High-Resolution UAV Orthophoto Mosaics of Chamanculo C, Maputo (Mozambique)

Description Dataset Overview This dataset contains high-resolution orthophoto mosaics generated from an Unmanned Aerial Vehicle (UAV) survey conducted in the Chamanculo C neighborhood, located in the Nlhamankulu urban district of Maputo, Mozambique. The flight operations were carried out on August 23, 2026, starting at 06:26 AM (CAT). Study Area: Chamanculo C Chamanculo C is an informal, densely populated peri-urban neighborhood in inner Maputo characterized by high architectural density, narrow unpaved pathways, complex informal infrastructure, and vulnerability to urban flooding. High-resolution spatial data for this area provides crucial baseline information for urban planning, risk mapping, informal settlement upgrading, and infrastructure management (Guy Norman et al. 2020, Marquez Martin et al.  2025,  Sara Márquez Martín et al 2024) Acquisition & Camera Parameters Images were captured using a commercial DJI Mini 4 Pro drone. Flight parameters and optical sensor characteristics include: Flight Altitude: ~100 meters Above Ground Level (AGL) Ground Sampling Distance (GSD): ~2.3 cm/pixel (at 100 m AGL in standard 12 MP capture mode) Image Sensor: 1/1.3-inch CMOS sensor Effective Resolution: 12 Megapixels (4000 × 3000) / 48 Megapixels Native Lens / Lens Focal Length: FOV 82.1°, 6.72 mm actual focal length (24 mm full-frame equivalent focal length) Aperture: f/1.7 Data Capture & Flight Plan The survey covered the target area through a meshgrid grid layout divided into 5 flight tiles (arranged in a 10×15 grid structure). A total of 750 aerial photographs (~150 images per tile) were collected with standard longitudinal and lateral overlaps suited for photogrammetric reconstruction. Photogrammetric Processing The raw aerial imagery was processed using OpenDroneMap (OpenDroneMap Authors ODM 2020) , open-source Structure-from-Motion (SfM) photogrammetry processing nodes. The pipeline performed feature matching, sparse/dense point cloud generation, Digital Surface Model (DSM) generation, and orthorectification, resulting in 5 distinct orthophoto GeoTIFF tiles.