Abstract
Creation of a consistent 3D model of a city requires accurate data. Usually, accuracy assurance problems of data are solved by time consuming and expensive process of collecting and aligning with ground control points (GCP). Therefore, alternative methods become important. Using existing Geographic Information Systems (GIS) databases may decrease the time and cost of creating a reference dataset by reducing the number of GCPs required for producing high quality 3D data or GIS databases can serve as reference data. For this purpose, new spatial data analysis methods are needed to assure that GIS databases are of high-quality. In this paper, we propose a novel methodology and its sample development for comparative spatial analysis of digitized point cloud and the corresponding GIS database in order to statistically assess opportunities to align Mobile Mapping Systems (MMS) data with existing GIS databases or to improve involved datasets. The method is evaluated using LiDAR data provided by Estonian company Reach-U Ltd. and GIS database layers from different Estonian open and closed databases.
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PostGIS 2.5.3dev Manual, https://postgis.net/docs/manual-dev/ST_ClusterDBSCAN.html.
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Acknowledgements
This research was partially supported by the Archimedes Foundation in the scope of the smart specialization research and development project #LEP19022 “Applied research for creating a cost-effective interchangeable 3D spatial data infrastructure with survey-grade accuracy”. The work of Hele-Mai Haav was also supported by the Institutional Research Grant IUT33-13 of the Estonian Research Council. Last but not least, we thank Marta Olvet and Kristiina Kindel for their work related to data pre-processing.
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Maigre, R., Haav, HM., Lillemets, R., Julge, K., Anton, G. (2020). A Method of Comparative Spatial Analysis of a Digitized (LiDAR) Point Cloud and the Corresponding GIS Database. In: Robal, T., Haav, HM., Penjam, J., Matulevičius, R. (eds) Databases and Information Systems. DB&IS 2020. Communications in Computer and Information Science, vol 1243. Springer, Cham. https://doi.org/10.1007/978-3-030-57672-1_17
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