A model-based approach for reconstructing a terrain surface from airborne LIDAR data

Authors: Sohn, Gunho1; Dowman, IanJ.2

Source: The Photogrammetric Record, Volume 23, Number 122, June 2008 , pp. 170-193(24)

Publisher: Wiley-Blackwell

Buy & download fulltext article:

OR

Price: $48.00 plus tax (Refund Policy)

Abstract:

Abstract

A lidar filtering technique is used to differentiate on-terrain points and off-terrain points from a cloud of 3D point data collected by a lidar system. A major issue of concern in this low-level filter is to design a methodology to ensure a continual adaptation to variations of terrain slopes and object scales. In this paper, a new lidar filtering technique which hierarchically fragments lidar data into piecewise planar terrain models is introduced. Once a number of hypothetical planar terrain models are generated to fit the terrain surface of the underlying area, the optimal terrain model to produce the minimum labelling errors is determined based on minimum description length (MDL) principles. This hypothesis-verification optimisation is achieved in a coarse-to-fine strategy by which the entire terrain surface is incrementally reconstructed by increasing the number of planar terrain models fitted. The proposed technique was successfully applied to a digital surface model provided within an OEEPE lidar trial, showing 0·94% of Type I errors and 6·75% of Type II errors compared to manually classified reference data.

Keywords: 3D reconstruction; DEM/DTM; automation; feature extraction; lidar

Document Type: Research Article

DOI: http://dx.doi.org/10.1111/j.1477-9730.2008.00483.x

Affiliations: 1: ( )York University, Toronto, Ontario, Canada, Email: gsohn@yorku.ca 2: ( )University College London, Email: idowman@ge.ucl.ac.uk

Publication date: June 1, 2008

Related content

Tools

Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content

Text size:

A | A | A | A
Share this item with others: These icons link to social bookmarking sites where readers can share and discover new web pages. print icon Print this page