Monitoring of Land Use and Land Cover Changes Based on Machine Learning in Rokan Hilir Peat Hydrological Unit, Riau
Monitoring Perubahan Tutupan dan Penggunaan Lahan Berbasis Machine Learning di Kesatuan Hidrologis Gambut Rokan Hilir, Riau
DOI:
https://doi.org/10.59465/jpht.v23i1.991Kata Kunci:
Degradation, land use-land cover, peatland, random forestAbstrak
Rokan Hilir Regency is one of the regencies in Riau that has experienced a high rate of peatland conversion. This study aims to identify the land cover and land use types that have undergone the most significant changes and to estimate the area of land cover and land use with the greatest changes in the Rokan Hilir Peat Hydrological Unit (PHU) from 2005 to 2023. A total of 12 algorithms index were used in the analysis. Land cover and land use were classified into 6 categories e.g water bodies, built-up land, bare land, oil palm plantations, natural forests, and forest plantations. The machine learning method used was Random Forest (RF). The results of the study show that between 2005 and 2023, the land cover types that experienced the most area decrease were natural forests (119,186.3 ha) followed with forest plantations (72,135.6 ha). The land use types that showed the most area increase were oil palm plantations (146,384.7 ha) and built-up land (22,101.2 ha).
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