Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/27743
Title: Geographically weighted methods for estimating local surfaces of overall, user and producer accuracies
Authors: Comber, Alexis J.
First Published: 12-Nov-2012
Publisher: Taylor & Francis
Citation: Remote Sensing Letters, 2013, 4 (4), pp. 373-380.
Abstract: The confusion matrix is the standard way for reporting the accuracy of land cover and other information classified from remote-sensing imagery. This letter describes a geographically weighted method for generating spatially distributed measures of accuracy (overall, user and producer accuracies) from a logistic geographically weighted regression. A kernel-based approach defines the data and weights that are used to calculate the accuracies at each location in the study area. The results compare the global accuracy measures from a standard confusion matrix with those that have been allowed to vary locally. Maps of spatially varying user and producer accuracies describe the spatial autocorrelation of error. The use of geographically weighted models in the context of land cover accuracy is discussed and suggested as a generic approach for examining how and where error processes vary.
DOI Link: 10.1080/2150704X.2012.736694
ISSN: 2150-704X
eISSN: 2150-7058
Links: http://www.tandfonline.com/doi/abs/10.1080/2150704X.2012.736694
http://hdl.handle.net/2381/27743
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2012 Taylor & Francis. Deposited with reference to the publisher's archiving policy available on the SHERPA/RoMEO website. This is an Author's Accepted Manuscript of an article published in Remote Sensing Letters, 2013, 4 (4), pp. 373-380. Copyright Taylor & Francis, available online at: http://www.tandfonline.com/10.1080/2150704X.2012.736694
Appears in Collections:Published Articles, Dept. of Geography

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