Airborne LiDAR for DEM generation: some critical issues

Article

Liu, Xiaoye. 2008. "Airborne LiDAR for DEM generation: some critical issues." Progress in Physical Geography: an international review of geographical work in the natural and environmental sciences. 32 (1), pp. 31-49. https://doi.org/10.1177/0309133308089496
Article Title

Airborne LiDAR for DEM generation: some critical issues

ERA Journal ID34380
Article CategoryArticle
Authors
AuthorLiu, Xiaoye
Journal TitleProgress in Physical Geography: an international review of geographical work in the natural and environmental sciences
Journal Citation32 (1), pp. 31-49
Number of Pages19
Year2008
Place of PublicationUnited Kingdom
ISSN0309-1333
1477-0296
Digital Object Identifier (DOI)https://doi.org/10.1177/0309133308089496
Web Address (URL)http://ppg.sagepub.com/content/32/1/31.full.pdf+html
Abstract

Airborne LiDAR is one of the most effective and reliable means of terrain data collection. Using LiDAR data for DEM generation is becoming a standard practice in spatial related areas. However, the effective processing of the raw LiDAR data and the generation of an efficient and high-quality DEM remain big challenges. This paper reviews the recent advances of airborne LiDAR systems and the use of
LiDAR data for DEM generation, with special focus on LiDAR data filters, interpolation methods, DEM resolution, and LiDAR data reduction. Separating LiDAR points into ground and non-ground is the most critical and difficult step for
DEM generation from LiDAR data. Commonly used and most recently developed LiDAR filtering methods are presented. Interpolation methods and choices of suitable interpolator and DEM resolution for LiDAR DEM generation are discussed in detail. In order to reduce the data redundancy and increase the efficiency in terms of storage
and manipulation, LiDAR data reduction is required in the process of DEM generation. Feature specific elements such as breaklines contribute significantly to DEM quality. Therefore, data reduction should be conducted in such a way that critical elements are kept while less important elements are removed. Given the highdensity
characteristic of LiDAR data, breaklines can be directly extracted from LiDAR data. Extraction of breaklines and integration of the breaklines into DEM generation are presented.

Keywordsairborne LiDAR; DEM; filter; resolution; data reduction; breakline
ANZSRC Field of Research 2020469999. Other information and computing sciences not elsewhere classified
401302. Geospatial information systems and geospatial data modelling
370999. Physical geography and environmental geoscience not elsewhere classified
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Byline AffiliationsAustralian Centre for Sustainable Catchments
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