This paper focuses on remote sensing information extraction in geological environment survey and disaster evaluation. DMC satellite multispectral data of tsunami area in Sumatran island and Namucuo area in Tibet is selected as the data source. After data processing and synthesis analysis such as fine geometric correction, image radiation analysis, information enhancement, information extraction, geological interpretation etc., and with the support of the known remote sensing and geological data, the information of Quaternary geology, environment, disaster, desertification in Namucuo Lake and surrounding area is extracted. With regard to tsunami area in Sumatran island, obvious linear and ringed textures in the image are extracted, mapped and analyzed from chromatic aberration of vegetation and texture information, and its geological meaning is interpreted. Northwest fault is the main fault, the smaller one is the northeast fault which is perpendicular to the main fault. Based on that, we have initially analyzed the fracture distribution characters that probably control or induce geologic disasters of the region, and we have also predicted three regions where geological disasters such as debris flow, landslip, landslide etc easily take place and two probable regions where volcanic activities happen. Using DMC satellite data of Namucuo Lake and its surrounding area in Tibet we can recognize lots of information such as lake-face stratum of the Quaternary, bare bedrock, linear feature, two-level and three-level water system, glacier distribution. Through the comparison and analysis of two-period image, we have found four debris flow areas caused by snow melting in the surrounding region of Bingna, Bencuoduo, and Qinglongxiang. In the aspect of land desertification, through image classification, we can extract remote sensing information such as bare ground with grit, meadow, wetland, desertification land (severe, moderate and slight) and alkaline land (moderate and slight) etc. in Namucuo Lake region and its surrounding region. Geological disaster evaluation using DMC satellite data indicates that it not only have huge application potential for disaster monitoring, but also have important application value for geologic environment monitoring.

Based on the status of remote sensing information application in China, from the aspect of geologic exploration, and new thinking of remote sensing information application, a new concept-"post-remote sensing application technology" has been put forward. The argument, the connotation, the technology construction, the research content and the application thinking are expounded and discussed in the paper. Taking uranium resources exploration in the north of Ordos basin for example, some key geologic problems have been studied and important achievements have been obtained. The practice indicates that the post-remote sensing application technology is of more values and better effect than these of single remote sensing technology. The new thinking of modern information technology in combination with traditional methods can also be used for reference to other fields of geosciences.

This paper puts forward to a geometric preprocessing model based on differential GPS (DGPS) and inertial measurement unit (IMU) data for airborne SAR image. Firstly, the DGPS/INS data are preprocessed to determine the SAR antenna centroid and platform attitude. Secondly, relative to SAR navigation coordinates system, observational coordinates of the radar images are calculated. Finally, after strip adjustment, the geometrically preprocessed SAR image or SAR ortho-image based on DEM are obtained. The correctness of mathematic model is verified with the results of test area in western part of China. Finally the main systematic error sources are analyzed and their correction method is presented.

In this paper, 2 kinds of atmospheric correction (AC) algorithms are presented for HY-1A CCD in Case 1 waters based on radiative transfer (RT) simulation: algorithms using lookup tables (LUTs) and algorithms using neutral network (NN), and are evaluated and compared. The LUTs AC algorithms consist of 4 aerosol correction algorithms based on 2 kinds of aerosol lookup tables: τ_a↔γ LUTs and ρ_as↔ρ_A LUTs. When applied to simulated data, the algorithm based on the τ_a↔γ LUTs performs the best. The NN AC algorithms are also successfully applied to simulated data, and not sensitive to randomly added noise of ±5%. Compared with LUTs algorithms, the NN algorithms have the highest R² and lowest RMSE, and have better interpolating ability among different aerosol models. Because of its high speed of data processing, the NN algorithm is another good choice for atmospheric correction in Case 1 waters.

The user requirement for the rice satellite (RICESAT) is analyzed, basing on the radar backscattering coefficient characteristic of rice crops. The orbital elements of RICESAT are selected. The payload of RICESAT was designed as C-band synthetic aperture radar (SAR) system with HH and VV polarization, operating in Strip Map mode or Scan SAR mode. The orbital elements of RICESAT are selected, and the key parameters of the SAR payload are designed. The computer simulation results are presented in the paper, which demonstrates the preliminary feasibility of RICESAT.

The tropical and subtropical regions are characterized by their extraordinary resource environment, weather and climate. So the spaceborne synthetic aperture radar (SAR) with all day and all weather imaging capability has particular function to detect these regions. The available spaceborne radar systems take into consideration observing the tropical and subtropical regions, however, until recently, there has not been the professional radar satellite for observing these regions. This paper proposed the concept of TSARSAT (Tropical SAR Satellite), and analyzed its technological characteristics. The radar satellite will play an important role in rice growth monitoring and yield estimation, tropical rain forest monitoring, disaster monitoring and warning, ocean detection, coast belt surveying and topography mapping.

For the large need of the high resolving power spatial data, a multi-mode airborne digital camera system (MADC) is researched and integrated which has the characters of wide field, multi-spectrum and stereo imaging. This paper introduces the constitution and the technical specifications. MADC can be combined with Position and Orientation System (POS) to get the orientation data of every image, thus, the geometric correction of the image can be done in case of that there are little or no ground control points (GCP), which saves the heavily late works. Many aerial experiments have been executed, and a mass of high quality images were captured. At last, the perspective of MADC's applications in the remote sensing fields is analyzed.

The concept of Delay/Doppler Radar Altimeter (DDA) was proposed by R.K Raney^[1] to improve the spatial resolution in the along-track direction, for rougher surfaces more irregular than open oceans. DDA also has many new advantages when it is used for open oceans, such as stronger response, being less sensitive to off-nadir angle errors, and being more sensitive to significant wave height (SWH) than Conventional Radar Altimeters (CRA). These new features and advantages will be validated by simulations in this paper.

As a new type of aviation remote sensing earth observation system, the UAVRSS (Unmanned Aerial Vehicle Remote Sensing System) has some special characteristics for getting the digital remote sensing images. Through some real flying experiments of the UAVRSS, the data and the images were obtained. These data and the images were analyzed by three methods from three aspects in this paper. The result shows that it is viable that using the UAV with remote sensing system to achieve the remote sensing works.

In projection Aero-Digital Camera with Large Format Array CCD, High Resolution, Large Field of View and Multi-mode, three cameras with 4k×4k CCD sizes are integrated separately in three modes, including large field of view mode, multi-spectral mode and stereophotography mode. Such methodology make one camera system to meet different roles according to the different setting ways before flight missions. Correspondingly the different modes have different geometric characteristics, and the situation looks like more complicate with some additive factors' variations of aircraft, such as pose, speed, height, and so on.The POS/DG system was carried in flight to aid to the upper geometric correction of CCD images. Some flight pose parameters, such as precision location coordinate, flight pose, dynamic variations etc. were directly used in the geometric correction models. One processing example is also provided in this paper.

Atmospheric correction based on hyperspectral image itself was performed on the new spaceborne imaging spectrometer CHRIS image by using the popular radiance transfer code ACORN(Atmospheric CORrection Now) and empirical algorithm as well, in this way, the calibration performance of CHRIS was evaluated by the retrieved spectra of vegetation and soil. It turned out, the vegetation reflectance spectra inverted by ACORN could characterize vegetation reflectance in the range of 498~760nm, but gave a fairly large deviation beyond 760nm, showing the deficiency of spectral calibration beyond 760nm. The ACORN derived soil reflectance decreased after 760nm, which is quite inconsistent with common sense, showing that the calibration accuracy couldn't meet requirements of ACORN for spectral and radiometric calibration at certain spectral range. In addition, the stripes on the retrieved water vapor content map indicated that the radiance calibration performance needs to be improved. On the contrary, AVIRIS was validated to have better calibration performance so that more precise spectra could be retrieved by ACORN5.

In this paper, the principle and processing procedures of two-pass Differential Interferometric Synthetic Aperture Radar (DInSAR) have been presented, and the difficulties and implementation of the key points are discussed in detail.

Interferometric Synthetic Aperture Radar (InSAR) is an effective measurement of generating large scale accurate digital elevation modeling (DEM). It is an important step in InSAR processing that removes the flat earth phase. Common flattening methods work on the assumptions that the interferometric baseline does not vary by time and approximation of local flat earth. These methods do not work well in reality due to the complicated situation. This paper analyzes the model of interferometric phase. Moreover, it puts forward an advanced method which takes into account the variation of baseline related to time. Finally, the actual data test shows the feasibility and validity of the new method.

The backscattering and emission measured respectively by scatterometer and radiometer show promise for the estimation of surface soil moisture and vegetation characteristics. In this paper, the 13.4GHz scatterometer of QuikSCAT and the 6.9GHz radiometer of AMSR-E are simultaneously used for the estimation of the near-surface soil moisture and vegetation water content. An algorithm using synthetic passive and active microwave data is proposed to estimation land surface parameters. At last, the retrieval algorithm was applied on AMSR and QUIKSCAT observations which have been carried out for the SMEX02 (Soil Moisture Experiment 2002) region in Ames, Iowa for the time period June 25 to July 13, 2002. The result shows a consistent performance.

Based on a SPOT-5 image, this study built knowledge pool of vegetation spectral information, adopted classification algorithm of decision tree, proposed a vegetation classification model based on their spectral information and classified the vegetation of Nanjing. The results showed that the overall accuracy was 86.95% and Kappa coefficient was 0.8287. Then the classification model was validated by using an IKONOS image of Yuhuatai region and was improved through combining the textural information. The classification overall accuracy was increased to 92.70% and Kappa coefficient was increased to 0.8648.

The Yellow River Estuary became an important plague region of locusts because of its special geographic location. Many years' survey data showed that the environment was the chief factor that influenced locust pest occurring. In the recent years, because the amount of water from the Yellow River and precipitation reduced and distributed asymmetrically, and soil salinization became serious much more, and many farmlands went out of cultivation, which improved the habitats for locusts, the plague of locusts happened frequently under condign climate. The field survey data from 1991 to 2000 showed that the plague of locust became more aggravating year after year. Therefore, it is important to monitor and control the plague of locusts. According to many years' investigation data analysis, got the condign habitat conditions for Locusta Migratoria Manilensis (Meyen) in the Yellow River Estuary. So the breeding areas of locusts monitoring with remote sensing imagery was to identify those regions according to the condign habitat conditions. Landsat ETM+ imagery (2000-05-02) data was chosen to identify the breeding areas of locusts in the Yellow River Estuary. Firstly classified Landsat TM imagery (2000-5-2) and extract reed lands and lawn lands and slightly salinized soils. Secondly made mask images through transforming these three raster classes into vector layers, then calculated a anti-atmospheric visible light vegetation index VARIg = (B2-B3)/(B2+B3-B1). According to field investigation data of vegetation fractional cover in 2000, got the relationship between vegetation fractional cover and VARIg values, 70% to 3.0, 50% to 2.3. As a result, the infrequent areas were where VARIg values were great than 3.0, and the moderate areas were where VARIg values were between 2.3 and 3.0, and frequent areas were where VARIg values were under 2.3. According to statistical analysis, the infrequent areas were percent 10 of the lands that have the condign soil salt content for locust growth, and the moderate areas of locusts were percent 40, and the frequent areas were percent 50. Because of the low spatial resolution of ETM+ imagery not enough to identify vegetation structure and components, and the quick spatial and temporal change of soil water content, this research only discussed vegetation fractional cover and soil salt content, and quantitative assessment of the identification results and a detailed research need more high spatial and temporal resolution remote sensing data and surface data supports in the future.

The EO-1 spacecraft, launched November 21, 2000 into a sun synchronous orbit behind Landsat 7, hosts advanced technology demonstration instruments, whose capabilities are currently being assessed by the user community for future missions. A significant part of the EO-1 program is to perform data comparisons between Hyperion, ALI and Landsat 7 ETM+. In this paper, a comparison of forest classification results from Hyperion, ALI, and ETM+ of Landsat-7 are provided for Wangqing Forest Bureau, Jilin Province, and Northeast of China. The data have been radiometrically corrected and geometrically resampled. Feature selection and statistical transforms are used to reduce the Hyperion feature space from 129 channels to 15 features. Classes chosen for discrimination included Larch, Oak, Birch, Popular, Young tree, mixed forest, Grassland and Shrub. Classification accuracies by sensors for classes in the demonstration area were: Hyperion 88.89%, ALI 85.19%, and ETM+ 77.78%. The results shows: Hyperion classification results were the best, ALI's were much better than ETM+. Therefore, we can consider that hyper spectral remote sensing provides significant advantages and greater accuracies over ETM+ for forest discrimination. The EO-1 sensors, Hyperion and ALI, provide data with better discrimination for Northeast forests of China in comparison to Landsat-7 ETM+.

Aiming at improving radiometric resolution in remote sensing images of the new generation, this paper developed a method for double byte joint entropy based on proper quantization, which is known to affect entropy, and decorrelation of pixels and bands in multi-spectral images. Joint entropy for images is computed and analyzed, which is close to non-memory, implying that the result is more accurate. The proposed method can be used for the optimum bands selection and quality evaluation in image fusion, which is valuable for increasing precision in entropy analysis.

We present a multi-sensor decision level image fusion algorithm based on fuzzy theory. The main interest of this method is its high speed classification and efficient fusion of complementary information. FCM classifiers are used for classification of each sensor image, and the classification results are fused by our fusion rule. The originality of this work is to define the fusion rule for multi-sensor image classification. Applications to SAR, infrared and multi-spectral image fusion produce interesting results.

According to Wavelet analytical principles and Fractal theories, we put forward a new physical quantity: the Vector of Wavelet-Fractal. We built up a new kind of method that analyses and calculates the nonlinear time series. Applying the ways and means we analysis rain-storm's nonlinear characteristic in the satellite remote sensing information, its result fitted with the variety tendency of actual rainfall in 1998, Wu Han.

A fractal-based image compression algorithm under wavelet transformation for hyper-spectral remote sensing image was introduced in this paper (also named AWFC algorithm). With the development of the hyperspectral remote sensing we have to obtain more and more spectral bands and how to store and transmit the huge data measured by TB bits level becomes a disaster to the limited electrical bandwidth. It is important to compress the huge hyperspectral image data acquired by hyperspectral sensor such as MODIS, PHI, OMIS etc. Otherwise, conventional lossless compression algorithm couldn't reach satisfied compression ratio while other loss compression methods could get results of high compression ratio but no good image fidelity especially to the hyperspectral image data. As the third generation image compression algorithm-fractal image compression is superior than traditional compression methods with high compression ratio, good image fidelity and less time complexity. In order to keep the spectral dimension invariability, we have compared the results of two compression algorithms based on the outside storage file structure of BSQ and BIP separately. The HV and Quad-tree partitioning and the domain-range matching algorithms have also been improved to accelerate the encode/decode efficiency. The proposed method has been realized and obtained perfect experimental results. At last, the possible modifications algorithm and the limitations of the method are also analyzed and discussed in this paper.

Voronoi Diagram is a fundamental geometric structure of space partition. To generate the Voronoi diagrams of the line or polygon objects, the raster method is more convenient than the vector method, while raster generation works better with the generation of full-feature Voronoi Diagram. But for the vector data, the computation in the raster method is realized based on the partition of space. So the generation algorithm is high level of space complexity and the obtaining the neighbors of pixel is very difficult. In order to resolve these problems, a generation of Voronoi Diagram with raster and vector properties based on linear quadtree structure is introduced. The main principle is to reduce the space complexity produced by the partition of space and obtains the neighbors by the spatial index which the linear quadtree structure itself is regarded as. The computing model of backward dilation based on mathematical morphology and several optimized computing characteristics of the model are proposed. The test proves that the time complexity of the method is lower than that of uniform grid structure and that of common quadtree structure, and the space complexity is lower than that of uniform grid structure.

It has become a great demand and a difficult task to study regional evapo-transpiration (ETs) in the field of geology and geography nowadays. As one of the most important contents in studying the interaction between land surface and atmosphere, the precise estimation of various land surface evapo-transpiration makes great sense to study the global climate change, as well as the reasonable utilization and distribution of water resources. Firstly, this paper analyzed several methods which are used to study ETs nowadays, especially the advantages and disadvantages of the prevailing method of RS for ETs, and proposed the new idea of combining the remote sensing method with the land-surface process model based on the previous work of Remote Sensing model for ETs. Then we drove CoLM (Common Land Model), which is the most advanced land surface process model in the world with GSWP-2 re-analyses meteorological data, and compared the ETs calculated by CoLM with the result calculated by a remote sensing model SEBS-China in 1991 of China. The result indicates that both models can simulate the monthly ETs however uncertainties exist in both of the models, which shows the significance and feasibility of the combination of two models in estimation of ETs. At last this paper analyzed the cause of the uncertainties of CoLM and prospected our future work, which is a preparation for the calibration to land surface model with RS model for ETs.

According to the feature of geology, geomorphology, vegetation and human action affect on desert and sandy desertification, by establishing the partition principle such as zone difference, developing rule and multilevel list, we develop the partition system principally based on geology, geomorphology and climate, and secondary based on spatial distribution feature. Using remote sensing technology, we divided the desert and sandy desertification land into drouthy desert, sandy desertification zone in the west of Helan mountain; Helan mountain-Daxinanlin drouthy and semiarid desert, sandy desertification zone; semiarid and half wetness sandy desertification in the east of Helan mountain. We did the actuality analysis of desert and sandy desertification land. The result as below: the area was comparatively little and the intensity was biggish in drouthy desert, sandy desertification zone in the west of Helan mountain; both of the area and intensity were biggish in Helan mountain-Daxinanlin drouthy and semiarid desert, sandy desertification zone; the intensity was less and the area was biggish in semiarid and half wetness sandy desertification in the east of Helan mountain.

To synthesize the observations of microwave and optical remote sensing, the data fusion technology is developed to study the Yangtze River estuary. Information extractions, such as classification of typical objects in the coastal zone, the tidal flat waterside lines and the suspended sediment information, using Chinese Moderate Resolution Imaging Spectroradiometer, are studied.

Regarding the area near the Yangtze River mouth as the demonstration region, this paper briefly introduces the algorithm for the extracting information of the sediment concentration, the main function of the extracting sediment concentration system and some pieces of key technology. Now the system has been trial running, and we get more accurate result, it gives a technique guarantee for the using of HY-1A data.

The field experiment of Dongpu reservoir has been carried out from April 11 to 20 in 2005, and the concentrations of dissolved organic matter (DOM) are measured and analyzed in combination with laser-induced fluorescence (LIF) measurements. The aim of the field investigations was to determine the concentration of DOM in water and evaluate the performance of fluorescence remote sensing system. In experiment, we obtained interesting data of DOM at 49.35m distance by changing the angle of excitation laser incidence to water. The concentration of the DOM is 3.325mg/l and the relative standard deviation is 2.65%. It has been shown that the measurement of water quality in real time and on line can be done using LIF technique with high sensitivity and high precision.

Ecotope diversity of land-cover in China is calculated on 4 different spatial scales by means of the scaling diversity model. The calculation is based on land-cover database derived from remotely sensed data in the late of 1980s, the middle of 1990s and the late of 1990s. The calculation result shows that on national scale, ecotope diversity has a decrease trend during the period from the late of 1980s to the middle of 1990s and has an increase trend from the middle of 1990s to the late of 1990s; on economic-region scale, the central region and eastern region have more ecotope diversity than the western region; on provincial scale, for any one of the three economic regions, if a province, termed A, has more ecotope diversity than a compared province, termed B, in one period, A must have more ecotope diversity than B in other two periods generally; on county scale, 14 hot-spots of ecological diversity conservation have more ecotope diversity in the three periods. Ecotope diversity on national scale is more than the one on economic-region scale; ecotope diversity on economic-region scale is more than the one on provincial scale, which is more than the one on county scale.

This paper applied MODIS images to capture LAI data and to evaluate the ecological environmental quality for Yangtze River drainage area. Based on 500mx500m grid data including LAI, topography, precipitation, heat, and other factors, the authors established a comprehensive assessment model of ecological environmental quality. Then we discussed types and spatial distributions of ecological environmental quality index. We found that Yangtze River drainage area had a middle-level ecological environmental quality to some extent, and that spatial difference in ecological quality was strongly impacted by the geographical differences of some natural factors, such as the altitude. Lastly we put forward some policies for ecological conservation in the research area.

The Iraq war has passed about three years. This paper introduces the analysis of the huge dust storm happened in the middle of the Arabia Peninsula on 25-27 March 2003, in course of Iraq war, with remote sensing technology, and shows that the weather condition is one of the important factors parameters in Modern warfare. The result of analysis is based on two kinds of meteorological satellite data, geostationary orbit satellite and polar orbit satellite, and shows that the FY-1C/LDPT data and the Metosate-5 images, have great effect on analyzing the dust storm.

This paper presents a case study of Daye, Hubei, China, to trace the mining activities and related environment changes during the past 10 years, with an emphasis on land cover changes. Three sets of satellite data have been used in this case study: TM (ETM+), SPOT-5 and QuickBird image data. A multi-temporal dataset consisting of two Land sat 5 Thematic Mapper (TM) images and one Enhanced Thematic Mapper Plus (ETM+) image including 1986, 1994 and 2002 have been used to compare the land cover changes of the Daye area, Hubei Province, China. The combined bands method, iron oxide index and the NDVI index method have been used to investigate the spectrum character and the space character of the different ground objects. The knowledge-based decision tree classification method has been used to get the highly accurate classification result with the TM and ETM+ image data; the interactive interpret Method has been used to interpret the mine distributing with the SPOT-5 and TM fusion image; the visual interpretation method has been used to interpret mine distributing and environment changes with the QuickBird panchromatic and the multi-spectral fusion image. The characteristics of the high accurate classification result and high accurate change detection make quantitative analysis of different mining area features possible. The results of change detection show that the water quality of the whole water body was still bad, although the water quality have been improved in some areas. Vegetation shows degradation trend especially in those areas close to the mining areas, large areas of wood land and plantations are reduced, the increasing bare areas appeared based on the mine database, the reclamation percentage of the abandoned mining is only 20% from 1986 to 2002. The ecological environment in the study area may become worse unless the efficient management of mining business and effective eco-environment protection in mining area are carried out instantly.

Locust plague is a kind of the world-wide biological calamity to agriculture. In China's history, more than 90% of locust plagues were caused by the oriental migratory locust, Locusta migratoria manilensis (Meyen). At the present time, it is difficult for monitoring and forecasting systems in this country to provide real time information of locust plague outbreak in large area. In order to adopt timely measures for prevention and control of locust outbreak, it is necessary to apply advanced remote sensing technology for monitoring and forecasting locust outbreak This paper introduces a case study on monitoring oriental migratory locust plague with remote sensing technology in 3 pilot sites, namely, Huangzao, Yangguangzhuang, and Tengnan, which were the 3 major locust damaged areas in Huanghua City, Hebei Province, China during the period of large scale oriental migratory locust breakout in 2002. In this study, locust damage intensity, areas with various damage intensities and their distribution in pilot sites are determined by means of comparison between Landsat ETM+ image of locust damaged vegetation on 31st May, 2002 and TM image of healthy vegetation before damage on 23rd May, 2002. Then, information of various locust distribution density in pilot sites is extracted by establishing the Locust Density Index (LDI).

On December 26, 2004, a tremendous seaquake up to grade 8.6 happened at the sea floor under the Pacific Ocean in southwest Sumatra Island, Indonesia, producing tsunamis to cause a series of serious hazards to 13 countries and regions in south Asia and around the Pacific Ocean. After the seaquake, through processing and analysis to the MODIS remote sensing image data, four kinds of strange remote sensing information with special characteristics and shapes were discovered, which are specifically the yellow island shore margin, seawater ring structure, sea-cloud ring and the sharp-horn-cloud in the sea-land area close to the epicenter. The study shows that the strange remote sensing information has much more significance than the original images themselves, thus helping understand more about the tremendous natural hazard through our analysis and interpretation.

In order to improve the efficiency of the information management and the quality of the services of public urban recreational spaces (PURS), the function-based classification are designed and the encoding scheme of the recreation spaces is brought forward on the demand of recreation activities. Shijiazhuang public recreation spaces web service system is constructed based on the three-layer model of Browser/Server (B/S) and can provide excellent services for residents' recreation. Via the Internet explorer, people can browse through the recreational spaces, query for recreation spaces, facilities, recreation function and bus route, and analyze the current service facilities. Build on the residents' recreation requirements, the system offers a way for the public recreation spaces' management, and can improve the quality of the residents' recreation activities.

Giving a full consideration of the environment protection in determining the railway location for the purpose of the sustainable development, with the help of remote sensing, GIS, 3D visualization and virtual reality technology, combined with the field geological survey, this paper conduct the remote sensing applications and 3D visualization researches of the Passenger Transportation Special Railway Line from Shijiazhuang City, Hebei province to Taiyuan City, Shanxi province. The research results show that remote sensing information has provided reliable references for the project-design selection of the Shi-Tai Passenger Transportation Special Railway Line in the general investigation of regional structures and geologic hazards; the 3D visualization analysis method based on the virtual reality technology has provided a new tool for the direct, interactive and scientific description in the railway location.

The basic principle of PHI hyperspectral imaging systems is introduced in this paper, and various methods for reflectance conversion are discussed and further reduced into three kinds, the methods based upon radioactive transfer theory, the normalization methods and empirical methods. By using the empirical line method, reflectance conversion of shanghais hyperspectral data was made. Experiments of hyperspectral image classification are practiced by using SAM matching model. The result of classification is better than that of traditional classification such as ISODATA. Research indicates that the diversity and complexity can be distinguished by using hyperspectral data.

After the outbreak of highly pathogenic Avian Influenza (HPAI) in South Korea in the end of year 2003, estimates of the impact of HPAI in affected countries vary greatly, the total direct losses are about 3 billion US dollars, and it caused 15 million birds and poultry flocks death. It is significant to understand the spatial distribution and transmission characters of HPAI for its prevention and control. According to 50 outbreak cases for HPAI in Chinese mainland during 2004, this paper introduces the approach of spatial distribution and transmission characters for HPAI and its results. Its approach is based on remote sensing and GIS techniques. Its supporting data set involves normalized difference vegetation index (NDVI) and land surface temperature (Ts) derived from a time-series of remote sensing data of 1 kilometer-resolution NOAA/AVHRR, birds' migration routes, topology geographic map, lake and wetland maps, and meteorological observation data. In order to analyze synthetically using these data, a supporting platform for analysis Avian Influenza epidemic situation (SPAS/AI) was developed. Supporting by SPAS/AI, the integrated information from multi-sources can be easily used to the analysis of the spatial distribution and transmission character of HPAI. The results show that the range of spatial distribution and transmission of HPAI in China during 2004 connected to environment factors NDVI, Ts and the distributions of lake and wetland, and especially to bird migration routes. To some extent, the results provide some suggestions for the macro-decision making for the prevention and control of HPAI in the areas of potential risk and reoccurrence.

Land use/cover change (LUCC) is a key aspect of global environment change and in a sense indicates the influence of human activities on natural environment. Regional case study is the core of LUCC research. The 28th Olympic Games will be hold in Beijing. The Olympic Green locates in northern Beijing, where there are villages, residential houses, arable land and commercial building. In order to detect the changes of land use in the past several years and monitor the change of the Olympic Green and the construction implementation in the past four years, one Quickbird image of 2002 and three aerial true color images of 2003, 2004 and 2005 in May or July are used to monitor the change and the location of construction, green land, water body after standardized radiometric normalization correction and geometrical correction. The land use changes during the past four years were statistically analyzed by the interpretation of the images that show clearly the location of the housebreaking area and the progress of the Olympic main venue construction area.

With the increasing of vehicles in China, photochemical smog pollution accidents may be greatly possible in some Chinese cities. However, the predicting and alarming of photochemical smog is only in the preliminary stage. MODIS Information Service Processing System established by NASA provides 10km×10km resolution aerosol optical depth (AOD) Level 2 products. This paper establishes the framework of advanced warning mechanism system for the urban photochemical smog pollution based on MODIS data. The framework includes MODIS data reception and processing, analysis of variation of meteorology, analysis of ground surface detection data, atmospheric pollution index, and determination of advanced warning scale etc. We can further develop advanced warning system on the existing framework process basis which is designed for urban atmospheric pollution aided monitoring and prediction and advanced warning of atmospheric pollution. Advanced warning mechanism system of the urban photochemical pollution may be a part of the urban disaster prevention and reduction system to publicize atmospheric photochemical pollution in time, provide grounds for controlling environmental pollution and reference information for our daily lives and outgoing.