Pemetaan Tutupan dan Penggunaan Lahan Perkotaan Beresolusi Tinggi Menggunakan Fotogrametri Berbasis Drone untuk Mendukung Evaluasi Pemanfaatan Ruang - Ivan Frits; Willem A Siahaya; Rafael Marthinus Osok (MAKILA, 2026)
Accurate and high-resolution land cover and land use (LCLU) data are essential for spatial utilization evaluation in urban areas. This study aimed to produce a detailed LCLU map of Masohi District using UAV-based photogrammetry and evaluate its geometric accuracy. UAV aerial photographs were processed through geometric correction and supervised classification using the Maximum Likelihood algorithm. Geometric accuracy was assessed using Independent Check Points (ICP), Root Mean Square Error (RMSE), and Circular Error 90% (CE90). The classification identified 44 LCLU classes, with settlements and yards as the dominant land uses. The resulting map achieved a CE90 value of 11.604 cm, meeting national photogrammetric mapping standards. Overlay analysis showed strong spatial agreement between the classified map and UAV imagery. These findings demonstrate that UAV photogrammetry can provide accurate and high-resolution spatial data to support spatial utilization evaluation and urban planning in data-limited regions.