Evaluasi Indeks Vegetasi Merah Hijau Biru dari Citra UAV untuk Pemantauan Tutupan Tajuk pada Area Revegetasi Pascatambang Batubara di Kalimantan Selatan: Evaluation of Red Green Blue Vegetation Index (RGBVI) from UAV Imagery for Monitoring Canopy Cover in Post Coal Mining Revegetation Areas of South Kalimantan - Noor Hadi, Wirawan; Satriadi, Trisnu (Jurusan Kehutanan, Fakultas Pertanian Universitas Palangka Raya, 2025)
The success of revegetation in post-coal mining areas is generally evaluated through manual field surveys, which are time-consuming, costly, and often subjective. This study offers an alternative quantitative approach using the Red-Green-Blue Vegetation Index (RGBVI) calculated from high-resolution drone imagery to monitor canopy cover in coal mine reclamation areas. The research was conducted on a 1-hectare reclamation site located in Tabalong District, South Kalimantan, Indonesia. UAV flights were carried out using a DJI Phantom 4 Pro at an altitude of 100 meters and analyzed with QGIS 3.34. Vegetation cover was classified using the RGBVI formula with a threshold value of 0.30 and validated through field measurements of canopy diameter. The results showed that canopy cover derived from image analysis reached 69%, while the ground check data indicated 75%, yielding an accuracy level of 92%. The RGBVI effectively distinguished between vegetated and non-vegetated areas and demonstrated a strong correlation with field data. These findings confirm that RGB drone imagery is a reliable, efficient, and low-cost ecological monitoring tool that supports the development of digital reclamation evaluation systems in tropical mining regions.