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Submitted
April 27, 2026
Accepted
September 29, 2026
Published
October 1, 2026
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Abstract

Tropical peatland degradation remains a critical environmental challenge in Southeast Asia, yet operational monitoring frameworks that align with governance boundaries remain limited. This study aimed to develop an open-data remote sensing framework for assessing peatland condition at the Peat Hydrological Unit (Kesatuan Hidrologis Gambut, KHG) scale in South Sumatra, Indonesia. Using Google Earth Engine, four satellite-derived indicators were extracted annually for 12 KHGs over seven years from 2018 to 2024: Normalized Difference Water Index from MODIS MOD09A1, Enhanced Vegetation Index from MODIS MOD13Q1, fire frequency from NASA FIRMS, and surface water extent from the JRC Global Surface Water dataset. The indicators were normalized and integrated into a weighted composite score using weights of 30% for NDWI, 25% for EVI, 30% for inverse fire frequency, and 15% for surface water extent. In 2024, seven KHGs were classified as At Risk and five as Intact/Recovering, with scores ranging from 46.5 to 76.9. Six KHGs declined between 2018 and 2024, while five improved. El Nino years reduced health scores by an average of 11.3 points, and cropland conversion was the strongest land-cover predictor of lower scores (r=−0.52). Weight sensitivity analysis showed that seven of twelve KHG classifications remained stable across five weighting scenarios. The framework was reproducible, governance-aligned, and suitable as a screening tool for peatland restoration prioritization.

Keywords

Google Earth Engine multi-criteria assessment peat hydrological unit peatland monitoring remote sensing

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Copyright (c) 2026 Muaffan Wisaksono, Abdhullah Syawalbhi Leo

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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Wisaksono, M. A., & Syawalbhi Leo, A. (2026). Open-data remote sensing framework for peat hydrological unit condition scoring in South Sumatra Peatlands (2018-2024). Jurnal Lahan Suboptimal : Journal of Suboptimal Lands, 15(2), 106–119. https://doi.org/10.36706/jlso.15.2.2026.818
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