A review of assessing the accuracy of classifications of remotely sensed data
Generate an AI Snapshot to get a quick, structured summary of this paper.
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
This paper reviews the necessary considerations and available techniques for assessing the accuracy of remotely sensed data including the classification system, the sampling scheme, the sample size, spatial autocorrelation, and the assessment techniques.
Abstract
This paper reviews the necessary considerations and available techniques for assessing the accuracy of remotely sensed data. Included in this review are the classification system, the sampling scheme, the sample size, spatial autocorrelation, and the assessment techniques. All analysis is based on the use of an error matrix or contingency table. Example matrices and results of the analysis are presented. Future trends including the need for assessment of other spatial data are also discussed.