Case study: object and ground point separation on a river bank using airborne based LIDAR data

Full text not archived in this repository.

Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Bartels, M. and Wei, H. orcid id iconORCID: https://orcid.org/0000-0002-9664-5748 (2007) Case study: object and ground point separation on a river bank using airborne based LIDAR data. In: Remote Sensing and Photogrammetry Society Annual Conference 2007, Newcastle, UK.

Abstract/Summary

In the past decade, airborne based LIght Detection And Ranging (LIDAR) has been recognised by both the commercial and public sectors as a reliable and accurate source for land surveying in environmental, engineering and civil applications. Commonly, the first task to investigate LIDAR point clouds is to separate ground and object points. Skewness Balancing has been proven to be an efficient non-parametric unsupervised classification algorithm to address this challenge. Initially developed for moderate terrain, this algorithm needs to be adapted to handle sloped terrain. This paper addresses the difficulty of object and ground point separation in LIDAR data in hilly terrain. A case study on a diverse LIDAR data set in terms of data provider, resolution and LIDAR echo has been carried out. Several sites in urban and rural areas with man-made structure and vegetation in moderate and hilly terrain have been investigated and three categories have been identified. A deeper investigation on an urban scene with a river bank has been selected to extend the existing algorithm. The results show that an iterative use of Skewness Balancing is suitable for sloped terrain.

Item Type Conference or Workshop Item (Paper)
URI https://reading-clone.eprints-hosting.org/id/eprint/14589
Divisions Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
Uncontrolled Keywords LIDAR, point cloud, object, ground, unsupervised segmentation, skewness
Download/View statistics View download statistics for this item

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar