Cellular Automata and Markov Chain Spatial Modeling for Residential Area Carrying Capacity in Samarinda City, East Kalimantan Province

The increase of population could leads to residential area availability. This could lead to imbalance between population and available housing and could results in higher population pressure on the available area. Spatial modeling prediction is needed as a prevention step to prevent excessive land cover change in the future. This research aims to analyze residential area carrying capacity and spatial modelling of land cover change of Samarinda in 2006, 2014 and 2020 using Cellular Automata Markov Chain (CAMC) and residential area carrying capacity index. The Cellular Automata Markov Chain (CAMC) results show that there is an expansion of residential area land cover which affected by driving factors that consist of distance from the nearby road, distance from the river, distance from the point of interest (health facility and education facility), slope, and elevation. Residential area land carrying capacity affected by population density, standard needed land area, and residential area extent in Samarinda City. Thus, it is needed to analyze the model to see the available area for residential area development sustainably.