The Implementation of Classification and Spectral Transformation Methods, Based on Extraction Landsat Imagery for Growth Center Mamminasata Region

Abstract

Urban growth begins from a center and affects its surrounding area, and this is due to the emergence of additional centers that will serve as a growth pole. Assessment of the dynamics of urban growth, some data, and extraction analysis methods are needed. This research examines various information by extracting of growth center area of Landsat 8 OLI / TIRS 2017 and utilizing spectral resolution on Landsat images in the Mamminasata region. The classification method tested is the OBIA classification and the Maximum Likelihood classification methods. Simultaneously, the Landsat image’s spectral resolution is maximized by spectral channel transformation sensitive to the building object. It is usually called the urban index. This study indicates that the OBIA classification method and NDBI spectral transformation proved to produce maps. It can also show center location growth with the best accuracy, especially in the Mamminasata region. Total accuracy from the accuracy-test matrix is 71.48% for building intensity and 78.57% for growth centers.