Remote Sens. 2013, 5(4), 1754-1773; doi:10.3390/rs5041754
Article

Improved Sampling for Terrestrial and Mobile Laser Scanner Point Cloud Data

Received: 23 January 2013; in revised form: 4 March 2013 / Accepted: 27 March 2013 / Published: 9 April 2013
(This article belongs to the Special Issue Advances in Mobile Laser Scanning and Mobile Mapping)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: We introduce and test the performance of two sampling methods that utilize distance distributions of laser point clouds in terrestrial and mobile laser scanning geometries. The methods are leveled histogram sampling and inversely weighted distance sampling. The methods aim to reduce a significant portion of the laser point cloud data while retaining most characteristics of the full point cloud. We test the methods in three case studies in which data were collected using a different terrestrial or mobile laser scanning system in each. Two reference methods, uniform sampling and linear point picking, were used for result comparison. The results demonstrate that correctly selected distance-sensitive sampling techniques allow higher point removal than the references in all the tested case studies.
Keywords: terrestrial; mobile; laser scanning; data reduction; sampling; distance distribution
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MDPI and ACS Style

Puttonen, E.; Lehtomäki, M.; Kaartinen, H.; Zhu, L.; Kukko, A.; Jaakkola, A. Improved Sampling for Terrestrial and Mobile Laser Scanner Point Cloud Data. Remote Sens. 2013, 5, 1754-1773.

AMA Style

Puttonen E, Lehtomäki M, Kaartinen H, Zhu L, Kukko A, Jaakkola A. Improved Sampling for Terrestrial and Mobile Laser Scanner Point Cloud Data. Remote Sensing. 2013; 5(4):1754-1773.

Chicago/Turabian Style

Puttonen, Eetu; Lehtomäki, Matti; Kaartinen, Harri; Zhu, Lingli; Kukko, Antero; Jaakkola, Anttoni. 2013. "Improved Sampling for Terrestrial and Mobile Laser Scanner Point Cloud Data." Remote Sens. 5, no. 4: 1754-1773.

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