiation, vegetation, terrain, temperature, precipitation, soil in 1 km resolution. Population density in 1 km resolution is used to detect the possible fishery investment of aquatic ecosystems. Increasing productivity coefficients, which show the ratios of fishery productivity under investment condition to that of natural condition, are estimated according to fishery investigation of different investment. With the natural fishery productivity and the increasing productivity coefficients, potential food provisioning services of continental aquatic ecosystems are estimated. The outcome of the assessment shows that 35.59 million tons of potential fish per year can be obtained from aquatic ecosystems, which includes 16.27 million tons from fishable paddy fields, 2.09 million tons from rivers and trenches, 4.97 million tons from lakes, and 15.25 tons from reservoirs and ponds.

Eco-water demand is a key subject in ecology and hydroscience research. Under the macro background of implementing the Western Development Strategy, pursuing the ecological project of grain for green and actualizing regional sustainable development of our country, the distribution of water and soil resources, especially the deficiency of water resources has been restraining the development and utilization of resources in Western China, which should be settled urgently. In this context, it is significant to assess the amount and intensity of ecosystem eco-water demand. The authors taking Keriya River Watershed, the typical arid watershed in Western China, as an example, to assess the comprehensive eco-water demand and discuss the demand-supply equilibrium of eco-water demand by analyzing the structure characteristics of different ecosystem. The result has much significance for local government to formulate the development and utilization plan of water and soil resources, to guarantee the benign cycle and to realize the sustainable utilization of water resources, and further more to rebuild the ecological environment.

The Chinese government established the Natural Forest Conservation Program(NFCP) in 1998. As nationwide engineering, one of the most important tasks of NFCP was to mandatory conversion of marginal farmlands to forestland or grassland(reforestation or afforestation in farmlands) where topographical slope steepness was more than 25. In order to quantitatively study the grade of agriculture soil loss amount and soil erosion volume spatio-temporal variation, as well as to guide the process of the conversion of farmlands to forest in upstream of Yangtze Rivers, western of Sichuan province in China. The research analyzed how to calculate K, S, L, C and P factors of Universal Soil Loss Equation(USLE) on the base of considering terrain, climate and characters of agricultural soil. The methods can adapt to the variation terrain of the dry valley region in western Sichuan province. As believed the reforestation was a long-term engineering, we thought the planning of reforest farmlands is a temporal decision, which should be considered that where should be afforested at once and where should afforested in abeyance on the basis of grading soil loss amount and the others conditions of reforesting farmland. Grading agricultural soil loss amount would be beneficial to program a feasible plan in the conversation of farmlands to forest.

With a subtropical climate, Guangxi has a typical karst landscape. Land degradation has become a serious environmental issue due to its high vulnerability caused by the joint effect of natural settings in geology, topography, rainfall, and vegetative cover, as well as human activities such as deforestation. Its eco-environment has deteriorated over recent years while cultivated land is disappearing quickly. This, in turn, has exacerbated the poverty level in rural areas. In this study we monitored the spatial distribution of land degradation and its temporal evolution using Landsat TM/ETM images of the late 1980s, mid-1990s and late 2000 (for simplicity, we identified them as 1985, 1995 and 2000). We also explored the causes of its initiation and expansion. Through constructing regression models using all the relevant variables and considering the lagged effects as well as fixed effects, we quantified the exact role of different factors in causing land degradation in the study area with new findings. Based on these results we further analyzed the hazard of land degradation and proposed a few practical rehabilitation measures, including forestation, infrastructure projects, and ecological projects. The findings in this study are invaluable in preserving, restoring, and reconstructing the degraded environment in Guangxi and other karst areas in Southwest China while alleviating poverty in rural areas.

Integrated temperature equipment system using advanced testing method with high accuracy has been well developed and applied in industries. However, costs of such a system are very high for agricultural applications. The objective of this paper is to develop a computer program based on virtual instrumentation (VI) method for thermal measurement system to conduct measurements of temperatures. A data acquisition program is developed with LabVIEW application software from National Instruments based on the HP 3497A. This computer program can automatically acquire reference temperatures through 80 channels simultaneously. The system integrated sensing, computing, and measuring technologies. The software designed by VI has capabilities of signal noise reduction and elimination, process displays, and storage of available data. The hardware of the system consists of a HP data acquisition board 3497A and a set of thermocouple sensors. The data boards acquire and convert analog signals in different channels simultaneously. The acquired signals are sent to the computer and processed automatically by the software through GPIB and Com. A program in VI that can measure temperatures and compensate the thermocouple measurement is developed. The test data show that results from the hardware compensated and the software compensated integrated temperature measurement system (ITMS) are close that of the reference measurement system.

Health and sustainability of agricultural ecosystems in Northeast China have been challenged by over-utilization and inappropriate management. A set of protective measures were developed and applied in Heilongjiang, China, to enhance the farmland sustainability while increasing or maintaining the needed productivity. These measures included no-till farming, return of agricultural residuals, high-efficiency irrigation, integrative pest management, crop rotation, and precision farming with remote sensing and GIS. Equipment and technologies were developed to implement the protective measures. Application of these technologies in the past several years has produced a significant improvement in both ecological and economical aspects. Potential application of such protective measures in other regions of China was also discussed.

The impact of climate change on Leaf Area Index (LAI) and its spatial pattern was studied by using climate data and LAI data retrieved from AVHRR (Advanced Very High Resolution Radiometer) during the study period (1981-2002). In recent 20 years, most areas of China became warmer and had more precipitation which resulted in higher LAI values and increased Gross Primary Production (GPP). There were higher LAI values in 1990s than 1980s in most areas of China, approximately 75% of the whole China land. In turn, the ecological environment of China had been improved and the region suitable for vegetation growth expanded westward, which leads the increase of the Net Primary Productivity (NPP).

In an attempt to understand the relative strengths of two state-of-art mesoscale models: WRF (Weather Research and Forecasting Model) and Penn State/NCAR MM5, a nested domain was constructed to simulate a precipitation process induced by land-sea wind shear in Southeastern China with the two models. The results indicate that both WRF and MM5 capture the local circulation and the heavy rainfall area well, but precipitation amounts are overestimated relative to observations. The WRF model is better than the MM5 in precipitation strength, but worse in the location of maximum rainfall. In comparison with the observations, the simulation by both MM5 and WRF is larger than observation, but the simulation of WRF is closer to observation than MM5. Except that the distribution tendency of simulated wind field by MM5 is better than by WRF, the distribution trend of 2-m temperature and precipitation simulated by WRF is closer to observation than by MM5, but there exists phase difference between simulation by WRF and observation, for precipitation with lagged phase, and for temperature with phase ahead

Using AVHRR (1982-1999) and MODIS (2000-2004) LAI products from 1982 to 1999, seasonal and interannual variability of LAI in China were analyzed. The results indicate that the LAI in most of China increase at different ratio while decreases in some area of Tibetan Plateau, the south of Xinjiang, Yunnan, and Sichuang Provinces and part of northeastern China. With the correlative degree method, it is demonstrated that temperature is the most closely related to the LAI change in China in this period; It also shows such LAI change has close relationship with soil moisture and precipitation as well. We compared the multi-year-averaged monthly LAI from AVHRR during 1982-1999 with the monthly LAI from MODIS during 2000-2004, finding that in winter, the LAI from AVHRR agrees to the LAI from MODIS, but in summer, during which the vegetation is growing up, the LAI from AVHRR is larger than from MODIS. The LAI from AVHRR is in good agreement with MODIS in each month in arid and semi-arid region. This long-term LAI data can be used in land surface model. Analysis was conducted to examine how sensitive land surface parameters are to LAI interannual variability. The result shows that the response is mainly in the range of ±15%, but for the fraction of the direct beam absorbed by canopy, the relative error is even larger than 40%, which suggest that the inter-annual difference of LAI must be considered in climate models.

China is a country with complex topography, land surface conditions, coastlines with the world highest plateau in its west and the largest ocean at its east, and with large contribution from mesoscale phenomena, such as the mei-yu frontal systems and tropical storms. To study the regional climate in such a region, a highly resolved regional climate model (RegCM) has been recently developed at the International Pacific Research Center (IPRC). The distinct features of this model include direct feedback of cumulus detrained cloud ice and cloud water into the grid-resolved quantities; the effect of cloud buoyancy on turbulence production with mixed-ice phase clouds; an explicit coupling between the cloud microphysics and radiation via cloud properties; an explicit coupling between land surface and radiation via surface albedo, direct and diffuse radiation fluxes; and the effect of frictionally generated dissipative heating. The performance of RegCM3 is demonstrated by its simulation of the 2003 summer extreme climate event over the whole China region including Tibetan Plateau. There have not had so many studies about this region on this regard. With the use of the NCEP Reanalysis 2 data provided by the NOAA-CIRES Climate Diagnostic Center, Boulder, Colorado, USA, from their Web site at http://www.cdc.noaa.gov/, which is available at 6hr intervals with a resolution of 2.5°×2.5°, as both the initial and lateral boundary conditions, the model was integrated from 1 May to 31 August 2003 with a resolution of 60km×60km covering the area of 15°-55°N, 70°-140°E. It is demonstrated that the RegCM3 has a pronounced rainfall downscaling scale, producing more realistic regional details and overall smaller biases than the driving reanalysis data. The model simulated realistically not only the temporal evolution of the area-averaged precipitation and the monthly mean precipitation spatial pattern but also the daily precipitation intensity distribution.

Based on the GLO-PEM simulated data, net primary productivity (NPP) and its spatiotemporal patterns in Loess Plateau were studied from 1981 to 2000. Our research indicated that the distribution of annual NPP in Loess Plateau was obviously different from east to west and from south to north. The average of annual total NPP is 0.15PgC, with an annual increasing rate of 0.01%. NPP decreased in most parts of Loess Plateau, with the largest decrease in the southeast of Shanxi Province and northeast of Loess Plateau, But it increased in the area along the boundary between Shaanxi Province, Inner Mongolia Province and Lanzhou Basin in the west of Loess Plateau, The early 1990s (1991-1995) is the time with fastest NPP increase. The variation of NPP is different seasonally. It decreased mostly in winter, with an annual rate of 0.57%, and increased with an annual rate of 0.51% from April to May.

Monitoring crop growth status and yields using remote sensing data have been a challenges both in estimating the growing parameters and quantifying the seasonal changes. Traditionally, NOAA AVHRR data was applied to estimate and predict crop yields with statistical correlation methods. However, its spatial resolution of 8-km is not satisfying in monitoring crop growth on the site level. The launch of TERRA with moderate resolution imaging spectroradiometer (MODIS) instruments onboard began a new era in remote sensing of the Earth system which is providing a series of products of unparalleled quality and sophistication for the observation and biophysical monitoring of the terrestrial environment. Crop growth models simulate biophysical processes in the soil-crop-atmospheric system provide a continuous description of crop growth and development. Combining a growth model with the input parameters derived from remote sensing data provides spatial integrity as well as a real-time "calibration" of model parameters. A field study was conducted to evaluate the applicability of the 8-day MODIS leaf area index (LAI) data product in operational assessment of wheat growth condition and yields in the region of Yucheng, ShanDong Province, in China. The MODIS LAI product were used to compared with the DSSAT LAI--the output of crop simulation model (DSSAT) and the observed LAI. The MODIS LAI corresponded comparatively well with the DSSAT LAI in the early stage which have been tested well with the observed LAI, however in the later wheat growing stage, there are still some difference between the MODIS LAI and observed LAI. Limitations of this study and its conclusions are also discussed.

Urban sprawl has sparked a new debate over land-use policy in Beijing metropolitan area in China during past three decades. Increasing populations and economics intensify the urban growth and cropland encroachment. The metropolitan area has gone through a rapid urban growth and transformation from rural to developed land over a short period of time and provided an excellent study area for this study. Using historical land use maps and a spatially explicit dynamic cellular automata urban sprawl model we present applications of a spatially explicit model of land use change. The use of the results for environmental assessments is illustrated by calculating spatial indices to assess the impact of land use change on forest fragmentation. It is concluded that spatially explicit modeling of land use change yields important information for environmental management and land use planning. We quantify the urban sprawl and model the spatial landscape pattern change in Beijing metropolitan area, China. These results constitute a foundation for spatial and ecosystem models to predict long-term environmental impacts of land use change in China.

Increasing populations and economics intensify the urban growth and cropland encroachment in Beijing metropolitan area. In this paper we investigated the effects of recent urban sprawl (1991-2001) in Beijing metropolitan region, People's Republic of China on ecosystem net primary production (NPP). The analysis employed a mechanistic model of NPP in combination with satellite-derived and ecological data. Our analysis shows that urban growth in the 10-year study period significantly altered the urban ecosystem component of the regional carbon cycle. The annual amount of atmospheric carbon assimilated into phytomass through NPP was reduced by approximately 50.71×10⁴ Mg C (-15.08%). More than half of this reduction is attributed to the loss of cultivated land. Vegetation removal and road disturbance by the expansion of urban areas reduced the amount of carbon uptake.

Under the guidance of eco-city theory, and its practice in China, we use grid calculation method of GIS & landsat pictures of remote sensing to assess the urban eco-environment quality, e.g. the situation and quality of water, air, land & soil in Longxi County, which is a poverty stricken county in long history in west China. Then we use the dynamic system to simulate the urban system of Longxi County, in which we contrast two kinds of developing models, i.e. the normal & transitional ways, and three types of indexes to evaluate the benefits of the developing model, i.e. the environmental, social and economical indexes. We try to find out the driving forces of the transition, which are population, economy, technology, governance, etc. The change of driving forces is the main factor that shapes the future Longxi, and the model shows that if the local policy makers had adopted the eco-city theory, the benefit of transitional eco-city would exceed the normal developing way, and the urban ecology would also be more stable, and the economy of Longxi would be more efficient. So only if the Longxi County were an eco-city, which composed by many eco-towns, eco-villages (some villages have begin to put this theory into practice), that the urban development of Longxi can be sustainable, compared with the normal developing way. And the main economic activities in Longxi will also be the recycling-economy, and resources-saving society, which can best utilize the resources of current Longxi.

The Mid-Yellow River region has been facing serious problems such as the most extensive soil erosion and water loss in the world, water shortage, flood disasters, ecological and environmental degradation. Evapotranspiration is a key component in the energy and water balance and plays an important role in the water cycle of the Mid-Yellow River region. Study on evapotranspiration and water consumption of vegetation (including forests and grasslands) over the Mid-Yellow River region will give basic knowledge of water supply and demand as well as water-consuming characteristics of vegetation. This study will also contribute to rationally develop and use limited water resources in the Mid-Yellow River region, and therefore, it has theoretical and practical significance. In this paper, based on Remote Sensing and GIS techniques, evapotranspiration and water consumption by vegetation were estimated in the Mid-Yellow River region. First, after the geometric correction, radiometric calibration and false color composition, Landsat TM Remote Sensing image in 2000 were interpreted carefully and the vegetation distribution data in the Mid-Yellow River region were gained. Then, by the ArcGIS 8.3 Software, the total area of various vegetation types was figured out and the 1km-Grid dataset was established by which the proportions and ratios of every type of vegetation on the scale of one square kilometer have been expressed. Finally, based on the meteorological data and the Penman-Monteith Method, evapotranspiration and water consumption for various types of vegetation were estimated. The results showed that in the Mid-Yellow River region, water consumption by forests and grasslands were 31.41 billion m³ and 44.08 billion m³ respectively.

The continuing rise in atmospheric CO2 is considered as a main cause of the future changes in global climate. Predicted climate changes include an increase in mean annual air temperature and alterations in precipitation pattern and cloud cover. Elevated atmospheric CO₂ and climate changes are expected to influence the ecosystems. The regional climate models (RCMs) will likely remain primary tools for climate prediction in the foreseeable future. The importance of RCMs is increasing in addressing scientific problems associated with climate variability, changes, and impacts at regional scales. The RCMs have been also used in climate impact studies on ecosystems, especially in agricultural crops by generating climate scenarios for input to crop models. With a large volume of satellite remote sensing data of the earth terrestrial surface becoming available, precisely monitoring the dynamics of the land surface state variables for agricultural and land use management becomes possible6. With the effort to study the climate crop interactions we plan to use a CWRF model (a climate extension of the Weather Research and Forecasting model-WRF) developed by the Illinois State Water Survey to form the climate scenarios. The WRF model is based upon the most advanced supercomputing technologies and promises greater efficiency in computation and flexibility in new module incorporation. This extension inclusively incorporates all WRF functionalities for numerical weather predictions while enhancing the capability for climate applications. To represent the surface-atmosphere interactions the CWRF requires specification of surface boundary conditions (SBCs) over both land and oceans. A comprehensive set of SBCs based on best observational data is desired for CWRF general applications for all effective, dynamically coupled or uncoupled, combinations of the surface modules, as well as for any specific region of the world. This report followed the approach of Liang et al. presents a preliminary work to construct vegetative SBCs for the CWRF modeling effort in China domain by using remote sensing data from TM, AVHRR, MODIS which are freely available. The full list of the CWRF SBCs was defined by Liang.

The Tibetan Plateau is among the fewest extensive regions remote far from the influences of human activities. It provides an ideal site to study the response of vegetation cover to water/thermal (WT) conditions, esp. the response of natural vegetation cover. The paper aims to discuss the spatial variation and then the relations of WT climate elements with satellite derived NDVI. The discussion is taken with the supports of ground climatic observation data and AVHRR NDVI product (8 Km) from year 1982 to 2000, in central and east Tibetan Plateau where the gauge is basically dense enough to qualify related analyses. Based on the simulation of egetation spatial distribution trend surfaces, the transect comparison of different directions and the work of vegetation grouping, the relationships between NDVI and precipitation (N-P for short), between NDVI and temperature (N-T for short) are respectively investigated and analyzed, both spatially and biologically. The results presented by this study indicate that in central/east Plateau annual mean NDVI is less influenced by WT conditions if the covered vegetation is dense and evergreen or totally sparse; the N-T and N-P values of peripheral Plateau regions are low while the values of main plateau body are higher than 0.75; in addition, altitude tends to play an obvious negative role in the spatial distribution of thermal condition, and then in the distribution of vegetation cover.

Forest is the main body of the land ecosystem. As key part of boreal forest in Eurasia, forest in the northeast China plays an important role in maintaining global carbon cycle and regional ecology security. The northeast China is the highest forest coverage ratio area in China, the forest coverage ratio in total area doesn't change much since reform and opening of China, but the spatial distribution of forest cover changes is in regional difference explicitly. Base on land use data of three period (1986a, 1996a, 2000a) remote sensing image, the research applying statistical analysis models and spatial analysis models, analyzed the forest cover change types, landscape characteristics and spatial distribution pattern from the middle of 1980s to 2000. The research result show that: (1) From 1980s, the main forest cover changes in northeast China was in interchange of forestland and cropland, and interchange of forestland and grassland. Among them, the forested land change plays mainly part, and deforest area is bigger than reforest one. (2) From 1980s, despite the forestland area decreases every year in northeast China, landscape pattern didn't change much, forestland is the main part of landscape, the degree of forest landscape fragmentation dropped every year. It shows that forest cover changes frequently take place at the edge of forest, which indicates that a neighborhood relation plays an important role in the forestland changes. (3) From 1980s, forest cover changes in northeast China most happened in hilly land at about 400m height, and took on obvious zonality in horizontal distribution: degree of forest cover change dropped off from south and north to middle, the degree of reforest dropped off from south to north, and the degree of deforest dropped off from north to south.

Benefiting from southeast monsoon, the red soil hilly region in southeast China has excellent water and heat conditions, and land use here changed rapidly these years. Unreasonable land use, however, resulted in serious ecosystem degradation. Before 1980, most of the zonal vegetation in the study area, mainly consisting of evergreen broad-leaved forest, had been seriously destroyed, and degraded to grassland dominated by perennial grasses with scattered trees and shrubs. At the same time, severe soil degradation also occurred in some places of this region. The ecosystem degradation not only reduces the land productivity, but also has a deep impact on global change. So the restoration and reconstruction of the degraded ecosystems are not only important to the sustainable development of agriculture, but also helpful in understanding the role of this region playing in global change. In this paper, soil nutrient changes in surface horizon (0-20cm) of masson pine woods, wetland pine woods and Chinese fir woods planted in 1984, which are widely planted in the red soil hilly area, were studied. The results showed that Soil Organic Carbon decreased dramatically in the first 10 years, then increased gradually in the following 6 years, and reached to a relative steady status in the latest 5 years, while total nitrogen remained relatively steady, and soil acidification is visible.

Study on seasonal change of terrestrial net primary production (NPP) and its responses to climate are to help understand the responses of terrestrial ecosystem to climate change and mechanisms of annual NPP increases. In this study, GLO-PEM simulating NPP data and corresponding climate data were used to explore the seasonal changes of terrestrial NPP and their geographical differences in China from 1981 to 2000. As the results, seasonal total NPP in China showed a significant increase for all four seasons during the past 20 years. The spring NPP indicated the largest increase rate, while the summer NPP was with the largest increase in magnitude. The area of NPP increase was largest in summer, and that of NPP decrease was largest in autumn. Seasonal NPP changed differently in different regions. Increased temperature or precipitation or their comprehensive functions might contribute to the NPP increase, and decreased precipitation might answer for the decreased NPP in most regions. South China had the largest NPP increase in spring, autumn and winter and the highest NPP increase rate in autumn, North China had the largest NPP increase rate in spring and winter, while Central China had the largest NPP increase and increase rate in summer.

Nowadays, urban vegetation abundance estimation using medium spatial resolution satellite images presents great challenges due to the intensive heterogeneity of urban landscapes. NSMA based on spectral mixture analysis (SMA) highlights the spectral shape information and minimizes the effects of absolute pixel reflectance values. It can effectively solve the spectral diversity problem of the same urban biophysical composition. In this study, Nanjing City, East China was chosen as study area. A Landsat TM image acquired in 1988 and a Landsat ETM+ image acquired in 2000 were used to extract vegetation fraction maps. Base on the idea of vegetation-impervious surface-soil (V-I-S) model and the actual condition of the study area, three endmembers (i.g. vegetation, impervious surface, and shade/water) were selected from the normalized images of the two periods. Urban vegetation fraction maps were acquired through applying a fully constrained SMA to the normalized images. Urban vegetation abundance was expressed by vegetation fraction maps. The spatiotemporal dynamics of urban vegetation abundance changes was analyzed systematically using vegetation fraction maps of the two periods. The relation between urban vegetation abundance and urban land use was analyzed, too. The accuracy of the vegetation fraction maps was validated using IKONOS images of the study area. Results indicate that NSMA method is a more powerful tool for estimating urban vegetation abundance. Furthermore, urban vegetation fraction maps may provide a reference for analyzing and monitoring urban environments and urban development.

Hyperspectral remote sensing is not only an important technical method in observing global ecosystems and vegetation cover change, but also a main aspect of studies on precision agriculture. In order to monitor crop nutrient supply condition and to realize precision fertilization, spectral red edge parameter for winter wheat was studied. Experiments were carried out through 8 years since 1997 under four nitrogen support levels in Luancheng Station, Hebei province (e.g., 0, 100, 200 and 300 kg N ha^-1). Canopy reflectance spectrum was measured by ASD HandHeld Spectroradiometer (325-1075 nm) during 2002 and 2004. The dynamics of red edge parameters for physiological stages of winter wheat canopy were calculated using first derivative curve. Analyses revealed that the red edge of the wheat canopy reflectance spectrum locates between 720-740 nm. All the different trial had distinct "red shift" trait, but higher N stress had shorter "red edge" wavelength. Position of red edge turned "blue shift" after pregnant period. Red edge swing is a first-order derivative spectrum when wavelength reached red edge position, red edge swing double peak shape showed that the pregnant period was the best stage to detect nitrogen deficiency. Red edge swing correlated with relative chlorophyll content and leaf N content. Area of red edge peak is the value of first-order derivative spectra accumulative total between 680 and 750 nm. These parameters can be used to estimate LAI and N accumulating quantities, and these results provide information needed for the development of variable-rate N application technology.

Natural Forest Conservation Program (NFCP) was established in China in 1998. As a nationwide engineering project, one of the most important tasks was to mandate conversion of marginal farmlands to forestland or grassland (reforestation or afforestation in farmlands) where topographical slope steepness was more than 25 degree. In order to quantitatively grade agriculture soil loss amount and assess spatio-temporal variation of soil erosion volume, as well as to guide the process of the conversion of farmlands to forest in upstream of Yangtze Rivers. The research analyzed how to calculate K, S, L, C and P factors of Universal Soil Loss Equation (USLE) on the base of considering terrain, climate and characters of agricultural soil using GIS technology. The methods can adapt to the variation terrain of the dry valley region in upstream of Yangtze Rivers. As believed the reforestation was a long-term engineering, the planning of reforest farmlands should be a temporal decision process, which should be considered that where should be afforested at once and where should afforested in abeyance on the basis of grading soil loss amount and the others conditions of farmland. Grading agricultural soil loss amount would be beneficial to program a feasible plan in the conversation of farmlands to forest.

Research and farmers' experiences have demonstrated that reduced tillage helps maintain surface residues and provide substantial benefits in terms of water use efficiency, soil condition and productivity. However, the impact of field traffic and its influence on the soil when tillage is reduced or eliminated have been ignored, for small to middle-sized machinery are mostly used in Chinese agriculture. There is a need to study on wheel traffic impacts and to test controlled traffic farming system for Chinese conditions. This paper reports the five-year controlled traffic conservation tillage experiment in North China. Two trial plots (Spring Maize and Winter wheat) with four treatments and five replications were set up. The results indicated that controlled traffic conservation tillage could minimize the compaction of wheel traffic, make field operation timely and precisely, improve soil structure and increase soil moisture on crop zone which is beneficial to crop establishment and growth. With the accumulation of damages year after year, the impacts of random wheeling are becoming more notable. Heavier machinery appeared to compact soil to a greater depth, but even small tractors could compact the surface 10cm, critical to rainfall infiltration, to a remarkable degree. For the small-scaled controlled traffic system tested in this study, traffic lanes occupy about 20% of the land, but the yields were similar to those in the non-controlled traffic fields. Further test is needed for the long-term impacts of the traffic lanes on soil structure and crop yield and detailed analysis is necessary to develop a suitable controlled traffic farming system.

In this study, we demonstrate that the conventional temperature/vegetation drought index (TVDI) approach tends to overstate the degree of drought condition in areas with dense vegetation. This is because the TVDI approach may specify points with significant evapotranspiration (ET) activities (i.e. points with soil water content significantly above the wilting point) as the drought points in these areas. To overcome this shortcoming, we construct a new drought index, termed evapotranspiration/vegetation drought index (EVDI), using evapotranspiration distribution derived from the remote sensing data. We apply both TVDI and EVDI approaches to calculate drought indices for a dominantly crop farming region, Luancheng County, in Hebei Province of China at the season of high fractional vegetation cover. We use Landsat7 ETM⁺ data to derive the surface temperature, the fractional vegetation cover and evapotranspiration distribution, and compute both TVDI and EVDI maps for this region. Result comparison and analyses show that the TVDI map overstates the drought condition. The EVDI map is a more accurate representation of the real condition.

A remote sensing and monitor system for a large poultry layer farm is developed based on distributed data acquisition and internet control. The supervising system applied patent techniques known as arc orbit movable vidicon, wireless video transmission and telecommunications. It features supervising at all orientations, and digital video telecommunicating through internet. All measured and control information is sent to a central computer, which is in charge of storing, displaying, analyzing and serving to internet, where managers can monitor real time production scene anywhere and customers can also see the healthy layers through internet. This paper primarily discusses how to design the remote sensing and monitor system (RSMS), and its usage in a large poultry farm, Deqingyuan Healthy Breeding Ecological Garden, Yanqing County, Beijing, China. The system applied web service technology and the middleware using XML language and Java language. It preponderated in data management, data exchange, expansibility, security, and compatibility. As a part of poultry sustainable development management system, it has been applied in a large farm with 1,200,000 layers. Tests revealed that there was distinct decline in the death ratio of chicken with 2. 2%, as the surroundings of layers had been ameliorated. At the same time, there was definite increase in the laying ratio with 3. 5%.

According to the ground resolution characteristic of Thematic Mapper (TM) image, we correspondingly measured the relative chlorophyll contents in four key developmental stages of winter wheat in the Lower plain of the Hai River Basin, North China, and explored their correlation with the reflected spectral values that can be obtained from TM image. Considering not only NDVI but also the relative content of the chlorophyll, 31 RS variables were selected and the relationship between the variables and the relative content of chlorophyll was established. Regression models were built for quantitatively predicting winter wheat growing condition from TM images. Also the spatiotemporal variability of the winter wheat growth status at heading and booting stages were analyzed by geostatictics approach. The correlated spatial variability of the relative content of chlorophyll existed in the case study area, and the range of correlative distance was from 145.4 to 320.0m. The spatially structured variances were between 75% and 21% of the total variances, and the empirical semivariograms in the four stages could be simulated in spherical models. The result showed that it is feasible to use TM data for real-time and highly accurate monitoring of crop growth status and nutrient management of farmland ecosystems.

Vegetation cover is the primary index of the earth's ecological system and the change in large-scale vegetation cover represents the effects of natural and human activities upon ecological environments and change in vegetation bears an intimate relation with that of climate, thus being one of the heated issues in the research of global change. In the context of 1981-2001 NOAA/AVHRR NDVI satellite sensings, classified vegetation types and climate data for the Huanghe-Huaihe-Haihe (HHH) zone and based on a range of vegetation types selected, including forested land, grassland, meadow and farmland, study is conducted on the dynamic variations of NDVI on a seasonal and an interannual basis, together with their relations to climate change investigated, thus achieving some preliminary findings regarding the seasonal and interannual variation features of the HHH vegetation. Results show that, viewing the situation as a whole, the yearly variation displays intense seasonality under the control of monsoon climate while looking at the interannual variation, the 1981-2001 mean NDVI exhibits insignificant rise trend, bigger in spring compared to other seasons; types of scattered vegetation and forests are more steady on an interannual basis but the agricultural types change dramatically, indicating relatively greater effect of human activities; the vegetation degradation has occurred in the HHH zone in recent years; farmland vegetation is dominant and natural vegetation is about half the agricultural area; for different vegetation types, multi-yearly mean NDVI follows almost the same course on an interannual basis, except for some difference in range between them; yearly rainfall and temperature have positive effect on dynamic NDVI variation while evaporation is in higher negative correlation with the NDVI; Water is a sensitive factor to the growth of conifers, grassland and crops in spring and summer. Water and heat are important to biannual crops, broadleaf trees and grassland vegetation in autumn. In winter all types of vegetation are insignificantly correlated to climate factors.

This work was based upon the combination of space- and ground-based data. Sensings at 1.1 km × 1.1 km resolution from the polar-orbiting weather satellite were retrieved by a range of split window algorithms to obtain surface temperatures, which were used to construct a regression equation with minimum surface temperatures (MST) measured at a number of meteorological stations, with the retrievals and measurements corrected by a variational scheme to get gridded MST's. After comparison of errors from these algorithms the best one was selected for retrieving. By use of the retrieved temperatures re-corrected by the variational technique, injury indices and wheat conditions during its growth stages, the regional distribution was prepared of varying-degree cold injuries to the crop, with corresponding hit areas statistically calculated, thereby making it possible to sensings monitor the injuries and precisely determine areas hit by the varying-degree droughts.

Using data from Zhengzhou the Excel-made time-dependent variations in the growth and development (G/D) stages of winter wheat in 1981-2002 are investigated, with analysis done of the curves. Also, the trends of G/D variations over the years are dealt with by use of the related tendency rates of the appearing dates of all the G/D stages of the crop. Results show that the dates of pre-winter G/D stages depend mainly on the seeding date and the overwhelming majority of the G/D stages shift to an earlier date in the vegetative growth period. A statistical expression is constructed by utilizing the 1981-2002 data of the number of days of the G/D stages and corresponding mean temperatures, with which to explain the variation of the G/D stages of winter wheat.

A steady model was used to investigate the effect of building parameters on solar energy collecting efficiency of solar greenhouses in north China from 35°N to 45°N, including Lanzhou, Xining, Jinan,Yinchuan, Beijing, Huhhot, Shenyang and Urumchi. Building parameters include span, height and angles of roof. Useful solar energy and heat load were simulated from November to March. The simulation results show that when inner temperature is set at 15°C, the ratio of useful solar energy to total heating requirement (heating guarantee ratio) is from25% to 49% for the same type of production structures at different latitudes in January, while in March, the heating guarantee ratio reaches 100% in Lanzhou, Jinan, Yinchuan and Beijing, and about 65% in Shenyang and Urumchi, and that solar energy collected inside greenhouses increases with the increase of span, height and angles of roof, however, the heating guarantee ratio has little change, which means that the variation of geometrical dimensions has little effect on energy saving when compared with production structures existed. The study also suggests that the solar energy heating guarantee ratio can reach up to 40% and 60%, respectively, at latitude of 44°N and 40°N during the coldest days by increasing heat resistance of south roof and reducing air infiltration. Air temperatures inside and outside a large-scale solar greenhouse without auxiliary heat resources in shenyang were measured from December to March to validate the model.

Landscape is a dynamic phenomenon that almost continuously changes. General speaking, landscape change is a dynamic process affected by geophysical conditions as well as human activities. However, numerous activities by a large number of individuals are not concerted and contribute to the autonomous evolution of the landscape in a similar way as natural processes do. There is a well-established need to detect landscape change so that appropriate policies for the regional sustainable development can be developed. Landscape change detection is considered to be effectively repeated surveillance and needs especially strict protocols to identify the change categories and intensity. Methods for monitoring and analyzing landscape change - for example, remote sensing and GIS - are increasingly used in attempts to understand the consequences of such change. This paper developed a hierarchical approach that combines remote sensing technology, GIS, and sophisticated analytical techniques to quantify land cover change at several spatial scales. Through human-machine interactive interpretation, the interpretation precision was 92.00% in 1986 and 89.73% in 2000. Based on the interpretation results of TM images and take Yulin Prefecture as the case study area, the area of main landscape types was summarized respectively in 1986 and 2000. The landscape pattern changes in Yulin could be divided into ten types.

Longdong region is known as one of the most serious soil erosion areas in the Loess Plateau of China. In this paper, Modified Soil Adjustment Vegetation Index (MSAVI) calculated from the shared Terra/MODIS data. Slope is derived from GTOPO-DEM data provided by the US Geological Survey (USGS). Soil Erosion Intensity of Longdong loess plateau region is calculated with the following three factors MSAVI, slope and average annual rainfall. Compared with previous soil erosion result produced in 1991, the two results match quite well, which shows that the remote sensing data of MODIS is applicable in rapid assessment of regional soil erosion.

The construction of many water conservancy projects home and abroad caused a series of ecological and environmental problems. The core issue was related to water. Based on this consideration, China stipulated that water resources justification must be conducted for construction projects. By briefly describing the necessity of considering eco-environment water right in water resources justification of construction projects, this paper explained the concept, property and allocation algorithm of river eco-environment water right and emphasized the research on the basic concept and algorithm of eco-environment water requirement. The paper pointed that the eco-environment water requirement could be divided into optimal eco-environment water requirement, objective eco-environment water requirement, critical eco-environment water requirement and status quo eco-environment water requirement by different water requirement properties. From the objective of maintaining the natural structure and function of water eco-environment, the paper pointed that the river eco-environment water requirement in water resources justification of construction projects mainly consisted of river course eco-environment water requirement and floodplain eco-environment water requirement and expounded in detail the theoretical method for calculating the two types of water requirements. By applying the method of calculating eco-environment water requirement for a diversion project of a certain waterworks, the paper found out that the eco-environment water requirement should be 3.854 billion m³.

Ecological security of Chanchuan watershed in the soft rock area of Middle Yellow River was synthetically evaluated and multi-objective programming of land use was forwarded by using RS and GIS techniques along with systems analysis methods. Moreover, according to the landscape ecology theory, digitalized optimum spatial patterns and rational proportion of land use were obtained through computer-aided adjustment with GIS software to get visible images of land use pattern that guarantees ecological security at Changchuan watershed. The results of comprehensive evaluation on ecological security of land use at Changchuan watershed indicate that measures of soil erosion control, ecological and environmental construction has certainly improved the situation of ecological security of this region during past decades, but the current situation of ecological security was not satisfactory. The results of multi-objective programming of land use pattern based on the ecological security evaluation indicate the optimum land use structure should be 3.7% of woodland, 38.6% of brushwood, 49.4% of grassland and 6.3% of crop land. Their spatial distributions were also patterned in light of requirement of ecological security. The average ESI in this region is leveled at relative secure, figuring at around 0.85.

The semi-arid catchment of the Loess Plateau of China is severely affected by soil erosion as it is revealed by the commonly occurring deep and wide gullies. Recent studies in the loess hill-gully terrain area show Gully erosion have a very significant contribution to total soil loss. Traditionally, gully erosion had been measured using a combination of field survey techniques and analogue, the advances in computing powering digital photogrammatric solution are now offering an affordable and cost effective way of estimating the gully erosion. This paper uses the digital elevation models (DEMs), which constructed from multi-date (1959,1981 and 1999) aerial photographs (1:55000, 1:20000 and 1:35000) as a tool to computing the sediment yield by gully erosion in a small catchment of 9.06 km² located in the Loess Plateau of China. The High-resolution DEMs (2 m grid) were derived from stereo image pairs separately and analyzed by means of geographical information system techniques. Gully breaklines and borderlines were positioned to measure the gully dynamics and soil loss was estimated from computed gully volumes using soil bulk density, and DEM-measured gully degradation rate was discussed as well. DEM-measurement techniques integrates the soil loss due to overland flow and mass movements and gully deepening, and put forward an improvement to locate the areas within the gullies with higher erosion possibility.

The Normalized Difference Vegetation Index (NDVI) and the thermal infrared information of remote sensing have been widely used to study urban climate. In this study, the time series of 8 km-spatial-resolution NDVI images obtained from the Pathfinder NOAA-AVHRR Land (PAL) dataset in the period of 1982 to 2000 was used to assess the trends of NDVI in Beijing both urban and rural areas. The relationship between the NDVI variation and urban heat island (UHI) intensity was investigated. And the results showed that the NDVI in Beijing urban region decreased with time and the NDVI in Beijing rural region had no obvious change. The annual UHI intensity increased with the increasing of NDVI difference between urban and rural regions. Meanwhile, the data of Landsat Enhanced Thematic Mapper Plus (ETM +) combined with classification-based surface emissivity in Beijing area were utilized to estimate land surface temperature (LST). The relationship between LST and NDVI derived from ETM+ showed an obviously negative correlation. In general, in Beijing area the distribution of NDVI directly defined the distribution of LST. In the urban region the NDVI was small and LST was high, while in the rural region the NDVI was large and LST was small. The derived LST from ETM+ was also compared with measured air temperature at weather stations. There was an obvious correlation between surface temperature and air temperature. This indicates that the surface temperature derived from Landsat can describe the distribution of UHI.

The new concept about the resource efficiency in Xinjiang has been discussed in this study based on the advanced technology theory in policy making perspective. The analysis is focused on the resources advantage in the development, resource pressure, resource efficiency and technical approach to resource efficiency. The idea of industrialized development centered on resource efficiency, its control factors and basic technical framework for realization of resource efficiency factors, which include technique in application of recycled materials; water-saving technique oriented for efficiency in applying water resource; bio-technology for high yield and better quality of farm crops; comprehensive technique involved in farm-produce further process and agricultural industrialization; information technology around information support and information-oriented society; technique in transforming resources including oil and natural gas, mineral products and wind power; technique in control of desertification and biological security.