Estimation of fuzzy error matrix accuracy measures under stratified random sampling

Stephen V. Stehman, Manoj K. Arora, Teerasit Kasetkasem, Pramod K. Varshney

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Abstract

A fuzzy error matrix may be used to summarize accuracy assessment information when both the map and reference data are labelled using a soft classification. Accuracy measures analogous to the familiar overall, user's, and producer's accuracies of a hard classification can be derived from a fuzzy error matrix. The formulas for estimating the fuzzy error matrix and accompanying accuracy measures depend on the sampling design used to collect the reference data. We derive these estimation formulas for stratified random sampling, a design commonly implemented in practice. A simulation study is conducted to confirm the validity of the stratified sampling estimators.

Original languageEnglish (US)
Pages (from-to)165-173
Number of pages9
JournalPhotogrammetric Engineering and Remote Sensing
Volume73
Issue number2
DOIs
StatePublished - Feb 2007

ASJC Scopus subject areas

  • Computers in Earth Sciences

Fingerprint

Dive into the research topics of 'Estimation of fuzzy error matrix accuracy measures under stratified random sampling'. Together they form a unique fingerprint.

Cite this