SOME THOUGHTS ON THE HISTORY AND FUTURE OF "SEEING" CAVES

Comprehending or analyzing a landform usually requires that it must somehow be mapped. For caves, which are negative landforms, the requirement is absolute. Although we can see a mountain from a perspective above (for example from a plane), it is impossible to "see" a cave without it being surveyed. This is because when one is inside of the cave, only a small portion is viewable, and the remainder is unseen. At the same time, these landforms are exceptionally challenging to measure and visualize. Intense field conditions, along with complex topology and obscured sections, require creative approaches both for the explorers who need to know where to go, and for the scientists who seek to analyze the cave. A symbiosis has developed between cave explorers and scientists, where each party is driven to improve maps/models/visualizations of caves. In practice, the best products employ dimensional measurements as well as human interpretation. Three hundred plus years of cave mapping covers products from pen-and-ink drawings (e.g. Martel), uncontrolled plan maps (e.g. the Bishop map of Mammoth Cave, Kentucky), compass-and-tape controlled hand-drawn maps (many examples from 1930's to 1980's), computer aided maps (many examples from 1990's onwards, some making use of in-cave tablet sketching), physical models (both negative and positive representations, such as Bosted's clay model of Soldier's Cave), and virtual (digital) models. Standard cave mapping techniques provide adequate geographical data and interpretive information for generating cave maps suitable for navigation or documenting length/depth, but lack the data density necessary for producing realistic cave models or for accurately calculating morphometric parameters such as volume. Increased data density such as that afforded by terrestrial lidar scans, structure-from-motion, or scooter-mounted sonar (submerged caves), opens new possibilities. But dataset sizes and structures present some roadblocks to usable outcomes. Quantitative analysis of digital karst models is not yet highly developed, though some very intriguing outcomes have been realized from fractal analysis. One of the biggest questions that remain is "What is the next step, now that we have these detailed models?"