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http://dx.doi.org/10.22640/lxsiri.2022.52.1.105

A Study on Building Object Change Detection using Spatial Information - Building DB based on Road Name Address -  

Lee, Insu (LX Spatial Information Research Institute)
Yeon, Sunghyun (LX Spatial Information Research Institute)
Jeong, Hohyun (LX Spatial Information Research Institute)
Publication Information
Journal of Cadastre & Land InformatiX / v.52, no.1, 2022 , pp. 105-118 More about this Journal
Abstract
The demand for information related to 3D spatial objects model in metaverse, smart cities, digital twins, autonomous vehicles, urban air mobility will be increased. 3D model construction for spatial objects is possible with various equipments such as satellite-, aerial-, ground platforms and technologies such as modeling, artificial intelligence, image matching. However, it is not easy to quickly detect and convert spatial objects that need updating. In this study, based on spatial information (features) and attributes, using matching elements such as address code, number of floors, building name, and area, the converged building DB and the detected building DB are constructed. Both to support above and to verify the suitability of object selection that needs to be updated, one system prototype was developed. When constructing the converged building DB, the convergence of spatial information and attributes was impossible or failed in some buildings, and the matching rate was low at about 80%. It is believed that this is due to omitting of attributes about many building objects, especially in the pilot test area. This system prototype will support the establishment of an efficient drone shooting plan for the rapid update of 3D spatial objects, thereby preventing duplication and unnecessary construction of spatial objects, thereby greatly contributing to object improvement and cost reduction.
Keywords
Spatial objects; spatial information; attribute; Road Name Address; Building register;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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