Analisis Komparasi Melalui Citra Satelit Sentinel dan Landsat untuk Pemantauan Pelaksanaan Reklamasi Lahan Bekas Tambang Batubara - Tedy Meilyanto; Hery Suhartoyo; Yansen Yansen; Wiryono Wiryono; Agus Susatya (Badan Penerbitan Fakultas Pertanian (BPFP), Universitas Bengkulu, 2025)
Mining activities can cause environmental degradation, especially in the form of changes in land cover and loss of vegetation. Therefore, monitoring the success of reclamation is important to ensure the restoration of post-mining ecosystems. This study aims to (1) monitor the implementation of post-mining land reclamation of PT. Bukit Sunur by analyzing canopy density or vegetation cover through Landsat and Sentinel imagery using the ArcGIS 10.8 platform, and (2) compare the NDVI values from both satellite images in the 2016, 2020, and 2024 periods to see the differences in the level of reclamation success detected by each satellite sensor. This study uses a remote sensing analysis method, where Landsat and Sentinel images are processed to extract NDVI (Normalized Difference Vegetation Index) values to identify changes in vegetation density over time. Vegetation density classification is carried out using the Kappa index and Overall Accuracy (OA) calculations to measure the accuracy of image classification. The results show that the reclamation of post-mining land of PT. Bukit Sunur experienced a significant increase in vegetation density. In 2016, most of the area was still dominated by the Low to Moderate Vegetation category, but in 2020 there was an increase in the area of High Vegetation due to the transition from the Fairly High Vegetation class. Furthermore, in 2024, Very High Vegetation increased drastically from 0 ha to 267 ha, indicating the success of reclamation in improving land cover. Furthermore, a comparison of Landsat and Sentinel imagery shows a similar trend of NDVI changes, although Sentinel provides a higher resolution in detecting detailed vegetation changes. Overall Accuracy (OA) and Kappa Index (KA) values reached 97%-100%, indicating a very high level of classification accuracy. The conclusion of this study is that reclamation monitoring using satellite imagery has proven effective in identifying vegetation changes over time, with Sentinel showing superiority in more detailed resolution co mpared to Landsat. The results of this study can be used as a basis for evaluating mine reclamation programs and planning for post-mining ecosystem sustainability. Keywords: Landsat, Mining Land Reclamation, NDVI, Sentinel, Vegetation Density