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Spatially optimised retrieval of 3D point cloud data from a geospatial database for road median extraction.
- Source :
- Journal of Spatial Science; Jan 2022, Vol. 67 Issue 1, p3-20, 18p
- Publication Year :
- 2022
-
Abstract
- We present the GLIMPSE system that provides a framework for storage, management, accessibility and integration of 3D LiDAR data acquired from multiple platforms. We detail a point cloud retrieval approach, which provides spatially optimised access to point cloud data from the system for a particular geographic area based on user specifications. We tested our point cloud retrieval approach to facilitate the extraction of road medians from large volumes of ALS data stored in the GLIMPSE system. The integrated use of a geospatial database, the GLIMPSE system and the point cloud retrieval approach improved the efficiency of road median extraction. [ABSTRACT FROM AUTHOR]
- Subjects :
- POINT cloud
GEOSPATIAL data
DATABASES
ROAD markings
Subjects
Details
- Language :
- English
- ISSN :
- 14498596
- Volume :
- 67
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Journal of Spatial Science
- Publication Type :
- Academic Journal
- Accession number :
- 155283078
- Full Text :
- https://doi.org/10.1080/14498596.2019.1687019