Project

Earth-Mars Cave Detection

Goal: Advance terrestrial cave detection techniques to improve our ability to find caves on other planets.

Date: 30 August 2005 - 30 March 2011

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Project log

Jut Wynne
added 2 research items
Since the initial experiments nearly 50 years ago, techniques for detecting caves using airborne and spacecraft acquired thermal imagery have improved markedly. These advances are largely due to a combination of higher instrument sensitivity, modern computing systems, and processor intensive analytical techniques. Through applying these advancements, our goals were to: (1) Determine the efficacy of methods designed for terrain analysis and applied to thermal imagery; (2) evaluate the usefulness of predawn and midday imagery for detecting caves; and (3) ascertain which imagery type (predawn, midday, or the difference between those two times) was most informative. Using forward stepwise logistic (FSL) and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses for model selection, and a thermal imagery dataset acquired from the Mojave Desert, California, we examined the efficacy of three well-known terrain descriptors (i.e., slope, topographic position index (TPI), and curvature) on thermal imagery for cave detection. We also included the actual, untransformed thermal DN values (hereafter "unenhanced thermal") as a fourth dataset. Thereafter, we compared the thermal signatures of known cave entrances to all non-cave surface locations. We determined these terrain-based analytical methods, which described the "shape" of the thermal landscape hold significant promise for cave detection. All imagery types produced similar results. Down-selected covariates per imagery type, based upon the FSL models, were: Predawn-slope, TPI, curvature at 0 m from cave entrance, as well as slope at 1 m from cave entrance; midday-slope, TPI, and unenhanced thermal at 0 m from cave entrance; and difference-TPI and slope at 0 m from cave entrance, as well as unenhanced thermal and TPI at 3.5 m from cave entrance. Finally, we provide recommendations for future research directions in terrestrial and planetary cave detection using thermal imagery.
This dataset is one of many used in the development of the manuscript 'Advancing Cave Detection using Terrain Analysis and Thermal Imagery' by Wynne et al. 2021. Manuscript Abstract: Since the initial experiments nearly 50 years ago, techniques for detecting caves using airborne and spacecraft acquired thermal imagery have improved markedly. These advances are largely due to a combination of higher instrument sensitivity, modern computing systems, and processor-intensive analytical techniques. Through applying these advancements, our goals were to: (1) determine the utility of methods designed for terrain analysis and applied to thermal imagery; (2) analyze the usefulness of predawn and midday imagery for detecting caves; and, (3) determine which imagery type (predawn, midday, or the difference between the two) was most useful. Using forward stepwise logistic (FSL) and Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis for model selection, and a thermal imagery dataset acquired from the Mojave Desert, California, we examined the efficacy of three well-known terrain descriptors (i.e., slope, topographic position index [TPI], and curvature) on thermal imagery for cave detection. We also included the actual, untransformed thermal DN values (hereafter "unenhanced thermal") as a fourth dataset. We then compared the thermal signatures of known cave entrances to all non-cave surface locations. We determined these terrain-based analytical methods, which described the "shape" of the thermal landscape, hold significant promise for cave detection. All imagery types produced similar results. Down-selected covariates per imagery type, based upon the FSL models, were: predawn-Slope, TPI, Curvature at 0 m from cave entrance, as well as Slope at 1 m from cave entrance; midday-Slope, TPI, and unenhanced thermal at 0 m from cave entrance; and, difference-TPI and Slope at 0 m from cave entrance, as well as unenhanced thermal and TPI at 3.5 m from cave entrance. We provide recommendations for future research directions in terrestrial and planetary cave detection using thermal imagery. These data may be downloaded via https://doi.org/10.5066/P9NF0L2I
Jut Wynne
added a research item
Caves often support sensitive animal populations ranging from bats to subterranean-adapted invertebrates, salamanders, and fishes. Developing a framework to detect caves using GIS and remote sensing could serve as an invaluable conservation tool. Researchers could systematic identify caves on the landscape, prioritize caves for biological survey due to proximity of human activities, inventory those features, and then make management recommendations accordingly. To this end, we examined whether cave entrances could be detected in thermal imagery employing methods used for analyzing surface topography. Under ideal conditions, cave entrance temperatures are resolvable in the thermal infrared – appearing as cooler features in daytime imagery and warmer features at night. These thermal anomalies were predicted to appear as distinct “topographic” features on a 3-D representation of a thermal image. We tested this idea using aircraft-borne thermal imagery acquired during two flights (at “predawn” and “midday”) of Pisgah Lava Beds, California using: (1) Topographic Position Index (TPI), (2) thermal gradient (or slope), and (3) curvature. TPI is the relative value of a specific pixel compared to the average thermal value of a neighborhood of pixels, where relatively warm regions present themselves appear as thermal hills, while cooler areas are rendered as thermal valleys. Thermal slope represents the rate of change of thermal values over space, indicating where temperature values change quickly. Curvature represents the rate of change in slope on the “thermal surface” depicted as regions of relatively cool concavity (dips or valleys) and relatively warm convexity (hills and peaks). We determined that these terrain-based analytical methods, which described the “shape” of the thermal landscape, hold significant promise for cave detection. Further, we found that both imagery sets produced similar results. We also compared thermal profiles along transects radiating out from cave entrances to similar profiles conducted at random points on the landscape. Similarly, this analysis revealed distinct signatures of cave entrances. As these findings may be useful in the conservation of sensitive cave-roosting populations, we provide recommendations for future research directions in terrestrial cave detection using thermal imagery.
Jut Wynne
added a research item
Research has shown one example differentiating caves from non-cave anomalies in the Mojave Desert, CA. This work has important implications for detecting caves on the Moon and Mars.
Jut Wynne
added a project goal
Advance terrestrial cave detection techniques to improve our ability to find caves on other planets.
 
Jut Wynne
added 8 research items
Jut Wynne
added 2 research items
Regions on Mars likely to contain caves and/or cave-bearing geology are identified using multispectral imagery from orbital missions and the exploration of terrestrial analogs for the characterization of associated thermal, and geo-signatures.
Jut Wynne
added 2 research items
The purpose of this study is to (1) demonstrate the viability of detecting terrestrial caves at thermal-infrared wavelengths, (2) improve our understanding of terrestrial cave thermal behavior, (3) identify times of day when cave openings have the maximum thermal contrast with the surrounding surface regolith, and (4) further our understanding of how to detect caves on Earth, the Moon and Mars. We monitored the thermal behavior of two caves in the Atacama Desert of northern Chile. Through this work, we identified times when temperature contrasts between entrance and surface were greatest, thus enabling us to suggest optimal overflight times. The largest thermal contrast for both caves occurred during mid-day. One cave demonstrated thermal behavior at the entrance suggestive of cold-trapping, while the second cave demonstrated temperature shifts suggestive of airflow. We also collected thermograms without knowing optimal detection times; these images suggest both caves may also be detectable during off-peak times. We suggest cave detection using thermal remote sensing on Earth and other planetary objects will be limited by (1) capturing imagery in the appropriate thermal wavelength, (2) the size of cave entrance vs. the sensor's spatial resolution, (3) the viewing angle of the platform in relation to the slope trajectory of the cave entrance, (4) the strength of the thermal signal associated with the cave entrance, and (5) the time of day and season of thermal image capture. Through this and other studies, we will begin to identify the range of conditions under which caves are detectable in the thermal infrared and thus improve our detection capabilities of these features on Earth, the Moon and Mars.
In the Atacama Desert, where caves are quite dry, the interior rock temperature should be a function of only the thermal conduction through the rock, which is driven by the mean temperature at the surface. In this paper, we test this hypothesis.