Spatial Dynamic Analysis of Changes in Land Use Applying Markov Chain and Cellular Automata

Abstract

Changes in land use in the Alo Pohu watershed have concerned the government in preventing the siltation of Limboto Lake, along with floods and slides. On that ground, the present study was conducted to analyze the spatial prediction of land-use changes in the Alo Pohu watershed, Gorontalo Regency, Indonesia, in the 2000-2017 period for the 2030 land use prediction. The method and analysis of spatial data to predict land-use changes involved the Powersim Version 10 and Idrisi apps. Further, the data consisted of two maps, i.e., the Indonesian topographical map and land use map. The Markov chain model applied to predict the land in the site area for the year of 2030 has an excellent suitability/agreement. Based on the validation test with the Kappa Index of Agreement, the value of K-standard gets 0.8 from 0-1 scale. Another validation using Google Earth is also employed, in which it shows an 83% of suitability level. Confirmed by the integration of the dynamic system simulation model, the map of land use resulting from the modeling is therefore scientifically acceptable. The study concluded that land conversion in the Alo Pohu watershed in Gorontalo Province has occurred.