Paper
9 June 2014 Correlation between lidar-derived intensity and passive optical imagery
Author Affiliations +
Abstract
When LiDAR data are collected, the intensity information is recorded for each return, and can be used to produce an image resembling those acquired by passive imaging sensors. This research evaluated LiDAR intensity data to determine its potential for use as baseline imagery where optical imagery are unavailable. Two airborne LiDAR datasets collected at different point densities and laser wavelengths were gridded and compared with optical imagery. Optech Orion C200 laser data were compared with a corresponding 1541 nm spectral band from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Optech ALTM Gemini LiDAR data collected at 1064 nm were compared to the WorldView-2 (WV-2) 949 – 1043 nm NIR2 band. Intensity images were georegistered and spatially resampled to match the optical data. The Pearson Product Moment correlation coefficient was calculated between datasets to determine similarity. Comparison for the full LiDAR datasets yielded correlation coefficients of approximately 0.5. Because LiDAR returns from vegetation are known to be highly variable, a Normalized Difference Vegetation Index (NDVI) was calculated utilizing the optical imagery, and intensity and optical imagery were separated into vegetation and nonvegetation categories. Comparison of the LiDAR intensity for non-vegetated areas to the optical imagery yielded coefficients greater than 0.9. These results demonstrate that LiDAR intensity data may be useful in substituting for optical imagery where only LiDAR is available.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jeremy P. Metcalf, Angela M. Kim, Fred A. Kruse, and Richard C. Olsen "Correlation between lidar-derived intensity and passive optical imagery", Proc. SPIE 9080, Laser Radar Technology and Applications XIX; and Atmospheric Propagation XI, 90800U (9 June 2014); https://doi.org/10.1117/12.2050023
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
LIDAR

Vegetation

Buildings

Near infrared

Roads

Orthophoto maps

Image sensors

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