Advancing Cave Detection Using Terrain Analysis and Thermal Imagery

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. We provide recommendations for future research directions in terrestrial and planetary cave detection using thermal imagery.

Hydrogeological Investigation for the Assessment of Spring Pollution Due to Abandoned Mines in a Karst Area

This paper presents a hydrogeological investigation case study for assessing the sources and pathways of spring pollution in a karst area in Guizhou Province, Southern China. Our methods included hydrogeological surveys, geophysical surveys, cave detection, tracer tests, and borehole drilling. The results showed that the pollution of the Longdong Spring is controlled by the amount of rainfall, which also determines the duration of pollution. The concentration of Fe and Mn ions in the spring was found to exceed that in the code for drinking water quality (China) by more than 300 times. The investigations showed that the source of the pollution is the mine water drainage from the abandoned Feilong coal mine, which is located to the northwest of the Longdong Spring. The drainage to the spring was found to occur 24 h after the groundwater level in the goaf reached approximately +908 m above sea level. This indicates a recharge pathway between the abandoned mine and the Longdong Spring. Recommendations for grouting around the spring and sinkhole for pollution control are put forth.