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Analysis of forest backscattering characteristics based on polarization coherence tomography

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 21 institute of Geo-Spatial Information science and Technology,University of Electronic science and Technology of{3.,Chengdu 610054,china 2 State key laboratory of remote Sensing science,Jointly Sponsored by the institute of remote Sensing applications of chinese Academy of {{13. and beijing Normal University,beijing 100101,china 3.0} 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{3.,Chengdu 610054,china State key Lab remote 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

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Cascade recursion models of computing the temperatures of underground layers

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science china(Technological sciences) 2006年第z2期49卷 30-38页

作者： HAN Liqun, BI Siwen & SONG Shixin School of Information Engineering, beijing Technology and Business University, beijing 10003., china State {3. laboratory of remote Sensing science, institute of remote Sensing applications, chinese Academy of sciences, beijing 100101, china beijing Technol & Business Univ Sch Informat Engn Beijing 100037 Peoples R China chinese Acad Sci Inst Remote Sensing Applicat State Key Lab Remote Sensing Sci Beijing 100101 Peoples R China

An RBF neural network was used to construct computational models of the underground temperatures of different layers, using ground-surface parameters and the temperatures of various underground layers. Because series recursion models also enable researchers to use above-ground surface parameters to compute the temperatures of different underground layers, this method provides a new way of using thermal infrared remote sensing to monitor the suture zones of large areas of blocks and to research thermal anomalies in geologic structures.

关键词： RBF network, underground temperature, modeling, cascade, recursion.

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Earth system multi-body restriction dynamics model research

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science china(Technological sciences) 2006年第z2期49卷 80-87页

作者： ZHANG Qingxian, BI Siwen& GONG Huili key laboratory of Three-Dimensional Information Acquisition and Application, Ministry of Education, Capital Normal University, beijing 10003.,{3. national key laboratory of remote Sensing science, institute of remote Sensing applications of chinese Academy of {{13., beijing 100101,{3. Capital Normal Univ Minist Educ Key Lab Dimens Informat Acquisit & Applicat 3 Beijing 100037 Peoples R China chinese Acad Sci Inst Remote Sensing Applicat Natl Key Lab Remote Sensing Sci Beijing 100101 Peoples R China

Research provides a theoretical basis for an Earth system multi-body mechanics model and its dynamics, including the Earth system multi-body restriction function and its power, Earth system multi-body restriction under decreasing generalized velocity and decreasing partial palstance, the Earth system multi-body decreasing generalized force, a moving mechanics function, and the Earth system multi-body restriction's wattful and wattless forces.

关键词： Earth system, multi-body restriction, dynamics model.

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Detection of the urban heat island in beijing using HJ-1B satellite imagery

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science china Earth sciences 2010年第S1期53卷 67-73页

作者： YANG Jun1,GONG Peng2,ZHOU JinXing3.HUANG HuaBing2 & WANG Lei2 1 key laboratory of Silviculture and Conservation,Ministry of Education,beijing Forestry University,beijing 100083.china 2 State key laboratory of remote Sensing science,jointly sponsored by the institute of remote Sensing applications,chinese Academy of {{13. and beijing Normal University,beijing 100101,china 3.institute of Desertification Studies,chinese Academy of Forestry,beijing 100091 china 1. key laboratory of Silviculture and Conservation Ministry of Education Beijing Forestry University Beijing 100083 China2. State Key Laboratory of Remote Sensing Science jointly sponsored by the Institute of Remote Sensing Applications Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China3. Institute of Desertification Studies Chinese Academy of Forestry Beijing 100091 China

Satellite images are used extensively in studying the urban heat island(UHI) *** evaluated the suitability of thermal infrared(TIR) data from the HJ-1B satellite for detecting UHI using a case study in *** modified algorithms for retrieving the land surface temperature(LST) from HJ-1B data were *** results were compared with LST images derived from a Landsat TM thermal band and the MODIS LST *** spatial pattern of UHI generated using HJ-1B data matched well with that produced using TM and MODIS *** the two algorithms,the mono-window algorithm performed better but further tests are *** more frequent coverage than TM and higher spatial resolution than MODIS,the HJ-1B TIR data present a unique opportunity to study thermal environments in cities in china and neighboring countries.

关键词： surface temperature NDVI mono-window algorithm single-channel algorithm

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A study on correlativity between Qinghai-Tibet Plateau thermal infrared remote sensing data and underground temperature

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science china(Technological sciences) 2006年第z2期49卷 114-120页

作者： HAN Liqun, BI Siwen & SONG Shixin School of Information Engineering, beijing Technology and Business University, beijing 10003., china {3. laboratory of remote Sensing Information sciences, institute of remote Sensing applications, chinese Academy of sciences, beijing 100101, china beijing Technol & Business Univ Sch Informat Engn Beijing 100037 Peoples R China chinese Acad Sci Inst Remote Sensing Applicat Key Lab Remote Sensing Informat Sci Beijing 100101 Peoples R China

Based on an analysis of the correlativity between Qinghai-Tibet Plateau thermal infrared remote sensing data (QPTIRSD) and underground temperature field distribution, the main factors which obviously influence underground-layer temperatures were derived. Using neural network technology, a model was built to compute underground temperatures via parameters out of the inversion of thermal infrared remote sensing (TIRS) and then analyze the correlativity between above-ground parameters and underground temperatures. This method offers a new way to apply TIRS in monitoring the suture zone of a large-area massif as well as to research structural thermal anomalies.

关键词： Qinghai-Tibet Plateau, TIRS, artificial neural network, temperature.

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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 laboratory of remote Sensing {3.,institute of remote Sensing applications,chinese Academy of sciences,beijing 100101,china 2 Zhejiang Climate Center,Hangzhou 3.0017,china 1. State key laboratory of remote Sensing {3. 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 400 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 25.2 W m-2,with a relative error of 5.9%.The root mean square error for accumulated daily PAR and observed values was 0.49 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

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Estimating forest aboveground biomass using HJ-1 Satellite CCD and ICESat GLAS waveform data

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science china Earth sciences 2010年第S1期53卷 16-25页

作者： GUO ZhiFeng1,CHI Hong1,2 & SUN GuoQing1,3.1State key laboratory of remote Sensing {3.,Jointly Sponsored by the institute of remote Sensing applications of chinese Academy of sciences and beijing Normal University,institute of remote Sensing applications,chinese Academy of sciences,beijing 100101,china 2Graduate University of chinese Academy of sciences,beijing 100049,china 3.epartment of Geography University of Maryland,College Park,MD 20742,USA 1. State key laboratory of remote Sensing {3. Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 China2. Graduate University of Chinese Academy of Sciences Beijing 100049 China3. Department of Geography University of Maryland College Park MD 20742 USA

The ecosystem in northeastern china and the Russian Far East is a hotspot of scientific research into the global carbon *** aboveground biomass(AGB) is an important component in the land surface carbon *** this study,using forest inventory data and forest distribution data,the AGB was estimated for forest in Daxinganlin in northeastern china by combining charge-coupled device(CCD) data from the Small Satellite for Disaster and Environment Monitoring and Forecast(HJ-1) and Geoscience Laser Altimeter System(GLAS) waveform data from the Ice,Cloud and land Elevation Satellite(ICESat).The forest AGB prediction models were separately developed for different forest types in the research area at GLAS footprint level from GLAS waveform parameters and field survey plot biomass in the Changqing(CQ) Forest Center,which was calculated from forest inventory *** resulted statistical regression models have a R2=0.68 for conifer and R2=0.71 for broadleaf *** models were used to estimate biomass for all GLAS footprints of forest located in the study *** GLAS footprint biomass coupled with various spectral reflectivity parameters and vegetation indices derived from HJ-1 satellite CCD data were used in multiple regression analyses to establish biomass prediction models(R2=0.55 and R2=0.52 for needle and broadleaf respectively).Then the models were used to produce a forest AGB map for the whole study area using the HJ-1 *** data obtained from forest inventory data of the Zhuanglin(ZL) Forest Center were used as independent field measurements to validate the AGB estimated from HJ-1 CCD data(R2=0.71).About 80% of biomass samples had an error less than 20 t ha-1,and the mean error of all validation samples is 5.74 t *** pixel-level biomass map was then stratified into different biomass levels to illustrate the AGB spatial distribution pattern in this *** was found that HJ-1 wide-swath data and GLAS waveform data can be combined to estim

关键词： Disaster and Environment Monitoring and Forecast Satellite ICESat GLAS waveform boreal forest forest aboveground biomass multiple linear regression

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Loose architecture of multi-level massive geospatial data based on virtual quadtree

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science china(Technological sciences) 2008年第S1期51卷 114-123页

作者： YANG ChongJun,WU Sheng,REN YingChao,FU Li,ZHANG FuQing,WANG Gang,TAN Jian,LIU DongLin,MA ChaoJi & LIANG Li State key laboratory of remote Sensing {3.,Jointly Sponsored by the institute of remote Sensing applications of chinese Academy of sciences and beijing Normal University,beijing 100101,china 1. State key laboratory of remote Sensing {3. Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China

This paper proposed a virtual quadtree (VQT) based loose architecture of multi-level massive geospatial data for integrating massive geospatial data dispersed in the departments of different hierarchies in the same sector into a unified GIS (Geographic Information System) platform. By virtualizing the nodes of the quad-tree,the VQT separates the structure of data organization from data storage,and screens the difference between the data storage in local computer and in the re-mote computers in network environment. And by mounting,VQT easily integrates the data from the remote computers into the local VQT so as to implement seam-less integration of distributed multi-level massive geospatial data. Based on that mode,the paper built an application system with geospatial data over 1200 GB distributed in 12 servers deployed in 12 cities. The experiment showed that all data can be seamlessly rapidly traveled and performed zooming in and zooming out smoothly.

关键词： massive geospatial data virtual quadtree loose architecture

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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 laboratory of remote Sensing {3.,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 100049,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 laboratory for remote Sensing of Environment and Digital Sites,beijing Normal University,beijing 100875,china State key laboratory of remote Sensing {3. 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 1546 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 ±20.9 cm.A data trap sizes of 4m 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

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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 100875,{3. 2 State key laboratory of remote Sensing science, chinese Academy of sciences, beijing 100101,{3. 3.institute of Erectronics, chinese Academy of sciences, beijing 100080,{3. 4 Center for for Assessment and Monitoring of Forest and Environmental Resources and Division of Ecosystem sciences University of California Berkeley, CA 94720-3.14, 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 {3. 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

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