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science china(Technological sciences) 2010年第S1期53卷 7-14页

作者： SUN KaiMin1,SUI HaiGang1,2.LI DeRen1 & XU Chuan1,2.1 state key {2. of Information Engineering in Surveying,Mapping and remote sensing,Wuhan University,Wuhan 4.0079,china 2.state key {2. of Subtropical Building science,South china University of Technology,Guangzhou 51064.,china 1. state key {2. of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan 430079 China 2. state key {2. of Subtropical Building {4. South China University of Technology Guangzhou 510640 China

The research purpose of this paper is to show the limitations of the existing radiometric normalization approaches and their disadvantages in change detection of artificial objects by comparing the existing approaches,on the basis of which a preprocessing approach to radiometric consistency,based on wavelet transform and a spatial low-pass filter,has been *** approach first separates the high frequency information and low frequency information by wavelet ***,the processing of relative radiometric consistency based on a low-pass filter is conducted on the low frequency *** processing,an inverse wavelet transform is conducted to obtain the results *** experimental results show that this approach can substantially reduce the influence on change detection of linear or nonlinear radiometric differences in multi-temporal images.

关键词： wavelet transform radiometric normalization low-pass filter change detection

Development of environmental monitoring satellite systems in china

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science china Earth sciences 2010年第S1期53卷 1-7页

作者： LI GuoPing1 & CAO ChunXiang2.1 School of Earth and Space sciences,Peking University,Beijing 100871,china 2.{2. key laboratory of remote sensing science,Jointly Sponsored by the Institute of remote sensing Applications of Chinese Academy of sciences and Beijing Normal University,Beijing 100101,china 1. School of Earth and Space sciences Peking University Beijing 100871 China2. State Key Laboratory of Remote Sensing Science Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China

With the increase in global environmental problems,the necessity and urgency of remote sensing technology being applied to environmental monitoring has been widely recognized around the *** has launched the environment and disaster monitoring and forecasting small satellite constellation HJ-1A/B and the FY3 atmosphere and environmental satellite,but they still cannot fully satisfy requirements for environmental *** paper summarizes the current status of satellite environmental monitoring in{2. and the existing problems of inadequate load design and low data utilization efficiency,and discusses the demand for environmental monitoring *** on the development of foreign satellite systems for environmental monitoring,the future development and key tasks of the environmental monitoring satellite system in{2. is discussed,as are some related initiatives.

关键词： environmental satellite environmental monitoring global climate change specialty load satellite system

Photosynthetically active radiation retrieval based on HJ-1A/B satellite data

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science china Earth sciences 2010年第S1期53卷 81-91页

作者： LI Li1,XIN XiaoZhou1,SU GaoLi1,2.& LIU QinHuo1 1 state key {2. of {4. sensing science,Institute of {4. sensing Applications,Chinese Academy of sciences,Beijing 100101,china 2.Zhejiang Climate Center,Hangzhou 310017,china 1. state key {2. of remote {4. science Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 China2. Zhejiang Climate Center Hangzhou 310017 China

Photosynthetically active radiation(PAR) is essential for plant photosynthesis and carbon cycle,and is also important for meteorological and environmental *** advance china's disaster and environmental monitoring capabilities,the HJ-1A/B satellites have been placed in Earth *** of their environmental monitoring objectives is the study of *** simulated direct solar,scattered and environment radiation between 4.0 and 700 nm under different atmospheric parameters(solar zenith angle,atmospheric water vapor,atmospheric ozone,aerosol optical thickness,surface elevation and surface albedo),and then established a look-up table between these input parameters and *** on the look-up table,we used HJ-1A/B aerosol and surface albedo outputs to derive the corresponding *** of inversed instantaneous and observed PAR values using HJ-1 Heihe experimental data had a root mean square error of 2..2.W m-2.with a relative error of 5.9%.The root mean square error for accumulated daily PAR and observed values was 0.4. MJ m-2.with a relative error of 3.5%.Our approach improved significantly the computational efficiency,compared with using directly radiation transfer *** also studied the sensitivity of various input parameters to photosynthetically active radiation,and found that solar zenith angle and atmospheric aerosols were sensitive PAR *** albedo had some effect on PAR,but water vapor and ozone had minimal impact on PAR.

关键词： Photosynthetically active radiation 6S HJ-1A/B satellites

Scale effects of leaf area index inversion based on environmental and disaster monitoring satellite data

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science china Earth sciences 2010年第S1期53卷 92-98页

作者： ZHANG Hao1,LI XiaoWen1,2.CAO ChunXiang1,YANG Hua2.GAO MengXu1,3,ZHENG Sheng1,3,XU Min1,3,XIE DongHui2.JIA HuiCong1,JI Wei1,ZHAO Jian1,3,CHEN Wei1,3 & NI XiLiang1,3 1 state {4. {2. of remote sensing science,Jointly Sponsored by Institute of remote sensing Applications,Chinese Academy of sciences and Beijing Normal University,Beijing 100101,china 2.state {4. {2. of remote sensing science,Jointly Sponsored by Beijing Normal University and Institute of remote sensing Applications of Chinese Academy of sciences,Beijing 100875,china 3 Graduate University of Chinese Academy of sciences,Beijing 10004.,china 1. state key {2. of remote {4. science Jointly Sponsored by Institute of Remote Sensing Applications Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China2. State Key Laboratory of Remote Sensing Science Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications of Chinese Academy of Sciences Beijing 100875 China3. Graduate University of Chinese Academy of Sciences Beijing 100049 China

The spatial distribution of sub-pixel components has an impact on retrieval accuracy,and should be accounted for when inverting a three-dimensional adiative transfer model to retrieve leaf area index(LAI).To investigate this effect,we constructed three realistic scenarios with the same LAI values and other properties,except that the simulated plants had different *** implemented the radiosity method to subsequently produce synthetic bidirectional reflectance factor(BRF) datasets based upon these simulated *** inversion was conducted using these data,which showed that spatial distribution affects retrieval *** inversion was also conducted for LAI based on charge-coupled device(CCD) data from the Environment and Disaster Monitor Satellite(HJ-1),which depicted both forest and drought-resistant crop land *** showed that heterogeneity in coarse-resolution remote sensing data is the main error source in LAI *** spatial distribution of global fractal dimension index,which can be used to describe the area of sub-pixel components and their spatial distribution modes,shows good consistency with the coarse resolution LAI inversion error.

关键词： HJ-1 leaf area index scale effect spatial distribution

Analysis of forest backscattering characteristics based on polarization coherence tomography

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science china(Technological sciences) 2010年第S1期53卷 166-175页

作者： LUO HuanMin 1,LI XiaoWen 1,2.CHEN ErXue 3,CHENG Jian 4.& CAO ChunXiang 2. Institute of Geo-Spatial Information science and Technology,University of Electronic science and Technology of{2.,Chengdu 610054.china 2.state key laboratory of remote sensing science,Jointly Sponsored by the Institute of remote sensing Applications of Chinese Academy of sciences and Beijing Normal University,Beijing 100101,china 3Institute of Forest Resources Information Technique of Chinese Academy of Forestry,Beijing 100091,china 4.School of Electronic Engineering,University of Electronic science and Technology of{2.,Chengdu 610054.china state key Lab {2. sensing Sci Beijing 100101 Peoples R China Beijing Normal Univ Beijing 100101 Peoples R China Univ Elect Sci & Technol china Inst Geospatial Informat Sci & Technol Chengdu 610054 Peoples R China Chinese Acad Forestry Inst Forest Resources Informat Tech Beijing 100091 Peoples R China Univ Elect Sci & Technol china Sch Elect Engn Chengdu 610054 Peoples R China

It is difficult to make an inventory of vertical profiles of forest structure parameters in field ***,analysis and understanding of forest backscattering characteristics contribute to estimation and detection of forest vertical structure because of the close relationships between backscattering characteristics and structure *** vertical structure function in the complex interferometric coherence definition,which represents the vertical variation of microwave scattering with the penetration depth at a point in the 2.D radar image and can be used to analyze the forest backscattering characteristics,can be reconstructed from polarization coherence tomography(PCT).Based on PCT,the paper analyzes the forest backscattering characteristics and explores the inherent relationship between the result of PCT and the forest structure parameters from numerical simulation of Random Volume over Ground model(RVoG),Polarimetric SAR interferometry(PolInSAR)simulation of forest scene and PolInSAR data at L-band of the test site ***,the effects of the extinction coefficient and surface-to-volume scattering ratio in RVoG model on vertical backscattering characteristics are analyzed by means of numerical ***,by applying PCT to L-band POLInSAR simulations of forest scene,different variations of vertical backscattering due to different extinction coefficients and the ratios of surface-to-volume scattering resulting from different polarizations,forest types and densities are displayed and *** a concept of relative average backscattering intensity is presented,and the factors which affect its vertical distribution are also *** results show that there is high sensitivity of the vertical distribution of forest relative average backscattering intensity to the polarization,forest type and ***,based on repeat pass DLR E-SAR L-band airborne POLInSAR data,the capability of PCT technology for detection

关键词： backscattering characteristic POLInSAR PCT vertical structure function

Principle of small target detection for hyperspectral imagery

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science china Earth sciences 2007年第8期50卷 1225-1231页

作者： GENG XiuRui1,2.3 & ZHAO YongChao2.3,4.1 Research Center for remote sensing and GIS, Department of Geography, Beijing Normal University, Beijing {2., china 2.state key laboratory of remote sensing science, Chinese Academy of sciences, Beijing 100101, china 3 Institute of Erectronics, Chinese Academy of sciences, Beijing 100080, china 4.Center for for Assessment and Monitoring of Forest and Environmental Resources and Division of Ecosystem sciences University of California Berkeley, CA 94.2.-3114. USA 1. Research Center for remote sensing and GIS Department of Geography Beijing Normal University Beijing 100875 China 2. state key laboratory of remote sensing science Chinese Academy of Sciences Beijing 100101 China 3. Institute of Erectronics Chinese Academy of Sciences Beijing 100080 China 4. Center for for Assessment and Monitoring of Forest and Environmental Resources and Division of Ecosystem sciences University of California Berkeley CA 94720-3114 USA

This paper generalizes the progress of algorithms in small target detection for hyperspectral imaging, and finds that whitening the image is the key point of many methods in small target detection. An al-gorithm is presented to detect desired targets by converting large targets into small ones based on the weighted sample autocorrelation matrix.

关键词： hyperspectral whiten target detection

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,{2. 2. Center of remote sensing and GIS of Beijing Normal University, Beijing 100875,{2. 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

Synchronous estimation of DTM and fractional vegetation cover in forested area from airborne LIDAR height and intensity data

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science china(Technological sciences) 2008年第S2期51卷 176-187页

作者： BAO YunFei1,2.CAO ChunXiang1,ZHANG Hao1,CHEN ErXue3,HE QiSheng1,2.HUANG HuaBing1,LI ZengYuan3,LI XiaoWen1,4.& GONG Peng1 1 state key {2. of remote sensing science,jointly sponsored by the Institute for remote sensing Applications of Chinese Academy of sciences and Beijing Normal University,Beijing 100101,china 2.Graduate University of the Chinese Academy of sciences,Beijing 10004.,china 3 Institute of Forest Resource Information Technique,the Chinese Academy of Forestry,Beijing 100091,china 4.Research Center for remote sensing and GIS,Department of Geography and Beijing key {2. for remote sensing of Environment and Digital Sites,Beijing Normal University,Beijing 100875,china state key {2. of remote {4. science jointly sponsored by the Institute for Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China Graduate University of the Chinese Academy of sciences Beijing 100049 China Institute of Forest Resource Information Technique the Chinese Academy of Forestry Beijing 100091 China Research Center for remote sensing and GIS Department of Geography and Beijing Key Laboratory for Remote Sensing of Environment and Digital Sites Beijing Normal University Beijing 100875 China

We proposed a method to separate ground points and vegetation points from discrete return,small footprint airborne laser scanner data,called skewness change *** method,which makes use of intensity of laser scanner data,is especially applicable in steep,and forested *** does not take slope of forested area into account,while other algorithms consider the change of slope in steep forested *** ground points and vegetation points can be used to estimate digital terrain model(DTM) and fractional vegetation cover,respectively.A few vegetation points which were classified into the ground points were removed as noise before the generation of *** method was tested in a test area of 10000 square meters.A LiteMapper -5600 laser system was used and a flight was carried out over a ground of 700―800 *** this tested area,a total number of 154. field measurement ground points were measured with a total station TOPCON GTS-602.and TOPCON GTS -7002.for validation of DTM and the mean error value is -18.5 cm and the RMSE(root mean square error) is ±2..9 cm.A data trap sizes of 4. in diameter from airborne laser scanner data was selected to compute vegetation fraction *** of fractional vegetation cover was carried out using 15 hemispherical photographs,which are georeferenced to centimeter accuracy by differential *** gap fraction was computed over a range of zenith angles 10° using the gap light analyzer(GLA) from each hemispherical *** R2.for the regression of fractional vegetation cover from these ALS data and the respective field measurements is *** this study presents a method for synchronous estimation of DTM and fractional vegetation cover in forested area from airborne LIDAR height and intensity data.

关键词： LIDAR intensity skewness synchronous DTM fractional vegetation cover

Latent ancestral graph of structure vector autoregressive models

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Journal of Systems Engineering and Electronics 2010年第2期21卷 233-238页

作者： Wei Gao1,2.nd Zheng Tian2.3 1.School of Statistics,Xi’an University of Finance&Economics,Xi’an 710061,P.R.china 2.Department of Applied Mathematics,Northwestern Polytechnical University,Xi’an 710072.P.R.china 3.{2. key laboratory of remote sensing science,Institute of remote sensing Applications,Chinese Academy of sciences,Beijing 100101,P.R.china School of Statistics Xi'an University of Finance & EconomicsXi'an 710061P.R.China Department of Applied Mathematics Northwestern Polytechnical UniversityXi'an 710072P.R.China Department of Applied Mathematics Northwestern Polytechnical UniversityXi'an 710072P.R.China state key {2. of remote {4. science Institute of Remote Sensing ApplicationsChinese Academy of SciencesBeijing 100101P.R.China

A class of latent ancestral graph for modelling the dependence structure of structural vector autoregressive （VAR） model affected by latent variables is proposed. The graphs are mixed graphs with possibly two kind of edges, namely directed and bidirected edges. The vertex set denotes random variables at dif- ferent times. In Gaussian case, the latent ancestral graph leads to a simple parameterization model. A modified iterative conditional fitting algorithm is presented to obtain maximum likelihood esti- mation of the parameters. Furthermore, a log-likelihood criterion is used to select the most appropriate models. Simulations are performed using illustrative examples and results are provided to demonstrate the validity of the methods.

关键词： multivariate time series latent ancestral graph itera- tive conditional fitting.

The quantification of remote sensing

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science china(Technological sciences) 2005年第S2期48卷 1-11页

作者： GU Xingfa1,2.3,TIAN Guoliang1,2. LI Xiaowen1,2.& GUO Jianning4.1. state {4. {2. of remote sensing science, Jointly Sponsored by the Institute of remote sensing Applications of Chinese Academy of sciences and Beijing Normal University, Beijing 100101, china 2. The Center for National Spaceborne Demonstration, Beijing 100101, china 3. Institut National de la Recherche Agronomique, Climat Sol Environnement, 84.14.Avignon, France 4. china Center for Resource Satellite Data and Application, Beijing 100830, 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 Ctr Natl Spaceborne Demonstrat Beijing 100101 Peoples R China Inst Natl Rech Agron F-84914 Avignon France china Ctr Resource Satellite Data & Applicat Beijing 100830 Peoples R China

The paper firstly defined the remote sensing information quantification, analyzed the necessity of developing remote sensing quantification, figured out the application guidelines requirement, and pointed out the importance of quantification research. Then taking the remote sensing application research of CBERS-02.data quantification as the example, the paper described the whole quantification system of “remotely sensed digital signal-radiation information-field parameter inversion”. Finally the paper gave the prospect for the development trend of the quantitative remote sensing.

关键词： remote sensing information quantification CBERS-02 radiometric calibration surface parame- ter reversion.