文章基本信息

标题：Post-Classification of Misclassified Pixels by Evidential Reasoning: A GIS Approach for Improving Classification Accuracy of RS Data
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作者：Yeqiao Wang
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：1992
卷号：XXIX Part B7
页码：80-86
出版社：Copernicus Publications
摘要：This paper discusses an approach for extracting supporting evidence from multisource spatial data and by rule-based modelsto incorporate the evidence with pre-classified Landsat TM data for improving classification accuracy. The process wasfocused on the extracted "possibly misclassified pixels" (PMPs) only. Based on Dempster-Shafer's theory of evidence, theconcepts of homogeneous, heterogeneous. and conflicting evidence and the rules for evidential combination are discussed.Boolean logic, conditional statement, and spatial relationship operations were employed in the models. By running the models,correct labels for the PMPs were judged by pooled evidence from multitemporal Landsat TM data and multisource spatial data
关键词：Post-classification; multisource data; evidential reasoning; modeling