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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 {2.) 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 {3. {2. science,jointly sponsored by the institute for {3. {2. applications of chinese {13. of {12. and beijing normal university,beijing 100101,china 2.Graduate university of the chinese {13. of {12.,beijing 100049,china 3.institute of Forest Resource Information Technique,the chinese {13. of Forestry,beijing 100091,china 4 Research Center for {3. {2. and GIS,Department of Geography and beijing key Laboratory for {3. {2. of Environment and Digital Sites,beijing normal university,beijing 100875,china State key Laboratory of remote {2. {3. jointly sponsored by the Institute for Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing China Graduate university of the chinese {2. of {3. Beijing China institute of Forest Resource Information Technique the Chinese Academy of Forestry Beijing 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 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 ±2..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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Estimating surface evapotranspiration using combined MODIS and CBERS-02.data

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science china(Technological {2.) 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 {3. {2. science, institute of {3. {2. applications, chinese academy of sciences, {13., {12. 2. Research Center for {3. {2. and GIS, Department of Geography, beijing normal university, beijing 100875, {12. 3. Graduate university of chinese academy of sciences, beijing 10003., {12. 4. Department of Atmospheric Physics, Peking university, beijing 100871, {12. State key Laboratory of remote {2. {3. Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing China Research Center for remote sensing and GIS Department of Geography Beijing Normal University Beijing China Graduate university of chinese {2. of {3. Beijing China Department of Atmospheric Physics Peking University 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 2.04. 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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On MSDT inversion with multi-angle remote sensing data

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science china Earth {2. 2007年第3期50卷 422-429页

作者： FENG XiaoMing1,2.& ZHAO YingShi1 1 College of Resources and Environment, Graduate university of the chinese {2. of sciences, beijing 100049, china 2.institute of remote sensing applications, chinese {2. of sciences, beijing 100101, china College of Resources and Environment Graduate University of the Chinese Academy of Sciences Beijing China institute of remote {2. {3. Chinese Academy of Sciences Beijing China

With the wavelet transform, image of multi-angle remote sensing is decomposed into multi-resolution. With data of each resolution, we try target-based multi-stages inversion, taking the inversion result of coarse resolution as the prior information of the next inversion. The result gets finer and finer until the resolution of satellite observation. In this way, the target-based multi-stages inversion can be used in remote sensing inversion of large-scaled coverage. With MISR data, we inverse structure parameters of vegetation in semiarid grassland of the Inner Mongolia Autonomous Region. The result proves that this way is efficient.

关键词： target-based multi-stages inversion multi-angle remote sensing wavelet transform

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

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science china(Technological {2.) 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 {2. {3.,jointly sponsored by the institute of remote sensing applications of chinese academy of sciences and beijing normal university,beijing 100101,china State key Laboratory of remote {2. {3. Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing 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 12.0 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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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.{3. 2.Department of Applied Mathematics,Northwestern Polytechnical university,Xi’an 710072.P.R.{3. 3.State key Laboratory of remote sensing science,institute of remote sensing applications,{12. academy of sciences,beijing 100101,P.R.{3. School of Statistics Xi'an University of Finance & Economics Xi'an 710061 P. R. China Department of Applied Mathematics Northwestern Polytechnical University Xi'an 710072 P. R. China Department of Applied Mathematics Northwestern Polytechnical University Xi'an 710072 P. R. China State key Laboratory of remote {2. {3. Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 P. 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.

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Principle of small target detection for hyperspectral imagery

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science china Earth {2. 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 {3. and GIS, Department of Geography, {2. normal university, {2. 100875, china 2.State key Laboratory of remote {3. {13., chinese {12. of sciences, beijing 100101, china 3.institute of Erectronics, chinese {12. of sciences, {2. 100080, china 4 Center for for Assessment and Monitoring of Forest and Environmental Resources and Division of Ecosystem sciences university of California Berkeley, CA 9472.-3.14, USA Research Center for remote sensing and GIS Department of Geography Beijing Normal University Beijing China State key Laboratory of remote {2. {3. Chinese Academy of Sciences Beijing China institute of Erectronics Chinese Academy of Sciences Beijing China Center for for Assessment and Monitoring of Forest and Environmental Resources and Division of Ecosystem sciences University of California Berkeley 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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The quantification of remote sensing

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science china(Technological {2.) 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 {3. Laboratory of remote {2. 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, 84914 Avignon, France 4. china Center for Resource Satellite Data and Application, beijing 10083., china State key Laboratory of remote {2. {3. Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing China The Center for National Spaceborne Demonstration Beijing China Institut National de la Recherche Agronomique Climat Sol Environnement Avignon France china Center for Resource Satellite Data and Application Beijing 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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Matrix calculation of high-dimensional cross product and its application in automatic recognition of the endmembers of hyperspectral imagary

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science china(Information {2.) 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,{2. academy of sciences,beijing 100080,china 2.tate key Laboratory of remote sensing science,{13. {12. by beijing normal university and the institute of remote sensing applications of {2. academy of sciences, School of Geography,beijing normal university,beijing 100875,china 3.chool of Electronics and Information Engineering,Beihang university,beijing 100191,china key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing China State key Laboratory of remote {2. {3. jointly sponsored by beijing normal university and the institute of remote {2. {12. of {13. academy of sciences School of Geography Beijing Normal University Beijing China School of Electronics and Information Engineering Beihang University Beijing 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

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Cascade recursion models of computing the temperatures of underground layers

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science china(Technological {2.) 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., {3. State key Laboratory of remote sensing science, institute of remote sensing applications, {12. {13. of sciences, beijing 100101, {3. 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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Retrieving crop leaf area index by assimilation of MODIS data into a crop growth model

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science china Earth {2. 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 {3. {2. science, jointly sponsored by beijing normal university and institute of {3. {2. {12., CAS, beijing 100875, china 2.School of Geography, beijing key Laboratory of Environmental {3. {2. and Digital City, beijing normal university, beijing 100875, china 3.Haihe River Water Conservancy Commission, Tianjin 3.0170, china 4 Department of Geography, university of Maryland, College Park, MD 2.742. USA State key Laboratory of remote {2. {3. Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications CAS Beijing China School of Geography Beijing Key Laboratory of Environmental Remote Sensing and Digital City Beijing Normal University Beijing China Haihe River Water Conservancy Commission Tianjin China Department of Geography University of Maryland College Park 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 {2., 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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