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Information flow and controlling in regularization inversion of quantitative remote sensing

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science china Earth sciences 2005年第1期48卷 74-83页

作者： YANG Hua, XU Wangli, ZHAO Hongrui, CHEN Xue & WANG Jindi Research Center for remote sensing and GIS, School of Geography, {2. Normal University, state key laboratory of remote sensing science, {2. key laboratory for remote sensing of Environment and Digital Cities, beijing 100875, china Department of Mathematics, {2. Normal University, beijing 100875, china Research Center for remote sensing and GIS School of Geography Beijing Normal University State Key Laboratory of Remote Sensing Science Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities Beijing China Department of Mathematics Beijing Normal University Beijing China

In order to minimize uncertainty of the inversed parameters to the largest extent by making full use of the limited information in remote sensing data, it is necessary to understand what the information flow in quantitative remote sensing model inversion is, thus control the information flow. Aiming at this, the paper takes the linear kernel-driven model inversion as an example. At first, the information flow in different inversion methods is calculated and analyzed, then the effect of information flow controlled by multi-stage inversion strategy is studied, finally, an information matrix based on USM is defined to control information flow in inversion. It shows that using Shannon entropy decrease of the inversed parameters can express information flow more properly. Changing the weight of a priori knowledge in inversion or fixing parameters and partitioning datasets in multi-stage inversion strategy can control information flow. In regularization inversion of remote sensing, information matrix based on USM may be a better tool for quantitatively controlling information flow.

关键词： regularization inversion, information flow, Shannon entropy decrease, information matrix.

Semi-Supervised Classification based on Gaussian Mixture Model for remote imagery

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science china(Technological sciences) 2010年第S1期53卷 85-90页

作者： XIONG Biao1,ZHANG XiaoJun1 & JIANG WanShou1,2.1 state key {2. of Information Engineering in Surveying,Mapping and remote sensing,Wuhan University,Wuhan 430079,china 2.state key {2. of remote sensing science,{12.,china state key {2. of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan China state key {2. of remote sensing science Beijing China

Semi-Supervised Classification (SSC),which makes use of both labeled and unlabeled data to determine classification borders in feature space,has great advantages in extracting classification information from mass *** this paper,a novel SSC method based on Gaussian Mixture Model (GMM) is proposed,in which each class’s feature space is described by one *** show the proposed method can achieve high classification accuracy with small amount of labeled ***,for the same accuracy,supervised classification methods such as Support Vector Machine,Object Oriented Classification,*** be provided with much more labeled data.

关键词： remote sensing image classification Semi-Supervised Classification Gaussian Mixture Model EM algorithms

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 {2. 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 {2. 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

Multiple time scale evaluation of the energy balance during the maize growing season,and a new reason for energy imbalance

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science china Earth sciences 2009年第1期52卷 108-117页

作者： GUO JianXia1,2.BIAN LinGen3 & DAI YongJiu2.1 Meteorological Observation Center of china Meteorological Administration,beijing 100081,{2. 2.state key laboratory of remote sensing science,School of Geography and remote sensing science,beijing Normal University,beijing 100875,{2. 3 Chinese Academy of Meteorological sciences,beijing 100081,{2. Meteorological Observation Center of china Meteorological Administration Beijing China state key {2. of remote sensing science School of Geography and Remote Sensing Science Beijing Normal University Beijing China Chinese Academy of Meteorological sciences Beijing China

Energy imbalance is a common problem associated with the measurement of surface energy using the eddy covariance *** the evaluation of the energy balance,people usually pay more attention to the statistical result that the effective energy(the sum of sensible and latent heat) is systematically lower than the available energy(the difference of net radiation and ground heat flux).However,little attention has been paid to the existence of the reversed situation when the effective energy is larger than the available energy or their contribution to the overall energy closure *** this paper,based on the analysis of the energy balance on multiple time scales across the maize growth season,we conclude that the non-synchronization of energy components is the main reason for the existence of the reversed *** shifting the phase of the effective energy components half an hour ahead,the rates of energy closure over all time scales are improved and dramatically reduce the number of the half-hourly samples when the energy ratio exceeds 1 or is below *** to the characteristics of the energy distribution and transformation over multiple time scales,latent heat is always the main type of energy cost,and the residual of the energy balance increases with the growth of the maize plant surpassing the sensible heat for seventy *** is suggested that the heat storage and photosynthetic energy play an important role in the energy balance during the growing period of maize.

关键词： maize energy balance multiple time scale energy hysteresis

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 {2. 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 {2. on remote sensing science, Institute of remote sensing Applications, Chinese Academy of sciences, beijing 100101, china state key {2. 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 {2. 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 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. School of Earth and Space sciences Peking University Beijing China state key {2. of remote sensing science Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing 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

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 {2. 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 {2. 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 2.742. USA state key {2. of remote sensing science 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

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 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 {2. of remote sensing science Jointly Sponsored by Institute of Remote Sensing Applications Chinese Academy of Sciences and Beijing Normal University Beijing China state key {2. 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 *** 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

Integrative inversion of land surface component temperature

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science china Earth sciences 2005年第11期48卷 2011-2019页

作者： FAN Wenjie1 & XU Xiru1,2.1. Institute of remote sensing and Geographical Information System, Peking University, {2. 100871, china 2. Center of remote sensing and GIS of {2. Normal University, beijing 100875, china Institute of remote sensing and Geographical Information System Peking University Beijing China Center of remote sensing and GIS of {2. Normal University Beijing China

In this paper, the row winter wheat was selected as the example to study the com-ponent temperature inversion method of land surface target in detail. The result showed that the structural pattern of row crop can affect the inversion precision of component temperature evi-dently. Choosing appropriate structural pattern of row crop can improve the inversion precision significantly. The iterative method combining inverse matrix was a stable method that was fit for inversing component temperature of land surface target. The result of simulation and field ex-periment showed that the integrative method could remarkably improve the inversion accuracy of the lighted soil surface temperature and the top layer canopy temperature, and enhance inver-sion stability of components temperature. Just two parameters were sufficient for accurate at-mospheric correction of multi-angle and multi-spectral thermal infrared data: atmospheric trans-mittance and the atmospheric upwelling radiance. If the atmospheric parameters and component temperature can be inversed synchronously, the really and truly accurate atmospheric correction can be achieved. The validation using ATSRII data showed that the method was useful.

关键词： components temperature, inverse pattern, atmospheric correction