Peer-Reviewed Journal Details
Mandatory Fields
Kumar P.;Lewis P.;Cahalane C.;Peters S.
2019
November
Journal of Spatial Science
Spatially optimised retrieval of 3D point cloud data from a geospatial database for road median extraction
Published
0 ()
Optional Fields
data segmentation Geospatial database point cloud retrieval road median extraction spatial hierarchy spatial optimisation
© 2019, © 2019 Mapping Science Institute, Australia and Surveying and Spatial Science Institute. 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.
1449-8596
10.1080/14498596.2019.1687019
Grant Details