Land Cover Changes Based on Landsat Imagery Interpretation

Abstract

This paper presents the use of satellite data (i.e., Landsat-5 & Landsat-8) to interpret the change of land cover from 1997 to 2020. The study area covers the administrative boundary of Lumajang Regency. The land-cover map of the year 1997 derived from Landsat-5. The Land-cover map of the year 2020 interpreted from Landsat-8. This study uses two methods of image classifications (i.e., unsupervised and supervised). The procedure includes image enhancement, registration, and classification. Then, classification results evaluated by confusion-matrix (overall and kappa accuracy). The supervised classification produces 7 classes of Land cover (i.e., forest, pavement/urban area), paddy field, plantation, rural area, water body and sand mining area. Unsupervised classification produced four 5 class i.e., forest, built-area, paddy field, rural area, and plantation. Supervised classification done the overall and kappa accuracy = 86% and  82%, while unsupervised classification = 73% and 64% for 1997 imagery. Furthermore, for 2020 image, the Supervised classification reaches the overall and kappa accuracy = 93% and  90%, while unsupervised classification done 81% and 72%. The supervised classification method gives a better result than un-supervised. Comparison of 1997 to 2020, it also shows the increase in pavement or build-area, followed by paddy field, rural area, and sand-mining. The change also appears as the decrease in forest and plantation areas.Keywords:   Landsat-5, Landsat-8, Unsupervised, Supervised, Lumajang