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《Geo-Information Science》 2008-06
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Forest Fuel Types Classification and Change Detection by Remote Sensing in Zhangping City

CHEN Yunzhi,CHEN Chongcheng,WANG Xiaoqin,TANG Liyu(Key Lab.of Spatial Data Mining & Information Sharing of Ministry of Education, Spatial Information Research Center,Fuzhou University,Fuzhou 350002,China)  
Forest fuel type's spatial distribution is one of the key factors to be considered during forest fire spread and fire-fighting visualization modeling and simulation.Based on review of the status of the study on forest fuel type classification,a classification method considering tree types was put forward.According to the attribute of predominant tree types of 2003 forest stand layers,four forest fuel types,i.e.,bamboo forest,broad-leaved forest,Chinese fir forest,and Masson pine forest and their spatial distribution in Zhangping was acquired firstly.The object-oriented classification technology,which using the techniques of image segmentation to construct objects containing information of size,shape,topography and class hierarchy besides spectral information,and involving procedures of segmentation,construction of class hierarchy,and classification,was then applied to the ASTER images to detect interior and exterior change of each type's.Accuracy assessment of the classification result indicated that by the technology of object-oriented classification,both the spectral features and class-related features were used,and the accuracy was improved in terms of area,reaching 89.3%.Because thematic layers were involved during the image segmentation,the boundaries of objects did not get across the boundaries of each thematic layer,this makes the updating of the existing layers become very convenient.Finally,the vector format data of remote sensing classification result was used to update the original forest stand layer in order to get the available inputs of fire visualization modeling.This study not only provided up-to-date input layers of forest fuels types for fire visualization modeling,but also detected the areas which have been changed without changing the boundaries of the original forest stands.For forest resource managers,it provided target areas for validation by field survey.
【Fund】: 国家973前期研究专项(2004CCA02100)“基于多尺度遥感动态信息的分布式虚拟地理环境研究”;; 国家自然科学基金(30671680)“基于本体的协同式虚拟森林环境研究”
【CateGory Index】: S762
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