Anisa Nabila Rizki Ramadhani, Berliana Dwi Prapningtyas, Aria Fathi Izaz, Zulfadly Deaz Putra, Rifa Putri Nur Azizah, Rifaldi Muhammad Zaki, Sofyan Chairul Anwar
Urban road inventories are essential for effective infrastructure management and transportation planning, as they provide a detailed understanding of roadway features and mobility patterns. Traditional approaches such as manual surveys and aerial imagery are limited by labor intensity, safety concerns, and insufficient spatial resolution. This study presents a mobile mapping-based approach for high-resolution urban road data acquisition, tested along Jalan Raya Muchtar in Depok City, Indonesia. Using a vehicle-mounted LiDAR system, the research achieved centimeter-level accuracy under real traffic conditions, enabling reliable extraction of curbs, lane markings, traffic signs, and other roadside elements. The workflow addressed common challenges in dense urban settings-such as signal interruptions and complex feature separation-through improved data processing and georeferencing strategies. The resulting dataset provides a robust foundation for spatial analysis, infrastructure modeling, and smart city planning. Overall, the study demonstrates how mobile mapping can deliver accurate, scalable, and efficient road inventories to support evidence-based urban development. © Published under licence by IOP Publishing Ltd.
Mapping Survey and Geographic Information Study Program, The Education University of Indonesia, Bandung, Indonesia; PT Jelajah Semesta Teknologi, Jakarta, Indonesia
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