Mapping Deforestation in The Tamiang Watershed Through NDVI Analysis of Sentinel-2 Imagery Based on Google Earth Engine

Faiz Urfan

Abstract


The Tamiang Watershed (DAS) faces pressure from human activities that cause deforestation and threaten water resource sustainability. This study aims to map and measure land cover changes, especially deforestation, in the Tamiang Watershed from 2021 to 2025. It uses the Google Earth Engine (GEE) cloud platform to analyse annual median composite images from Sentinel-2. The Normalized Difference Vegetation Index (NDVI) analysis reclassifies land cover into four categories. Change detection employs the post-classification comparison method to identify land conversions. Results reveal significant net deforestation, with high-density vegetation (forest) decreasing by 133.39 km² over five years. This loss was mainly converted into medium and low-density vegation, which rose sharply by 103.50 km². The findings highlight a rapid land clearing rate that threatens watershed degradation. The study recommends strengthening integrated, cross-jurisdictional watershed management and adopting machine learning techniques for future predictive analysis.

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References


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