Abstract
Abstract. Developing a 3D city model is always a challenging task, whether on how to obtain the 3D data or how to present the model to users. Lidar is often used to produce real-world measurement, resulting in point clouds which further processed into a 3D model. However, this method possesses some limitation, e.g. tedious, expensive works and high technicalities, which limits its usability in a smaller area. Currently, there exists pipeline utilize point-clouds from Lidar data to automate the generation of 3D city model. For example, 3dfier (http://github.com/tudelft3d/3dfier) is a software capable of generating LoD 1 3D city model from lidar point cloud data. The resulting CityGML file could further be used in a 3D GIS viewer to produce an interactive 3D city model. This research proposed the use of Structure from Motion (SfM) method to obtain point cloud from UAV data. Using SfM to generate point clouds means cheaper and shorter production time, as well as more suitable for smaller area compared to LiDAR. 3Dfier could be utilized to produce 3D model from the point cloud. Subsequently, a game engine, i.e. Unity 3D, is utilized as the visualization platform. Previous works shows that a game engine could be used as an interactive environment for exploring virtual world based on real-world measurement and other data, such as parcel boundaries. This works shows that the process of generating 3D city model could be achieved using the proposed pipeline.
Highlights
Presenting a 3D city model from real-world data is a challenging task
For a less-detailed 3D city model focused on geospatial data visualization, the process could be more straightforward
The point cloud obtained from Structure from Motion (SfM) method have different characteristics compared to point cloud obtained from LiDAR, additional processing should be employed to produce point cloud which could be used as an input for 3Dfier
Summary
Presenting a 3D city model from real-world data is a challenging task. Various data acquisition methods could be employed to obtain accurate representations of cities components. Development of a 3D city model using LiDAR requires tedious and expensive efforts: Point-clouds obtained from LiDAR data should be filtered, classified and subsequently converted into 3D models (Popovic et al 2017). This approach could be used to obtain detailed building models (e.g. LOD3), preserving the buildings‟ height and roof shape on the 3D model (Tse, Gold, and Kidner 2008). A 3D modelling software could be employed to extrude the digitized building footprints to form corresponding 3D Models This approach, possesses some limitations, since the height of the buildings could not be obtained directly and needs to be manually assigned by the operator for each building unit (Aditya and Laksono 2017)
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