Using Remote Sensing for Mapping Land Use/Land Cover of The City of Baubau, Southeast of Sulawesi Rini Anggraini, S Baja, R Neswati
1 Post Graduate Student of Regional Planning and Development, Hasanuddin University,
Makassar, Indonesia
2 Department of Soil Science, Hasanuddin University, Makassar, Indonesia
Abstract
Land use and land cover (LULC) mapping is a crucial instrument in spatial planning and environmental management, particularly in urban areas with high spatial dynamics. This study aims to update the LULC map of BauBau City (study area 28,619 ha) using Landsat 8 imagery (September
2024). The method employed is supervised classification using the Maximum Likelihood Classification (MLC) algorithm, supplemented by manual interpretation to enhance classification accuracy. The research process includes data preprocessing (geometric, radiometric, and atmospheric corrections), image classification, and accuracy testing using the stratified random sampling approach at 300 reference points. The initial classification results identified five land cover classes, which were then refined through manual interpretation to produce five main classes: forest, agriculture, built up land, open land, and water bodies. The evaluation yielded an overall accuracy of 91.7% and a Kappa coefficient of 0.843, indicating an extreme level of classification suitability for field conditions. This combined approach has proven effective in enhancing the spatial and thematic representation of LULC mapping and can support sustainable, data-driven urban development planning.
