Analisis Spasial dan Temporal Tanaman Eceng Gondok di Danau Rawa Pening Tahun 2021-2025
Studi Kasus di Danau Rawa Pening
DOI:
https://doi.org/10.55606/sinov.v8i1.877Keywords:
Google Earth Engine, Random Forest, Remote Sensing, Spatial-Temporal Analysis, Water HyacinthAbstract
Lake Rawa Pening is one of Indonesia’s priority lakes facing serious ecological pressure due to the rapid proliferation of water hyacinth. This study aims to classify and map the distribution of water hyacinth in Rawa Pening Lake during the 2021–2025 period and to analyze the seasonal distribution patterns of water hyacinth. Sentinel-2 imagery processed on the Google Earth Engine platform was classified using the Random Forest algorithm combined with hybrid sampling and spectral indices (NDVI, NDWI, MNDWI, and SRI). Classification accuracy assessment showed high performance with an Overall Accuracy of 97.45% and a Kappa coefficient of 0.949. The results indicate significant spatial-temporal fluctuations, with the highest coverage recorded in March–April 2021 (855.75 ha) and the lowest in May–June 2022 (108.44 ha). Seasonal-Trend Decomposition using Loess (STL) revealed consistent seasonal patterns, with peak expansion occurring during the rainy season, particularly in January–February. Although initial implementation of lake management policies reduced coverage, subsequent increases suggest that control measures remain insufficiently sustainable. This study demonstrates the effectiveness of cloud-based satellite monitoring for evaluating lake management policies and supporting evidence-based environmental management strategies.
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