Vegetation cover change detection (2000–2020) in Raub District, Malaysia using supervised and unsupervised classification techniques

This study evaluates and compares four algorithms: maximum likelihood classification (MLC), minimum distance classifier (MDC), parallelepiped classifier (PPC), and k-means clustering, on their performance in detecting change of vegetation cover from multi-temporal Landsat images in Raub District, Ma...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής

Κύριοι συγγραφείς:	Siti Salwa Shapiaai, Kean Hua Ang
Μορφή:	Artigo
Γλώσσα:	Inglês
Έκδοση:	Polish Academy of Sciences 2026-02-01
Σειρά:	Journal of Water and Land Development
Θέματα:	accuracy assessment k-mean maximum likelihood classification (mlc) minimum distance classifier (mdc) parallelepiped classifier (ppc) tropical deforestation
Διαθέσιμο Online:	https://journals.pan.pl/Content/138218/2026-01-JWLD-04.pdf
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