This PDF file contains the front matter associated with SPIE Proceedings Volume 7083, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.

Vegetation indices are valuable in many fields of geosciences. Conventional, visible-near infrared, indices are often limited by the effects of atmosphere, background soil conditions, and saturation at high levels of vegetation. In this study, the theoretical basis for a new type of passive microwave vegetation indices (MVIs) based on data from the Advanced Microwave Scanning Radiometer (AMSR-E) on the Aqua satellite is developed. Numerical simulation results were used to establish relationships of bare soil surface emissivities at different frequencies. Using a radiative transfer model, a linear relationship between the brightness temperatures observed at two adjacent radiometer frequencies can be derived. The intercept and slope of this linear function depend only on the vegetation properties and can be used as vegetation indices. These can be derived from the dual-frequency and dual-polarization satellite measurements under the assumption that there is no significant impact of the polarization dependence on the vegetation signals. To demonstrate the potential of the new microwave vegetation indices, we compared them with the Normalized Difference of Vegetation Index (NDVI) derived using MODIS at continental and global scales. The results indicate that the MVIs provide a complementary dataset for monitoring global short vegetation and seasonal phenology from space.

Previously, urban growth pattern is described and measured by the pixel-by-pixel comparison of satellite images. The geographic extent, patterns and types of urban growth are derived from satellite images separated in time. However, the pixel-by-pixel comparison approach suffers from several drawbacks. Firstly, slight error in image geo-reference can cause false detection of changes. Secondly, it's difficult to recognize and correct artifact changes induced by data noise and data processing errors. Thirdly, only limited information can be derived. In this paper, we present a new objectbased method to describe and quantify urban growth patterns. The different types of land cover are classified from sequential satellite images as urban objects. The geometric and shape attributes of objects and the spatial relationship between them are employed to identify the different types of urban growth pattern. The algorithms involved in the object-based method are implemented by using C++ programming language and the software user interface is developed by using ArcObjects and VB.Net. A simulated example is given to demonstrate the utility and effectiveness of this new method.

The purpose of this work is to measure changes in deciduous tree reflectance spectra as a function of time from late summer to autumn senescence. Leaves were harvested from two maple trees growing in eastern Massachusetts. Reflectance in the 350-2500 nm range was measured in the laboratory on stacks of freshly-harvested leaves. We calculated a number of published spectral indices, finding that most of the indices varied remarkably little across the time period. In some case, the measurement uncertainty was small, although the measurements exhibited wide scatter over the time period. The Normalized Difference Vegetation Index showed only a slight downward drift throughout the measurement period. The red edge wavelength was observed to decrease dramatically from the summer growth period (~725 nm) to autumn senescence (~700 nm).

A method is presented to reconstruct the three-dimensional (3D) canopy and stem based on terrestrial laser scanning (TLS) data. Multiple range images are obtained and aligned on a 25 m x 25 m plot, where the single specie conifer forests are growing in Gansu province, China. With regard of organizing the raw point cloud, firstly, a kind of kd-tree structure is built to make the spatial index of them, and then, a kind of region grow is performed to segment them to smaller size, and third step, an algorithm is make to extract a single canopy and stem. The segmentation processing is based on "connected constraint", which can segment each individual tree in one subset. RANSAC and GAUSS image are used to find cylinder in 3D point cloud to obtain the individual tree measurements, including the tree position and DBH. Each cylinder is parameterized by its orientation and radius and is estimated iteratively.

Lake Okeechobee, Florida is the largest freshwater lake in the southeastern U.S. It is a key component in the hydrologic system of south Florida providing water supply for agriculture, the environment, and urban areas Excessive phosphorus loads, from the Okeechobee watershed over the last few decades have led to increased eutrophication of this. Much of the excess phosphorus has been sequestered into the sediments. Sediment water interactions, including diffusive fluxes and sediment resuspension are a source of available phosphorus for phytoplankton. As a consequence, nutrient-enriched lake water have led to phytoplankton blooms. These blooms are quantified by measurement of chlorophyll-a concentrations. While the in-situ water quality monitoring is time-consuming and costly, multispectral remote sensing sensors onboard satellites can detect chlorophyll-a contained in most phytoplankton efficiently. The objective of this study is to demonstrate the use of MODIS/Terra Surface Reflectance 8-Day images to estimate the chlorophyll-a concentrations in the Lake Okeechobee. Using the integrated genetic programming and multiple linear regression models helps the information retrieval for spatial mapping of chlorophyll-a concentrations.

This article examines several major bathymetry mapping methods and describes an experimental procedure of determining seabed bathymetry from multi-source passive remote sensing data. Issues to be addressed include how to deal with less desirable spectral data quality and the absence of in-situ water depth measurements. A case study was presented using DigitalGlobe QuickBird and Landsat-7 ETM+ multispectral images of different dates and spatial resolutions to determine water depth for the Beilun Estuary, China. The preliminary results have led to three findings. First, it was feasible to use the tidal water line derived from the near-infrared bands as a good approximation of water surface when observed tidal data is absent. Second, the reflectance ratio transform model developed by Stumpf et al. was proven suitable for spectrally-based water depth estimation when in-situ data is absent. Finally, the data quality problem caused by thin clouds could be effectively removed by fusing remote sensing images of two different sources.

The monitoring and assessment of land cover in Three gorges area, one of the main ecological flimsy zones in China, is helpful for better understanding the function of natural and human factors on ecosystems. With the construction of Three gorges project, the concerns on the land cover change in Three gorges area by policy makers are raising. In this paper, Landsat TM images in 1986, 1996, 2000 and CBERS images in 2006 are used to detect the change of land cover in Three gorges area, which include the main regions and land cover types. A series of models are built to assess these changes. Land use intension index model and land use comprehensive benefit model are used to assess the use effect of land. Land use dynamic degree model is built to detect the intension of change for each land cover type in each county of this area. Land use centroid model is used to detect the spatial shift, which shows the human activities become more and more near the bank of Three gorges reservoir in recent 20 years. At last, this paper analyzes the temporal-spatial change of land-use and land-cover of Chongqing and discusses the main driving forces of land cover change in Three gorges area with the method of correlation analysis, and constructs a Markov matrix model to forecast the land cover change in the future 10 years.

The climate is changing due to higher concentrations of greenhouse gases. If concentrations continue to increase, climate models project climate change in this century, with significant impacts on many human sectors, and particularly agriculture. Agriculture is a fundamental production sector for society, especially for large population countries such as China. Wheat is the second most important crop in China. Therefore, using climate change projections and crop models in order to understand the impacts of climate change on Chinese agriculture, especially on winter wheat, is extremely helpful to policy makers and international agencies. CERES-Wheat, a dynamic process crop growth model, will be calibrated and validated for current production at ten sites in the major winter wheat-growing region of China-Yellow Huai-Hai plain. Using two Global Climate Models, it will then be used to simulate production changes under IPCC SRES A2 and B2 climate change scenarios. Simulations will consider impacts for rainfed and irrigated winter wheat, with and without CO2 fertilization. Simulation results indicated the possibility of significant impacts of climate change on winter wheat production in this region, with marked differences between rainfed and irrigated production. In conclusion, this exercise successfully tested the applicability of standard climate change impact assessment methodology to an important production region of China.

Ecological economics crossed extensively with some disciplines such as ecology, geography, economics, etc in China. And it is promoting the relevant disciplines to develop effectively in depth fields. The key research direction of eco-economic regionalizing is eco-economic space pattern, rule of territorial differentiation and eco-economic topological optimization. Based on GIS spatial analyze, the article elaborates the main characteristics and the problems of every eco-economic zones, districts and regions with the comprehensive geographical statistic data. The western eco-economic regionalizing was delimited by analyzing the superposition for ecological environment value and human actives value, refer to the topography and administrative boundary between provinces and the cities, the attachment of the regionalizing plans and territorial the continuity. There have several main indexes used in the regionalizing and the results to show the main character of each region, which comprise precipitation, temperature, primary production potential, while the population carrying capacity, and the index of water resources, land resources, landscape degradation, urbanization, and economic development, etc. To each type of eco-economic region, there are other analyzes respectively from the social, economic, and natural environment aspects. The result shows that there does now have serious economic development in western China, while the environmental problem still cannot be ignored.

Under the influence of the global change and human activity, the land use/land cover change (LUCC) is remarkable. The evapotranspiration is one of the key taches of the water cycle. And it's the component of both water balance and energy balance, which embodiments the balance of the substance, energy and the information system. The evapotranspiration is closely related to the land use and land cover change. In this paper, we first gives the dynamic characteristics of the land use and land cover change; and then, the distribution of the land surface water and heat flux and evapotranspiration, by means of the SEBAL equation, based on the radiation balance equation and energy balance equation; and finally, based on the tempo-spatial characteristics of evapotranspiration, we discusses the influence of land use/cover change to the land surface evapotranspiration from two aspects: land use/land cover type and fresh/salt water.

Two images of Landsat TM/ETM+ which belong to 1990 and 1999 respectively, were used to get the information of Land Use/Cover Change (LUCC) of Sangong River basin. Land surface temperature (LST) of corresponding periods was calculated by using the mono-windows algorithm, Bihong Fu's algorithm and Hongbo Su's algorithm. Based on accuracy assessment, the response of LST to LUCC of this region and the relationship between LST and NDVI were analyzed by combining the LUCC and LST. The results showed that, in this decade (1990-1999), urban development and increasing of land use for agriculture caused significant changes of land use/cover in this region, which led to the land surface temperature rising by 10 in average. As the study area is oasis which is located in the edge of desert, the vegetation had an obvious influence on the LST which showed a negative correlation with vegetation index.

A remote sensing regional evapotranspiration (ET) model was built on the basis of topography correction (slope, aspect and elevation), herein. A variety of satellite data which have visible, near-infrared and thermal infrared remote sensing data can be used by this improved model. Combined with conventional ground meteorological information, it can estimate regional distribution of ET under different climate and terrain conditions, expanding the scope of application. This research indicates that application of medium or high resolution satellite data to calculate regional ET under undulating landform should consider the impact of terrain. The analysis of the impact of the ET results simulated by the model in combination with terrain factors (altitude, slope, aspect) show that the ET results will overestimate about 30% in high altitude and shady slope region if the terrain is not taken into account. It improves the accuracy of ET estimates and has important reference value for the work of the regional water balance and regional agricultural climate research.

Spatial and temporal distribution of vegetation net primary production (NPP) in China was studied using three light-use efficiency models (CASA, GLOPEM and GEOLUE) and two mechanistic ecological process models (CEVSA GEOPRO). Based on spatial and temporal analysis (e.g. monthly, seasonally and annually) of simulated results from ecological process mechanism models of CASA, GLOPEM, and CEVSA, the following conclusions could be made: (1) during the last 20 years, NPP change in China is followed closely by the seasonal change of climate affected by the monsoon with an overall trend of increasing. (2) Average annual NPP in China was 2.864±1GtC. All five models were able to simulate spatial features of biomass for different ecological types in China. This paper provides a baseline for China's total biomass production. It also offers a means of estimating the NPP change due to afforestation, reforestation, conservation and other human activities and could aid people in using for-mentioned carbon sinks to fulfill China's commitment of reducing greenhouse gases.

Photosynthetically active radiation (PAR) is an essential parameter in vegetation growth model and soil carbon sequestration models. A method is presented with which instantaneous PAR can be calculated with high accuracy from Moderate Resolution Imaging Spectroradiometer (MODIS) atmosphere and land products. The method is based on a simplification of the general radiative transfer equation, which considers five major processes of attenuation of solar radiation: Rayleigh scattering, absorption by ozone and water vapor, aerosol scattering, multiply reflectance between surface and atmosphere. Comparing 108 retrieveled results to filed measured PAR in Yucheng station of Chinese Ecosystem Research Network (CERN) in 2006, and the r-square of 0.855 indicates that the computed results can interpret actual PAR well.

A new simple model has been developed that incorporates Digital Elevation Model (DEM) and Moderate Resolution Imaging Spectroradiometer (MODIS) products to produce incident photosynthetically active radiation (PAR) for tilted surface. The method is based on a simplification of the general radiative transfer equation, which considers five major processes of attenuation of solar radiation: 1) Rayleigh scattering, 2) absorption by ozone and water vapor, 3) aerosol scattering, 4) multiple reflectance between surface and atmosphere, and 5) three terrain factors: slope and aspect, isotropic sky view factor, and additional radiation by neighbor reflectance. A comparison of the model results with observational data from the Yucheng and Changbai Mountain sites of the Chinese Ecosystem Research Network (CERN) shows the correlation coefficient as 0.929 and 0.904, respectively. A comparison of the model results with the 2006 filed measured PAR in the Yucheng and Changbai sites shows the correlation coefficient as 0.929 and 0.904, respectively, and the average percent error as 10% and 15%, respectively.

The theory of fractal is a new tool for studying spatial pattern of land use, and the techniques of remote sensing and GIS offer a technical support. Firstly, under the support of RS and GIS, the classification information of land use is extracted from the Lands ant TM imageries of the Baiyang River of two periods (2000 and 2005),and a spatial database of land use is built. Secondly, in order to improve the understanding about the land use change about the Baiyang River, we use the fractal model to calculate fractal indices of different landscape patterns, Combining some landscape indices including the indices of the landscape diversity, the landscape fragmentation, the landscape shape and landscape separation, we analyze the characteristics of land use change quantificationally and provide sustainable development of land use with several pieces of advice in the end.

Using the CBERS data in August,2005 and the corresponding measured grass yield data from 15 samples in the region of Bayinbuluke grassland, we established the monadic linear regression models the non-linear regression models and the logarithm models to express the relationship between grassland aboveground biomass and the Vegetation Index(VI). The results showed that: 1)there were close relation between the VI and grassland aboveground biomass: 2) the comparison of different forms showed that the logarithm equation was the best one in terms of the suitability of use in study area: 3) the results from the non-linear regression analysis showed that the order was MSAVI NDVI LAI and SAVI in terms of the fitting accuracy between these VI and grassland aboveground biomass data: 4) the non-linear regression Y=-1242.2MSAVI³+6254.1MSAVI²-10044MSAVI+5267 was the best model which could be used in monitoring grassland biomass based on the VI Bayinbuluke grassland.5) the calculated results were as follows: the total aboveground biomass of Bayinbuluke in 2005 was 1.23x10⁴t; the total biomass of high grass was 8.82×10³t and the density was 116.14g/m²;the total biomass of low grass was 2.04x10³t and the density was 70.33g/m² the total biomass of swampland was 1.30x10³t and the density was 122.36g/m² Keywords Remote Sensing, vegetation index(VI), grassland, aboveground biomass, Bayinbuluke

Based on NCAR/NCEP daily reanalysis, a study is performed of the circulation background for the South-China torrential rains leading to flash floods in June 2005 with the possible causes explored. Results show that a weak El Nino episode in 2004-2005 is the climate background of the flooding. Compared to the situation of the summer 2005, the apparent heat source (Q₁) and the apparent vapor sink (Q₂) are anomalously intense in the rainy period June 17~26 over the study region, with their high-value belts resembling the rainfall distribution and their centers roughly coincident with the rainfall cores. The anomalous heating source from the eastern coast of the Arabian Sea to the Bay of Bengal excites a high-level abnormal anticyclone to the northwest, making the south-Asian high intensified and westward of normal, during which China mainland is under the effect of an anomalous cyclonic circulation that keeps the south-Asian high from northward displacement, allowing it to stay in the south of the Tibetan plateau - South China, a situation that South China is situated in the rising area on the south side of upper-air westerly jets, making for the occurrence and maintenance of the intense rains, resulting in extensive flooding.

Based on the system of three-dimensional variational assimilation (3D-VAR), the numerical experiments of ensemble hindcasting for 17 years are performed in East Asia in this paper. There are two groups of experiments, the initial conditions are supplied by the system of 3D-VAR in the first group experiment and that in the second are NCEP-DOE Reanalysis 2 data. The experiments use the model which is a grid-point Atmospheric General Circulation Model with 9 vertical levels and a resolution of 2° in latitudinal and 2.5° in longitudinal direction, developed by the Institute of Atmospheric Physics, the Chinese Academy of Sciences (IAP9L2×2.5-AGCM).The technique of Correlation Analysis is applied. Comparison results show that anomaly correlation coefficients of most variables (for example, geopotential height and temperature, etc) are larger in the first experiment not only in the mid- and upper troposphere, but also in lower troposphere. This is an indication that initial conditions provided by 3D-VAR may include more information, What's more, they may be corresponded to dynamical model.

Plants cover more than 70% of our earth's land surface and play an important role in the exchange of materials and energy between land and atmosphere. The biochemical substances existing in leaves have been proven to be critical factors in influencing, or even controlling, this exchange by means of various physiological processes, including photosynthesis, evaportranspiration, litter decomposition, etc. Compared to traditional wet chemistry methods, estimation of their contents through leaf and canopy reflectance spectra has become a rapid, efficient, and promising method over the past few decades, which had been physically based on the selective absorption features of a particular substance. This paper discusses the responses of plant biochemical substances to the reflectance spectra at both leaf and canopy scales. We use a leaf optical model PROSPECT and a leaf-canopy coupled optical model PROSAIL to generate large amounts of leaf and canopy spectra. Both of these models contain three biochemical parameters: cab-chlorophyll concentration, Cw-equivalent leaf water thickness, and Cm-dry matter concentration. Local and global sensitivity analysis (SA) methods are used on the simulated spectra to differentiate their contributions to the outcome spectra at both scales so as to investigate their scale effects. Results show that the maximum sensitivities of chlorophyll and water are much higher than that of dry matter at leaf scale, and they tend to decrease at canopy scale because canopy shape, soil, and incident/reflected geometric factors have a large influence on canopy spectra. However, the sensitivity of dry matter exceeds the maximum sensitivity of mesophyll structure parameters at canopy scale and becomes the top contributor at the beginning of near infrared.

This paper presents an unsuccessful attempt to identify different mangrove species from the DigitalGlobe's QuickBird high-resolution multispectral image data for a coastal estuary located in the north of South China Sea. A conventional supervised classification was conducted with 102 signatures trained for five cover classes, with 32 of the signatures being used to separate up to five mangrove species. The results indicated that spectral characteristics alone as provided by the QuickBird's four spectral bands were not sufficient for the discrimination among mangrove species, other information such as textual and structural characteristics of mangrove species would be needed to enhance the discrimination power. In addition, the confusion between upland forests and mangroves render a removal of uplands from the classification process. Finally, the shadow effect within the mangrove patches suggested the use of NDVI in the future classification attempts.

Since the summer rainfall over Yangtze River and Huaihe River often leads to the occurrence of floods, with inconsistent distribution among those years, it is important to investigate the characteristics and the causes of rainfall anomalies. Therefore, REOF analysis is performed on 1951-1998 monthly mean precipitation from both CMA (China Meteorological Administration)-provided 160 weather stations and NCEP/NCAR re-analyses. Results show that: 1) summer rainfall over the mid-lower reaches of Yangtze River (MLRYR) can be divided into two rain belts in the south and north of the study region, called as the southern and northern branch of rain belt, respectively. In detail, the southern belt is located in south of the MLRYR, i.e. regions of Jiangxi, Hunan and Zhejiang, and the other is located in regions of Chongqing, southeast Shaanxi, Hubei, south Henan and Anhui, with east-west zonal distributions for the both; 2) both the rain belts are marked by conspicuous intra-annual and inter-decadal oscillations, with remarkable 14-/8-yr periods on the inter-decadal scale for the southern/northern belt. Besides, two belts are different in the amount of precipitation during the same stage, which is closely related to the large-scale circulation, especially the strength of summer monsoon and subtropical high, both impacting greatly on amount and distribution of the precipitation in two belts.

Using experimental data on winter wheat from Bushland, Texas and Zhengzhou, Henan, analysis is performed of the distribution of its root system in 0~50 (50~100) cm soil depth, with the density of root length and its weight making up 57.7% (23.4%) and 66.7% (18.7%), respectively, thereby constructing the model of the roots growth and also by the distribution of the root system and its water absorption, study is undertaken of the appropriate depth of background field moisture for growing winter wheat.

Variation of winter and summer temperature in China were discussed in detail by using EOF analysis and differences between the datasets derived from in situ stations of china meteorological data sharing service system and NECP/NCAR reanalysis, ERA40 reanalysis were compared in winter and summer temperature in China. Results showed that: 1) Winter temperature increases linearly with identical signs all over china except the Tibetan plateau. It is colder than the normal before the late 1970s and warmer since then, especially in 1990s.2) Variation of summer temperature is complicated that it increases in north China but decreases in south to mid-lower reaches of Huanghe and the north of Jiangnan district; 3) The values of NCEP/NCAR and ERA40 reanalysis data are commonly lower than the observations in winter and higher in summer; meanwhile, the change ranges of the reanalysis are closer to the observations'. The spatial and temporal features of winter temperature obtained from the reanalysis data are consistent with that of the observations, but for summer temperature, the spatial and temporal features derived from the ERA40 are better than that of NCEP/NCAR. ERA40 can represent main variations of the summer temperature as the spatial distributions, linear trend and inter-decadal characteristics, but the NCEP/NCAR dataset shows significant differences from the observations for the spatial/temporal variations, the remarkable abrupt change around mid-1970s in NCEP/NCAR can not be seen in observations and in ERA40.

The Common Land Model (CLM) has been validated by observation experiments over different land surfaces in various climate zones throughout the world. These experiments have shown that CLM simulates the characteristics of land-atmosphere interactions over different land surfaces, except in the East Asian monsoon zone where complex land surface conditions exist. China lies on this East Asian monsoon zone which consists of complex terrain, various vegetation types, and specific land surface conditions, and experiences frequent drought and flood disasters. It is important to study how varying land surfaces affect the interaction of energy, mass, and momentum between land and atmosphere. Owing to poor simulation of soil moisture by most land surface models, CLM has chosen to simulate the distribution of soil moisture over China. Meanwhile, station-observed soil moisture, drought monitoring data from a pole orbit meteorology satellite, and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) remote-sensed soil moisture are used to verify the capability of CLM simulation, especially for surface and soil moisture at a 20 cm depth. The results show that the surface soil moisture distribution and variation trend of CLM simulation coincides with pole orbit meteorology satellite monitoring and AMSR-E, and that soil moisture at a 20 cm depth coincides with station observation products from the National Climate Center. It also illustrates that CLM can reasonably simulate the distribution and variation of soil moisture over China. It is meaningful to study the climate response of the lack of soil moisture on soil moisture data. Key words: CLM, soil moisture, drought, AMSR-E

Ecological vulnerability evaluation has important real significance and scientific value. In this study, under the support of Remote Sensing and Geographic Information System, we use TM images, distribution map of sand desertification and soil salinization, and related geographic information, and adopt a combined landscape pattern and ecosystem sensitivity approach to access the ecological vulnerability of Duerbete County. We consider the following five factors to develop the model: (1) reciprocal of fractal dimension (FD'), (2) isolation (FI), (3) fragmentation (FN), (4) sensitivity of sand desertification (SD), and (5) sensitivity of soil salinization (SA). Then we build the evaluation model and calculate the vulnerability of landscape type of Duerbete. Through Kriging interpolation, we get the regional eco-environment vulnerability of whole county. Then we evaluate this cropping-pastoral interlacing region-Duerbete County. The conclusions are: (1) The vulnerability of all landscape types is in the following decreasing order: grassland > cropland > unused area > water area > construction area > wattenmeer > reed bed > woodland > paddy field; (2) There are significant positive relationships between VI and FN, VI and SD, SD and FN, SA and FN. This suggests that FN and SD have considerable impact on the eco-environmental vulnerability; (3) With the combination of FN, SD and SA, the regional eco-environment vulnerability can be evaluated well. The result is reasonable and can support ecological construction.

Floods over the main-stream basin of the Songhua River in NE China are characterized by 24 and 3 ~ 4 year periods, and by 4 phases: 1911-1914, 1930-1940, 1954-1958 and 1984-1998. The flooding frequency is increased remarkably as time goes on. The paper is devoted to the direct cause of the flooding due to July ~ August flash rainfall in the Nen River valley and the Second Songhua - Gelin River catchment area, for which the 500 hPa circulation background is studied, that is, the July ~ August anomalous pattern of the Tibetan plateau to Alaska exhibits a "+ - + -" structure, with a blocking high over the Okhotsk Sea and NE China under the control of a trough. In the year of flooding the Aleutian low deepens in the spring, extending westward and the Ural high is established and moves east. The 1998 deluge over the Song-Nen Plain was related broadly to the circulation pattern anomaly and excessive precipitation except that much-more-than-record rainfall occurred in June and August over the Nen River basin.

Based on the IR cloud imagery from the Chinese FY-2C satellite for June ~ August, 2005 - 2007, statistics is undertaken of meso convective systems (MCS) over NE China and its neighborhood, obtaining the space - time distributions of MCS. MCS include elliptical type( MCC's) , persistent elongated type (PECS's), in shape. Dividing the total MCS into MαMCS, MβMCS and MCC (PECS) . Results show that the number of meso-α MCS (dominantly PECS's) is considerably more than that of meso-β MCS (largely MCCss), which are observed mainly in the NE China plain and Daxing'an Mountains, especially in the entrance to the plain as well as its central ~ northern portion; the MCS occur mainly in June ~ August, particularly in June; the extratropical MCS show two peak phases, one being in 1500-2200 BST the other being 0000-0700 BST as the secondary peaking interval.

In line with the equation of soil moisture balance and the results from field experiments for years, the source and consumption of soil water components and their calculating models were scientifically analyzed. And based on the wheat condition in its whole growth and development period, as well as water consumption pattern and soil water stress index, a computer-based comprehensive study was made for discussing spatial distribution of non-stress soil water content, field moisture utilization and irrigation mode for winter wheat in different climate years to provide useful suggestion as to directing irrigation and management. The analysis showed that: no matter under what type of climatic conditions, winter wheat fields need irrigation at least once in northern part of Henan Province, however, in southern part, especially the southern area of Huai River, irrigation is needless; cornfields in the middle of the province should be irrigated once in the years short of precipitation, while not be irrigated in the years with abundant rainfall.

With the rapid pace of industrialization and urbanization, there is a significant increase of the atmospheric aerosol concentrations. The high aerosol concentration has already had negative impacts on ecological environment, especially on crop production, becoming a focus of attention by scientific communities. So far, no dedicated experiments on the impacts of aerosols radiation effects to crop's growth has been conducted yet. This paper intends to assess the impacts through the numerical simulations. In the research, a crop model (Crop-DNDC) is coupled with aerosol radiation effects model. The study is targeted to the rice, a primary crop grown in the Yangtze River Delta region, and the simulations focuses on the impacts of the changing atmospheric aerosol concentrations on rice growth and yield in the region with the coupled model. As the first step, analysis on radiation changes over the Yangtze Delta Region is made. Then the atmospheric aerosol radiation effects model is coupled with Crop-DNDC, which is used to simulate the impacts of radiation effects on rice growth in the region due to changes of aerosol concentration which is expressed by atmospheric optical depth (AOD). It is found that under the current average atmospheric aerosol concentration status over the Yangtze Delta Region (AOD = 0.78), PAR for rice growth period may be reduced by 17.6%, compared with that without the atmospheric aerosol (AOD = 0). Similarly the grain yield of rice may decrease by 9.3%. Our finding shows that if the atmospheric aerosol optical depth is doubled, PAR for rice could be reduced by additional 15.7%. Consequently, the rice grain weight could be decreased by additional 8.1%.

Soil moisture and vegetation growth are the most important and direct index for drought. The interpreting to vegetation and spectrum analysis of soil are two important elements in the judgment of drought. Recently, Abduwasit Ghulam and other researchers, on the basis of the spatial distribution characters of soil moisture in near infrared spectrum, adopt the expansion analysis method and establish PDI. Later, vegetation index is introduced by establishing a new drought monitoring method MPDI after comprehensively considering about the soil moisture and vegetation growth characters. The article, directing against the drought in different periods of Henan Province, adopts the MODIS image data to undertake PDI and MPDI calculations and compares with the soil moisture data with that of the same period, concluding that: PDI and MPDI are closely related with the original data from land observation, among which the relations between MPDI and 0-20cm calculation is the closest; PDI and MPDI are all close to the drought situation concluded from the calculation of bared land and the early growth period of vegetations; MPDI is more suitable for the areas with vegetations.

Eco-system in karst regions is unstable, and karst-desertificaton induced by soil erosion is an important threat in southwest China. Evaluation of soil erosion is necessary for planning of soil and water conservation for sustainability of land resources and eco-system in those regions. This paper was to estimate risk of soil erosion and understand its spatial distribution in karst regions in Chongqing where are typical area with crisp eco-system in the southwest China. Land use/land cover data was deduced from remote sensing data of TM images of study area in 2000. Soil erodiable K values were estimated from soil texture and organic matter. The data of erosivity of precipitation, terrain, land use/land cover, soil erodible K values was used in this study with rectified USLE model and grid calculation of ArcGIS9 software to evaluate the soil erosion risk and analyze its spatial distribution in this region. The results showed that the risk of soil erosion was severe in the mass and its spatial difference was obvious due to integrative effect of rainstorms, Soil erodibility, topography, and land use/land cover in karst regions in Chongqing. The distribution of soil erosion risk class was closely related to the terrain, land use/land cover in those Karst regions. The large risk rate happened in areas where the terrain is steeper and the human activities were frequent for the agriculture was intensified. This must be paid more attention to by local government and people to take measures for regional soil and water conservation and sustainable development of eco-environment in karst regions in Chongqing.

Spatial pattern of urban thermal environment has an important impact on urban microclimate ecology and human living environment. Because of the limitation of current research methods and techniques, spatial patterns and dynamic characteristics of the urban heat island were not well understood. This paper took the core urban area of Chongqing as the research object, used Landsat TM images in 1988,2001 and 2006, coupled with the ground meteorological data, to detect the hot field thermodynamic landscape heterogeneity. Supported with RS, GIS and the basic theory of "landscape ecology", this paper quantitatively explored the change patterns of several basic landscape metrics and the indexes of grain autocorrelation at different scales, such as Landscape Shape Index (LSI), Fractal Dimension-Mean Nearest (FRAC-MN), Shannon-Weaver Landscape Diversity Index (SHDI), Moran I index, and Geary C index and so on. The result showed that the urban thermodynamic landscape heterogeneity in Chongqing urban area was very obvious; landscape metrics were sensitive to grain variance; urban thermodynamic landscape pattern was spatially dependent on the scale; different metrics responded to the different scale; the resolution of 150 meters was an intrinsic scale for the heterogeneity in Chongqing core city. This research also indicated that decreasing consumption of heat energy and enlarging the area of greenbelt and water are effective ways to weaken urban heat effect.

The autumn of 2007 has seen the most serious drought of last 30 years in the Poyang Lake Watershed (PLW, for short), which resulted in the sharp shrinkage of Poyang Lake from 3000 km2 of normal water coverage sharply to about only 50 km2 at drought peak. This paper adopted the data products of Moderate Resolution Imaging Spectroradiometer (MODIS, boarding on NASA satellites of Terra and Aqua) to analyze temporal process and spatial extension of this Drought in PLW. MODIS-derived Normalized Difference Water Deviation Index (NDWDI, for short) was calculated to examine the water balance of soil against background level, which was expressed with the NDWI average during 2000~2007. Though the Poyang Lake experienced sharp shrinkage in water area, the region near the Lake didn't show corresponsive serious water stress in NDWDI image series. This fact lies in that though the river runoff into the Lake decreased obviously, the soil of lake basin was exposed to less l water stress as the low terrain can easily supply water balance via ground flux.

Using 1994-2006 typical-station agricultural data of the Huang-Huai winter wheat zone for the adjustment and validation of the DSSAT-CERES Wheat model, which is then used with the IPCC SRES climate scenarios (A2 and B2) through a stochastic weather generator, simulation is undertaken of effects of the 2050s climate regime on winter wheat yield, growth/development and water requirement in the Huang-Huai plain. Results suggest that of the two emission schemes, A2 gives higher negative influence compared to B2; the wheat growth/development period is shortened by 18 days, on average, for the region due to global warming leading to the accelerated growth, the flowering occurring ~20 days in advance, the span from flowering to maturity shortened 1~2 days, and the regional yield reducing by ~10%, on the average. Enough irrigation will be needed to alleviate the yield decline but the wheat productivity per unit water volume is to reduce.

Biomass can indicate plant growth status, so it is an important index for plant growth monitoring. This paper focused on the methodology of estimating winter wheat biomass based on LANDSAT TM and EOS MODIS images. In order to develop the method of retrieving wheat biomass from remote sensing data, field measurements were conducted when LANDSAT satellite passed over the study region. In the experiments, five LANDSAT TM images were acquired respectively at early erecting stage, jointing stage, earing stage, flowering stage and grain-filling stage of winter wheat, and experiment sites' wheat biomass was measured at each stage. Based on the TM and MODIS images, spectral indices such as NDVI, RDVI, EVI, MSAVI, SIPI and NDWI were calculated. Then the correlation coefficients between wheat biomass and spectral indices of the experiment sites were computed. According to the correlation coefficients, the optimal spectral indices for estimating wheat biomass were determined. The best-fitting method was employed to build the relationship models between wheat biomass and the optimal spectral indices. Finally, the models were used to estimate wheat biomass based on TM and MODIS data. The RMSE of estimated biomass was not more than 66.403 g/m².