Modeling Land Cover Change Using Markov Chain- Cellular Automata in Sorong, West Papua Province

Abstract

Land cover change is a complex interaction of environmental and socioeconomic factors. The purpose of this article is to determine changes in land cover using satellite imagery data, predict land cover in the next ten years and determine the factors that affect land cover change. The Markov Chain and Cellular Automata (Markov-CA) approach have been applied to create land-use change modeling dynamics in Sorong Regency, Papua Barat, Indonesia. The multi-temporal remotely sensed data, Landsat 7 TM in 2003 and Landsat 8 OLI in 2017, were used to produce the landcover maps. The results showed that land cover change during 2003-2017 is dominated by reducing forested land and becoming settlement and shrub area. The integration of Markov Chain and Cellular Automata can construct a spatial prediction of land cover change in 2017-2025 in Sorong City. Therefore, this modeling can be used to create maps of land cover change in the future.