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Title Semi-Automatic Model For Detecting The Discrepancy Between Cadastral Data And Building Footprint Extraction Using Unmanned Aerial Vehicles (Uav) Lidar In The Perspective Of Smart City
ID_Doc 48301
Authors Gamal A.; Zulkarnain F.; Indratmoko S.; Ardiansyah; Rohmah L.; Mushfiroh A.
Year 2023
Published 1st International Conference on Technology, Engineering, and Computing Applications: Trends in Technology Development in the Era of Society 5.0, ICTECA 2023
DOI http://dx.doi.org/10.1109/ICTECA60133.2023.10490944
Abstract In general, the Metropolitan Area region in Indonesia experiences problems such as: high population growth rates and limited housing and land. This rapid development is not followed by the capability of local government to supervise the development due to the limited capacity of the bureaucracy and manpower. Rapid development does not necessarily contribute to local tax revenues because the built-up area is often not in accordance with the design permitted by the government through the Building Construction Permit (BCP) document. It is not uncommon for government officials to find conditions where the built-up area is larger than the design of the BCP. The most efficient and the least-costly method to investigate the inconsistency between BCP and existing cadastre data is urgently needed. This paper describes the potential of using Light Detection and Ranging (LiDAR) Unmanned Aerial Vehicle (UAV) technology for updating 3D cadastre models and building footprint in the big umbrella of smart city. This study uses a GIS model with UAV LiDAR data to generate 3D buildings. Accuracy is tested via RMSE method by comparing LiDAR-based volume calculations to cadastral data from field surveys. Thus, this paper offers an integrative concept to incorporate the cadastre model from various ministries and local governments at cities/regencies level with the LiDAR UAV technology and to surveil the development violation from the LiDAR UAV technology without any high-cost door-to-door surveys. © 2023 IEEE.
Author Keywords Building footprint; LiDAR; Tax violation; UAV technology


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