Intelligence Based Automatic Detection and Classification of Ground Collapses Using Object-Based Image Analysis Method:A Case Study in Paitan of Pearl River delta

摘要：

In this paper,a new method is proposed by applying case-based reasoning technique for detecting the ground collapses.The study demonstrates that the high resolution remote sensing images are suitable for monitoring the ground collapses in the study area with karst relief.With the help of object-based image analysis method,the generic algorithm (GA) for optimizing the spatial,shape,spectral,hierarchy and textural features was used in the multi-scale image segmentation with the good fitness value,and then the case library was built for detecting the collapse.The case library is reusable for place-independent detection.The proposed method has been tested in the Pearl River Delta in south China.The result of ground-collapse detection is well.

关键词： ground collapse CBR case library object-based classifications Genetic algorithms

作者: Jie Dou Xiao-zhan Zheng Jun-ping Qian Rui-hua Liu Qitao- Wu

作者单位: Guangzhou Institute of Geochemistry,Chinese Academy of Sciences Guangzhou 510640,PR China;Guangzhou Guangzhou Institute of Geological Survey,Guangdong 510500,PR China Guangzhou Institute of Geography Guangdong 510070,PR China;School of Geography and Planning,SunYet-S Guangzhou Institute of Geography Guangdong 510070,PR China

会议类型: 国际会议

会议名称: 第16届国际地理信息科学与技术大会(16th International Conference on GeoInformatics and the Joint Conference)

会议地点: 广州

会议语种:英文

在线出版日期: 2008-06-28（万方平台首次上网日期，不代表论文的发表时间）