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science china(Information sciences) 2011年第1期54卷 197-203页

作者： GENG XiuRui1,ZHAO YongChao1,LIU SuHong2 & WANG FuXiang3 1key Laboratory of Technology in Geo-spatial Information Processing and Application System, institute of Electronics,chinese academy of {4.,beijing 100080,china 2state key Laboratory of remote sensing science,Jointly Sponsored by beijing Normal University and the institute of remote sensing applications of{14., School of Geography,beijing Normal University,beijing 100875,china 3School of Electronics and Information Engineering,Beihang University,beijing 100191,china 1. key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing 100080 China2. State Key Laboratory of Remote Sensing Science Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing Applications of Chinese Academy of Sciences School of Geography Beijing Normal University Beijing 100875 China3. School of Electronics and Information Engineering Beihang University Beijing 100191 China

This paper gives the definition of the high-dimensional cross product and its calculation by extending the 3-D cross product definition into the high-dimensional vector *** on the properties of the cross product,the volume variance index(VVI)is proposed to be used in extracting automatically the endmembers of the hypherspectral imagery which eliminates the shortcoming of the traditional method of using simplex only where the extraction results were easily impacted by the abnormal pixels.A case study of endmembers extraction experiment using the VVI method with the AVIRIS data for Cuprite has shown a very good result.

关键词： endmember simplex hyperspectral imagery cross product

Retrieving crop leaf area index by assimilation of MODIS data into a crop growth model

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science china Earth sciences 2010年第5期53卷 721-730页

作者： WANG DongWei1,2,3, WANG JinDi1,2 & LIANG ShunLin4.1 state key Laboratory of remote sensing {4., Jointly Sponsored by beijing Normal University and institute of remote sensing applications, CAS, beijing 100875, china 2 School of Geography, beijing key Laboratory of Environmental remote sensing and Digital City, beijing Normal University, beijing 100875, china 3 Haihe River Water Conservancy Commission, Tianjin 300170, china 4.Department of Geography, University of Maryland, College Park, MD 2074., USA 1. state key Laboratory of remote sensing {4. Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications CAS Beijing 100875 China2. School of Geography Beijing Key Laboratory of Environmental Remote Sensing and Digital City Beijing Normal University Beijing 100875 China3. Haihe River Water Conservancy Commission Tianjin 300170 China4. Department of Geography University of Maryland College Park MD 20742 USA

Leaf area index (LAI) is an important parameter in monitoring crop growth. One of the methods for retrieving LAI from remotely sensed observations is through inversion of canopy reflectance models. Many model inversion methods fail to account for variable LAI values at different crop growth stages. In this research, we use the crop growth model to describe the LAI changes with crop growth, and consider a priori LAI values at different crop growth stages as constraint information. The key approach of this research is to assimilate multiple canopy reflectance values observed at different growth stages and a priori LAI values into a coupled crop growth and radiative transfer model sequentially using a variational data assimilation algorithm. Adjoint method is used to minimize the cost function. Any other information source can be easily incorporated into the inversion cost function. The validation results show that the time series of MODIS canopy reflectance can greatly reduce the uncertainty of the inverted LAI values. Compared with MODIS LAI product at Changping and Shunyi Counties of beijing, this method has significantly improved the estimated LAI temporal profile.

关键词： inversion leaf area index crop growth model time series MODIS

Automatic generalization of metro maps based on dynamic segmentation

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science china(Technological sciences) 2010年第S1期53卷 158-165页

作者： DONG WeiHua 1,TIAN Yuan 2 & ZHANG Yi 2 1 institute of Geography and remote sensing,beijing Normal University,beijing 100875,china 2 institute of remote sensing and Geographic Information System,Peking University,beijing 100871,china 1. institute of Geography and remote sensing Beijing Normal University Beijing 100875 China 2. institute of remote sensing and Geographic Information System Peking University Beijing 100871 China

A metro map is usually optimized for the readability of connections and transportation networks *** order to assure good readability and meet aesthetic considerations,a set of principles for good metro map layout are *** to these principles,a new methodology based on dynamic segmentation is presented to produce the metro maps ***,routes are constructed according to the line attribute similarity and geometry *** a set of cartographic generalization methods about the shape,angle,length,and topology are presented for these *** method is validated by beijing metro plan *** the experiment results,it can be concluded that this new method is more effective than the static segmentation method to produce metro maps with better readability for route plans.

关键词： metro maps generalization dynamic segmentation visualization

remote sensing based shrub above-ground biomass and carbon storage mapping in Mu Us desert,china

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science china(Technological sciences) 2010年第S1期53卷 176-183页

作者： XU Min 1,2,CAO ChunXiang 1,TONG QingXi 1,LI ZengYuan 3,ZHANG Hao 1,HE QiSheng 1,2,GAO MengXu 1,2,ZHAO Jian 1,2,ZHENG Sheng 1,2,CHEN Wei 1,2 & ZHENG LanFen 1 1state key Laboratory of remote sensing {4.,Jointly Sponsored by the institute of remote sensing applications of chinese academy of sciences and beijing Normal University,beijing 100101,china 2 Graduate School of the chinese academy of sciences,beijing 10004.,china 3 Research {14. of Forest Resources and Information Techniques,chinese academy of Forestry,beijing 10009,china 1. state key Laboratory of remote sensing {4. Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China 2. Graduate School of the chinese academy of sciences Beijing 100049 China 3. Research institute of Forest Resources and Information Techniques Chinese Academy of Forestry Beijing 10009 China

The estimation of above-ground biomass(AGB) and carbon storage is very important for arid and semi-arid ***-1A/B satellite data combined with field measurement data was used for the estimation of shrub AGB and carbon storage in the Mu Us desert,*** correlations of shrub AGB and spectral reflectance of four bands as well as their combined vegetation indexes were respectively analyzed and stepwise regression analysis was employed to establish AGB prediction *** prediction equation based on ratio vegetation index(RVI)was proved to be more suitable for shrub AGB estimation in the Mu Us desert than *** AGB and carbon storage were mapped using the RVI based prediction model in *** statistics showed the western Mu Us desert has relatively high AGB and carbon storage,and that the gross shrub carton storage in Mu Us desert reaches 16 799 200 t,which has greatly contributed to the carbon fixation in northern china.

关键词： above-ground biomass carbon storage Mu Us desert HJ-1A/B remote sensing

Absolute radiometric calibration of CBERS-02 IRMSS thermal band

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science china(Technological sciences) 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 Laboratory of remote sensing {4., Jointly Sponsored by the institute of remote sensing applications of chinese academy of sciences and beijing Normal University, beijing 100101, china 2. Graduate University of chinese academy 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, 84.14.Avignon, France 5. National Satellite Meteorological Center, beijing 100081, china 6. state Environmental Protection Administration, beijing 100029, china chinese Acad Sci Inst Remote Sensing Applicat State Key Lab Remote Sensing Sci Beijing 100101 Peoples R China beijing Normal Univ State Key Lab Remote Sensing Sci Beijing 100101 Peoples R China chinese Acad Sci Grad Univ Beijing 100039 Peoples R China Ctr Natl Spaceborne Demonstrat Beijing 100101 Peoples R China INRA F-84914 Avignon France Natl Satellite Meteorol Ctr Beijing 100081 Peoples R China state Environm Protect Adm Beijing 100029 Peoples R 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, 2004.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 normal 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, 2004.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?2sr?1μm?1) and 4..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 sciences) 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 Laboratory of remote sensing {4., Jointly Sponsored by the institute of remote sensing applications of chinese academy of sciences and beijing Normal University, beijing 100101, china 2. Graduate University of chinese academy 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, 84.14.Avignon, France 5. china Center for Resource Satellite Data and Application, beijing 100830, china 1. state key Laboratory of remote sensing {4. Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University 100101 Beijing China 2. Graduate University of chinese academy of sciences 100039 Beijing China 3. The Center for National Spaceborne Demonstration 100101 Beijing China 4. Institut National de la Recherche Agronomique Climat Sol Environnement 84914 Avignon France 5. china Center for Resource Satellite Data and Application 100830 Beijing 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.

Spatial prediction and analysis of Himalayan marmot plague natural epidemic foci in china based on HJ-1 satellite data

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science china Earth sciences 2010年第S1期53卷 8-15页

作者： GAO MengXu1,4.LI XiaoWen1,2,CAO ChunXiang1,ZHANG Hao1,LI Qun3,ZHOU Hang3 HE QiSheng1,4.XU Min1,4.ZHAO Jian1,4.ZHENG Sheng1,4.& CHEN Wei1,4.1state key Laboratory of remote sensing {4.,Jointly Sponsored by the institute of remote sensing applications of chinese academy of sciences and beijing Normal University,beijing 100101,china 2School of Geography,beijing Normal University,beijing 100875,china 3Office for Disease Control and Emergency Response,{14. Center for Disease Control and Prevention,beijing 102206,china 4.raduate University of chinese academy of sciences,beijing 10004.,china 1. state key Laboratory of remote sensing {4. Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China4. Graduate University of Chinese Academy of Sciences Beijing 100049 China2. School of Geography Beijing Normal University Beijing 100875 China3. Office for Disease Control and Emergency Response Chinese Center for Disease Control and Prevention Beijing 102206 China

Plague,caused by the gram-negative bacterium Yersinia pestis,is a serious and rapidly progressing illness in humans that can be fatal if not treated *** Qinghai-Tibet Plateau is the largest area of natural Himalayan marmot(Marmota himalayana) plague foci in china and covers more than 630000 *** County in Gansu Province is a part of this natural focus of plague and was chosen as a study *** study used an ecological niche modeling(ENM) approach to predict the potential distribution of the Himalayan *** and Disaster Monitor Satellite(HJ-1) data was used to investigate environment factors that affect plague host animal *** animal point data from active surveillance was combined with environmental variables from the HJ-1 satellite and other databases,and the models of the potential distribution of Himalayan marmot were produced with the Genetic Algorithm for Rule-Set Production(GARP).The probability of marmot presence was divided into 0-5%,5%-20%,20%-4.%,4.%-80%,and 80%-100% *** with 80%-100% probability exhibited the greatest potential for the presence of Himalayan *** to the predicted potential distribution of Himalayan marmot in the study area,active surveillance of plague hosts and plague control and prevention could be more efficient.

关键词： Himalayan marmot plague spatial prediction GARP HJ-1 satellite

The correlation of multi-angle thermal infrared data and the choice of optimal view angles

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science china Earth sciences 2004年第6期47卷 570-576页

作者： FAN Wenjie1 & XU Xiru1,2 1.institute of remote sensing and GIS of Peking University,beijing 100871,{4. 2.Center of remote sensing and GIS of beijing Normal University,beijing 100875,{4. 1. institute of remote sensing and GIS of Peking University 100871 Beijing China 2. Center of remote sensing and GIS of beijing Normal University 100875 Beijing China

Based on the matrix formula of thermal infrared radiant system, the components temperature can be retrieved by the inversive matrix. Around the stability problem of retrieved result, the research work we did was focused on (i) the correlation of (wk,j) which is the key to affect the retrieval accuracy, (ii) a general method which can help us find the number of retrievable parameters and evaluate the retrieval error before its performance, (iii) the choice of “optimal viewing angle group” based on the formula of absolute error propagation. The row winter wheat field was chosen as an example. The results can provide a theoretical basis for multi-angle thermal infrared remote sensing and components temperature retrieval.

关键词： components temperature retrieval, correlation, number of retrievable parameters, optimal viewing angle group.

Integrative inversion of land surface component temperature

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science china Earth sciences 2005年第11期48卷 2011-2019页

作者： FAN Wenjie1 & XU Xiru1,2 1. institute of remote sensing and Geographical Information System, Peking University, beijing 100871,{4. 2. Center of remote sensing and GIS of beijing Normal University, beijing 100875,{4. 1. institute of remote sensing and Geographical Information System Peking University 100871 Beijing China 2. Center of remote sensing and GIS of beijing Normal University 100875 Beijing China

In this paper, the row winter wheat was selected as the example to study the com-ponent temperature inversion method of land surface target in detail. The result showed that the structural pattern of row crop can affect the inversion precision of component temperature evi-dently. Choosing appropriate structural pattern of row crop can improve the inversion precision significantly. The iterative method combining inverse matrix was a stable method that was fit for inversing component temperature of land surface target. The result of simulation and field ex-periment showed that the integrative method could remarkably improve the inversion accuracy of the lighted soil surface temperature and the top layer canopy temperature, and enhance inver-sion stability of components temperature. Just two parameters were sufficient for accurate at-mospheric correction of multi-angle and multi-spectral thermal infrared data: atmospheric trans-mittance and the atmospheric upwelling radiance. If the atmospheric parameters and component temperature can be inversed synchronously, the really and truly accurate atmospheric correction can be achieved. The validation using ATSRII data showed that the method was useful.

关键词： components temperature, inverse pattern, atmospheric correction

A method for blind separation of components information from mixed pixel

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Progress in Natural science:Materials International 2006年第07期16卷 760-765页

作者： FAN Wenjie and XU Xiru ( institute of remote sensing and Geographical Information System, Peking University, beijing 100871,{4. Center of remote sensing and GIS of beijing Normal University, beijing 100875,{4.) [a]institute of remote sensing and Geographical Information System Peking University Beijing China [b]Center of remote sensing and GIS of beijing Nornal University Beijing China

In the field of remote sensing, it is important to separate the component information from mixed pixel. If the physical process of remote sensing can be expressed by a set of linear equations, the remote sensing information matrix is equal to the weight matrix multiplied by the component information matrix. Generally speaking, the precondition of retrieval of component information matrix is that the weight matrix is known. However, the blind signal separation (BSS) method can separate the matrix unconditionally, whose basic principle is that the additive information needing separation can be achieved from the statistical characteristics contained in a mass of samples in the remotely sensed information matrix. Therefore, the values of the component information matrix and the weight matrix can be estimated. The wave shape of components can be retrieved by BSS, but the amplitude cannot. In this paper, the plant-soil mixed pixels were chosen as the studying targets in this paper to quantitatively separate the component information and solve the uncertainty of BSS. Simulation and field test verify the reliability of the method. Results show that the BSS can be one of the effective methods of mixed pixel separation, and the foreground of application is very promising.

关键词： mixed pixel component information blind signal separation.