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Land cover classification of remotely sensed image with hierarchical iterative method

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Progress in Natural Science:Materials International 2005年第5期15卷 442-447页

作者： LI Peijun* and HUANG Yingduan(institute of remote sensing and gis, peking university, beijing 100871, china) Inst. of remote sensing and gis Peking Univ. Beijing 100871 China

Based on the analysis of the single-stage classification results obtained by the multitemporal SPOT 5 and Landsat 7 ETM+ multispectral images separately and the derived variogram texture, the best data combinations for each land cover class are selected, and the hierarchical iterative classification is then applied for land cover mapping. The proposed classification method combines the multitemporal images of different resolutions with the image texture, which can greatly improve the classification accuracy. The method and strategies proposed in the study can be easily transferred to other similar applications.

关键词： multitemporal iterative classification texture land cover image classification.

A static and dynamic factorscoupled forecasting model of regional rainfall-induced landslides:A case study of Shenzhen

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Science china(Technological Sciences) 2008年第S2期51卷 164-175页

作者： JIA GuiYun,TIAN Yuan,LIU Yu & ZHANG Yi institute of remote sensing and gis,peking university,beijing 100871,china institute of remote sensing and gis Peking University Beijing China

Most rainfall-induced landslide forecasting models focus on the relation between landslides and rainfall,which is one of the dynamic factors,and seldom consider the stacitc factors,such as geological and geograpical *** susceptibility,however,is determinded by both static and dynamic *** article proposes a static and dynamic factors-coupled forecasting model(SDFCFM) of regional rainfall-induced landslides,which quantitatively considers both the static and dynamic factors that affect *** generalized additive model(GAM) is applied to coupling both factors to get the landslide *** the case study,SDFCFM is applied to forecast the landslide occurrences in Shenzhen during a rainfall process in *** with the rainfall logistic regression model,the resulting landslide susceptibility map illustrates that SDFCFM can reduce the forecast redundancy and improve the hit *** is both applicable and *** application of SDFCFM in landslide warning and prevention system will improve its efficiency and also cut down the cost of human and matreial resources.

关键词： regional rainfall-induced landslides static and dynamic factors-coupled forcasting model(SDFCFM) generalized additive model(GAM) landslide susceptibility

The correlation of multi-angle thermal infrared data and the choice of optimal view angles

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Science china Earth Sciences 2004年第6期47卷 570-576页

作者： FAN Wenjie1 & XU Xiru1,2 1.institute of remote sensing and gis of peking university,beijing 100871,china 2.Center of remote sensing and gis of beijing Normal university,beijing 100875,china institute of remote sensing and gis of peking university Beijing China Center of remote sensing and gis of beijing Normal university Beijing China

Based on the matrix formula of thermal infrared radiant system, the components temperature can be retrieved by the inversive matrix. Around the stability problem of retrieved result, the research work we did was focused on (i) the correlation of (wk,j) which is the key to affect the retrieval accuracy, (ii) a general method which can help us find the number of retrievable parameters and evaluate the retrieval error before its performance, (iii) the choice of “optimal viewing angle group” based on the formula of absolute error propagation. The row winter wheat field was chosen as an example. The results can provide a theoretical basis for multi-angle thermal infrared remote sensing and components temperature retrieval.

关键词： components temperature retrieval, correlation, number of retrievable parameters, optimal viewing angle group.

Framework and development of digital china

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Science china(Technological Sciences) 2008年第S1期51卷 1-5页

作者： WU Lun & TONG QingXi institute of remote sensing and Geographical Information Systems,peking university,beijing 100871,china institute of remote sensing and Geographical Information Systems Peking University Beijing China

Digital china (DC) has recently drawn much attention. It is a strategic project for china in response to the challenge of sustainable development of population,re-source,and environment. Intending to establish the national information infra-structure (NⅡ),the DC project forms a solid foundation for Chinese informatization. In such an NⅡ,multi-sourced spatial data are integrated. They focus on various themes and have different space and time features. Based on the NⅡ,numerous applications and services can be developed so that spatial information will benefit everyone. Since lots of organizations,such as governments,universities,and en-terprises,are involved in the implementation of DC,the DC project will significantly prompt the relevant scientific research as well as economic progress in china.

关键词： Digital Earth Digital china spatial information sciences and technology

A method for blind separation of components information from mixed pixel

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Progress in Natural Science:Materials International 2006年第7期16卷 760-765页

作者： FAN Wenjie and XU Xiru ( institute of remote sensing and Geographical Information System, peking university, beijing 100871, china Center of remote sensing and gis of beijing Normal university, beijing 100875, china) peking Univ Inst Remote Sensing & Geog Informat Syst Beijing 100871 Peoples R China beijing Normal Univ Ctr Remote Sensing & GIS Beijing 100875 Peoples R China

In the field of remote sensing, it is important to separate the component information from mixed pixel. If the physical process of remote sensing can be expressed by a set of linear equations, the remote sensing information matrix is equal to the weight matrix multiplied by the component information matrix. Generally speaking, the precondition of retrieval of component information matrix is that the weight matrix is known. However, the blind signal separation (BSS) method can separate the matrix unconditionally, whose basic principle is that the additive information needing separation can be achieved from the statistical characteristics contained in a mass of samples in the remotely sensed information matrix. Therefore, the values of the component information matrix and the weight matrix can be estimated. The wave shape of components can be retrieved by BSS, but the amplitude cannot. In this paper, the plant-soil mixed pixels were chosen as the studying targets in this paper to quantitatively separate the component information and solve the uncertainty of BSS. Simulation and field test verify the reliability of the method. Results show that the BSS can be one of the effective methods of mixed pixel separation, and the foreground of application is very promising.

关键词： mixed pixel component information blind signal separation.

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, beijing 100871, china 2. Center of remote sensing and gis of beijing Normal university, beijing 100875, china institute of remote sensing and Geographical Information System Peking University Beijing China Center of remote sensing and gis of beijing 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

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 100875,china 2 institute of remote sensing and Geographic Information System,peking university,beijing 100871,china institute of Geography and remote sensing Beijing Normal University Beijing China institute of remote sensing and Geographic Information System Peking University Beijing 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

A common sense geographic knowledge base for GIR

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Science china(Technological Sciences) 2008年第S1期51卷 26-37页

作者： ZHANG Yi,GAO Yong,XUE LuLu,SHEN Si & CHEN KaiChen institute of remote sensing and Geographic Information System,peking university,beijing 100871,china institute of remote sensing and Geographic Information System Peking University Beijing China

As background knowledge of geographic information retrieval (GIR),the gazetteers have their limitations. In this paper we propose to develop and implement a com-mon sense geographic knowledge base (CSGKB) instead of the gazetteers. We define that CSGKB is concerned with the representation of geographic knowledge in human brain and the simulation of geographic reasoning in daily life. Traditional geographic information system (gis) is based on the model of map with its data based on geographic coordinates and its computation based on geometry. However,CSGKB,which is made up of geographic features and relationships and is based on qualitative spatio-temporal reasoning,can be viewed as the direct model of geographic world. This paper also discusses the characters of CSGKB and pre-sents its structure which is composed of knowledge base,inference engine,geo-graphic ontology and learner. The applications using CSGKB include geographic information retrieval (GIR),natural language processing (NLP),named entity rec-ognition (NER),Semantic Web,etc. At present,our work focuses on the design of geographic ontology and the implementation of the CSGKB knowledge base. In this paper we describe the CSGKB ontology structure,top ontology,geographic loca-tion ontology,spatial relationship ontology,and domain ontologies. Finally,we in-troduce the current state of implementation of CSGKB and give an outlook on our future researches.

关键词： geographic information retrieval common sense geographic knowledge base geographic ontology

Architecture and key technologies of grid geographic information system

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Science china(Technological Sciences) 2008年第S1期51卷 102-113页

作者： FANG Yu,HUANG Zhou,CHEN Bin,WU Lun & YIN DaFei institute of remote sensing and Geographic Information System,peking university,beijing 100871,china institute of remote sensing and Geographic Information System Peking University Beijing China

The highly efficient and stable collaborative computation platform for geospatial information can be constructed on the basis of Grid computing technology,com-bined with Peer-to-Peer (P2P) computing technology and geospatial database technology. This paper proposed the architecture and key technologies of the Grid gis (Geographic Information System) incorporated with P2P structure,and corre-spondingly a Grid gis prototype named Nebula was designed and then imple-mented. Nebula is a suite of middleware for geospatial Grid computing,which could be deployed onto various service nodes in network. Based on Grid protocols and infrastructure,Nebula provides invocation interfaces to users in form of Grid services. By using P2P message based communication mechanism,complex geospatial computation tasks could be accomplished by Nebula in a collaborative way. This paper introduced Nebula's architecture and key modules,and according to experimental data,we discussed the Grid gis's advantages,application scenar-ios and future directions.

关键词： Grid gis distributed geospatial computing Peer-to-Peer computing