文章基本信息

标题：Automatic Feature-level Change Detection (flcd) for Road Networks
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作者：H. Sui ; D. Li ; J. Gong 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2004
卷号：XXXV Part B2
页码：459-464
出版社：Copernicus Publications
摘要：Automatic change detection and data updating is a very important issue for keeping the temporal accuracy and currency of spatial data sets. Road networks are one of the most important parts of geographic database. Firstly two kinds of new algorithms for detecting feature changes that is buffer detection (BD) algorithm and double-buffer detection (DBD) algorithm are illustrated in detail. The corresponding buffer detection distance formulas are deduced theoretically. Then the change detection techniques between new map and old map are proposed. For change detection between new/old maps with same map scale the so-called buffer detection algorithm is employed and for new/old maps with different map scale a change detection expert system integrated with GIS environment is presented. Corresponding experiments results for detection algorithms are given in the paper. The main difficulty of automatic change detection for road network between new image and old map lies in two aspects: one is the tracing of unchanged road and another is the extraction of new road. For detection and tracing of unchanged old road, automatic detecting algorithms based on GIS information are proposed. For the extraction of new road, some new ideas and strategies including hybrid feature grouping techniques, automatic road recognition based on knowledge base, knowledge inference for road recognition, road re-grouping etc. are discussed. At last conclusions and future work are given
关键词：Feature Level Change Detection; Remote Sensing; GIS; Feature Extraction; Knowledge base; Expert System