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

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science china Earth {2. 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 {3., School of Geography and remote sensing, beijing normal university, beijing 100875, china 2. State key Laboratory of remote sensing {3., institute of remote sensing applications, chinese academy of {3., beijing 101001, china 3. institute of Geographical {3. and Natural Resources Research, chinese academy of {3., beijing 101001, china State key Laboratory of remote {2. {3. School of Geography and Remote Sensing Beijing Normal University Beijing China chinese academy of {2. 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 3. 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

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

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science china Earth {2. 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 {3. Laboratory of remote {2. science,jointly sponsored by institute of remote {2. applications,{13. academy of {12. and beijing normal university,beijing 100101,china 2.State {3. Laboratory of remote {2. science,jointly sponsored by beijing normal university and institute of remote {2. applications of {13. academy of {12.,beijing 100875,china 3.Graduate university of {13. academy of {12.,beijing 100049,china State key Laboratory of remote {2. {3. Jointly Sponsored by Institute of Remote Sensing Applications Chinese Academy of Sciences and Beijing Normal University Beijing China State key Laboratory of remote {2. {3. Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications of Chinese Academy of Sciences Beijing China Graduate university of chinese {2. of {3. 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 *** 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

Parallel algorithm for real-time contouring from grid DEM on modern GPUs

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science china(Technological {2.) 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 {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

A real-time algorithm for constructing contour maps from grid DEM data is *** runs completely within the programmable 3. visualization *** interpolation is paralleled by rasterizer units in the graphics card,and contour line extraction is paralleled by pixel *** 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 *** implement this method in our global 3.-digitalearth system with Direct3.?9.0c API and tested on some consumer level PC *** 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 3. terrain GPU digital earth

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 {3., chinese academy of {3., beijing 100080, china National key Laboratory on remote sensing science, institute of remote sensing applications, chinese academy of {3., 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 {2. {3. 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 {2.. A popular way to overcome instability is the Tikhonov regularization. However, difficulties will encounter when adjusting the so-called regularization parameter a. 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.

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

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science china Earth {2. 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 sciences and beijing normal university,beijing 100101,china 3.institute of Desertification Studies,chinese academy of Forestry,beijing 100091 china key Laboratory of Silviculture and Conservation Ministry of Education Beijing Forestry University Beijing China State key Laboratory of remote {2. {3. jointly sponsored by the Institute of Remote Sensing Applications Chinese Academy of Sciences and Beijing Normal University Beijing China institute of Desertification Studies Chinese Academy of Forestry Beijing 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

Analysis of forest backscattering characteristics based on polarization coherence tomography

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science china(Technological {2.) 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 {3. and Technology,{2. of Electronic {3. and Technology of china,Chengdu 610054,china 2.State key Laboratory of remote sensing {3.,{13.,beijing 100101,china 3.2} of Forest Resources Information Technique of chinese academy of Forestry,beijing 100091,china 4 School of Electronic Engineering,{2. of Electronic {3. and Technology of china,Chengdu 610054,china institute of Geo-Spatial Information science and Technology University of Electronic Science and Technology of China Chengdu 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 institute of Forest Resources Information Technique of chinese {2. of Forestry Beijing China School of Electronic Engineering University of Electronic Science and Technology of China Chengdu 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

Monitoring of rice crop using ENVISAT ASAR data

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science china Earth {2. 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 {2. science, institute of remote {2. applications, chinese academy of sciences, beijing 100101, {12. 2. Graduate university of chinese academy of sciences, beijing 10003., {12. 3. Department of Geography, university of Maryland, College Park, MD 2.742. USA 4. Forest remote {2. Lab, Research institute of Forest Resource and Information Technology, chinese academy of For-estry, beijing 100091, {12. State key Laboratory of remote {2. {3. Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing China Graduate university of chinese {2. of {3. 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.

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

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science china Earth {2. 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 {2. science,jointly sponsored by the institute of remote sensing applications of chinese academy of sciences and beijing normal university,institute of remote {2. applications,chinese academy of sciences,{12.,china 2.raduate university of chinese academy of sciences,beijing 100049,china 3.epartment of Geography university of Maryland,College Park,MD 2.742.USA 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 Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing China Graduate university of chinese {2. of {3. 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 *** 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 Geo{2. 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 2. 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

Polynomial analysis of canopy spectra and biochemical component content inversion

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science china Earth {2. 2005年第10期48卷 1780-1791页

作者： YAN Chunyan1, LIU Qiang1, NIU Zheng1, WANG Jihua2. HUANG Wenjiang2.& LIU Liangyun 2.1. 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. National Engineering Research Center for Information Technology in Agriculture, beijing 100089, china jointly sponsored by the institute of remote sensing applications of chinese academy of sciences and beijing normal university National Engineering Research Center for Information Technology in Agriculture

A polynomial expression model was developed in this paper to describe directional canopy spectra, and the decomposition of the polynomial expression was used as a tool for re-trieving biochemical component content from canopy multi-angle spectra. First, the basic formula of the polynomial expression was introduced and the physical meaning of its terms and coeffi-cients was discussed. Based on this analysis, a complete polynomial expression model and its decomposition method were given. By decomposing the canopy spectra simulated with SAILH model, it shows that the polynomial expression can not only fit well the canopy spectra, but also show the contribution of every order scattering to the whole reflectance. Taking the first scattering coefficients a10 and a01 for example, the test results show that the polynomial coefficients reflect very well the hot spot phenomenon and the effects of viewing angles, LAI and leaf inclination angle on canopy spectra. By coupling the polynomial expression with leaf model PROSPECT, a canopy biochemical component content inversion model was given. In the simulated test, the canopy multi-angle spectra were simulated by two different models, SAILH and 4-SCALE re-spectively, then the biochemical component content was retrieved by inverting the coupled polynomial expression + PROSPECT model. Results of the simulated test are promising, and when applying the algorithm to measured corn canopy multi-angle spectra, we also get relatively accurate chlorophyll content. It shows that the polynomial analysis provides a new method to get biochemical component content independent of any specific canopy model.

关键词： polynomial expression, canopy spectra, decomposition, biochemical component content, inversion.