Abstract
This paper provides the innovative approach of using a spatial extract, transform, load (ETL) solution for 3D building modelling, based on an unmanned aerial vehicle (UAV) photogrammetric point cloud. The main objective of the paper is to present the holistic workflow for 3D building modelling, emphasising the benefits of using spatial ETL solutions for this purpose. Namely, despite the increasing demands for 3D city models and their geospatial applications, the generation of 3D city models is still challenging in the geospatial domain. Advanced geospatial technologies provide various possibilities for the mass acquisition of geospatial data that is further used for 3D city modelling, but there is a huge difference in the cost and quality of input data. While aerial photogrammetry and airborne laser scanning involve high costs, UAV photogrammetry has brought new opportunities, including for small and medium-sized companies, by providing a more flexible and low-cost source of spatial data for 3D modelling. In our data-driven approach, we use a spatial ETL solution to reconstruct a 3D building model from a dense image matching point cloud which was obtained beforehand from UAV imagery. The results are 3D building models in a semantic vector format consistent with the OGC CityGML standard, Level of Detail 2 (LOD2). The approach has been tested on selected buildings in a simple semi-urban area. We conclude that spatial ETL solutions can be efficiently used for 3D building modelling from UAV data, where the data process model developed allows the developer to easily control and manipulate each processing step.
Highlights
We are living in the information era, surrounded by a variety of geospatial data from diverse sources
This paper provides the innovative approach of using a spatial extract, transform, load (ETL) solution for 3D building modelling, based on an unmanned aerial vehicle (UAV) photogrammetric point cloud
We have presented an approach to data-driven 3D building modelling in the spatial ETL environment, using UAV photogrammetric point cloud as input data
Summary
We are living in the information era, surrounded by a variety of geospatial data from diverse sources. For obtaining useful and reliable information for decision-making, the data must be properly acquired, processed, and analysed This is a challenging task, in the field of 3D geospatial data modelling [1,2], where the current software support is mostly inadequate. A spatial ETL solution supports geospatial data extraction from homogeneous or heterogeneous sources, transforms (processes) the data into a proper storage format/structure, and, loads the data into a target database, such as a topographic database. It is a virtual environment with data manipulation tools that enable better spatial and non-spatial data management. In addition to data transformation tools, spatial ETL solutions contain various geoprocessing algorithms to process and analyse spatial and non-spatial data, e.g., geometry validation and repair, topology check, or creating and merging attributes [4]
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