Paper
27 April 2009 Hyperspectral imagery and LiDAR for geological analysis of Cuprite, Nevada
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Abstract
Fusion of Light Detection and Ranging (LiDAR) and Hyperspectral Imagery (HSI) products is useful for geological analysis, particularly for visualization of geomorphology and hydrology. In early 2007, coincident hyperspectral imagery and LiDAR were acquired over Cuprite, Nevada. The data were analyzed with ENVI and the ENVI LiDAR Toolkit. Results of the analysis of these data suggest, for some surfaces, a correlation between mineral content and surface roughness. However, the LiDAR resolution (~1 meter ground sampling distance) is likely too coarse to extract surface texture properties of clay minerals in some of the alluvial fans captured in the imagery. Though not demonstrated in this particular experiment (but a goal of the research), the relation between surface roughness and mineral composition may provide valuable information about the mechanical properties of the surface cover-in addition to generating another variable useful for material characterization, image classification, and scene segmentation. Future mission planning should include consideration of determining optimal ground sampling to be used by LiDAR and HSI systems. The fusion of LiDAR elevation data and multi- and hyperspectral classification results is, in and of itself, a valuable tool for imagery analysis and should be explored further.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael S. West and Ronald G. Resmini "Hyperspectral imagery and LiDAR for geological analysis of Cuprite, Nevada", Proc. SPIE 7334, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV, 73341C (27 April 2009); https://doi.org/10.1117/12.819315
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Cited by 6 scholarly publications.
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KEYWORDS
LIDAR

Minerals

Surface roughness

Image fusion

Hyperspectral imaging

Mars

Reflectivity

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