文章基本信息

标题：Calibrating quantitative errors on categorical maps using the contingency table
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作者：DongMei Goodchild Michael Chen
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：2007
卷号：XXXVI-2/C43
出版社：Copernicus Publications
摘要：This paper presents and compares approaches of estimating true area on the ground and calibrating quantitative errors of area esti- mate on categorical maps from the contingency table. Results directly estimated from the contingency table and those from two cali- bration methods were compared on two maps of 10 different land cover classes with known errors between them. The estimated true area percentage from the contingency table and two calibration approaches showed obvious improvement when compared with un- calibrated values. However, there is no significant difference among the estimates from the contingency table and the two calibration methods. Although the inverse method led to mean estimates closer to the true values for all classes than other methods, comparing the individual area estimates for each class showed that the inverse method did not always produce the most accurate estimate. Ho- mogeneous classes with high classification accuracy have a better chance of achieving more accurate estimates from calibration than heterogeneous classes. Compared with large classes, classes covering a small percentage of a map are more vulnerable to the quanti- tative error and more sensitive to sampling error
关键词：Categorical map; Area estimation; Quantitative error; Sampling; Contingency table; Calibration model