Evaluation of the performance of DEM interpolation algorithms for LiDAR data

Paper

Liu, Xiaoye, Zhang, Zhenyu and Peterson, Jim. 2009. "Evaluation of the performance of DEM interpolation algorithms for LiDAR data." Ostendorf, Bertram, Baldock, Penny, Bruce, David, Burdett, Michael and Corcoran, Paul (ed.) 2009 Surveying and Spatial Sciences Institute Biennial International Conference (SSC 2009): Spatial Diversity. Adelaide, Australia 28 Sep - 02 Oct 2009 Adelaide, Australia.
Paper/Presentation Title

Evaluation of the performance of DEM interpolation algorithms for LiDAR data

Presentation TypePaper
AuthorsLiu, Xiaoye (Author), Zhang, Zhenyu (Author) and Peterson, Jim (Author)
EditorsOstendorf, Bertram, Baldock, Penny, Bruce, David, Burdett, Michael and Corcoran, Paul
Journal or Proceedings TitleProceedings of the 2009 Surveying and Spatial Sciences Institute Biennial International Conference (SSC 2009)
Number of Pages9
Year2009
Place of PublicationAdelaide, Australia
ISBN9780958136686
Web Address (URL) of Paperhttp://www.researchgate.net/publication/228633996_Evaluation_of_the_performance_of_DEM_interpolation_algorithms_for_LiDAR_data
Conference/Event2009 Surveying and Spatial Sciences Institute Biennial International Conference (SSC 2009): Spatial Diversity
Spatial Sciences Institute Biennial Conference (SSC)
Event Details
2009 Surveying and Spatial Sciences Institute Biennial International Conference (SSC 2009): Spatial Diversity
Parent
Surveying and Spatial Sciences Institute Biennial International Conference
Event Date
28 Sep 2009 to end of 02 Oct 2009
Event Location
Adelaide, Australia
Event Details
Spatial Sciences Institute Biennial Conference (SSC)
Abstract

Airborne light detection and ranging (LiDAR) is one of the most effective means for high quality terrain data acquisition. The high-accuracy and high-density LiDAR data
makes it possible to model terrain surface in more detail. Using LiDAR data for DEM generation is becoming a standard practice in the spatial science community. Of the three commonly used digital elevation models (e.g., triangular irregular network (TIN), gridded DEM and contour line model), the gridded DEM is the simplest and the most efficient approach in terms of storage and manipulation. However, this approach is liable to introduce errors because of its discontinuous representation of the terrain surface based on the interpolation process of sampled terrain points. Given the characteristics of LiDAR data, much attention must be paid to the selection of an appropriate interpolation algorithm, otherwise the accuracy of produced DEM from LiDAR data will be compromised. This study aims to evaluate the performance of commonly used interpolation algorithms to the LiDAR data, including inverse distance weighted (IDW) method, Kriging method, and local polynomial method. All these interpolation algorithms are applied to DEMs generated from LiDAR at various data density levels. The performance of these interpolation methods is evaluated by using both cross-validation and validation test methods. The results showed the performance of each interpolation algorithm for two study sites with different terrain types and analysed the relationship between interpolation algorithms and LiDAR data density. Considering accuracy and computing time for large volume of LiDAR data, IDW is recommended for LiDAR DEM generation from this study.

KeywordsLiDAR; DEM; interpolation
ANZSRC Field of Research 2020469999. Other information and computing sciences not elsewhere classified
460304. Computer vision
401304. Photogrammetry and remote sensing
Public Notes

This publication is copyright. It may be reproduced in whole or in part for the purposes of study, research, or review, but is subject to the inclusion of an acknowledgment of the source. This article was peer reviewed by two independent and anonymous reviewers.

Byline AffiliationsDepartment of Surveying and Land Information
Monash University
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