Journal
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
Volume 66, Issue 5, Pages 637-641Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.isprsjprs.2011.04.002
Keywords
Hyperspectral; Supercontinuum; LiDAR; Point cloud classification; Spectral Correlation Mapper
Categories
Funding
- Academy of Finland
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In this paper, a measurement system for the acquisition of a virtual hyperspectral LiDAR dataset is presented. As commercial hyperspectral LiDARs are not yet available, the system provides a novel type of data for the testing and developing of future hyperspectral LiDAR algorithms. The measurement system consists of two parts: first, backscattered reflectance spectra are collected using a spectrometer and a cutting-edge technology, white-light supercontinuum laser source; second, a commercial monochromatic LiDAR system is used for ranging. A virtual hyperspectral LiDAR dataset is produced by data fusion. Such a dataset was collected on a Norway spruce (Picea abies) sample. The performance of classification was tested using an experimental hyperspectral algorithm based on a novel combination of the Spectral Correlation Mapper and a region growing algorithm. The classifier was able to automatically distinguish between needles, branches and background, in other words, perform a difficult task using only traditional TLS data. (C) 2011 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
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