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An Earth multi-body system elasticity and plasticity dynamics model

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science china(Technological {2.) 2006年第Z2期49卷 23-29页

作者： ZHANG Qingxian, BI Siwen & GONG Huili Education Ministry key laboratory of Three-Dimensional Information Extraction and Application, Capital {2. University, beijing 100037, china state key laboratory of remote sensing science, IRSA, chinese {{12. of sciences, beijing 100101, china Capital normal Univ Educ Minist Key Lab Dimens Informat Extract & App Beijing 100037 Peoples R China chinese Acad Sci IRSA State Key Lab Remote Sensing Sci Beijing 100101 Peoples R China

Research on the elasticity and plasticity dynamics of the Earth multi-body system, including the Earth multi-body system stratum-block's equivalent inertia force system and generalized inertia force, the Earth multi-body system stratum-block's equivalent inertia force system expressed with partial velocity and partial palstance, and Earth multi-body system generalized inertia force expressed with partial velocity and partial palstance. This research provides a theoretical foundation for further investigation of Earth multi-body dynamics.

关键词： Earth multi-body system, equivalent inertia force system, generalized inertia force, elasticity and plasticity, dynamics model.

An efficient rendering method for large vector data on large terrain models

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science china(Information {2.) 2010年第6期53卷 1122-1129页

作者： YANG Ling1,ZHANG LiQiang1,KANG ZhiZhong2.XIAO ZhiQiang1,PENG JunHuan2.ZHANG XingMing1 & LIU Liu11state key {2. of remote sensing science,jointly sponsored by beijing normal University and the institute of remote sensing Applications of chinese academy of sciences,beijing 100875,china 2.epartment of Geodesy and Geomatics,School of Land science and Technology,china University of Geosciences,beijing 100083,china state key {2. of remote sensing science Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing Applications of Chinese Academy of Sciences Beijing China Department of Geodesy and Geomatics School of Land Science and Technology China University of Geosciences Beijing China

This paper presents an efficient way to render large-scale vector maps on level-of-detail(LOD) digital elevation models(DEMs).By using the frame buffer and Voronoi diagram,we achieve a rapid simplification of large-scale vector maps while keeping their original topological *** the simplified maps,we establish level-of-detail vector map *** the detailed level,we use the stencil shadow volume approach to render the map accurately,and in the coarse level we use substitute techniques to render the map approximately yet more *** method proposed in this paper is universally applicable to rendering vector maps on various LOD terrain models,and the overlaying performance is independent of the complexity of underlying terrain *** use of the view frustum culling and sub-region index techniques,the impact of complexity of vector maps is reduced,and the rendering time is restricted to a certain ***,we can achieve seamless and rapid rendering of large-scale vector maps on LOD terrain surfaces.

关键词： large-scale vector maps LODs view-dependent visualization

Change of surface cover greenness in china between 2.00 and 2.10

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chinese science Bulletin 2012年第22期57卷 2835-2845页

作者： LIU Shuang1,4& GONG Peng1,2.31state key {2. of remote sensing science, jointly sponsored by institute of remote sensing Applications of chinese {{12. of sciences,and beijing normal University, beijing 100101, china 2.8} for Global Change Studies & Center for Earth System science, Tsinghua University, beijing 100084, china 3Department of Environmental science, Policy and Management, University of California, Berkeley, CA9472., USA 4Graduate University of chinese {{12. of sciences, beijing 100049, china state key {2. of remote sensing science Jointly Sponsored by Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing China Graduate University of chinese academy of {2. Beijing China institute for Global Change Studies & Center for Earth System science Tsinghua University Beijing China Department of Environmental science Policy and Management University of California Berkeley USA

Surface greenness reflects the situation of vegetation *** index calculated from the Red and Near Infrared bands of remote sensing images,whose values indicate the level of photosynthetic activity,is monotonically related to surface greenness when vegetation canopy does not fully cover the background *** for desert regions,vegetation index is positively correlated with vegetation ***,vegetation index can be used to study the change in greenness of desert *** study collected MODIS {2.ized Difference Vegetation Index (NDVI) data from 2.00 to 2.10 and analyzed their change over china in this *** results showed that an increasing trend of NDVI occurred over 66.84% (OLS fitting) or 64.2.% (LAD fitting) of china,indicating that china's greenness is increasing ***,desertification of china *** showing large increase in greenness are found in Shaanxi,Shanxi,Ningxia,Henan,Shandong,Qinghai,and Gansu while regions with large decrease in greenness are found in Northeast Inner Mongolia,South Tibet,Jiangsu,and *** of Qinghai,Gansu,Xinjiang and South Tibet could probably be driven by climate *** of greenness in Northeast Inner Mongolia was related to agricultural *** of greenness in Jiangsu and Shanghai was related to rapid *** factors did not exhibit obvious correspondence to the large increase in greenness in Shaanxi,Shanxi,Ningxia and Gansu,indicating that the changes might have been caused by human *** reduction of desert areas in china could probably have been caused by human management and protection at the national scale.

关键词：中国地表覆盖归一化植被指数植被覆盖度沙漠地区 NDVI 西藏南部气候因素

Biomass estimation and uncertainty analysis based on CBERS-02.CCD camera data and field measurement

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science china(Technological {2.) 2005年第S2期48卷 116-128页

作者： CHEN Liangfu1,2. GAO Yanhua1,3, CHENG Yu1,3, WEI Zheng1,3, XIAO Qing1,4, LIU Qinhuo1, YU Tao1, LIU Qijing5, GU Xingfa1 & TIAN Guoliang1 1. state key {2. of remote sensing science, institute of remote sensing Applications, chinese academy of sciences, {{12., china 2. Geography and Environment College, Jiangxi normal University, Nanchang 33002., china 3. Graduate University of chinese academy of sciences, beijing 100039, china 4. beijing Research institute of Uranium Geology, beijing 100875, china 5. institute of Geographic sciences and Natural Resources Research, chinese academy of sciences, {{12., china state key {2. of remote sensing science Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 China Geography and Environment College Jiangxi Normal University Nanchang 330027 China Graduate University Chinese Academy of Sciences Beijing 100039 China beijing Research institute of Uranium Geology Beijing 100875 China institute of Geographic sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China

The study site is located in Qianyanzhou experimental station and the surrounding area. Based on CBERS-02.satellite data and field measurement, we not only discussed the relationship between NDVI and biomass of two species of coniferous plantations, namely, Pinus massoniana Lamb and Pinus elliottii Engelm, but also introduced the biomass models based on NDVI. The comparison between measured biomass in Qianyanzhou and biomass derived from CBERS-02.CCD data showed that it is feasible to estimate biomass based on NDVI. But its limitations cannot be ignored. This kind of model depends on the dominant vegetation species. There are some effect factors in estimating biomass based on NDVI. This paper analyzes these factors based on fine-resolution CBERS-02.CCD data and some conclusions are drawn: In Qianyanzhou, the area with good vegetation coverage, the nonlinearity of NDVI has little influence on scaling-up of NDVI. As a result of surface heterogeneity, scaling-up can cause NDVI within each pixel to change. Because scaling-up can cause pixel attribute to change, the applicability of biomass model is one of the sources of error in estimating biomass.

关键词： NDVI biomass scaling effect scaling-up.

Cotton pixel identification with CBERS-02.CCD data based on spectral knowledge

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science china(Technological {2.) 2005年第S2期48卷 129-144页

作者： LI Jing1,2.3, LIU Qinhuo1,3, LIU Qiang1, CHEN Liangfu1, BO Junhua3 & LI Shaokun3 1. state key {2. of remote sensing science, IRSA, chinese academy of sciences, beijing 100101, china 2. Graduate University of chinese academy of sciences, beijing 100049, china 3. The key Oasis Eco-agriculture {2. of Xinjiang Production and Construction Corps, Shi Hezi 832.00, china state key {2. of remote sensing science IRSA Chinese Academy of Sciences Beijing 100101 China Graduate University Chinese Academy of Sciences Beijing 100049 China key Oasis Eco-agriculture laboratory Xinjiang Production and Construction Corps. Shi Hezi 832000 China

In this paper the in-situ experiment data are collected from the Spectral Library to estimate the possible values of the primary structural parameters in each cotton growing season by statistics. Based on these values the spectra of the cotton major growing seasons were simulated and analyzed using the canopy reflectance model, SAILH. In this way we also simulated the cotton pixel spectra corresponding to CBERS-02.CCD and took them as the reference spectra for spectra fitting. Then No.143 Regiment of No.8 Agricultural Division of Xinjiang Production and Construction Corps (XPCC) was chosen as the study area, and two spectra fitting methods, Mahalanobis distance and spectra angle, were used to identify cotton pixel from CBERS-02.CCD image of the study area. At last we analyzed the effect of the calibration coefficients error on cotton identifying. The results showed that within 4% error the spectral angle classifier can still have a good performance.

关键词： CBERS-02 cotton pixel identification spectra fitting.

Quantitative estimation of the shrub canopy LAI from atmosphere-corrected HJ-1 CCD data in Mu Us Sandland

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science china Earth {2. 2010年第S1期53卷 26-33页

作者： CHEN Wei1,2.CAO ChunXiang1,HE QiSheng1,2.GUO HuaDong3,ZHANG Hao1,2.LI RenQiang4,ZHENG Sheng1,2.XU Min1,2.GAO MengXu1,2.ZHAO Jian1,2.LI Sha1,NI XiLiang1,2.JIA HuiCong1,JI Wei1,TIAN Rong1,2.LIU Cheng1,2.ZHAO YuXing5 & LI JingLu6 1 state key {2. of remote sensing science,jointly sponsored by the institute of remote sensing Applications of chinese {{12. of sciences and beijing normal University,beijing 100101,china 2.Graduate University of chinese {{12. of sciences,beijing 100049,china 3 Center for Earth Observation and Digital Earth,chinese {{12. of sciences,beijing 100190,china 4 china key {2. of Ecological Network Observation and Modeling,institute of Geographical sciences and Natural Resources Research,chinese {{12. of sciences,beijing 100101,china 5 Ordos Forestry Sand Control science institute,Dongsheng 017000,china 6 Inner Mongolia Biomass Thermoelectricity Limited Company,Wushen 017300,china state key {2. of remote sensing science Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing China Graduate University of chinese academy of {2. Beijing China Center for Earth Observation and Digital Earth Chinese Academy of Sciences Beijing China china key {2. of Ecological Network Observation and Modeling Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China Ordos Forestry Sand Control science institute Dongsheng China Inner Mongolia Biomass Thermoelectricity Limited Company Wushen China

The leaf area index(LAI) is an important ecological parameter that characterizes the interface between vegetation canopy and the *** addition,it is used by most process-oriented ecosystem *** paper investigates the potential of HJ-1 CCD data combined with linear spectral unmixing and an inverted geometric-optical model for the retrieval of the shrub LAI in Wushen Banner of Inner Mongolia in the Mu Us ***(Moderate Resolution Atmospheric Radiance and Transmittance Model) was used for atmospheric *** was extracted using the threshold of the normalized difference vegetation index,with which water bodies and farmland were separated,in combination with a vegetation map of the People's Republic of china(1:1000000).Using the geometric-optical model,we derive the per-pixel reflectance as a simple linear combination of two components,namely sunlit background and *** fraction of sunlit background is related to the shrub *** the support of HJ-1 CCD data,we employ linear spectral unmixing to obtain the fraction of sunlit background in an atmospherically corrected HJ *** addition,we use the measured shrub canopy structural parameters for shrub communities to invert the geometric-optical model and retrieve the pixel-based shrub *** total,18 sample plots collected in Wushen Banner of Inner Mongolia are used for *** results of the shrub LAI show good agreement with R2.of 0.817 and a root-mean-squared error of 0.173.

关键词： shrub leaf area index inversion HJ-1 data geometric-optical model MODTRAN Mu Us Sandland

Absolute radiometric calibration of CBERS-02.IRMSS thermal band

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science china(Technological {2.) 2005年第S2期48卷 72-90页

作者： ZHANG Yong1,2.3, GU Xingfa1,3,4, YU Tao1,3, ZHANG Yuxiang5, CHEN Liangfu1,3, LI Xiaoying1,2.3, LI Xiaowen1,3 & HE Liming6 1. state key {2. of remote sensing science, jointly sponsored by the institute of remote sensing Applications of chinese {{12. of sciences and beijing normal University, beijing 100101, china 2. Graduate University of chinese {{12. of sciences, beijing 100039, china 3. The Center for National Spaceborne Demonstration, beijing 100101, china 4. Institut National de la Recherche Agronomique, Climat Sol Environnement, 84914 Avignon, France 5. National Satellite Meteorological Center, beijing 100081, china 6. state Environmental Protection Administration, beijing 10002., china state key {2. of remote sensing science Beijing Normal University Chinese Academy of Sciences Beijing 100101 China Graduate University Chinese Academy of Sciences Beijing 100039 China Center for National Spaceborne Demonstration Beijing 100101 China National Satellite Meteorological Center Beijing 100081 China Institut National de la Recherche Agronomique Climat Sol Environnement 84914 Avignon France state Environmental Protection Administration Beijing 100029 China

Based on the laboratory calibration before launch of CBERS-02.IRMSS thermal infrared channel, the onboard blackbody calibration, the radiometric cross- calibration against TERRA MODIS corresponding channel and the in-flight field calibration at Lake Qinghai: water surface radiometric calibration test site of china on Aug. 17, 2.04 are carried out in this research. When making onboard blackbody calibration of CBERS-02.IRMSS, it is necessary to understand inside structures and light path in IRMSS camera and receive and process calibration blackbody signals at {2. and high temperatures. Onboard blackbody calibration results of each detector are very important to relative radiometric calibration of images processing and absolute radiometric calibration of each detector. In-flight field calibration mainly contains field experiments, obtaining synchronous images, spectrum marching and MODTRAN radiative transmi- ssion computation. Radiometric cross-calibration of CBERS-02.IRMSS thermal band against TERRA MODIS selected 6 times synchronous images of two sensors passing through Lake Qinghai and Lake Taihu from August to December, 2.04 to compute the cross calibration data. Combining the in-flight field calibration and radiometric cross calibration data, the absolute radiometric calibration coefficients are calculated by the linear regression method. This new calibration model can obviously control the radiometric calibration uncertainties aroused by the single point method used in the in-flight calibration of CBERS-02.IRMSS, this kind of sensors cannot receive the cosmic background radiation. In this research, the radiometric calibration coefficients obtained through the linear regression model are 8.53 (gain, unit: DN/W m?2.r?1μm?1) and 44.92.(offset, unit: DN).

关键词： CBERS-02 IRMSS thermal band in-flight field calibration onboard blackbody calibration cross calibration.

Radiometric cross-calibration of the CBERS-02.CCD camera with the TERRA MODIS

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science china(Technological {2.) 2005年第S2期48卷 44-60页

作者： LI Xiaoying1,2.3, GU Xingfa1,3,4, MIN Xiangjun5, YU Tao1,3, FU Qiaoyan5, ZHANG Yong1,2.3 & LI Xiaowen1,3 1. state key {2. of remote sensing science, jointly sponsored by the institute of remote sensing Applications of chinese {{12. of sciences and beijing normal University, beijing 100101, china 2. Graduate University of chinese {{12. of sciences, beijing 100039, china 3. The Center for National Spaceborne Demonstration, beijing 100101, china 4. Institut National de la Recherche Agronomique, Climat Sol Environnement, 84914 Avignon, France 5. china Center for Resource Satellite Data and Application, beijing 100830, china state key {2. of remote sensing science Beijing Normal University Chinese Academy of Sciences Beijing 100101 China Graduate University Chinese Academy of Sciences Beijing 100039 China Center for National Spaceborne Demonstration Beijing 100101 China Institut National de la Recherche Agronomique Climat Sol Environnement 84914 Avignon France china Center for Resource Satellite Data and Application Beijing 100830 China

For the application of the CCD camera, the most important payload on CBERS-02. the key is to provide long-term stable radiometric calibration coefficients. Although the vicarious calibration had been proved successful, it had its limitations such as test site requirement and unsuitable for historical data. Cross-calibration is one of the alternative methods, but it needs synchro surface spectrum to achieve spectral band matching factors. Our effort is to probe the influences on these factors. Simulations with a lot of surface spectrum showed that the factors changed with the viewing geometry, atmospheric condition and surface targets. However, simulating with the same viewing geometry and atmospheric condition, the spectral band matching factors of the same or similar surface targets’ spectrum acquired from different dates and different places would like to be consistent to each other within 1%―5%. Thus, the synchro measurement data can be substituted by the same or similar target from other source. Based on this method, using the MODIS as the reference, the cross-calibration was performed for CCD camera. The research demonstrated that the traditional method with single calibration site was inappropriate for CCD camera, since the offsets for its four spectral bands were not zeros. With four calibration sites, these offsets were obtained. And the camera was detected to degrade with dates based on four times of cross-calibrations.

关键词： CBERS-02 CCD camera cross-calibration the spectral band matching factors.

The application of hyperspectral remote sensing to coast environment investigation

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Acta Oceanologica Sinica 2009年第2期28卷 1-13页

作者： ZHANG Liang ZHANG Bin CHEN Zhengchao ZHENG Lanfen TONG Qingxi state key {2. of remote sensing science Institute of Remote Sensing Applications Chinese Academy of Science Beijing 100101 China Naval institute of Hydrographic Surveying and Charting Tianjin 300061 China Center for Earth Observation and Digital Earth Chinese Academy of Science Beijing 100190 China

Requirements for monitoring the coastal zone environment are first summarized. Then the appli- cation of hyperspectral remote sensing to coast environment investigation is introduced, such as the classification of coast beaches and bottom matter, target recognition, mine detection, oil spill identification and ocean color remote sensing. Finally, what is needed to follow on in application of hyperspectral remote sensing to coast environment is recommended.

关键词： hyperspectral remote sensing coastal zone ocean color remote sensing