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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, {2. 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 1. 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 100080 Beijing China 2. National key Laboratory on remote {2. Science Institute of Remote Sensing Applications Chinese Academy of Sciences 100101 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.

Development of environmental monitoring satellite systems in china

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Science china Earth sciences 2010年第S1期53卷 1-7页

作者： LI GuoPing1 & CAO ChunXiang2.1 School of Earth and Space sciences,Peking University,beijing 100871,{2. 2.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,{2. 1. School of Earth and Space sciences Peking University Beijing 100871 China2. 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

With the increase in global environmental problems,the necessity and urgency of remote sensing technology being applied to environmental monitoring has been widely recognized around the *** has launched the environment and disaster monitoring and forecasting small satellite constellation HJ-1A/B and the FY3 atmosphere and environmental satellite,but they still cannot fully satisfy requirements for environmental *** paper summarizes the current status of satellite environmental monitoring in{2. and the existing problems of inadequate load design and low data utilization efficiency,and discusses the demand for environmental monitoring *** on the development of foreign satellite systems for environmental monitoring,the future development and key tasks of the environmental monitoring satellite system in{2. is discussed,as are some related initiatives.

关键词： environmental satellite environmental monitoring global climate change specialty load satellite system

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 {2. 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 2.742. USA 4. Forest {2. sensing Lab, Research institute of Forest Resource and Information Technology, chinese academy of For-estry, beijing 100091, china 1. state key Laboratory of {2. 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.

Long term monitoring of urban subsidence by Permanent Scatterer DInSAR

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Progress in Natural Science:Materials International 2007年第1期17卷 107-111页

作者： TANG Yixian, ZHANG Hong and WANG Chao ( The chinese remote {2. Satellite Ground Station, chinese academy of sciences, beijing 100086, china state key Laboratory of remote {2. IRSA, chinese academy of sciences, beijing 100101, china) [a]The chinese remote {2. Satellite Ground Station Chinese Academy of Sciences Beijing China [b]state key Laboratory of {2. sensing IRSA Chinese Academy of Sciences Beijing China

When using differential SAR interferometry (DInSAR) to monitor the surface deformation over a long time scale, it is often strongly affected by the spatial and temporal decorrelations and atmospheric dishomogeneities. The recently developed Permanent Scatterers (PS) technique proposed by Fertti et al. can overcome these difficulties by interpreting time-series of interferometric phase only at coherent point scatterers. In this study, we apply this PS technique using 2. ERS-1/2.scenes from 1992.to 2.00 to monitor the subsidence in Suzhou. By using the linear deformation model, the deformation map in Suzhou urban area over the eight years is obtained. And the calculated results are in good agreement with the measurements of leveling.

关键词： Permanent Scatterer differential SAR interferometry urban subsidence.

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

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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 {2. 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 {2. 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 1. state key Laboratory of {2. sensing Science Jointly Sponsored by Institute of Remote Sensing Applications Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China2. 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 China3. Graduate University of Chinese Academy of Sciences Beijing 100049 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

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 {2. sensing Science,institute of {2. sensing applications,chinese academy of sciences,beijing 100101,{12. 2.Zhejiang Climate Center,Hangzhou 310017,{12. 1. state key Laboratory of {2. sensing Science 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 2..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

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 {2. sensing Science,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 {2. sensing Science Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China

A real-time algorithm for constructing contour maps from grid DEM data is *** runs completely within the programmable 3D 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 3D-digitalearth system with Direct3D?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 3D terrain GPU digital earth

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 {2. sensing Science,Jointly Sponsored by the institute of remote sensing applications of chinese academy of sciences and beijing Normal University,institute of {2. sensing applications,chinese {12. of sciences,beijing 100101,china 2.raduate University of chinese academy of sciences,beijing 100049,china 3Department of Geography University of Maryland,College Park,MD 2.742.USA 1. state key Laboratory of {2. 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 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 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

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.china 2.Department of Applied Mathematics,Northwestern Polytechnical University,Xi’an 710072.P.R.china 3.{2. key Laboratory of remote sensing Science,institute of remote sensing applications,chinese academy of {12.,beijing 100101,P.R.china School of Statistics Xi'an University of Finance & EconomicsXi'an 710061P.R.China Department of Applied Mathematics Northwestern Polytechnical UniversityXi'an 710072P.R.China Department of Applied Mathematics Northwestern Polytechnical UniversityXi'an 710072P.R.China state key Laboratory of {2. sensing Science Institute of Remote Sensing ApplicationsChinese Academy of SciencesBeijing 100101P.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.