Penggunaan DTM Presisi dari Fotogrametri UAV untuk Analisa Bencana Longsor Menggunakan Sistem Informasi Geografis - Vikanisa Rahmadany; Martinus Edwin Tjahjadi; Fransisca Dwi Agustina (Universitas Negeri Gorontalo, 2022)
The morphologies of the Pandansari Village (Ngantang District, Malang Regency, Indonesia) are vulnerable to landslide disasters that may damage human properties, infrastructures, and even fatalities. Landslide disaster mitigation can be carried out by conducting disaster-prone mapping utilizing Unmanned Aerial Vehicle (UAV) photogrammetry along with geographic information systems (GIS) to produce precise Digital Elevation Model/Digital Terrain Model (DEM/DTM). The purpose of this study is to analyze areas prone to landslides using precision DTM data from UAV technology integrated with geospatial data. DEM is widely used for disaster mapping applications in the form of DTM, representing the ground surface. DTM can be generated from UAV images with photogrammetric processing and additional procedures for removing non-ground objects. This study utilizes PCI Geomatics software to remove vegetation and human-made objects off the ground surfaces semi-automatically. The evaluation revealed that LE 90% of the DTM has only deviated at approximately 0.81 m. This value follows the introductory map geometric accuracy provisions according to BIG No.15 of 2014 for a scale of 1:2500 in class 2. The landslide hazard map classifications using the landslide estimation Puslittanak are dominated by a high classification landslide hazard level with an area of 20.1 ha (48%). In addition, the validation of the landslide-prone map using the accuracy assessment method obtained a percentage of 83%.