Geographia Technica, Vol 20, Issue 2, 2025, pp. 283-302
PREDICTION OF SPATIAL LAND USE LAND COVER CHANGES IN BOVEN DIGOEL, SOUTH PAPUA IN 2031 AND 2041 USING LCM AND CA-MARKOV MODELS
Dewi Novita SARI 
, Muhammad Hafizh Fadhl MUTASHIM, Frichelia Varadhita RESTUVICA, Kusuma Prayoga Basuki PUTRA, Aziz Akbar MUKASYAF , Nirma Lila ANGGANI , Ayodya Rido NUGRAGA
ABSTRACT: Boven Digoel Regency, located in South Papua Province, is one of the eastern regions of Indonesia targeted by the government for the development of a food estate project. However, massive land use and land cover (LULC) change require careful prediction over the coming decades to balance development with environmental sustainability. This study integrates advanced spatial modeling techniques to analyze recent trends and predict future LULC changes for 2031 and 2041. The objectives of this study are (1) to analyze the trend of forest to non-forest land use change in Boven Digoel Regency in 2024 using Land Change Modeler (LCM) and (2) to analyze the prediction of forest to non-forest land use change in 2031 and 2041 using Cellular Automata Markov (CA-Markov). The data used in this study include the administrative boundary of Boven Digoel, SPOT 6/7 imagery from 2016 and 2021, Digital Elevation Model (DEM), road network, government centers, river network, and settlements. The methods used in this study are a deep learning approach based on the LCM and a CA–Markov model, which combines CA-Markov land cover prediction methods. Results show that forest areas increased by 27.58% from 2016 to 2021 but are predicted to decline by 18.73% in 2031 and 51.49% in 2041, mainly due to ongoing plantation expansion in southern and northern Boven Digoel. This plantation expansion is predicted to spread from the southern and northern parts of Boven Digoel. Future studies should incorporate updated boundary information and integrate socio-economic, policy, and environmental drivers, such as soil and rainfall, to improve spatial accuracy and enhance the relevance of land use and land cover analysis.
Keywords: LULC change, Multi-Criteria, LCM, CA-Markov, GIS
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