The quality assessment and updating of spatial geodatabases (geoDBs) are essential tasks for effective spatial data management. This paper introduces an innovative methodology called Virtual Reconnaissance (VRec), which leverages Mobile Laser Scanning (MLS) systems based on Simultaneous Localization and Mapping (SLAM) technology. VRec aims to support both field reconnaissance and the geometric/semantic validation of GeoDBs. After reviewing the state-of-the-art, a case study in the municipality of Lecco (Italy) is presented, where a portable MLS device was used to acquire high-resolution point clouds. These data were georeferenced using GNSS ground control points (GCPs) and compared with the existing geoDB. Results demonstrate that VRec enables accurate quality assessment within official tolerance thresholds and offers promising capabilities for GeoDB updating, especially in complex urban environments. While data processing still requires skilled operators and significant time investment, future integration with artificial intelligence techniques may enhance efficiency and scalability.

Update and Quality Assessment of GeoDBs in Urban Areas Based on SLAM Technology

genzano nicola;scaioni marco
2025-01-01

Abstract

The quality assessment and updating of spatial geodatabases (geoDBs) are essential tasks for effective spatial data management. This paper introduces an innovative methodology called Virtual Reconnaissance (VRec), which leverages Mobile Laser Scanning (MLS) systems based on Simultaneous Localization and Mapping (SLAM) technology. VRec aims to support both field reconnaissance and the geometric/semantic validation of GeoDBs. After reviewing the state-of-the-art, a case study in the municipality of Lecco (Italy) is presented, where a portable MLS device was used to acquire high-resolution point clouds. These data were georeferenced using GNSS ground control points (GCPs) and compared with the existing geoDB. Results demonstrate that VRec enables accurate quality assessment within official tolerance thresholds and offers promising capabilities for GeoDB updating, especially in complex urban environments. While data processing still requires skilled operators and significant time investment, future integration with artificial intelligence techniques may enhance efficiency and scalability.
2025
INTERNATIONAL ARCHIVES OF THE PHOTOGRAMMETRY, REMOTE SENSING AND SPATIAL INFORMATION SCIENCES
Mobile Laser Scanning
Quality Assessment
SLAM
Geospatial Database
Updating
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1299743
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