Terrestrial LiDAR survey and morphological analysis to identify infiltration properties in the Tamala Limestone, Western Australia

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Date
2015-07-16
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Publisher
IEEE
Abstract
Caves are an ideal observatory of infiltration water in karstified limestone, and the application of remote sensing techniques can bring new insights toward flow patterns and processes. We present an exhaustive characterization of Golgotha Cave in SW Western Australia, based on a light detection and ranging (LiDAR) measurement campaign. The cave is developed in Quaternary age aeolianite (dune limestone) and its infiltration waters form speleothems. We collect ground-based LiDAR scans of the cave ceiling at three sites within the cave system. The resulting point-clouds are analyzed using mathematical morphology to determine statistical information on stalactite widths, lengths, and spatial distributions. We establish a relationship between stalactite diameter and length that is in agreement with the platonic ideal of stalactite shape. We relate stalactite density variation with topography of the cave ceiling and variations in hydraulic gradient. From this analysis, it appears that longer stalactites tend to occur in comparatively lower ceiling elevation, which, we hypothesize, represents greater mass of water in the limestone above the roof of the cave. We also investigate the relationship between stalactite distribution and ceiling features such as fractures. We apply this to identify different types of possible flow patterns such as matrix flow and fracture flow. This analysis demonstrates a spatial variability, with one site having linear groups of stalactites and another site mostly dominated by stalactite clusters. © 2015, IEEE.
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Keywords
Caves, Optical radar, Morphology, Limestone, Topography, Quaternary period
Citation
Mahmud, K., Mariethoz, G., Treble, P. C., & Baker, A. (2015). Terrestrial LiDAR survey and morphological analysis to identify infiltration properties in the Tamala Limestone, Western Australia. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(10), 4871-4881. doi:10.1109/JSTARS.2015.2451088
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