Land Use Change Analysis Using Plugin MOLUSCE in Yogyakarta Urban Agglomeration Area

Rapid and dynamic changes in land use have the potential to impact a variety of environmental and socio-economic factors. This research endeavors to project land use change in the Yogyakarta Urban Agglomeration Region in 2024 and 2026 by leveraging image analysis technology. The proposed methodology involves the implementation of image analysis through the utilization of the MOLUSCE (Modeling Land Use Change) plugin and Artificial Neural Networks (ANN). The MOLUSCE plugin facilitates the modeling and simulation of land use change, informed by historical data and environmental variables. The employment of ANN enhances prediction accuracy by leveraging its sophisticated and non-linear data processing capabilities. The satellite image data from recent years was processed to identify patterns of change and their driving factors. The analysis of land use change between 2024 and 2026 in the study area revealed a substantial increase in built-up land, amounting to 9.03%, indicative of the proliferation of urbanization. Conversely, green open space witnessed a substantial decline of 25.96%, signifying the conversion of green land into built-up land.