The broader scientific community is slowly coming to grips with the concept of sustainability. An inherent difficultly with this concept has been that, unlike traditional scientific investigations that seek to explain how things currently function or how previous events led to current phenomena, sustainability research is forward-looking with the goal to understand how both current, and indeterminate future, societal needs can be met. This goal is further constrained by an imperative for maintaining ecological and environmental integrity. This conference addresses several important themes pertinent to the challenge of sustainable ecosystems: data collection and monitoring of natural systems and their components, analysis of those data in the context of biophysical ecosystem models, and application of model outputs to environmental and economic issues for management and policy making. Ecological scale and systems science are two important, but often underappreciated, concepts that are critical for advancing our understanding of sustainability. New sustainability sciences, appearing at the interface of traditional disciplines, are better poised to integrate these concepts. The most important objective of our data collection and modeling efforts will be to anticipate sustainability problems and recommendation alternative courses of action, while aiding social learning by the non-scientific community.

The initial adoption of site-specific management for cotton production was slower than by commodities grown in the mid-west. Part of the delayed adoption can be explained by the lack of functional cotton yield monitors. Now that yield monitors are commercially available, cotton producers are beginning to find many applications for geospatial technologies. The emphasis of this paper is on applications that are being implemented at some level on commercial farms. Traditional grid-based soil sampling has found some use for pre-plant application of fertilizer, and soil conductivity mapping has been used to apply variable rate soil amendments in the west. During the growing season, vegetation indices such as the normalized difference vegetation index (NDVI) have been used as a tool to direct scouting for insect infestations. The scouting information and NDVI are combined to create variable rate insecticide application maps. A catalyst to this approach has been the recent development of aerial variable rate application technology. In some production regions, it is necessary to control cotton's vegetative development rate with plant growth regulators (PGRs). Vegetation indices are very useful for defining areas of the field where PGRs are needed. Research is also being conducted on the use of imagery for the development of defoliation application maps before harvest. In the short-term, simple vegetation indices can meet many of management information needs for cotton when combined with directed scouting of the field. However, to be ultimately successful, dependable and frequent sources of imagery will be required. Near-real time delivery is essential, as a majority of the management decisions are often made on a daily basis. Most producer-based applications of these data have been from airborne platforms managed by local image providers where flexible image acquisition schedules are possible.

Land-Use/Land-Cover Change (LUCC) affects farmland productivity by changing the quality of land resource and pattern of land-use. Based on meteorological data and land-use/cover observation dataset obtained from the dynamic serving system of National Resources and Environment Database (NRED), this paper calculated the Photosynthetic Thermal Productivity (PTP)of farmland, and analyzed impact of recent LUCC and climate fluctuation on PTP. Results showed that under the influence of LUCC, PTP distribution had an extensive and unbalanced change. LUCC increased China’s total PTP by 26.22 million tons, while climate fluctuation increased it by 169.92 million tons. The ratio between LUCC and climate fluctuation was 1:6.48. Due to the direct effect of LUCC, PTP increased in the following regions: Northeastern Plain, Inner Mongolia, and Xinjiang province. This increase was primarily driven by plantation reclamation. PTP decreased in the Huang-Huai-Hai Plain, the Yangtse Rive delta, the Zhujiang delta, the Southeastern coastal provinces, the southeastern Sichuan basin and the Xinjiang oasis. The decrease was mainly caused by urban expansion.

Hyperspectral imagery is capable of providing detailed spectral reflectance information of agricultural fields for potential use in site-specific management operations. Analysis of these data are complicated by the large number of spectral bands, the many different components or endmembers (e.g. plant and soil), and the presence of shadows. Unlike simple unmixing approaches which compute the fraction of a fixed number of components, multiple endmember spectral mixture analysis (MESMA) also determines which components are present in each pixel. This study compared whether using different shadow endmembers (EM) in a 4-EM model (sunlit green leaf, sunlit soil, shadowed leaf, shadowed soil) would improve estimates of scene components compared to a 3-EM model (sunlit green leaf, sunlit soil, photometric shade). Results revealed that correlations with percent cover and height were improved when shadow or shade endmembers were included for both models compared to the green leaf fraction alone. The 3-EM model was superior for developing a direct relationship for estimating cover and height but was not able to estimate SPAD or chlorophyll a. The 4-EM model showed the best results for SPAD and chlorophyll a, with r² values of 0.84 and 0.77, respectively.

We describe development of a background spectral library for Fort A. P. Hill, located in northeastern Virginia, based on hyperspectral images and an extensive land cover database. The database was used to identify areas of uniform land cover. The library contains means and standard deviations for 15 spectra measured in these uniform areas. Terrain categorization products consist of classification maps and fractional abundance maps determined by linear mixture analysis. There is excellent qualitative agreement between the linear unmixing results and the known land covers.

The performance of a home-built tunable diode laser (TDL) spectrometer has been optimized regarding multi-line detection of carbon dioxide in natural gases. In the regime of the (30⁰1)_III;←(000) band of ¹²CO₂ around 1.6 μm, the dominating isotope species ¹²CO₂, ¹³CO₂, and¹²C¹⁸O¹⁶O were detected simultaneously. In contrast to most established techniques, selective measurements are performed without any sample preparation. This is possible since the CO₂ detection is free of interference from water, ubiquitous in natural gases. Detection limits in the range of a few ppmv were obtained for each species utilizing wavelength modulation (WM) spectroscopy with balanced detection in a long-path absorption cell set-up. Linear calibration plots cover a dynamic range of four orders of magnitude, allowing for quantitative CO₂ detection in various samples, like soil and breath gas. High isotopic resolution enables the excellent selectivity, sensitivity, and stability of the chosen analytical concept. The obtained isotopic resolution of typically ± 1.0 % and ± 1.5 % (for 3 vol. % and 0.7 vol. % of CO₂, respectively) offers a promising analytical tool for isotope-ratio determination of carbon dioxide in soil gas. Preliminary experiments on soil respiration for the first time combine the on-line quantification of the overall carbon dioxide content with an optode sensor and isotopic determination (TDL system) of natural gas species.

This paper reports a comprehensive analysis on farm production and resources sustainability in Northwest China during 1978 to 1999. Besides the five provincial regions (Shaanxi, Gansu, Ningxia, Qinghai, and Xinjiang), the upper and middle parts of the Yellow River Basin were also included as a nested area for detailed evaluation. The gross value of farm production was chosen to be the dependent variable in data analysis. Independent variables include farm inputs of irrigation ratio, agricultural labor, fertilizer application, and farm machinery use. In the study period, farm production increased four- to five-fold in the regions, strongly associated with the increased application of technological inputs of fertilizer and machinery. Multivariate regressions were performed based on Cobb-Douglas and Frontier production functions between farm production and inputs. Based on the function parameters, the growth of farm production was decomposed into the contributions by farm inputs and total factor productivity. 10-20% of the growth in farm production was attributed to the increased irrigation ratio in Shaanxi, Gansu, and Ningxia, where the irrigation ratio was relatively lower than other regions and increased significantly during the study period. Productivity in irrigated farmland was found to be over 10 times higher than that of rainfed areas in the regions. For the provincial regions, technological input of fertilizer and machinery contributed to more than half of the growth in farm production in the period of 1978-1998. For the upper and middle parts of the Yellow River Basin, total factor productivity accounted for two-thirds of the farm output growth after 1985. In late 1990s, the regress of total factor productivity caused a significant reduction in farm production due to the drop in grain price and basin-wide drought. Total factor productivity in the basin was decomposed as two components of technological progress and relative technological efficiency. The relative technological efficiency was below 70% with a decreasing trend during 1980 to 1999. To integrate hydrological and economic processes in this study, a spatial model was developed to predict water supply and demand. Some preliminary results of this model were also presented.

Quantitative remote sensing and GIS technologies are providing opportunities for Bioproduction and natural resources monitoring. Some gross primary production (GPP) and net primary production (NPP) models take ecological structure parameters (Land cover, LAI, and biomass) retrieved from remote sensing data as inputs to get information on ecosystem exchange on a global scale. Our recent research focuses on key problems in retrieving variable parameters of land surfaces from remote sensing observations, such as, the observing scale is different from the measuring scale of ground truth, the parameters which application requires may not be the same as the parameters of current physical models, the uncertainty of retrieved parameters by model inversion. In this paper, we present our new approaches on scaling effect modeling, physical model inversion by using prior knowledge, field experiments and setup of the spectrum knowledge base of typical objects, and the applications of the quantitative remote sensing research achievements in ecosystem assessment and monitoring, such as, in GPP and NPP of forest, energy exchange of crop field and grassland, water cycle, climate change. Some new modeling ideas and parameters retrieving results will be shown in this paper, as well as some remote sensing application samples.

Human-induced land-cover and land-use change (LCLUC) has a profound impact on the magnitude and dynamics of spatial and temporal patterns of greenhouse gas emissions and regional climate change in a wetland-dominated Amur River Basin, henceforth referred to as the Three-River-Plain (TRP) region, in Northeast China. The TRP region has the largest natural wetland extent in China. Drainage of wetlands and conversion from wetland into agriculture land use may be one of the primary reasons for the regional climate change. The region's temperature experienced two sudden increases in early 1970s and late 1980s and those changes were coincident with the time frames of large-scale agricultural reclamations. The TRP region warrants a significant regional study to answer questions such as “were human-induced LCLUC significant to affect the magnitude and spatial temporal greenhouse gas emissions and further responsible for regional climate change?” Integration of satellite remotely sensed land surface conditions and in situ measurements of greenhouse gas fluxes provide a reliable information source to study the spatial-temporal patterns of greenhouse gas emissions. Integration of remote sensing detected land-cover change and patterns of greenhouse gas fluxes associated with different land-cover types allows quantification of regional greenhouse gas emission and further studies the driving factors of regional climate change. Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing data are necessary toward this effort.

International experience shows that rapid economic growth is accompanied by a large shift of agricultural land to other uses. The overall goal of this study is to examine the changes of the area and bioproductivity of cultivated land in China where the size of the economy doubled every 8 years. Based on Landsat TM/ETM digital images covering China’s territory in the past 15 years and by utilizing the AEZ methodology, our study finds that contrary to many people’s expectations, China recorded a net increase of cultivated land by 2.65 million hectares in 1986-2000 and accounted for nearly 2% of all cultivated land. We also found that the average productivity of cultivated land declined by about 0.31%, as the bioproductivity of new cultivated land converted from other uses was generally lower than that of cultivated land converted to other uses. Despite a decline in land bioproductivity in the past and a likely decline in total cultivated land in the future, their impact on agricultural production will be minimal. China can maintain a healthy cultivated land base for food and agricultural production in the long term.

Northwestern China, located in the hinterland of the Asia-European continent, is composed of arid and semi-arid areas, with a very vulnerable natural environment and a long history of oasis economy. Implementation of the new policy of development of Western China resulted in both economic progress and environmental crisis. This article, using Wuwei City as an example, evaluated the sustainability of its environment and analyzed the scenarios of energy, pollution discharge, transportation, food, industry and urbanization. Polestar language, the model developed and used by the Global Scenario Group, was applied to simulate the development of the study area. The results revealed that Wuwei city would reach a severe eco-environmental crisis under the conventional development patterns in the next ten to twenty years. Therefore, a sustainable scenario was recommended in the urbanization of Wuwei, and appropriate suggestions were also put forward to the policy makers.

Consecutive droughts that have occurred in the Canadian prairies have resulted in significant economic losses, ecological degradation, and environmental deterioration. The purpose of this study was to investigate the efficiency of remotely sensed data on drought assessment combined with climate data. The study area was the Canadian prairie ecozone in the provinces of Alberta, Saskatchewan, and Manitoba. There objectives were five-fold: 1) comparing Kriging and inverse distance weighting (IDW) interpolation methods, 2) comparing four spectral variables, the normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the red and the mid infrared (MIR), 3) comparing three moisture indices (P-PET, P/PET and (P-PET/PET), 4) evaluating the relationships between spectral variables and moisture indices, and 5) assessing drought effects on different ecoregions. Results showed that there is no significant difference between Kriging and IDW, the two interpolation methods. MODIS vegetation indices could effectively assess drought conditions, especially EVI. Among the moisture indices compared, P-PET showed a better result. The impacts of droughts vary from year to year and from ecoregion to ecoregion. Aspen Parkland has higher drought resistance because of tree components.

There is more population but less cultivated land in the Pearl River estuary region South China. The commissariat provision in the region is not enough for a long amount of time. The distribution of acid sulphate soil (ASS) is constantly changing for the Pearl River Delta as it expands seaward. It is important to research the ASS for land use planning and crop potentiality in appraising the Pearl River estuary. As more than 20 years have passed since the soil type maps and reports of the 2nd national soil investigation were made, soil quality problems have appeared. These problems can be solved by modern remote sensing and GIS techniques. The ASS units are updated by the analysis of the new remote sensing images and the application of digital elevation model (DEM). Changes in the ASS area are also produced by GIS. Finally, a practical distribution of ASS is presented in the map. The authors found out that the results of remote sensing and the GIS methods are of high reliability and spatial conclusiveness by comparing the result data with the past investigation report of soil and some field exploration data.

The objective of the PEEIR (Pacific Estuarine Ecosystem Indicator Research Consortium) program is to develop new indicators for assessing wetland health or condition. As part of PEEIR program we are investigating the use of imaging spectrometry to map and characterize marsh vegetation of several estuarine systems in California. We obtained airborne Advanced Visible Infrared Imaging Spectrometer (AVIRIS) data, an instrument which measures a detailed reflectance spectrum (400-2500nm) for each pixel, over paired tidal marshes, having either a history of exposure to pollution or no known exposure. AVIRIS image data was analyzed based on comparison to field measurements and reflectance changes measured in hydroponic experiments. We report leaf and canopy reflectance measurements of several common plant species of Pacific coast salt marshes exposed to different concentrations of heavy metals (Cd, V) and crude oil contaminants. Species exhibited differential sensitivities to specific contaminants, however in general, Salicornia virginica, the most salt tolerant species and the dominant species in these wetlands (70-90% cover) was most sensitive to metal and petroleum contaminants. Field measurements of canopy reflectance, biomass and vegetation structure were acquired across GPS-located transects at each field site. The AVIRIS data were calibrated to surface reflectance using the FLAASH radiative transfer code and geometrically registered to coordinates using the 1m USGS digital orthophoto quads. AVIRIS results show spatial patterns of plant stress indicators (e.g., reduced chlorophyll and water contents) are consistent with known patterns of contamination in these tidal wetlands.

The development of spectral libraries for specific vegetation species and soils is useful for identifying different physiological or physical-chemical characteristics. Usually, spectral libraries are provided as a data-base add-in of current commercial software used for analyzing hyperspectral imagery. The use of those databases requires installation of the software in the user’s machine for either visualizing or using the spectral libraries. There are also spectral libraries available on the web but the data is static and partitioned by spectrum of vegetation or soil because the size of the files of actual hyperspectral images precludes it’s publication on the web. In this paper, a web-based simulation environment for generating hyperspectral synthetic imagery of cotton plots is presented. The system was developed using Java and is based on a previous synthetic imagery program¹. The mathematical and numerical formulation of the model is briefly sketched. The core computing components of the simulation environment were written in C for their computational efficiency. The emerging Java Native Interface (JNI) technique and standard Java techniques were used to design a user-friendly simulator. The simulation system provides interactive user control and real time visualization of the resulting hyperspectral image through standard web browsers. It shows potential for providing web-based hyperspectral libraries, in the form of images, for public use.

External-interface computer code has been written for the cotton growth model, Gossym, such that it can be operated from the ArcView GIS interface. Remote-sensing data have been incorporated as an estimator of plant height for feedback to the model. Management zones are delineated automatically based on available spatially variable data, and Gossym subsequently calculates outputs for each management zone, and uses current remote-sensing data in the calculations. This advanced Gossym model system also gathers local weather data automatically over the internet. Development and use of the model system are also described. Site-specific field data and remotely sensed images have been collected extensively on two agricultural fields in Mississippi from 1998 through 2003. Evaluation of yield prediction based on the Gossym model system indicated that current remote-sensing data can enhance accuracy. Details of experimentation and data analysis are presented.

We present the results of recent experiments and analysis on the polarization discrimination technique developed by us to separate elastic reflectance and fluorescence components resulting from white light illumination of algae in seawater. The technique uses the polarized properties of elastically scattered light and unpolarized properties of fluorescence to separate the two. The approach was successfully applied to measurements on four types of algae of different sizes and shapes in the laboratory, with both polarized and unpolarized illumination sources, and, with in some cases, the addition of different concentrations of clay as well as in-situ field measurements in eastern Long Island. The procedure is shown to be effective for extraction of the chlorophyll fluorescence in the 685 nm region from reflectance of algae dominated by chlorophyll pigments. We also report the results of preliminary experiments of the impact of surface roughness on the efficacy of the technique for measurements both above and under the surface.

Radiometric surface temperature (T_s) is commonly used as a surrogate for aerodynamic temperature (T_o) in computing the sensible heat flux term (H) in the energy balance. However, these temperatures may differ by several degrees, leading to possible errors (especially for large H) and their relationship is not well known. Previous researchers have established empirical and semi-empirical parameterizations of the radiometric roughness length (z_or) or some related form (e.g., kB_r⁻¹ = ln[z_om/z_or], where z_om is the momentum roughness length). In this paper, we estimated T_o - T_a (where T_a is air temperature at 2 m height) and z_or using large, precision weighing lysimeters planted with irrigated alfalfa, irrigated and dryland cotton, and dryland grain sorghum. T_s was measured by infrared thermometers mounted over the lysimeters. No apparent relations were found between (T_o − T_a) and (T_s - T_a) or between z_or (in the kB_r⁻¹ form) and meteorological variables or leaf area index (LAI). The kB_r⁻¹ parameter appeared to be most influenced by the different surface roughness of each crop type. Using constant kB_r^-1 values established for each type of surface, the energy balance model showed reasonable agreement with H and LE derived from lysimeter measurements.

In water limited environments, the density and water content of plant canopies are highly correlated to available soil moisture. Specific absorption bands for liquid water are identifiable and the variation in their depths can be related to canopy water content using high spectral resolution (hyperspectral) imagery. The spectral absorption feature centered at approximately 980 nm has been widely utilized for estimating equivalent water thickness, a measure of the volume of canopy water if it is equally distributed over the area of the pixel. Although it is affected by canopy structure, it is highly correlated with plant water content, and is independent of reflectance changes due to photosynthetic pigments. This study relates the depth of the 980 nm water band absorption, measured by the continuum removal (CR) technique, to crop water stress, and compares these results to other vegetation and plant stress indicators, NDVI and NDWI.

Plant foliage density expressed as leaf area index (LAI) is an important parameter that is widely used in many ecological, meteorological and agronomic models. LAI retrieval using optical remote sensing usually requires the collection of surface calibration values or the use of image information to invert radiative transfer models. A comparison of LAI retrieval methods was conducted that included both empirical methods requiring ground based LAI calibration measurements and image based methods using remotely sensed data and literature reported parameter values. The empirical approaches included ordinary least squares regression with the Normalized Difference Vegetation Index (NDVI) and the Gitelson green index (GI) spectral vegetation indices (SVI) and a geostatistical approach that uses ground based LAI measurements and image derived kriging parameters to predict LAI. The image based procedures included the scaled SVI approach, which uses NDVI to estimate fraction of vegetation cover, and a hybrid approach that uses a neural network and a radiative transfer model to retrieve LAI. Comparable results were obtained with the empirical SVI methods and the scaled SVI method. The geostatistical approach produced LAI patterns similar to interpolated ground-based LAI measurements. The results demonstrated that although reasonable LAI estimates are possible using optical remote sensing data without in situ calibration measurements, refinements to the analytical steps of the various approaches are warranted.

The Relationships between rape biomass and hyperspectral vegetation indices are investigated in this paper. The data for this study comes from field hyperspectral reflectance measurements of rape during 2002-2003 growing period. Reflectance was measured in discrete narrow bands between 350 and 2500 nm. Observed rape biomass included wet biomass (WBM including leaf wet biomass-LWBM, stem wet biomass-SWBM, fruit wet biomass-FWBM), and dry biomass(DBM: including leaf dry biomass-LDBM, stem dry biomass, fruit dry biomass-FDBM). Narrow band normalized difference vegetation index (NBNDVI) and narrow band ratio vegetation index (NBRVI)involving all possible two-band combinations of discrete channels was tested. Special narrow band lambda (λ1) versus lambda (λ2) plots of R2 values illustrate the most effective wavelength combinations (λ1 and λ2) and band-width (Δλ1 and Δλ2) for predicting rape biomass at different development stage. A strong relationship with rape biomass is located in red-edge, the longer portion of red, moisture-sensitive NIR, longer portion of the blue band, the intermediate portion of SWIR, and the longer portion of SWIR.

Evaluation of near-surface soil properties via remote sensing (RS) could facilitate soil survey mapping, erosion prediction, fertilization regimes, and allocation of agrochemicals. The objective of this study was to evaluate the relationship between soil spectral signature and near surface soil properties in conventionally managed row crop systems. High-resolution RS data were acquired over bare fields in the Coastal Plain, Appalachian Plateau, and Ridge and Valley provinces of Alabama using the Airborne Terrestrial Applications Sensor (ATLAS) multispectral scanner. Soils ranged from sandy Kandiudults to fine textured Rhodudults. Surface soil samples (0-1 cm) were collected from 163 sampling points for soil water content, soil organic carbon (SOC), particle size distribution (PSD), and citrate dithionite extractable iron (Fed) content. Results showed that covariance among soil properties combined with mixed signatures limited our ability to identify discrete spectral response patterns for near-surface soil attributes. Dry, sandy epipedons at the Coastal Plain site provided ideal conditions and allowed for better discrimination among soil properties. Using ATLAS thermal infrared (TIR) bands, this study provides evidence that thermal spectra are more sensitive to small changes in near -surface mineral, organic and water content.

Landsat TM/ETM+ sensor data has proven to be a highly effective data source for vegetation and land use classification at both global and regional scales. In this study, based on land cover classification, we conducted computer-aided analysis of degradation sequence of the meadow grassland in Xilin River Basin, Inner Mongolia, using 4 sets of Landsat TM/ETM+ images (WRS 124-39 and 124-30) acquired on Jul.31, 1987, Aug.11, 1991, Sep. 27, 1997 and May 23, 2000, respectively. Primarily, 17 sub-class land cover types were recognized, including 9 grassland types at community level: F. sibiricum steppe, S. baicalensis steppe, A. chinensis + forbs steppe, A. chinensis + bunchgrass steppe, A. chinensis + Ar. frigida steppe, S. grandis + A. chinensis steppe, S. grandis + bunchgrass steppe, S. krylavii steppe, Ar. frigida steppe and 8 non-grassland types: active cropland, harvested cropland, urban area, wetland, desertilized land, saline and alkaline land, cloud, water body + cloud shadow. Then we created thematic maps of the areal change and spatial variation of the meadow grassland in Xilin River Basin, Inner Mongolia. We used Geographical Information System (GIS) tools to create thematic maps of the meadow grassland and then analyzed its degradation sequence (or the evolution route). Driven by overgrazing, the meadow grassland ecosystem in Xilin River Basin, Inner Mongolia had undergone and was undergoing degradation evolution; the evolution route was from meadow grassland (F. sibiricum steppe, S. baicalensis steppe), via temperate grassland (A. lymus + bunchgrass steppe, A. lymus + forbs Steppe, A. lymus + S. grandis steppe, S. grandis + bunchgrass steppe, S. grandis + forbs steppe and A. lymus + Ar. frigida steppe) to desert grassland (S. krylavii steppe and Ar. frigida steppe). Results of this study show that increasing human population and accelerated social-economic development has caused dramatic degradation and fragmentation to the grassland ecosystems in Xilin River Basin.

A new parameterization of snow-free land surface albedo is developed using the MODerate resolution Imaging Spectroradiometer (MODIS) products of broadband black-sky and white-sky reflectance and vegetation information as well as the North American and Global Land Data Assimilation System (LDAS) outputs of soil moisture during 2000-20003. It represents the predictable albedo dependences on solar zenith angle, surface soil moisture, fractional vegetation cover, and leaf plus stem area index, while including a statistic correction for static effects specific of local surface characteristics. All parameters are estimated by solving optimization problems of a physically based conceptual model for the minimization of the bulk variances between simulations and observations. A preliminary result showed that, for composites of all temporal and spatial samples of a same land cover category over North America, correlation coefficients between the new parameterization with the MODIS data range from 0.6 to 0.9, while relative errors vary within 5-20%. This is a substantial improvement over the existing state-of-the art Common Land Model (CLM) abide scheme, which has correlation coefficients from -0.5 to 0.5 and relative errors of 20-100%.

INEA has developed a study, based on remote sensing and Geographic Information System (GIS) technologies, on the changes in land use, vegetation conditions and crop water requirements after the realisation of a tunnel in the Apennine. In fact, this tunnel has significant effects on the drainage of superficial and underground waters. The diachronic NDVI and land use analysis in 1992 and 2001 (before and after the tunnel realisation) show significant negative changes in vegetation index, and certain vulnerability of some agricultural surfaces. For a better estimation of the influence of water drainage on NDVI and to establish the exact correlation between the changes in vegetation index and lower levels of humidity in soils and in vegetation, the NDVI analysis was made on clusters of pixel corresponding to each zone of water drainage/gallery. For each drainage zone the drained volumes of water were also related to the total crop water requirements. To complete the analysis and to isolate the effects due to the gallery from a generalised reduction of NDVI in the area, an examination of the differences of the index between 1992 and 2001 in both areas (influenced and not by the gallery) was made.

The Pearl River Delta of Guangdong province in China is one of the world’s largest growths in urbanization for the past 20 years. The objective of this research is to explore the relationship between urbanization and water quality in this area. Present and past remote sensing data including MSS< TM/ETM and ASTER are used to research the urbanization and its impact on water quality. Land use and water quality information are extracted from remote sensing data. Data of population, industrial and agricultural productivity indices are integrated with the thematic maps derived from remote sensing data by GIS method. Spatial analysis methods are applied on these data and the results indicate that population, waste water both from household and industrial and chemical fertilizer consumptions are main controls of the regional water quality and environment.

Soil erosion is a widespread geological process with strong capabilities to entrap, transport, and redistribute surface soil. It is important to grade erosion intensity and estimate eroded soil mass. On the other hand, soil organic carbon pool (SOC), as the largest terrestrial carbon content, is prone to be affected by soil erosion. Soil erosion redistributes surface soil over landscape, and changes the physical environmental conditions. The consequences are depletion of SOC in eroded regions, emission of carbon dioxide during transportation and input of extra SOC in deposited sites. This paper quantified the effects of soil erosion on soil organic carbon through following three steps: firstly, soil erosion type and soil erosion intensity was determined by interpreting Landsat TM images. Secondly, through field investigation, soil type and soil profile data were collected, and SOC contents in the 0-20cm layers were constructed. Finally, supported by map algebra in Geographic Information System (GIS), soil organic carbon loss induced by soil erosion was calculated based on the national soil erosion modulus standard. Total annual SOC loss in China was about 1.595×10⁸ ton−C yr−¹. Assuming 20% of SOC was oxidized, erosion induced CO₂ emission was about 3.19×10⁷ ton−Cyr−1.

Based on the GLO-PEM simulation data, Net primary productivity (NPP) and its spatiotemporal patterns in Northeast China were studied from 1981 to 2000. Our research indicated that the distribution of annual NPP in Northeast China was obviously different from east to west. The averaged annual total NPP is 0.50PgC, with an annual increasing rate of 0.55%. NPP increased in most parts of Northeast China from 1981 to 2000, with the largest increase in the western part of Liaoning province, but it decreased in eastern Hulun Buir Plateau, Horqin Sandy Land, Changbai Mountains and northern Da Xingan Ling mountains. The early 1990s (1991-1995) is the time with fastest NPP increasing. NPP varies in different seasons. It increases mostly in summer, with an annual rate of 0.65%, but it decreasing in non-growing seasons.

During the past 20 years, China’s agro-ecosystems have great changes in response to changes in climate and agricultural management. Agricultural productivity is of vital importance to the national food security and sustainable development. So far, agricultural statistics are the only source of the data about changes in agricultural productivity in national scale, and there is little geo-spatial information on these changes. Remote sensing provides an important tool to monitor the spatial and temporal variations at high resolution, but it had yet to used fully at regional and national scales to assess the interannual and long-term changes in agricultural productivity. This study estimated agricultural net primary productivity (ANPP) at the national level using a remote sensing-based production efficiency model, GLO-PEM. In the study, the arable area has been derived from TM data. ANPP was calculated from 8m, 10-day composite Advanced Very High Resolution Radiometers (AVHRR) data from 1981 to 2000 using GLO-PEM model. Using the data we analyzed the spatial variations in agricultural productivity in China between the 1980s and the 1990s. A 3-level hierarchy regionalization system is used in analyzing the spatial pattern and its changes in the agricultural productivity. China’s average agricultural ANPP increased 59.8 million tons from the 1980s to the 1990s. The increment of ANPP mainly occurred in the major cereal-planting plains, especially HuangHuaiHai Plain. The characteristics of land resources are the dominating factors to cause the changes at 10 years scale. There were some decreases, which mainly caused by the degradation on fragile lands, the rapid expansion of rural industries, and the urban development from high-quality arable lands.

Hyperspectral images of the Earth’s surface are increasingly being acquired from aerial platforms. The dozens or hundreds of bands acquired by a typical hyperspectral sensor are acquired either through a scanning process or by collecting a sequence of images at varying wavelengths. This latter method has the advantage of acquiring coherent images of a scene at different wavelengths. However, it takes time to collect these images and some form of co-registration is required to build coherent image cubes. In this paper, we present a method to register many bands acquired sequentially at different wavelengths from a helicopter. We discuss the application of the Phase Correlation (PC) Method to recover scaling, rotation, and translation from an airborne hyperspectral imaging system, dubbed PHyTIS. This approach is well suited for remotely sensed images acquired from a moving platform, which induces image registration errors due to along and across track movement. We were able to register images to within ± 1 pixel across entire image cubes obtained from the PHyTIS hyperspectral imaging system, which was developed for precision farming applications.

The data for this study was collected from two-year (1999 and 2000) field experiments that based on different artificial nitrogen treatments. Linear, non-linear and stepwise multiple regression analysis were adopted for modeling The data in 1999 was utilized as training sample for modeling hyperspectra remote sensing estimation of rice aboveground fresh biomass, and the data in 2000 was evaluated and tested the models' predictive accuracy. Results of fitness analysis between hyperspectral variables and rice aboveground fresh biomass indicate that some hyperspectral characteristic variables and their combinations are closely correlated to aboveground biomass, such as red edge wavelength (λr),maximum reflectivity in green region, minimum reflectivity in red region, and the vegetation index based on the sum of first derivative spectral reflectance in blue region and that in red region. Determining the highest correlated wavebands and the best-fitting variables for raw spectra, first derivative spectra and hyperspectral characteristic variables through stepwise multiple regressions, and the results reveal that the relationship between the first derivative spectra and rice aboveground biomass is much clearer and simpler when compared with the rest. The best model for rice aboveground biomass estimation is based on the ration vegetation indices that calculated with the sum of the first derivative spectra reflectance in blue region and that in red region.

Urban expansion continues to accelerate and herewith changes profoundly the Earth surface and results in many environmental consequences, such as affecting ecological sustainability in the rapid urbanized area of China. Therefore,it is of significance to map the intensity and spatial pattern of urban expansion and assess its environmental effects. The objectives of this paper are three-folds: (1) using two-period Landsat TM/ETM images from 1988 to 2000, urban expansion in Mianyang prefecture of China was mapped out. Results showed that urbanization in Mianyang increased dramatically with an expansion rate of 76.8%. Most of the new urban development was done at the cost of arable land. (2) The study found determinants of urban expansion, and concluded that urban expansion was constrained by biophysical as well as social-economic factors. The change of industrial structure in downtown area and the improvement of transportation were predominant drivers for urban expansion. (3) Combining with statistical environmental-data, the paper analyzed environmental effects of urban expansion in Mianyang, such as urban heat island effect (UHI), water pollution and acid rain.

This paper proposes a number of analytical approximations to the classic and recently measured seawater light scattering phase functions. The three types of analytical phase functions are derived: individual representations for 15 Petzold, 41 Mankovsky, and 91 Gulf of Mexico phase functions; collective fits to Petzold phase functions; and analytical representations that take into account dependencies between inherent optical properties of seawater. The proposed phase functions may be used for problems of radiative transfer, remote sensing, visibility and image propagation in natural waters of various turbidity.

The remote sensing coefficient or radiance reflection coefficient is a principal product of atmospheric correction algorithms applied to the remotely measured optical images of the ocean. This coefficient contains information about angular structure of light radiance, roughness of the ocean surface, and optical properties of the water. This presentation analyses remote sensing coefficient and presents it as a product of three physically different values or factors. The first factor depends on geometrical parameters of illumination and atmospheric optical properties, the second factor depends on roughness of the ocean surface, and the third one depends on the optical properties of seawater. The approach used to derive the third in-water factor is valid for all levels of water turbidity - from the clearest open waters to the most turbid waters of river mouths and extremely scattering waters of Yellow Sea type.

The spatial and angular structure of light radiance in the depth of seawater can be precisely computed with such numerical programs like Hydrolight. Unfortunately such calculations demand a lot of computational time if used for problems of visibility of submerged objects. In this case, due to the much greater computational efficiency and logarithmic dependence of visibility parameters on radiance values, analytical radiative transfer methods are preferable. In this presentation a new analytical radiative transfer method is proposed to solve visibility problems in seawater. The angular structure of depth-dependent light radiance in the sea is obtained in the framework of previously published selfconsistent approximation. The analytical expressions proposed in this paper allow to compute a horizontal visibility of submerged objects. This approach can be applied to problems of diver visibility in shallow water bodies of arbitrary turbidity and illumination.

Loess Plateau is a unique region in the world where the human activities are very intensive and the eco-environment is highly frangible. During the past two decades, the Land Use/Cover Change has been considered as one of the most important reasons for the eco-environment degeneration in Loess Plateau. In this paper, land use data in 1990, 1995 and 2000 were got based on the Landsat TM Remote Sensing images, and the 1km-grid land use change data of 1990-1995, 1995-2000 and 1990-2000 was made using the data management and spatial analysis techniques of ArcGIS 8.3 software. Furthermore, statistical tabular data of Grain for Green Project on county level in recent years were joined in the administrative regionalism spatial data. Based on all of these data, temporal-spatial characteristics of land use change in Loess Plateau were studied in detail, and its driving forces were discussed either. It turned out that land use change in different periods had very different characteristics. On the whole, from 1990 to 2000, farmland and built-up increased greatly, and forest, grassland, water body and unused land decreased remarkably. On the contrary, conversions from farmland and unused to forest or grassland has become the dominant land use change process since 2000. The regional social-economic development and the national macro-control policy have been the most important driving forces of land use change since 1990. Especially, from 2000 to now, the widely implemented Grain for Green Project, under which farming on fragile land gives way to forestation, has become and will remain the most radical and effective driving force to both the land use change and the regional eco-environment restoration.

The objective of this paper is to discuss the action of derivative spectra of corn in determining spectral bands that are best suited for characterizing corn agronomic parameters. The data for this study comes from filed and indoor reflectance measurements of corn by a ASD FieldSpec Pro FR. Observed corn characteristics included leaf area index, aboveground fresh biomass chlorophyll concentration and carotenoid concentration. The study shows that the derivative spectra can determine some characteristic wavelength of corn and eliminate the influence of soil background in some degree. Leaf area index, above-ground biomass, chlorophyll concentration and carotenoid concentration were strongly correlative to the red edge parameters which derive from derivative spectra of corn (the position of red edgeλ_red, the slope of red edge D_red and the area of red edge S_red). A strong relationship with corn characteristics is located in specific narrow bands in the longer wavelength portion of red (710nm to 740nm). The study concludes it is feasible for the derivative spectra of corn to determine its some agronomic parameters.

Northeast China is the national commercial grain base of China. It provides the critical food supply for other areas of the country every year. In this region dramatic changes, such as population increase, deforestation, grass land degeneration, wetland shrinking and so on, have taken place in recent several decades. The changes in resources and environment in this region have significant impacts on human living, social economy and many other aspects of the regional development. In this study uses Remote Sensing (RS), GIS and other information technology to reconstruct a digital Northeast China of the last 100 years from year 1900 to 2000. This paper first introduces the Digital Northeast China of this 100 years which includes the system targets, data foundation and design frame. Then as a case study, the woodland resource changes after 1980s based on the completed dataset are analyzed. This Digital Northeast China is based on satellite remote sensing images (Landsat TM and ETM) and topology maps and can help people solve problems related to population, natural resources and environment. On the other hand, the Digital Northeast China system can help farmers make wise use of land, increase production and preserve environment simultaneously. Furthermore, using data contained in the system, geographical scientists can analyze the resource and environment changes and make certain forecasts of the future development.

Wetlands are special ecosystem lying between the terrestrial and open-water areas. Similar to forest, grass, and ocean ecosystems, wetlands take parts in protecting environments and exploring resources. In China, wetlands are undergoing significant degradation that is caused by both natural processes and human activities. In order to know the details of wetlands change so as to take suitable actions to protect wetlands, Landsat TM/ETM images are used as main data sets. Accessorial data such as topography map and China mire map are also used. In this paper, wetlands are defined as swamplands, potholes, wet meadow, riverine, lacurtrine. Three periods (1990a, 1995a, 2000a) data of wetlands in china are extracted from TM through the interactive interpretation. Applying spatial analysis function of GIS technology and statistics methods, the spatial distribution pattern and temporal changes are studied. The research results show that, during the 10 years from 1990 to 2000, wetlands area decreased largely, and spatial difference is notable. Finally, the driving forces resulting in mires changes are analyzed.

In this paper, we conducted a case study on the relationship between the soil geochemical components and the occurrence of soil salinization in the west of Jilin Province in China employing the GIS technologies and statistical analysis. We found that (i) the geochemical components are closely correlated with soil salinization and (ii) the selected eighteen geochemical components, S, K, Be, Cu, MgO, CaO, Na₂O, Ph, Eh, Ba, Sb, F, Tl, Sr, Th, Pb, Se, Ge, were characterized with hierarchy and could be restructured into ten determinant factors after a CLUSTER and FACTOR analyses. In addition, this paper developed a binary logistic model with the occurrence or without occurrence of soil salinization as the dependent variable while the soil geochemical components as independent variables, which can be employed to diagnose and assess the current or potential soil salinization. A surface interpolation was conducted to validate and check the robustness of the models. We found that the classical statistical methods combining the surface interpolation constituted an effective and efficient framework to identify the relationship between soil geochemical components and the salinization and make an assessment on the soil salinization.

The semi-arid and semi-humid agricultural region in Northeast China occupies parts of the Songnen Grassland and the Horqin Grassland. The region has been an important base in food production and stockbreeding. During the past 50 years land cover in the region underwent dramatic changes. Based on thematic maps and statistical data, the change trajectories of cultivated land and grassland were traced for the period from 1950 to 1985. Visual interpretation of the false composite images followed by screen digitizing was applied to obtain digital data of land cover. With the spatial analysis techniques of GIS, the spatial patterns and changing characteristics of land cover for the period of 1986-2000 were analyzed. The percentage of cultivated land expanded from 38.6% to 48.4% from 1986 to 2000. Salinized land also increased rapidly. The area of grassland decreased severely with the reduction 6.8% at annual loss rate of 1.98%. Forestland, grassland and water area are more fragmented. The dominant land cover changes were the conversion of grassland and forestland into cultivated land, dryland into paddy field, and grassland into salinized land. Land cover changes were closely related to climate fluctuation, rapid growth of population and underdeveloped economic position.

The policy of ecological return of cultivated land has been carried out for several years in China and the cultivated land is decreasing. The objective of this study is to explore the potential and the methodology for the cropland change detection with Discrete Fourier Transform (DFT) approach using high temporal resolution imagery and some ancillary data. The data used in this study are 10-day composite SPOT-4 VEGETATION (VGT) Normalized Difference Vegetation Index (NDVI) over the period from April to November in 1998 and 2002 respectively, and the ancillary data include the existing land cover dataset derived from TM images and agricultural phonological calendar. The DFT method was applied to the NDVI data set on a per pixel basis. The magnitude of the difference of amplitudes in the first three harmonics was used to identify the areas where changes might occur, and then the unsupervised classification was used to determine the types of change. The methodology used in this study can minimize the influence of noise and phenology variance to the change detection. The result showed that the significant change of cropland and other land cover can be detected with this method.

According to the analysis to the climatic data of Xiao Tang in desert, Lun Tai in oasis during 1992 to 1997, the following viewpoints were noted: (1)The air temperature of desert is lower than the one of oasis in winter, the air temperature rise gradually from oasis to desert in summer. The diurnal range and annual range of air temperature in desert is wide than the one in oasis. (2)The precipitation of oasis is more than the precipitation of desert. The difference of seasonal precipitation is great in desert, the most of precipitation is in warm period, it is basic characteristics that mean-square diviations of precipitation are big in desert. Not only large-scale weather system affects the precipitation in desert, but also violent local thermal circulation can form the local unstable precipitation in desert. (3)The Humidity of desert is lower than humidity of oasis and the evaporation amount of desert is bigger than evaporation amount of oasis. The evaporation capableness of desert is mighty, the difference of seasonal evaporation amount is great in desert and the 77% of annual mean evaporation amount is in summer and spring.(4)The days of sand blown by wind weather in desert are more than the one of oasis. The wind speed in desert is faster than the one of oasis. These indicate that the difference is apparent between desert and oasis. This is caused by differences of Landscape and water amount. The exploitation and utilization on oasis enlarge this difference.

The previous studies on the effects of artificial oases to the climatic environment were mainly based on the comparison of the observed data from very few sites in short periods (for several days or several months) and the analysis on the differences of the climatic factors between oases and deserts as well as the mechanism of energy exchange. In this paper, the representative series reflecting the climatic background change and the climatic series representing the different oases are developed by carefully selecting the observed data from some meteorological stations where the change of the observation environment is slight, the regions are sparsely populated, and the large-scale water and land exploitations are not undertaken yet. The change ratio differences of the interannual change trends of 10 climatic factors, such as the air temperature, precipitation, vapor pressure, evaporation and wind speed, are analyzed, and the compositive effects of oasis development to the long-term climate change are researched. The results show that the climatic environmental effects caused by oasis development are significant in affecting the local long-term climate change trend. In summer, the increase trend of the mean air temperature in the oases is lower than that of the background change trend, and the change trends of air temperature are in a slight decrease status in some oases, such as in the oases in the Turpan-Shanshan-Toksun Basin and the Yarkant River watershed. The oases play an obvious restraining role in the increase trend of the maximum temperature, in which the change trends of the maximum temperature are in a slight decrease status in the oases in the Yarkant River watershed and the middle reaches of Tarim River. The oases play a certain active role in increasing the minimum temperature, and the oasis effects make the diurnal-nocturnal temperature difference become smaller and smaller. In summer, the oases play an obvious role in increasing the air vapor pressure, and make the evaporation potential become lower and lower and the precipitation be increased to a certain extent. The most significant aspect of the oasis effects is the change of wind speed, that is the average wind speed and the occurring days of gales are sharply reduced in the oases.

Based on the conventional weather observational data of the weather stations around Tarim Basin, a set of categorical standard to forecast sandstorm in Tarim Basin is set up. At the same time, the sandstorms in Tarim Basin are divided into four types from the synoptic meteorological point of view, a sandstorm warning system is established.

Oasis stability is a concept under certain scaled conditions. It is different that the mechanism of the oasis stability, main driving forces of stability and diagnostic results from the different scales. The particular scales that are chosen and the varying combinations of those scales are the main contributing factors to oasis stability study. This paper reviews the research history of oasis stability, discusses the basic academic standpoints on the stability of the oasis ecosystem, and puts forward the relationship between the oasis stability conception and its related scales. It suggests that: 1) The scales are related to certain preconditions; 2) The stability scales should be classified as: spatial-temporal changes, system organization, society target, and landscape; 3) The mechanisms of the oasis stability and its resulting assessment methods are consequently based on the variation of scales.

To sum up, the conclusions about the characteristics of the sand-surface reflectivities of visible light channel and near infrared channel in the Tazhong region in the hinterland of the Taklimakan Desert in winter are as following:(1) On fine days, the sand-surface average reflectivities of visible light channel and near infrared channel in the Tazhong region are 25.8% and 28.6% respectively. It is roughly estimated that the atmosphere can reduce the reflectivities of these two channels for 5.2% and 7.5% respectively comparing with the RS data of NOAA satellite in the corresponding period.(2) On fine days, the reflectivities of visible light channel and near infrared channel have the following characteristics: 1. At all the positions of a dune, the reflectivity of near infrared channel is higher than that of visible light channel, and 4.3% higher in maximum on the sand-falling slope and the left wing of dune; 2. Among the different positions of a dune, the reflectivity change of visible light channel is low but that of near infrared channel is high, and the latter is about 5 times of the former: 3. The reflectivities of both visible light channel and near infrared channel on the south-facing slopes are slightly higher than that on the north-facing slopes.(3) The reflectivities of visible light channel and near infrared channel are the highest on cloudy days comparing with that on fine days and thin-cloudy days; from the fine days to the thin-cloudy days and cloudy days, the green values, reflectivity difference between the near infrared channel and visible light channel of dunes, and the maximum reflectivity difference of near infrared channel between the different dune positions are successively reduced; but the maximum reflectivity difference of visible light channel between the different dune positions are gradually increased.(4) On fine days, the dune reflectivities of visible light channel and near infrared channel are reduced with the increase of sun's altitude, but the negative correlation between the reflectivity of visible light channel and the sun's altitude is higher than that between the reflectivity of near infrared channel and the sun's altitude.(5) Frost on sand surface can increase the reflectivities of visible light channel and near infrared channel, and increase for 2.6% and 3.5% respectively compared with that without frost.

In-season N management of irrigated corn requires frequent acquisition of plant N estimates to timely assess the onset of crop N deficiency and its spatial variability within a field. This study compared ground-based Exotech and QuickBird satellite multispectral data using the normalized GNDVI to produce N status maps of a study site on three days during the corn vegetative growth period. Scale factors to represent N sufficient and N deficient corn were determined for both systems from relationships between the normalized GNDVI and the NSI. A third classification was required for this study to classify areas that exhibited leaf chlorosis that was not caused by N deficiency, i.e., not N related. N status maps generated from normalized GNDVI values showed similar patterns between the two systems for the three corn growth stages (V10, V12, and V15) investigated. However, the extent of the pattern varied between systems. On 2 July (V10), six of six sample sites were correctly classified using leaf N content to indicate plant N status. On the other two days (7 July and 15 July), four of six sites were correctly classified. Two not N related areas were classified as N deficient when leaf N content was adequate.

Songnen Plain is located in the intersection area of agriculture and forestry in Jilin Province and Heilongjiang Provinces of Northeast China. In recent years, grasslands in the area have gradually decreased year by year due to the unplanned use in a large scale, being the most typical pattern in study on regional land use and cover change. This paper has well utilized the remote sensing imagery and regional feature analysis approach (referred to as geoanalysis) to model its dynamic change based on the survey data. Combination of remote sensing information and field investigation data, we did an analysis on its driving force in light of the regional characteristics and the policies of rapid economic development put forward by Chinese Government. In practice, mapping the grasslands in 1986, 1996 and 2002 respectively was carried out to overlay each other and extract these varied patches with a feature, and thus a trend map of its development was compiled towards a decade to come. Finally, author brought up an idea how to better utilize grasslands in the area on the basis of the regional feature of China.

Northwest China includes six provincial districts of Inner Mongolia Autonomous Region, Shaanxi Province, Gansu Province, Qinghai Province, Ningxia Autonomous Region and Xinjiang Autonomous Region. This region is located in the alpine frigid region, arid region and the loess plateau, therefore, its eco-environment is frail and the economy is under-developed. Based on climate data, land use data, and socio-economic statistic data, this article analyzed the data of precipitation, air temperature, humidity, population, GDP, industrial structure, land use changes, designed water-heat condition, and integrated human activity pressure. By utilizing ArcGIS 8, we divided the eco-economic region into three-level categories according to the environment condition and human activities in a county scale in Northwest China, and analyzed the basic characteristics and main eco-economic problems of each eco-economic region.

The style of water use was restricted in a large extent by the fragile eco-environment in Ningxia and Inner Mongolia Autonomous along the Yellow River. Applying the runoff data and the field survey data, we analyze the main contradictions between water use and environment in this area. And by overlaying the meteorological data with the statistic data of soci-economy, we regionalize the ecologically geographical zones. We also analyzed the main style of water use based on the ecologically geographical zones. In conclusion, it is strongly proposed that harmonious relationships in water-man and water-environment systems have to be established to realize sustainable water supply in this area.

Application of geo-information science methods in ecotourism development was discussed in the article. Since 1990s, geo-information science methods, which take the 3S (Geographic Information System, Global Positioning System, and Remote Sensing) as core techniques, has played an important role in resources reconnaissance, data management, environment monitoring, and regional planning. Geo-information science methods can easily analyze and convert geographic spatial data. The application of 3S methods is helpful to sustainable development in tourism. Various assignments are involved in the development of ecotourism, such as reconnaissance of ecotourism resources, drawing of tourism maps, dealing with mass data, and also tourism information inquire, employee management, quality management of products. The utilization of geo-information methods in ecotourism can make the development more efficient by promoting the sustainable development of tourism and the protection of eco-environment.

Based on land-use datum (at scale of 100,000) of the interpretation of Landsat Thematic Mapper in 1980, 1995 and 2000, which came from environmental database of the Chinese Academy of Sciences, the authors investigated land-use change and influential factors by the combined use of geographic information systems (GIS) method, Markov model and canonical correlation analysis (CCA) statistical method. The results showed that, in the periods 1980-2000, crop land increased by 0.58 percent (4278.86 hectares), of which 92.93 percent was transformed from grassland and 7.07 percent from forestland. Urban or built-up land increased by 26.23 percent (687.45 hectares), of which 77.35 percent was transformed from cropland. Rural residential land increased by 5.17 percent (1324.37 hectares). Forestland and water land decreased in area. Grassland decreased by 0.57 percent (5706.77 hectares). Secondly, transition rate of landscape spatial pattern among the landscape elements from 1995 to 2000 was slower than that from 1980 to 1995. Land use types as cropland, grassland, woodland and rural residential land were the primary change types from 1995 to 2000. Thirdly, both natural and social economic factors influenced land use pattern. The population and per capita grain yield were positively correlated to rural residential pattern. The spatial distribution of grassland and cropland showed strong positive correlation to annual rainfall and annual air temperature, and negative association to annual per capita net income of rural residents. The poor annual per capita net income of rural residents and investment in capital construction restricted the extended area of urban build-up land. Therefore, the drought is not proportional to pattern of urban build-up land. The study verified the analysis conclusion of influential factors by redundancy degree of CCA. The integration of remote sensing data, GIS, Markov process and CCA provided a comprehensive method to analyze land use pattern and process with influential factors.

Dongting Lake area, located on the southern bank of the middle Yangtze River in central China, is one of the regions experiencing rapid land use change and seriously suffering from flooding disaster in the country. In this paper, a series of land-use coverage was generated through visually interpreting Landsat MSS, TM and ETM images, of 1980, 1990 and 2000 respectively. Then, the spatial-temporal characteristics and the driving forces of the land use changes were analyzed in the study area. The results show that, from 1980 to 2000, the areas of farmland, woodland and non-used land decreased, while those of built-up land, water area and grassland increased. There was a significant shifting from farmland to water or built-up area, and the large-scale reclamation from the lake ever in history has not been found since 1980. The fastest changed area was in Shishou City, Yueyang City and Jinshi City, and the slowest in the eastern and southeastern area. About 49% of the changes were caused by the adjustment of agricultural economic structure, 29.75% by the urbanization and industrialization, and 21.41% by the environmental pressure. The policy, market price and tax on land products also have definitively influences on the land-use changes.

This study presented the temporal and spatial variation patterns of the seasonal NPP, temperature and precipitation. The NPP simulated by using the GLO-PEM. A semi-mechanistic model of plant photosynthesis and respiration driven entirely by the satellite observations was combined with climate data in Xinjiang of China over the past 20 years to study the impact of seasonal climate changes on the seasonal NPP. The higher correlation coefficients between the seasonal NPP and the corresponding seasonal temperature and precipitation over the past 20 years happened in the areas covered with forest lands, grasslands, oasis and croplands in the northern and southern foothills of Tianshan Mountain, Iili River Valley, Tarim Basin and Junggar Basin. In these areas, the vegetation growth was greatly influenced by interannual changes of seasonal temperature and precipitation. The spatial patterns of the correlation coefficients in Xinjiang showed that the higher correlation coefficients between seasonal NPP and seasonal temperature and precipitation in 1990s than in 1980s. With the increased temperature and precipitation, the areas of grasslands and oasis in Xinjiang were expanded over the last 20 years.

In the past 20 years, great changes have taken place in the climate of China, which have exerted an important impact on the productivity and carbon cycle of terrestrial ecosystem. This study uses a process-based ecosystem model driven with the land use data based on remote-sensing observation and climate data with high space-time resolution to estimate the impact of climate changes on net primary productivity (NPP) in China. The results show that over the past 20 years, due to climate warming (with an average annual increase in temperature of 0.055 ) and an increase in precipitation (with an annual increase of 0.65 mm), NPP has obviously increased in China (with an increase of 11 TgC). Seasonal temperature and precipitation have greatly impacted the temporal and spatial variation of NPP in China. NPP of vegetation is obviously impacted by seasonal precipitation change in forest covered areas in China. The impact of seasonal precipitation on NPP in semiarid and semi-humid areas is more obvious than that in humid and arid areas in China. The growth of vegetation is remarkably impacted by seasonal temperature changes in about 70% of the regions in China. The correlation between NPP and seasonal temperature change is obvious.

Based on studies of lake sediment, loess sediment and ice amass record and using geographical information system, remote sensing and ecological landscape methodologies, a systematic study on the structure, processes and evolution of the ecosystems in the western China arid region was conducted on time scales of 10,000 years, 1000 years, 100 years, and less than 100 years. Beginning from the Brand-new Life era, the climate of the western China arid region has been changing alternatively between warm-dry and cold-wet periods. The characteristics of climate differ among places and years in the early, middle, late Brand-new Life era. The human population relied mainly on the degree of aridity over the past 280-350 years when the rainfall demonstrated periodical changes and a slight decrease trend. However, in the past half century, the climate of Tianshan Mountain and Xinjiang area showed increases in both air temperature and rainfall. In these areas, vegetative land covers, especially typical grasslands, expanded significantly from 1980s to 1990s. It is also found that within certain climate environments the vegetative land covers in the oases have positive impacts on regional whether by increasing the rainfall of the areas.

We studied changes in the oasis-desert ecosystems of Akesu Oasis in Xingjiang, China. We used the ‘frontier theory’ of landscape ecology to analyze changes from 1990 to 2000. The results show that considerable landscape changes occurred during that time as a result of changes in both natural and social-economic factors. However, the influence of socioeconomic factors predominated.

The paper calculated an ecological footprint of Wusu city in 1990, 1996 and 2003, and analyzed the current status of sustainable development and dynamic change. Results show that the per capita ecological footprint of Wusu is constantly increasing, but the per capita ecological carrying capacity is decreasing. The per capita ecological footprint in this region varied from surplus, deficit to deteriorating in thirteen years. In addition, diversification of ecological footprint in Wusu city, potential of ecological economy system and efficiency in resource utilizing were steadily improved. It can be concluded that ecological economy system in Wusu city is a unsustainable one.

The application of remote sensing in the study of terrestrial productivity opens up an effective way for simulating terrestrial ecosystem productivity. Observation by space-borne sensors can provide parameters to describe ecosystem processes related to plant growth. In this paper, a biogeographic process model (forest-BGPG) is established to estimate forest net primary productivity, which caters for mountainous distribution and species' diversity of forest in China. Gross photosynthesis and respiration are evaluated separately in forest-BGPG because of different meteorologic, soil and biological factors exert varies degrees of control on these processes. In forest-BGPG, an alternative satellite algorithm is used to estimate photosynthetically active radiation absorbed by forest canopy (APAR), spatial and seasonal patterns of the maximum efficiency of PAR utilization of forest woodland are simulated by a physiological model at stand level. Taking temperate deciduous forest in northeast China as an example, forest-BGPG is applied to simulate NPP of temperate deciduous forest over study area using MODIS data. The mean NPP value is close to 4.7 MgC ha⁻¹ for deciduous broadleaved forest, and 4.32 MgC ha⁻¹ for deciduous coniferous forest in northeast China at the period from November of 2002 to October of 2003. Compared with MODIS NPP products from School of forestry of the university of Montana, both of them are in agreement.

Spatial analysis is applied in this case study to mine the information in the fundamental national geographical database of CASW. The geographic parameters used for the case study include the longitude, latitude, slope, aspect, distance to water resources and elevation of the residential spots in three phases of TM image of Longxi County in Gansu Province (1980, 1995, and 2000). The spatial analyzing projects are managed in VBS and AML languages within the ArcWorkstation 8.3 and ArcDesktop 8.3. The results are expected to be helpful for policy makers of local administration in the eco-environment immigration, in order to alleviate the pressures imposed by the local residents who are heavily stricken by poverty.

To make better use of the land, the regional climate response to vegetation change with oasis-desert-nesting structure in sensitive climatic area was studied in this paper. Three vegetation change experiments with different oasis-desert-nesting structure were designed and the differential charts between control and sensitivity simulation run were made. The results indicated that for oasis-desert-nesting structure, whose width reached certain width so as to engender local circulation, such as EXP1 and EXP2, its width change mainly affected intensity of climatic response while its complexity affected spatial distribution of climatic response. For commensurate mosaic oasis-desert nested structures in the same sensitive area, they had the same distribution type of climatic response but different intensity. EXP1, EXP2, and EXP3 presented that certain complexities can make nesting fields appear with a whole-field characteristic; there were different climate response to vegetation change between sensitive climatic area and ordinary one, the former with greater response than the latter.