Preliminary Study of Land Cover Changes on Mangrove Area Using Markov Chain – Cellular Automata (Case study: Teluk Batang, West Kalimantan Province Indonesia)
Keywords:Mangrove, Landcover changes, Markov chain - Cellular automata
Ecosystem of mangrove forest is one of wetlands forest which land cover changing because of human activities. On this study we utilized spatio-temporal data to investigate the classification methods and to predict the model of mangrove land-use change using CA- Markov model in Teluk Batang, West Kalimantan. The data collection was used Landsat 5 (TM), Landsat 7 ETM, and Landsat 8 OLI in 1997, 2002, 2011, and 2018. The classification method were compairing for the supervised classification of the minimum distance, parallelepiped and support vector machine (SVM). The result showed that the SVM method was the best classification. Mangrove forest areas in the years until 2018 has decreased from 2499.66ha to 2016.36ha. Based on the predicted image for 2025 with the 2018 classification result image, the area of mangrove forest will increase from 2018 to 2025 of 3093.3ha from 2016.36ha to 5109.66ha.