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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. {5. key {2. of remote sensing sciences, School of Geography and remote sensing, Beijing Normal University, Beijing 100875. china {15.s, 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 1. state key {2. of remote sensing {5.s School of Geography and Remote Sensing Beijing Normal University 100875 Beijing China 2. Chinese Academy of sciences State Key Laboratory of Remote Sensing SciencesInstitute of Remote Sensing Applications 101001 Beijing China 3. Institute of Geographical sciences and Natural Resources Research Chinese Academy of Sciences 101001 Beijing 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

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, Beijing Normal University, {2. key laboratory of remote sensing science, Beijing key laboratory for remote sensing of Environment and Digital Cities, Beijing {12. china Department of Mathematics, Beijing Normal University, Beijing {12. china 1. 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 100875 Beijing China 2. Department of Mathematics Beijing Normal University 100875 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.

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,china 2.{2. key laboratory of remote sensing science,School of Geography and remote sensing science,Beijing Normal University,Beijing 100875.china 3 Chinese Academy of Meteorological sciences,Beijing 100081,china Meteorological Observation Center of china Meteorological Administration Beijing 100081 China state key {2. of remote sensing {5. School of Geography and Remote Sensing Science Beijing Normal University Beijing 100875 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

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 {5. sensing science, Jointly Sponsored by Beijing Normal University and Institute of {5. sensing Applications, CAS, Beijing 100875. china 2.School of Geography, Beijing key {2. of Environmental {5. 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 1. state key {2. of remote sensing {5. Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications CAS Beijing 100875 China2. School of Geography Beijing Key Laboratory of Environmental Remote Sensing and Digital City Beijing Normal University Beijing 100875 China3. Haihe River Water Conservancy Commission Tianjin 300170 China4. Department of Geography University of Maryland College Park MD 20742 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 Beijing, 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 {2. 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 {2. 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 1. state key {2. of remote sensing {5. 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

Automatic generalization of metro maps based on dynamic segmentation

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science china(Technological sciences) 2010年第S1期53卷 158-165页

作者： DONG WeiHua 1,TIAN Yuan 2.& ZHANG Yi 2.1 Institute of Geography and remote sensing,Beijing Normal University,Beijing {2.{5. 2.Institute of remote sensing and Geographic Information System,Peking University,Beijing 100871,{5. 1. Institute of Geography and remote sensing Beijing Normal University Beijing 100875 China 2. Institute of remote sensing and Geographic Information System Peking University Beijing 100871 China

A metro map is usually optimized for the readability of connections and transportation networks *** order to assure good readability and meet aesthetic considerations,a set of principles for good metro map layout are *** to these principles,a new methodology based on dynamic segmentation is presented to produce the metro maps ***,routes are constructed according to the line attribute similarity and geometry *** a set of cartographic generalization methods about the shape,angle,length,and topology are presented for these *** method is validated by Beijing metro plan *** the experiment results,it can be concluded that this new method is more effective than the static segmentation method to produce metro maps with better readability for route plans.

关键词： metro maps generalization dynamic segmentation visualization

Water target based cross-calibration of CBERS-02.CCD camera with MODIS data

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science china(Technological sciences) 2005年第S2期48卷 61-71页

作者： TANG Junwu1,2. GU Xingfa2. NIU Shengli1, MA Chaofei1 & MIN Xiangjun3 1. National Satellite Ocean Application Service (NSOAS), Beijing 100081, china 2. state key laboratory of remote sensing science, Beijing 100010, china 3. china Center for Resource Satellite Data and Applications (CRESDA), Beijing 100083, china 1. National Satellite Ocean Application Service (NSOAS) 100081 Beijing China 2. state key laboratory of remote sensing science 100010 Beijing China 3. china Center for Resource Satellite Data and Applications (CRESDA) 100083 Beijing China

In order to make quantitative watercolor sensing with china-Brazil Earth Resources Satellite (CBERS-02. CCD camera, the MODIS data with higher accuracy is used to cross-calibrate the CCD camera over water targets. In homogeneous clear water area, two pairs of images obtained over the same area on the same day by the two sensors are selected. The top-of-atmosphere (TOA) radiances of the multispectral bands of CCD are calculated with the water and aerosol parameters from MODIS based on a water-atmosphere radiative transfer algorithm. The stripes in CCD image that caused by unequal response of the CCD array detectors are firstly removed before making the cross-calibration. The same part of CCD detectors is selected for the calibrations in the two images to eliminate the residual error of destriping and uniformity correction for the focus plane irradiance. It is shown that the calibration results from two different images are consistent. The error of this method is about 5..

关键词： CBERS-02 CCD MODIS radiometric calibration cross-calibration. DOI: 10.1360/05.e1006

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 sciences) 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 {2. of {5. sensing science,jointly sponsored by the Institute for {5. sensing Applications of Chinese Academy of sciences and Beijing Normal University,Beijing 100101,china 2.Graduate University of the Chinese Academy of sciences,Beijing 100049,china 3 Institute of Forest Resource Information Technique,the Chinese Academy of Forestry,Beijing 100091,china 4 Research Center for {5. sensing and GIS,Department of Geography and Beijing key {2. for {5. sensing of Environment and Digital Sites,Beijing Normal University,Beijing 100875.china state key {2. of remote sensing {5. jointly sponsored by the Institute for Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China Graduate University of the Chinese Academy of sciences Beijing 100049 China Institute of Forest Resource Information Technique the Chinese Academy of Forestry Beijing 100091 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 100875 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 -5.00 laser system was used and a flight was carried out over a ground of 700―800 *** this tested area,a total number of 15.6 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

Principle of small target detection for hyperspectral imagery

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science china Earth sciences 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 sensing and GIS, Department of Geography, Beijing Normal University, Beijing {2. {5. 2.state key laboratory of remote sensing science, Chinese Academy of sciences, Beijing 100101, {5. 3 Institute of Erectronics, Chinese Academy of sciences, Beijing 100080, {5. 4 Center for for Assessment and Monitoring of Forest and Environmental Resources and Division of Ecosystem sciences University of California Berkeley, CA 9472.-3114, USA 1. Research Center for remote sensing and GIS Department of Geography Beijing Normal University Beijing 100875 China 2. state key laboratory of remote sensing science Chinese Academy of Sciences Beijing 100101 China 3. Institute of Erectronics Chinese Academy of Sciences Beijing 100080 China 4. Center for for Assessment and Monitoring of Forest and Environmental Resources and Division of Ecosystem sciences University of California Berkeley CA 94720-3114 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