RECORD

A Multiscale Curvature Algorithm for Classifying Discrete Return LiDAR in Forested Environments

Title:
A Multiscale Curvature Algorithm for Classifying Discrete Return LiDAR in Forested Environments
Creator:
Evans, Jeffery S.; Huldak, Andrew T.
Date Created:
2007
Description:
One prerequisite to the use of light detection and ranging (LiDAR) across disciplines is differentiating ground from nonground returns. The objective was to automatically and objectively classify points within unclassified LiDAR point clouds, with few model parameters and minimal postprocessing. Presented is an automated method for classifying LiDAR returns as ground or nonground in forested environments occurring in complex terrains. Multiscale curvature classification (MCC) is an iterative multiscale algorithm for classifying LiDAR returns that exceed positive surface curvature thresholds, resulting in all the LiDAR measurements being classified as ground or nonground. The MCC algorithm yields a solution of classified returns that support bare-earth surface interpolation at a resolution commensurate with the sampling frequency of the LiDAR survey. Errors in classified ground returns were assessed using 204 independent validation points consisting of 165 field plot global positioning system locations and 39 National Oceanic and Atmospheric Administration-National Geodetic Survey monuments. Jackknife validation and Monte Carlo simulation were used to assess the quality and error of a bare-earth digital elevation model interpolated from the classified returns. A local indicator of spatial association statistic was used to test for commission errors in the classified ground returns. Results demonstrate that the MCC model minimizes commission errors while retaining a high proportion of ground returns and provides high confidence in the derived ground surface
Document Type:
Research Article
Subjects:
Classification curvature digital elevation model filtering forestry light detection and ranging LiDAR thin-plate spline, vegetation
Latitude:
46.869607
Longitude:
-116.733856
Publisher:
J. S. Evans and A. T. Hudak, "A Multiscale Curvature Algorithm for Classifying Discrete Return LiDAR in Forested Environments," in IEEE Transactions on Geoscience and Remote Sensing, vol. 45, no. 4, pp. 1029-1038, April 2007, doi: 10.1109/TGRS.2006.890412.
Department:
Moscow Forest Sciences Laboratory, USDA, Forest Service, Moscow, Idaho, United States
Type:
Text
Format:
record

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Preferred Citation:
"A Multiscale Curvature Algorithm for Classifying Discrete Return LiDAR in Forested Environments", UIEF Research Exchange, University of Idaho Library Digital Collections, https://www.lib.uidaho.edu/digital/uief/items/uief_0324.html
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In copyright, educational use permitted.
Standardized Rights:
http://rightsstatements.org/vocab/InC-EDU/1.0/