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

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 Key Laboratory 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 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,China 3 Graduate University of chinese academy of sciences,Beijing 100049,China State Key Laboratory of remote sensing Science Jointly Sponsored by Institute of Remote Sensing Applications Chinese Academy of Sciences and Beijing Normal University Beijing China 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 China Graduate University of chinese academy of sciences Beijing 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 distributions.We implemented the radiosity method to subsequently produce synthetic bidirectional reflectance factor(BRF) datasets based upon these simulated scenes.The inversion was conducted using these data,which showed that spatial distribution affects retrieval accuracy.The 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 cover.This showed that heterogeneity in coarse-resolution remote sensing data is the main error source in LAI inversion.The 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

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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 Science,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 3Department of Geography University of Maryland,College Park,MD 20742,USA 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 Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing China Graduate University of chinese academy of sciences Beijing China Department of Geography University of Maryland College Park USA

The ecosystem in northeastern China and the Russian Far East is a hotspot of scientific research into the global carbon balance.Forest aboveground biomass(AGB) is an important component in the land surface carbon cycle.In 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 data.The resulted statistical regression models have a R2=0.68 for conifer and R2=0.71 for broadleaf forests.These models were used to estimate biomass for all GLAS footprints of forest located in the study area.All 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.Biomass 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 ha-1.The pixel-level biomass map was then stratified into different biomass levels to illustrate the AGB spatial distribution pattern in this area.It was found that HJ-1 wide-swath data and GLAS waveform data can be combined to estimate forest biomass with good precision,and the b

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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Effective solutions to a global 3D visual system in networking environments

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Science China Earth sciences 2005年第11期48卷 2032-2039页

作者： ZHANG Liqiang1,2, ZHANG Yan3, YANG Chongjun2, LIU Suhong1, REN Yingchao2, RUI Xiaoping2 & LIU Donglin2 1. State Key Laboratory of remote sensing sciences, School of Geography and remote sensing, Beijing Normal University, Beijing 100875, China 2. State Key Laboratory of remote sensing sciences, institute of remote sensing applications, chinese academy of sciences, Beijing 101001, China 3. institute of Geographical sciences and Natural Resources Research, chinese academy of sciences, Beijing 101001, China State Key Laboratory of remote sensing sciences School of Geography and Remote Sensing Beijing Normal University Beijing China chinese academy of sciences State Key Laboratory of Remote Sensing SciencesInstitute of Remote Sensing Applications China institute of Geographical sciences and Natural Resources Research Chinese Academy of Sciences China

The development of Web-based global 3D visual system has made progresses. However, there exist few mature and effective ways for managing, transmitting and visualizing massive spatial data. Based on the related work, the paper illustrates the ellipsoidal quadtree technique for rapid access multi-scale and multiple level geographical data, integrates the streaming with level-of-detail rendering method for transmitting the data on the network, and im-plements large-scale terrain surface simplification using M-band wavelet transforms and mul-tiresolution triangulations. We fulfil a web-based global terrain visual system using COM com-ponents on the basis of the above techniques. The system has a good prospect in the military simulation and city plans.

关键词： massive spatial data, streaming transmission, system architecture, M-band wavelet

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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 Science,institute of remote sensing applications,chinese academy of sciences,Beijing 100101,China 2 Zhejiang Climate Center,Hangzhou 310017,China State Key Laboratory of remote sensing Science Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing China Zhejiang Climate Center Hangzhou China

Photosynthetically active radiation(PAR) is essential for plant photosynthesis and carbon cycle,and is also important for meteorological and environmental monitoring.To advance China's disaster and environmental monitoring capabilities,the HJ-1A/B satellites have been placed in Earth orbit.One of their environmental monitoring objectives is the study of PAR.We 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 PAR.Based on the look-up table,we used HJ-1A/B aerosol and surface albedo outputs to derive the corresponding PAR.Validation 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 equations.We also studied the sensitivity of various input parameters to photosynthetically active radiation,and found that solar zenith angle and atmospheric aerosols were sensitive PAR parameters.Surface 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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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 Science,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 sensing Science 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 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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Parallel algorithm for real-time contouring from grid DEM on modern GPUs

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Science China(Technological sciences) 2010年第S1期53卷 33-37页

作者： CHEN Zhuo,SHEN Lei,ZHAO YanQing & YANG ChongJun 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 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 China

A real-time algorithm for constructing contour maps from grid DEM data is pre-sented.It runs completely within the programmable 3D visualization pipeline.The interpolation is paralleled by rasterizer units in the graphics card,and contour line extraction is paralleled by pixel shader.During each frame of the rendering,we first make an elevation gradient map out of original terrain vertex data,then figure out the final contour lines with image-space processing,and directly blend the results on the original scene to obtain a final scene with contour map using alpha-blending.We implement this method in our global 3D-digitalearth system with Direct3D?9.0c API and tested on some consumer level PC platforms.For arbitrary scene with certain LOD level,the process takes less than 10 ms,giving topologically correct,anti-aliased contour lines.

关键词： contour map contour lines paralleled computing 3D terrain GPU digital earth

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A new trust region algorithm for image restoration

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Science China Mathematics 2005年第2期48卷 169-184页

作者： WEN Zaiwen & WANG Yanfei State Key Laboratory of Scientific Engineering Computing, institute of Computational Mathematics and Scientific/Engineering Computing, academy of Mathematics and System sciences, chinese academy of sciences, Beijing 100080, China National Key Laboratory on remote sensing Science, institute of remote sensing applications, chinese academy of sciences, Beijing 100101, China State Key Laboratory of Scientific Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and System Sciences Chinese Academy of Sciences Beijing China National Key Laboratory on remote sensing Science Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing China

The image restoration problems play an important role in remote sensing and astronomical image analysis. One common method for the recovery of a true image from corrupted or blurred image is the least squares error (LSE) method. But the LSE method is unstable in practical applications. A popular way to overcome instability is the Tikhonov regularization. However, difficulties will encounter when adjusting the so-called regularization parameter α. Moreover, how to truncate the iteration at appropriate steps is also challenging. In this paper we use the trust region method to deal with the image restoration problem, meanwhile, the trust region subproblem is solved by the truncated Lanczos method and the preconditioned truncated Lanczos method. We also develop a fast algorithm for evaluating the Kronecker matrix-vector product when the matrix is banded. The trust region method is very stable and robust, and it has the nice property of updating the trust region automatically. This releases us from tedious finding the regularization parameters and truncation levels. Some numerical tests on remotely sensed images are given to show that the trust region method is promising.

关键词： trust region algorithm, image restoration, Lanczos method, Kronecker matrix-vector product, preconditioning.

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Monitoring of rice crop using ENVISAT ASAR data

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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 20742, USA 4. Forest remote sensing Lab, Research institute of Forest Resource and Information Technology, chinese academy of For-estry, Beijing 100091, China State Key Laboratory of remote sensing Science Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing China Graduate University of chinese academy of sciences Beijing China Department of Geography University of Maryland College Park USA Forest remote sensing Lab Research Institute of Forest Resource and Information Technology Chinese Academy of Forestry Beijing 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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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 Science,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 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 China Graduate School of the chinese academy of sciences Beijing China Research institute of Forest Resources and Information Techniques Chinese Academy of Forestry Beijing China

The estimation of above-ground biomass(AGB) and carbon storage is very important for arid and semi-arid ecosystems.HJ-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,China.The 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 equation.The prediction equation based on ratio vegetation index(RVI)was proved to be more suitable for shrub AGB estimation in the Mu Us desert than others.Shrub AGB and carbon storage were mapped using the RVI based prediction model in final.The 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

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Iterative implementation of the adaptive regularization yields optimality

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Science China Mathematics 2005年第4期48卷 485-492页

作者： MA Qinghua & WANG Yanfei Department of Information sciences, College of Arts and Science of Beijing Union University, Beijing 100038, China National Key Laboratory on remote sensing Science, institute of remote sensing applications, chinese academy of sciences, Beijing 100101, China Department of Mathematics, University of Central Florida, P. O. Box 161364, Orlando, FL 32816-1364, USA Department of Information sciences College of Arts and Science of Beijing Union University Beijing China National Key Laboratory on remote sensing Science Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing China

The adaptive regularization method is first proposed by Ryzhikov et al. for the deconvolution in elimination of multiples. This method is stronger than the Tikhonov regularization in the sense that itis adaptive, i.e. it eliminates the small eigenvalues of theadjoint operator when it is nearly singular. We will show in this paper that the adaptive regularization can be implemented iterately. Some properties of the proposed non-stationary iterated adaptive regularization method are analyzed. The rate of convergence for inexact data is proved. Therefore the iterative implementation of the adaptive regularization can yield optimality.

关键词： ill-posed problems, non-stationary iterated adaptive regularization, optimality.

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