Spatially optimised retrieval of 3D point cloud data from a geospatial database for road median extraction. Issue 1 (2nd January 2022)

• Record Type: Journal Article
• Authors: Kumar, Pankaj; Lewis, Paul; Cahalane, Conor; Peters, Stefan
• Is Part Of: Journal of spatial science. Volume 67:Issue 1(2022)
• Page Start: 3
• Page End: 20
• Publication Date: 2022-01-02
• Subjects: Geospatial database -- spatial hierarchy -- data segmentation -- spatial optimisation -- point cloud retrieval -- road median extraction; Geographic information systems -- Periodicals; Cartography -- Periodicals; Surveying -- Periodicals; Geodesy -- Periodicals; Photogrammetry -- Periodicals; Cartography; Geodesy; Geographic information systems; Photogrammetry; Surveying; Periodicals; 526.05
• DOI: 10.1080/14498596.2019.1687019
• Languages: English
• ISSNs: 1449-8596

Abstract

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.