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Monitoring of rice crop using ENVISAT ASAR data

Science china Earth Sciences 2006年第7期49卷 755-763页

作者： DONG Yanfang1, 2, SUN Guoqing1,3 & PANG Yong4.1. State Key laboratory of remote sensing Science, Institute of remote sensing Applications, Chinese Academy of Sciences, beijing 100101, china 2. Graduate University of Chinese Academy of Sciences, beijing 100039, china 3. Department of Geography, University of Maryland, College Park, MD 2074., USA 4. forest remote sensing lab, Research Institute of forest Resource and Information Technology, Chinese Academy of For-estry, beijing 100091, china 1. State Key laboratory of remote sensing Science Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 China 2. Graduate University of Chinese Academy of Sciences Beijing 100039 China 3. Department of Geography University of Maryland College Park MD 20742 USA 4. forest remote sensing lab Research Institute of Forest Resource and Information Technology Chinese Academy of Forestry Beijing 100091 China

Because of the cloudy conditions during the rice growth period, rice is one of the agri-cultural crops most suited to monitoring with the SAR instruments. Backscatter response measured by SAR is correlated with rice conditions, including height, density, biomass and structure, which are variable at different growing stages. In this paper, multi-date ENVISAT ASAR Alternating Polarization Mode (APMode) imageries were acquired during the rice crop growing cycle. At the same time, the rice parameters were measured in field. A continuous canopy model was used to compute the back-scattering from rice fields during the growth cycle, and the relationship between rice parameters and radar backscattering coefficients from both ASAR and modeling was analyzed. The effects of polari-zation, incidence angle and polarization on radar backscattering coefficients were analyzed. It was found that simulated radar backscatter has similar trends as ASAR data. This will be meaningful for the further research of rice parameters estimation from ASAR data. Different features show signifi-cantly different signatures in ASAR images and they follow some certain laws, so rice area can be accurately mapped by using multi-temporal SAR images, then rice yield can be estimated.

关键词： rice, ASAR, radar backscattering, model.

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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 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 {13.,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 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 ±20.9 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

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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 21 Institute of Geo-Spatial Information Science and Technology,University of Electronic Science and Technology of china,Chengdu 610054.china 2 State Key laboratory of remote {4. Science,Jointly Sponsored by the Institute of remote {4. 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 {13.,china 4.School of Electronic Engineering,University of Electronic Science and Technology of china,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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Study on NDVI-T_s space by combining LAI and evapotranspiration

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Science china Earth Sciences 2006年第7期49卷 747-754页

作者： HAN Lijuan1,2,3, WANG Pengxin4. YANG Hua1,2,3, LIU Shaomin1,2,3 & WANG Jindi1,2,3 1. Research Center for remote sensing and GIS, School of Geography, beijing Normal University, beijing 100875,{4. 2. State Key laboratory of remote sensing Science, beijing 100875,{4. 3. beijing Key laboratory for remote sensing of Environment and Digital Cities, beijing 100875,{4. 4. Department of Information Management, College of Information and Electronic Engineering,{4. Agricultural University, beijing 100083,{4. 1. Research Center for remote sensing and GIS School of Geography Beijing Normal University Beijing 100875 China 2. State Key laboratory of remote sensing Science Beijing 100875 China 3. beijing Key laboratory for remote sensing of Environment and Digital Cities Beijing 100875 China 4. Department of Information Management College of Information and Electronic Engineering China Agricultural University Beijing 100083 China

This paper focuses on interpreting the different spatial relationships between NDVI and Ts, a triangular or a trapezoid, and on analyzing transformation conditions, the physical and ecological meanings of the vegetation index-surface temperature space as well. Further, we use the Tempera-ture-Vegetation Dryness Index (TVDI) to explain the existent meaning of a triangular space after NDVI reaches its saturated state by employing the relationships between NDVI, LAI and evapotranspiration. The specific relations between NDVI and Ts are useful for describing, validating and updating land surface models.

关键词： NDVI, land surface temperature, evapotranspiration, leave area index.

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Estimating surface evapotranspiration using combined MODIS and CBERS-02 data

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Science china(Technological Sciences) 2005年第S2期48卷 145-160页

作者： XIN Xiaozhou1,2, LIU Qinhuo1, TANG Yong1,3, TIAN Guoliang1, GU Xingfa1, LI Xiaowen1,2, ZHENG Hongsheng4.& CHEN Jiayi4.1. State Key laboratory of remote sensing Science, Institute of remote sensing Applications, Chinese Academy of Sciences, beijing 100101, china 2. Research Center for remote sensing and GIS, Department of Geography, beijing Normal University, beijing 100875, china 3. Graduate University of Chinese Academy of Sciences, beijing 100039, china 4. Department of Atmospheric Physics, Peking University, beijing 100871, china 1. State Key laboratory of remote sensing Science Institute of Remote Sensing Applications Chinese Academy of Sciences 100101 Beijing China2. Research Center for Remote Sensing and GIS Department of Geography Beijing Normal University 100875 Beijing China3. Graduate University of Chinese Academy of Sciences 100039 Beijing China4. Department of Atmospheric Physics Peking University 100871 Beijing China

Spatial scale error is one of the most serious problems in the estimates of land surface heat fluxes of sensible and latent from satellite-borne data such as MODIS 1km resolution reflectance and emissive data. One of the feasible and economic ways to decrease the spatial scale error is to use high resolution land use class data together with the MODIS data. CBERS-02 data were used to produce land use class of Baiyangdian area, Hebei Province, china in the autumn of 2004. The area ratio of each class in MODIS pixel was calculated, and used to derive the heat fluxes of the mixed pixel. The results showed that the estimated heat fluxes of soil, sensible and latent have been changed remarkably after using the high resolution land class data. It could be concluded from the comparison between simulated and ground-measured fluxes as well as the theoretical analysis that high resolution land class data are useful to diminishing the scale error of heat fluxes estimated from low resolution satellite data.

关键词： surface evapotranspiration spatial scale error MODIS CBERS land class.

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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,{4. 2 State Key laboratory of remote sensing Science, Chinese Academy of Sciences, beijing 100101,{4. 3 Institute of Erectronics, Chinese Academy of Sciences, beijing 100080,{4. 4.Center for for Assessment and Monitoring of forest and Environmental Resources and Division of Ecosystem Sciences University of California Berkeley, CA 94.20-3114. 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

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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 Science, 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 Science 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

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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 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 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.

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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 100037, china Key laboratory of {4. sensing Information Sciences, Institute of {4. 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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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 100037, china State Key laboratory of {4. sensing Science, Institute of {4. 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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