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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, beijing Normal University, State key laboratory of remote sensing Science, beijing key laboratory for remote sensing of environment and digital cities, beijing 100875, China Department of Mathematics, beijing 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.

Research on scale effect of histogram

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Science China Earth Sciences 2002年第10期45卷 949-960页

作者：张颢李小文阎广建焦子锑王锦地赵红蕊杨华苏理宏 Research Center for remote sensing and GIS Department of Geography and Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities Beijing Normal University Beijing China Center for remote sensing and Department of Geography Boston University USA

To describe the spatial relationship among the earth objects compactly, in this paper, we raised the concept of histo-variogram based on the analysis of the characteristics of other spatial analyzing methods such as variogram, information entropy. And we also raised a new spatial analysis method of histogram decomposition based on the definition of standing pixel and contour pixel. At the end of this paper, we demonstrated the characteristics of histo-variogram by two experiments, one for spatial analysis, the other for image fusion.

关键词： histo-variogram, scaling, histogram-decomposition, standing-pixel, HIS transform.

Evaluating the generalization ability of convolutional neural networks for built-up area extraction in different cities of China

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Optoelectronics Letters 2020年第1期16卷 52-58页

作者： ZHANG Tao TANG Hong State key laboratory of remote sensing Science Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of SciencesBeijing 100875China beijing key laboratory for remote sensing of environment and digital cities Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China

The difficulty of build-up area extraction is due to complexity of remote sensing data in terms of heterogeneous appearance with large intra-class variations and lower inter-class variations. In order to extract the built-up area from Landsat 8-OLI images provided by Google earth engine(GEE), we propose a convolutional neural networks(CNN) utilizing spatial and spectral information synchronously, which is built in Google drive using Colaboratory-Keras. To train a CNN model with good generalization ability, we choose beijing, Lanzhou, Chongqing, Suzhou and Guangzhou of China as the training sites, which are very different in term of natural environments. The Arc GIS-Model Builder is employed to automatically select 99 332 samples from the 38-m global built-up production of the European Space Agency(ESA) in 2014. The validate accuracy of the five experimental sites is higher than 90%. We compare the results with other existing building data products. The classification results of CNN can be very good for the details of the built-up areas, and greatly reduce the classification error and leakage error. We applied the well-trained CNN model to extract built-up areas of Chengdu, Xi’an, Zhengzhou, Harbin, Hefei, Wuhan, Kunming and Fuzhou, for the sake of evaluating the generalization ability of the CNN. The fine classification results of the eight sites indicate that the generalization ability of the well-trained CNN is pretty good. However, the extraction results of Xi’an, Zhengzhou and Hefei are poor. As for the training data, only Lanzhou is located in the northwest region, so the trained CNN has poor image classification ability in the northwest region of China.

关键词： networks neural generalization

Study on NDVI-T_s space by combining LAI and evapotranspiration

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Science China Earth Sciences 2006年第7期49卷 747-754页

作者： HAN Lijuan1,2,3, WANG Pengxin4, YANG Hua1,2,3, LIU Shaomin1,2,3 & WANG Jindi1,2,3 1. Research Center for remote sensing and GIS, School of Geography, beijing Normal University, beijing 100875, China 2. State key laboratory of remote sensing Science, beijing 100875, China 3. beijing key laboratory for remote sensing of environment and digital cities, beijing 100875, China 4. Department of Information Management, College of Information and Electronic Engineering, China Agricultural University, beijing 100083, China Research Center for remote sensing and GIS School of Geography Beijing Normal University Beijing China State key laboratory of remote sensing Science Beijing China beijing key laboratory for remote sensing of environment and digital cities Beijing China Department of Information Management College of Information and Electronic Engineering China Agricultural University Beijing China

This paper focuses on interpreting the different spatial relationships between NDVI and Ts, a triangular or a trapezoid, and on analyzing transformation conditions, the physical and ecological meanings of the vegetation index-surface temperature space as well. Further, we use the Tempera-ture-Vegetation Dryness Index (TVDI) to explain the existent meaning of a triangular space after NDVI reaches its saturated state by employing the relationships between NDVI, LAI and evapotranspiration. The specific relations between NDVI and Ts are useful for describing, validating and updating land surface models.

关键词： NDVI, land surface temperature, evapotranspiration, leave area index.

Thermal bidirectional gap probability model for row crop canopies and validation

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Science China Earth Sciences 2003年第12期46卷 1241-1249页

作者：阎广建蒋玲梅王锦地陈良富李小文 Research Center for remote sensing and GIS Department of Geography and Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities Beijing Normal University Beijing 100875 China LARSIS Institute of Remote Sensing Application Chinese Academy of Sciences Beijing 100101 China Department of Geography and Center for remote sensing Boston University Boston MA 02215 USA

Based on the row structure model of Kimes and the mean gap probability model in single direction, we develop a bidirectional gap probability model for row crop canopies. A concept of overlap index is introduced in this model to consider the gaps and their correlation between the sun and view directions. Multiangular thermal emission data sets were measured in Shunyi, beijing, and these data are used in model validation in this paper. By comparison with the Kimes model that does not consider the gap probability, and the model considering the gap in view direction only, it is found that our bidirectional gap probability model fits the field measurements over winter wheat much better.

关键词： row crop, bidirectional gap probability, thermal emission, hot spot effect.

Assessing the uncertainties of phytoplankton absorption-based model estimates of marine net primary productivity

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Acta Oceanologica Sinica 2017年第6期36卷 112-121页

作者： TAO Zui MA Sheng YANG Xiaofeng WANG Yan State key laboratory of remote sensing Science Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijing 100101China beijing North-Star digital remote sensing Technology Co.Ltd. Beijing 100120China State environmental Protection key laboratory of Numerical Modeling for environment Impact Assessment Beijing 100012China

Satellite-derived phytoplankton pigment absorption （aph） has been used as a key predictor of phytoplankton photosynthetic efficiency to estimate global ocean net primary production （NPP）. In this study, an aph-based NPP model （AbPM） with four input parameters including the photosynthetically available radiation （PAR）, diffuse attenuation at 490 nm （Ka（490））, euphotic zone depth （Zeu） and the phytoplankton pigment absorption coefficient （aph） is compared with the chlorophyll-based model and carbon-based model. It is found that the AbPM has significant advantages on the ocean NPP estimation compared with the chlorophyll-based model and carbon- based model. For example, AbPM greatly outperformed the other two models at most monitoring sites and had the best accuracy, including the smallest values of RMSD and bias for the NPP estimate, and the best correlation between the observations and the modeled NPPs. In order to ensure the robustness of the model, the uncertainty in NPP estimates of the AbPM was assessed using a Monte Carlo simulation. At first, the frequency histograms of simple difference （fi）, and logarithmic difference （~LOG） between model estimates and in situ data confirm that the two input parameters （Zeu and PAR） approximate the Normal Distribution, and another two input parameters （aph and Ka（490）） approximate the logarithmic Normal Distribution. Second, the uncertainty in NPP estimates in the AbPM was assessed by using the Monte Carlo simulation. Here both the PB （percentage bias）, defined as the ratio of ANPP to the retrieved NPP, and the CV （coefficient of variation）, defined as the ratio of the standard deviation to the mean are used to indicate the uncertainty in the NPP brought by input parameter to AbPM model. The uncertainty related to magnitude is denoted by PB and the uncertainty related to scatter range is denoted by CV. Our investigations demonstrate that PB of NPP uncertainty brought by all parameters with an annual mean of 5.5% covered a ran

关键词： marine net primary production phytoplankton pigment absorption satellite remote sensing uncertainty analysis Monte Carlo simulation

Permafrost environment monitoring on the Qinghai-Tibet Plateau using time series ASAR images

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International Journal of digital Earth 2015年第10期8卷 840-860页

作者： Zhen Li Panpan Tang Jianmin Zhou Bangsen Tian Quan Chen Sitao Fu key laboratory of digital Earth Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijingChina Institute of remote sensing and digital Earth University of the Chinese Academy of SciencesBeijingChina

The permafrost in Qinghai-Tibet Plateau(QTP)has long been the focus of many *** this study,we first use the method that integrates synthetic aperture radar(SAR)intensity and phase information to monitor permafrost environment in the Beiluhe Region,using time series advanced SAR *** backscattering coefficients(σ^(0))and deformation were extracted for the main features,and the influences of meteorological conditions to them were also *** results show that both the change inσ^(0)and surface deformation are closely related to the active layer,and the deformation is also affected by the permafrost ***,over meadow and sparse vegetation regions,σ^(0)rose about 6.9 and 4 dB from the freezing to thawing period,respectively,which can be mainly attributed to the thaw of the active layer and increased ***,seasonal deformation,derived from the freeze-thaw cycle of the active layer,was characteristic of frost heave and thaw settlement and exhibited a negative correlation with air *** magnitude was larger than 1 cm in a seasonal ***,significant secular settlement was observed,with rates ranging from-16 to 2 mm/a,and it was primarily due to the thaw of the permafrost table caused by climate warming.

关键词： Qinghai-Tibet Plateau ASAR permafrost environment backscattering coefficients deformation climate warming

Development of ecohydrological assessment tool and its application

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Science China(Technological Sciences) 2009年第7期52卷 1947-1957页

作者： LIU ChangMing YANG ShengTian WEN ZhiQun WANG XueLei WANG YuJuan LI Qian SHENG HaoRan Institude of Water Science Beijing Normal UniversityBeijing 100875China State key laboratory of remote sensing Science Beijing Key Laboratory for Remote Sensing of Environment and Digital CitiesSchool of GeographyBeijing Normal UniversityBeijing 100875China key laboratory of Water Resources and Related Land Surface Processes Institute of Geographical Sciences and Natural ResourcesChinese Academy of SciencesBeijing 100101China

The development of Hydro-Informatic Modelling System (HIMS) provides an integrated platform for hydrological simulation. To extend the application of HIMS, an ecohydrological modeling system named ecohydrological assessment tool (EcoHAT) has been developed. Integrating parameter-management tools, RS (remote sensing) inversion tools, module-design tools and GIS analysis tools, the EcoHAT provides an integrated tool to simulate ecohydrological processes on regional scale, which develops a new method on sustainable use of water. EcoHAT has been applied to several case studies, such as, the Yellow River Basin, the acid deposition area in Guizhou province and the riparian catchment of Guanting reservoir in beijing. Results prove that EcoHAT can efficiently simulate and analysis the ecohydrological processes on regional scale and provide technical support to integrated water resources management on basin scale.

关键词： EcoHAT ecohydrology distributed model remote sensing

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 laboratory of remote sensing Science,jointly sponsored by the Institute for remote 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 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 State key laboratory of remote sensing Science jointly sponsored by the Institute for Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing China Graduate University of the Chinese Academy of Sciences Beijing China Institute of Forest Resource Information Technique the Chinese Academy of Forestry Beijing 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 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 -5600 laser system was used and a flight was carried out over a ground of 700―800 *** this tested area,a total number of 1546 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 ±20.9 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