ArticleData in brief2026
UAV-LiDAR dataset of Pangandaran coastal tourism hotspots for tsunami and climate risk valuation and exposure mapping.
Article in Data in brief, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This article presents a high-resolution UAV-LiDAR dataset acquired over the main coastal tourism hotspots of Pangandaran, West Java, Indonesia (WGS84 / UTM Zone 49S). The survey was conducted using a DJI Matrice 300 RTK equipped with a CHCNAV AA450 LiDAR system at altitudes of 77-83 m AGL, following grid-based flight lines with 80% forward and 70% side overlap. The final point cloud, delivered in LAS format, exhibits a mean density of approximately 865 pts/m², with dominant values of 600-800 pts/m² across roads, roofs, and open terrain, and localized peaks exceeding 3,000 pts/m² in areas of flight-line overlap. Ground control was established using three static base stations, with 14 calibration control points and 8 independent validation check points. Accuracy assessment yields RMSE values of 0.072 m (Easting), 0.062 m (Northing), and 0.138 m (Elevation), with corresponding mean biases of 0.017 m, 0.017 m, and 0.044 m, confirming centimeter-level positional precision suitable for detailed coastal mapping. The dataset includes DSM and DTM derivatives, block-based tiles, metadata, and processing reports, supporting its use in tsunami exposure assessment, climate-risk valuation, urban coastal planning, and remote-sensing education. As one of the first openly accessible UAV-LiDAR datasets for an Indonesian coastal tourism hotspot, it provides a reproducible, high-density 3D resource for research, hazard analysis, and sustainable coastal development.
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