Modeling Land Use and Land Cover Dynamic Using Geographic Information System and Markov-CA

Abstract

The need for built-up area increases along with a rise in population growth in many regions. This phenomenon leads to a tremendous change in agricultural land and decrease in the environmental carrying capacity. Therefore, this study aims to determine Land Use and Land Cover (LULC) dynamics and the drivers used for its modeling in 2030. This is a quantitative study, which uses the dynamic models of Geographic Information System (GIS) and Markov-CA. Data were obtained from the CNES-Airbus satellite imageries in 2009, 2014, and 2019 by using Google Earth at East Cirebon. The drivers include road density, distance to CBD, total population, distance to settlements, land slope and distance to rivers. The interaction between drivers and LULC change was analyzed using binary logistic regression. The results showed that the rise of built-up area reached 36.4 percent and causes the loss of 0.78 km2 of agricultural land from 2009 to 2019. The LULC simulation in 2030 shows an increase in the built-up area by 82.85 percent with probabilities above 0.6. Meanwhile the significant drivers for changes include road density and distance to settlements. In conclusion, efforts to reduce LULC change in agricultural land into built-up area is by re-strengthening spatial planning-based environmental awareness for the community.
 Keywords: Built-up area; GIS; LULC; Markov-CA; Spatial modeling
 
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