Land Cover Changes from Forest Fires Using CA-Markov in Pelalawan, Indonesia

Abstract

Forest and land fires pose significant risks to ecosystems, particularly in Pelalawan Regency, Indonesia, where slash-and-burn practices during the dry season exacerbate peatland degradation. This study integrates Cellular Automata (CA) and Markov-chain analysis to model and predict land cover changes and carbon stock dynamics over the next 20 years. The model projects spatial patterns of land cover changes from 2002-2033 by analyzing historical forest fire intensity and land use data. The study incorporates three key variables: CA simulation results, landscape carbon assessment, and forest fire vulnerability to develop spatial planning scenarios aimed at mitigating fire risks and supporting sustainable development. The results show a substantial decline in forest cover (from 92% in 2002 to an estimated 22% by 2033), alongside an increase in non-forest land use. Carbon stock analysis highlights a significant release of 18 million tons of carbon dioxide due to forest degradation. This research provides actionable insights for policymakers in spatial planning and fire risk management to balance ecological preservation with development demands.