Prediksi Perubahan Penggunaan Lahan dan Pola Berdasarkan Citra Landsat Multi Waktu dengan Land Change Modeler (LCM)

Abstract

Land use/cover greatly affect the quality of an area. Therefore, many regional planners need assistance byother fields, such as geoinformatics, computer science, environment, and others. Although prediction and forecasting have been widely studied, in regardto real conditions (geospatial)itstill needmoredevelopment, especially thoseinvolving a combination of regional types, such as urban and suburban areas. This study uses a remote sensing base and geographic information system in predicting land in the city and district of Bekasi, West Java, Indonesia. With two scenarios compared (business as usual and vegetation conservation), the model that has been created and validated (with an AUC accuracy result of 0.828) is used to predict land use change until 2030. Scenarios with vegetation conservation are able to keep green areas to switch to land types others, such as buildings and industry

Integration of LULC change/prediction and hydrological modeler for assessment of the effect of LULC Change on peak discharge in Sari Watershed, Sumbawa Island, Indonesia

“…Understanding LULC change/prediction and its influence on discharge are necessary information in flood risk reduction planning. Regarding the analysis of LULC change and prediction, Cellular Automata Markov (CA-Markov) model was widely applied modeling for several studies [6][7] [8]. The combination of CA-Markov and remote sensing/GIS technology was a powerful method for evaluating LULC dynamics spatially and temporally.…”

“…In Indonesia, many studies of LULC change and prediction have been carried out using the CA-Markov model. For example, the study of LULC Change/prediction in the city of Surabaya [9], in the town of Bekasi [6] in the Bila watershed of South Sulawesi [10], in Lampung Regency [11], in Cirebon City [7], and the Citarum Watershed of West Java [12].…”