Linking Forest-Area Conversion And Land-Cover Change In Central Sulawesi Grand Forest Park
DOI:
https://doi.org/10.55173/agriscience.v10i1.213Keywords:
forest-function conversion; land-cover change; Grand Forest Park; remote sensing; Random ForestAbstract
Studies on forest-area conversion generally examine land-cover dynamics and forest policy separately, leaving the relationship between formal changes in forest designation, actual landscape conditions, and their underlying institutional factors insufficiently understood. This study addresses this gap by integrating multi-temporal land-cover classification with policy, regulatory, and interview analyses to evaluate the conversion of part of the Central Sulawesi Grand Forest Park (Tahura). Sentinel-2 imagery from 2019, 2020, and 2025 was classified using the Random Forest algorithm on the Google Earth Engine platform. The spatial findings were complemented by document analysis and semi-structured interviews with three key informants from relevant forestry institutions. Classification performance showed Overall Accuracy values of 92.99%, 89.77%, and 95.30%, with Kappa coefficients of 0.8855, 0.81, and 0.86 for 2019, 2020, and 2025, respectively. The results indicate that the Tahura area decreased from 7,128 ha to 5,149 ha following Minister of Environment and Forestry Decree No. SK.6624/MENLHK-PKTL/KUH/PLA.2/10/2021. The converted area comprised 1,933 ha designated as Limited Production Forest and 46 ha as Other Land Use Areas. In 2025, the remaining Tahura was dominated by primary forest covering 3,105.38 ha (60.31%) and secondary forest covering 1,040.47 ha (20.21%). Although the conversion complied with formal procedures, it revealed tensions between regional development interests and conservation objectives. The novelty of this study lies in linking legally mandated forest-area conversion with empirically observed land-cover dynamics and institutional explanations within a single analytical framework. Practically, the findings provide a basis for post-conversion monitoring, rehabilitation prioritization, spatial-policy evaluation, tenure-conflict resolution, and the protection of ecologically important areas.
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