Special Issue "Terrestrial Laser Scanning"
A special issue of Remote Sensing (ISSN 2072-4292).
Deadline for manuscript submissions: closed (31 May 2011) | Viewed by 114867
Interests: laser scanning; photogrammetry; self-calibration; bundle adjustment; registration; point cloud processing; network design; multi-sensor systems; sensor integration; imaging metrology; deformation measurement
Special Issues, Collections and Topics in MDPI journals
Terrestrial laser scanning (TLS) is a ground-based, active imaging method that rapidly acquires accurate, dense 3D point clouds of object surfaces by laser rangefinding. The number and variety of remote sensing applications of TLS instruments continues to increase. Static systems operated from atop a surveying tripod are commonly employed for the as-built documentation of industrial plants, the recording of cultural heritage sites, the measurement of natural processes such as sand transport and tree defoliation, structural deformation measurement and the measurement of the human body. Mobile systems comprising integrated laser scanning and platform georeferencing technologies are deployed on road vehicles, rail cars or small water vessels for kinematic data capture. The utilisation and number mobile laser scanning systems have risen dramatically in recent years for rapid corridor mapping and the compilation of asset inventories.
Prospective authors are invited to contribute to this Special Issue of Remote Sensing by submitting an original manuscript of their latest research results in terrestrial laser scanning. Contributions may be from, but not limited to:
- scanner system modelling, calibration, performance evaluation and validation
- algorithms for automated point cloud registration
- techniques for the fusion of TLS data with that of other sensors
- automated feature extraction and object recognition
- mobile terrestrial scanning system developments
- novel applications of static or mobile terrestrial laser scanning
Dr. Derek Lichti
- terrestrial laser scanning
- point clouds
- object recognition
- mobile scanning