Terrain classification using multi-wavelength LiDAR data
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Authors
Thomas, Judson J. C.
Subjects
remote sensing
LiDAR
multi-wavelength
terrain classification
spectral
LiDAR
multi-wavelength
terrain classification
spectral
Advisors
Olsen, Richard
Date of Issue
2015-09
Date
Sep-15
Publisher
Monterey, California: Naval Postgraduate School
Language
Abstract
With the arrival of Optech’s Titan multispectral LiDAR sensor, it is now possible to simultaneously collect three different wavelengths of LiDAR data. Much of the work performed on multispectral LiDAR data involves gridding the point cloud to create Digital Elevation Models and multispectral image cubes. Gridding and raster analysis can have negative implications with respect to LiDAR data integrity and resolution. Presented here is a method of attributing the Titan LiDAR point cloud with the spectral information of all three lasers and the potential improvement of performing all analysis within the point cloud. Data from the Optech Titan are analyzed for purposes of terrain classification, adding the spectral component to the LiDAR data point cloud analysis. The approach used here combines the three spectral sensors into one point cloud, integrating the intensity information from the 3 sensors. Nearest-neighbor sorting techniques are used to create the merged point cloud. Standard LiDAR and spectral classification techniques are then applied. The ENVI spectral tool n-Dimensional Visualizer is used to extract spectral classes from the data, which can then be applied using supervised classification functions. The Maximum Likelihood classifier provided consistent results demonstrating effective terrain classification for as many as eleven classes.
Type
Thesis
Description
Series/Report No
Department
Systems Academic Group
Systems Academic Group
Organization
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NPS Report Number
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Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.