In order that people grasp the elementary knowledge of MODIS data application status in China’s terrestrial science, this paper describes the achievements acquired by Chinese scholars in the MODIS data processing, the remote sensing information extraction and the application of productive practices, with an aim of expressing the continuous improvement and the difficulties in the study of terrestrial science based on the MODIS data. The result could provide the theoretical support for further enrichment and improvement of the MODIS data application. At the end of the paper, three measures are put forward for further practicability of MODIS data, i.e., the improvement of MODIS data source quality, the perfection of the information extraction methods, and the construction of the MODIS data analysis models.

Global change has cross-border and multi-scale characteristics and needs the development of systematic data observation program to acquire consistent data so as to meet the requirements of global change research. Requirements of global change for remote sensing data and systematic data observation program of ALOS are dealt with in this paper. Studies show that, with the development of China’s economy and the enrichment of China’s satellite data, it is necessary to implement systematic data observation program so as to lift China’s voice in the aspect of global change and environmental protection.

 It is difficult to determine the complex polygonal boundary information only through the line-polygon topology. In view of this situation, the authors proposed a sorting algorithm based on the judgment of minimum angle to get the orderly boundary of complex polygon. As the polygon boundaries are usually irregular curves in the investigation of land use，the authors introduced the curve tangent to get the angle and to determine the next boundary according to the size of the angle，which can solve the sorting processing problems of complex polygonal boundaries，such as multi-edge sharing of a common node which includes islands holes, etc.， to meet the requirements of  VCT  data production in the land use investigation.

In consideration of the features of remote sensing image, this paper presents a new method for classification of remote sensing images based on multiple classifiers combination. In this method, three supervised classifications, Mahalanobis Distance, Maximum Likelihood and SVM, which are of more precision and better diversity in classification, are selected to serve as the sub-classifications,  and the simple vote classification, maximum probability category method and fussy integral method are combined together according to certain rules. The authors adopted Huairen county in Shanxi as the study area for land use classification using color infrared aerial images. Experimental result showed that the overall classification accuracy was improved by 12% and Kappa coefficient was increased by 0.12 in comparison with SVM classification which has the highest accuracy in single sub-classifications. This result indicates that the classification of multiple classifiers combination is an effective classification method.

L band microwave can penetrate the soil, and its bright temperature data contain layers of soil temperature information within the penetration depth. L band effective soil temperature and infrared soil temperature have different physical significances and values. The SHAW model was verified by using the observed data of the automatic weather station in Huailai and was driven to simulate the soil temperature and humidity profile data by using 2006~2009 meteorological observation data from Huailai experimental area. The L band effective soil temperature was computed using the soil temperature and humidity profile data in an hour interval. An analysis of the difference between infrared soil temperature and L band effective soil temperature was made tentatively. The result constitutes a basis for further exploration of the relationship between infrared soil temperature and L band effective soil temperature and also provides a theoretical support for concerted inversion of soil temperature combining infrared and passive microwave data.

 Taking the tungsten ore district of Dayu County in Jiangxi Province as an example，the authors analyzed the parameters and relationship between the WorldView II bands，selected the best bands for the information extraction of water in the study area，and tested and analyzed a variety of fusion methods to access the suitable fusion method that uses WorldView II image to extract the water information in the ore district. The water information in the ore district was extracted by calculating NDWI，analyzing spectral relations between different bands，and making supervised classification. The interpretation accuracies of NDWI, Spectral Relation Act and supervised classification were tested by visual interpretation. The interpretation results were revised to attain the accuracy of 92%，and the field verification accuracy can reach 90%，which meets the requirements of the work.

Vegetation coverage is always an obstacle in the lithological information extraction from optical remotely sensed imagery. Aimed at enhancing lithological and soil information in vegetation coverage area, this paper used a three-step (i.e., masking, enforced variance, histogram equalization) general vegetation suppression approach. Four experiments were conducted by using different datasets in different locations, which included a Landsat ETM+ image in Hangzhou of  Zhejiang, a Landsat ETM+ image in Funing of Yunnan, a Hyperion image in Rongtang of Jiangxi and a MODIS image in Guangdong. The results indicate the effectiveness of the proposed approach in suppressing vegetation in optical remote sensing images with different spatial and spectral resolutions.

In consideration of characteristics of road greenbelts in high spatial resolution satellite imagery, this paper proposes a method combining features of shape with those of spatial distribution of road greenbelts to recognize road edges and road centerlines. The method first extracts greenbelt information from a NDVI image, then differentiates road greenbelts from other greenbelts by means of linear features of road greenbelts and their related shape indices such as area, principal axis direction, compactness, rectangularity, and ratio of width and length. After that, the road greenbelts adjacent to other greenbelts are separated by generating buffers of known road greenbelts as well as according to the spatial relationships between different greenbelts and between road greenbelts and other greenbelts. Finally road edges and road centerlines are extracted in accordance with the direction and distance characteristics of road greenbelts.

 It is necessary that all variables be considered as discrete variables, or discretization be conducted in a traditional discrete Bayesian network classifier. The information loss in discretization is inevitable, and the discretization of continuous variables will lead to dramatic expansion of search space and great expenses in computation and storage in multi-source data processing and analysis. To solve these problems, the authors have developed the Hybrid Bayesian network classifier for land use classification, which first conducts normal distribution test for all variables in the study area. For the variables that meet Gaussian distribution assumptions, the authors do not discrete them and regard them as continuous variables. Parameter learning of discrete variables and that of continuous variables are carried out respectively, and then the parameters are merged. These parameters are used for reasoning and classification of Bayesian network at last. Experiments of land use classification in Fujian show that the model is superior to the traditional discrete Bayesian network classifier, and hence has great research and application value.

This study develops a new algorithm for estimating bare surface soil moisture using combined active/passive microwave remote sensing on the basis of TRMM (Tropical Rainfall Measuring Mission). To accurately estimate bare surface soil moisture, the algorithm simultaneously uses a precipitation radar (PR) and microwave imager (TMI) for observation. In this paper, through an analysis of the numerically simulated surface backscattering and emissivity database by Advanced Integral Equation Model (AIEM) with a wide range of soil moisture and surface roughness conditions，the authors have found that the surface roughness parameter has an important impact on both backscattering coefficient and emissivity. Based on the simulated database by AIEM, the authors use theoretical model (Geometrical Optical Model) and semi-empirical model (Qp Model) through the analysis of surface roughness as well as TRMM/PR and TMI data to develop the algorithm for estimating bare surface soil moisture.

 Zn contamination of rice with different concentrations of stress was identified by the remote sensing diagnosis method from the potential Hyperspectral index and the representative spectral reflectance. At the spectral index level, the authors systematically analyzed the responsive relationships of the Hyperspectral index and four important physiological parameters under the stress of Zn pollution，which include chlorophyll content， water content，cell structure and leaf area index. Through the experiments，the authors extracted Hyperspectral remote sensing indexes which reflect the change of ecological parameters and their interactive reglarity，thus establishing the three-dimensional identification model of Hyperspectral remote sensing indexes which reflect the change of Zn contamination. At the spectral reflectance level，spectral reflectance of representative bands in visible and near infrared spectral bands were decomposed using the method of independent component analysis (ICA)，and the independent components which reflect the change of Zn contamination concentration were found. Thus the visible-near infrared independent component space was established. Zn contamination with different concentrations exhibits different laws in the Hyperspectral index and independent component space，Zn contamination of rice with different concentrations can be determined combined with Hyperspectral index and independent component space，the reliability and sensitivity is improved.

In this paper，an automatic approach for alluvial fan extraction based on TM image is put forward. Firstly，the spectral feature differences between alluvial fan and other surface features were analyzed；then，in view of the facts that the band ratio between red band and near-infrared band can increase the differences between alluvial fan and other surface features and the decreasing rates of bright values of shadow in blue and green bands are significantly different，the authors built the model of alluvial fan extraction based on ratio and difference operations. Using this model in combination with the algorithm of automatic threshold extraction，the authors separated the alluvial fan from other surface features，and then applied the dilation and erosion filtering algorithm of mathematical morphology. An analysis and comparison of experimental results show that the proposed approach can extract the alluvial fan from hilly areas in South China with high precision. Moreover，the approach can effectively remove the interferential information such as shadow and vegetation.

 To solve the problem that the first-order and second-order statistics may be inadequate for obtaining a complete representation of the data，a high-order statistics-based method， kurtosis-based independent component analysis (KICA)，is introduced to implement unsupervised classification of hyperspectral data. Aimed at the purpose that kurtosis can be very sensitive to outliers such as noise，the improved KICA (IKICA) model is proposed in the work when kurtosis is used as optimization criterion for the ICA problem. To evaluate the performance of the proposed algorithm and its application capability in unsupervised classification, IKICA is compared with maximum likelihood-based ICA and negentropy-based ICA，and the synthesized and real hyperspectral data acquired by Object Modularization Imaging Spectrometer (OMIS) and Pushbroom Hyperspectral Imager (PHI) are used. The results show that convergence speed and robustness are enhanced obviously and anti-noise capability is improved in the authors’ work. The application result has high precision of classification.

 To some extent, remote sensing alteration anomalies can reflect the alteration of wall rocks. The characteristics of absorption and reflection in ASTER can be obtained by analyzing the spectra of altered minerals. Some bands reflecting obvious characteristics can be calculated on the basis of principal component analysis, with the choice of the principal component of alteration information in accordance with the relationship between the spectra and the eigenvector. The thresholds of the anomalous gray are computed on the fractal model, and the extracted anomalies are well coincident with the known ore deposits.

Water surface temperature is one of the important environmental parameters at the breeding aquatics area in shore. The highly dynamic monitoring of this temperature will help to arrange aquaculture production and breeding production. Remote sensing technology is a very efficacious means for monitoring water surface temperature in high dynamic condition. At present, weather and ocean satellites which have lower spatial resolution are widely used in water surface temperature remote sensing monitoring, with the spatial resolution being 1 000 m. However, water bodies in shore are influenced by land and ocean as well as the spatial changes of water surface temperature, and hence satellites data which have higher spatial resolution are needed to meet the monitoring for water surface temperature in high dynamic condition. HJ-1B/IRS has a 4-band infrared sensor (IRS). One of the bands is the thermal band which can be used to retrieve water surface temperature. In this paper, data of about ten images of HJ-1B/IRS thermal band obtained from 2008 to 2009 and the atmosphere measurement data at the time when the HJ-1B satellite passed through the area were collected. Based on the monowindow algorithm and referring to the temperature product from EOS/MODIS, the authors established a model for water surface temperature retrieval from HJ-1B/IRS data. Moreover, a comparison was made between two retrieval methods for surface temperature from HJ-1B/IRS thermal band and from the temperature product by EOS/MODIS. The results show that the absolutely average temperature error from the monowindow algorithm and from the temperature product by EOS/MODIS is 7.84℃, while that from the method proposed in this paper is 0.83℃. The model for water surface temperature retrieval from HJ-1B/IRS data established in this paper was applied in the area of Liaodong Bay for the purpose of carrying out dynamic monitoring of water surface temperature.

 If the classification type is unknown，the K-means algorithm will randomly select the initial values，and different initial values will lead to differences in remote sensing image classification results. To solve such problems，this paper proposes an improved K-means algorithm. First, logarithmical transform is performed for the original data，and then principal component transformation is implemented. The number of principal components for the K-means algorithm is determined according to the contribution rate (≥85%). The proposed method can weaken the noise. Kernel density estimation can be used to determine the probability density function of the first principal component, from which the initial label for multi-dimensional K-means algorithm can be efficiently determined，and the sensitivity of the initial value selected at random can be avoided.  Experiments show that the accuracy of the method proposed in this paper is higher than that of the traditional K-means based on mean-variance.

Taking the Longnan gold ore district in Gansu Province as the study area, this paper carried out the study of extracting iron alteration information from satellite-based remote sensing images from SPOT data. Based on analyzing the geological background and rock alteration types, the authors used SPOT 5 satellite remote sensing images and, by utilizing a variety of image processing methods, extracted the iron alteration information closely related to gold mineralization and explored the feasibility of extracting alteration information from moderate and high resolution satellite data. The results show that, in comparison with ETM，ASTER and other satellite data， SPOT does not have a broader spectral range and higher spectral resolution，but can play an effective role in carrying out some specific tasks in particular area.

 The extensive distribution of geomorphic surface is the main geomorphologic characteristic of Guizhou and its adjacent areas，and the detailed study of this characteristic is very important in reconstructing Cenozoic evolution. Taking Guizhou and its adjacent areas as the study district， based on ASTER-GDEM data (30 m)  and using ArcGIS platform，the authors extracted the geomorphic surfaces with slope data and statistical method，and obtained the precise quantitative features of the geomorphic surfaces in this district for the first time. The results provide a new insight into the study of step-like landforms. It is shown that there are 4 steps of geomorphic surfaces in the study district， which suggests that Guizhou and its adjacent areas has experienced at least 3 times of complicated tectonic uplift since Cenozoic with the uplifted elevation being 300～500 m each time, and remain in the process of uplifting at present.

This paper intends to examine spatial distribution of soil moisture in Shiyang River basin in eastern Hexi corridor, an important arid ecosystem in Northwest China. The MODIS data MOD11A2, MOD13A1 and MCD43A3 were used to compute such parameters as NDVI, ATI and TVI required for the study. An applicable approach from ATI and TVI has been proposed to estimate the soil moisture in the basin, using NDVI as a threshold for each pixel. The approach was validated with the field data. The distribution pattern of the soil moisture in Shiyang River basin was further analyzed using DEM data. The results show that the compound ATI and TVI models can effectively improve retrieval accuracy and remedy the shortage of one-sided method. The results were acceptable through a comparison with the field data. The study reveals that in Shiyang River basin, the soil moisture is degressive from the upstream area to downstream area, and it is obviously lower in the sloping land of foothills, the edge of oasis and desert area. Relatively, the soil moisture has observably changed in the upstream and downstream areas and marginal areas of oasis. In Shiyang River basin, the soil moisture distribution shows significant differentiation with the change of elevation, slope and other terrain factors. In Shiyang River basin, the drought is mainly distributed in farmland and grassland, and the drought extent of farmland is in different degrees of seriousness in different landuse types. 

 Celluar Automata (CA) featured by self-organizing evolvement is used to establish the urban expansion model. This paper introduces a CA model and adopts a neighbor factor to implement controllable neighbor-effect on the basis of exploring the influence of several location feature variables on cell status conversion in historical data. Obtaining simulated results with different spatial patterns is possible through changing the value of the neighbor factor. Taking the urban district of Changsha and it vicinities as the study area, the authors conducted an experiment to simulate and predict the process of urbanization, and then evaluated and analyzed the results.

To further understand the ecologic restoration level after water supplying，the authors studied vegetation coverage （Fv）in the water supply area of the lower reaches of the Tarim River. Correlation equation and two-dimensional scatter plot between Fv and vegetation index （VI） could be obtained based on MODIS data by constructing a variety of VIs in combination with measured Fvs，and the value of Fv could be figured out based on the relevant equation. The results show that there exist good correlations between the VIs such as NDVI，MSAVI，SAVI and EVI and Fvs on the basis of MODIS data. With these VIs，the inversion accuracy of the Fvs in the order from higher to lower is NDVI, EVI, MSAVI and SAVI. The authors suggest using MODIS data to monitor vegetation change in the arid desert area，with the optimal choice of VI being NDVI.

On the basis of the measurement of ecological parameters by using remote sensing technology, combined with the ecological method and TM/ETM+, the authors made a quantitative measurement of ecological assets of Jilin Province in 2000 and 2008, obtained the spatial distribution of ecological assets and carried out a dynamic analysis. The results show that, from 2000 to 2008, the total value of ecological assets of Jilin Province increased from 438.561 billion to 675.131 billion yuan，and the value per unit area increased to 241.7 kilo yuan /(km2·a). In different ecosystem types, the total value of ecological assets of the forest had the biggest changes, and the increase of the total value amounted to 119.36 billion yuan in 8 years, while the ecological value of the building land had the minimum increase, with the increase of only 1.575 billion yuan. According to the spatial distribution of the total value of ecological assets, the distribution of total value of Jilin Province's ecological assets in 2000 and 2008 showed the trend of decreasing from east to west.

In this paper, some change detection methods were used for assessment of urbanization and ecosystem changes. The urbanization area index (UAI) derived from land cover was used to reflect the speed of urban expansion, while the fraction of vegetation cover (FVC) retrieved from NDVI was used to represent the status of urban ecologic environment. The NDVI time series were derived from MOD13Q1 by using an annual stacking approach. Land cover maps were retrieved from annual NDVI time series from 2000 to 2009. This paper focused on the assessment study of urbanization level and ecologic environment changes in Shanghai. The results indicate that: (1) the urban area of Shanghai increased continuously in the past 10 years; (2) the UAI increased by an annual average rate of more than 1.73%, with its peak value being 4.36% during 2008-2009; (3) on the whole, FVC decreased continuously over the past decade, while the FVC of the urban area increased slightly and the FVC of some islands and outer suburbs increased slightly too; (4) the urban ecologic environment of Shanghai became more and more "green" at the cost of decreased cropland and natural vegetation cover. The assessment of urbanization and ecosystem changes suggests that suburban ecosystem protection is an important and urgent problem and the government should implement more effective environmental management policies.

 The flow accumulation and catchment watershed of the Dexing copper ore district and the Fujawu copper ore district in Jiangxi Province were simulated by using 1∶50 000 DEM with the support of ArcGIS in this paper. Firstly，the authors divided the area into 2 watersheds named a and b respectively，then divided the watershed a into 3 small catchment watersheds. Supported by metallogeny and mining science，the authors used GeoEye-1 data of American satellite to make a quick survey of the solid waste in Fujawu copper ore district with the method of human-computer interaction，and found that the area is 2.105 km2. Then the authors made a spatial overlap on the distribution of solid waste and watershed delineation and found that, as the original topography of the site of solid waste has a large slope and a large thickness of accumulation，it poses a threat of debris flow to the residents in downstream areas like Yangcun and, what is more, because of the corrosion of surface water，the exposed wastes make a serious impact on the water quality of Jishui River as well as residents’ drinking water in downstream areas.

Located on the east edge of middle Kangdian axis，the Boka gold deposit has complicated ore-forming background and great ore-prospecting potential. In this paper，ETM+ remote sensing image was used to conduct tectonic interpretation and extraction of mineralized alteration information in the study area，combined with a comprehensive prospecting analysis of regional geological and geochemical information. The intense anomaly information of mineralized alteration at the intersection between the NS-trending and EW-trending structural zones displays  regular variation regularity, suggesting that the southern part of the Boka gold deposit and the NS-striking alteration belt of the study area has good ore-search prospects.

 Based on World Wind Java SDK, the authors have developed the 3DGIS applied in the emergency management of the high-sulfur field. Through temporal-spatial construction analysis and pre-creation clips，difficulties of data-transmission and visualization of numerical simulation model of H2S gas dispersion in 3D environments caused by massive data volume can be solved. Emergency management data and model database are achieved in the visualized 3D environment and the emergency application functions are developed in terms of business process, which include receiving alarm, emergency analysis and emergence disposal on the 3DGIS platform. This research not only attempts to construct the technology of 3DGIS but also offers a tool of 3DGIS to both research and practice for critical incident management in the high-sulfur gas field.

This paper presents the technical route of designing the database of specialized map symbols for geological hazard and its realization according to relevant national standard in this field. Tests of the database of specialized map symbols for geological hazard were made on the basis of the method presented in this paper through practical application. The release, application and share of this database were realized.