SEMI-AUTOMATIC GENERATION OF AN LOD1 AND LOD2 3D CITY MODEL OF TANAUAN CITY, BATANGAS USING OPENSTREETMAP AND TAAL OPEN LIDAR DATA IN QGIS

Abstract

3D city models have found purpose beyond simple visualization of space by serving as building blocks of digital twins and smart cities. These are useful to urban areas in the Philippines through diversified applications: urban planning, disaster mitigation, environmental monitoring, and policy making. This study explored the use of free and open-source software to generate an LOD1 and LOD2 3D city model of Tanauan City, Batangas using building footprints from OpenStreetMap and elevation models from Taal Open LiDAR data. The proposed approach consists of GIS-based methods including data pre-processing, building height extraction, roof identification, building reconstruction, and visualization. The study adopted methods from previous studies for building detection and from Zheng et al. (2017) for LOD2 building reconstruction. For LOD1, a decision tree classifier was devised to determine the appropriate height for building extrusion. For LOD2, a model-driven approach using multipatch surfaces was utilized for building reconstruction. The workflow was able to reconstruct 70.66% LOD1 building models and 55.87% LOD2 building models with 44.37% overall accuracy. The RMSE and MAE between the extracted heights from the workflow and from manual digitization has an accuracy lower than 1 m which was within the standards of CityGML. The processing time in test bench 1 and test bench 2 for LOD1 took 00:12:54.5 and 00:09:27.2 while LOD2 took 02:50:29.1 and 01:27:48.2, respectively. The results suggest that the efficient generation of LOD1 and LOD2 3D city models from open data can be achieved in the FOSS environment using less computationally intensive GIS-based algorithms.