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Cave type and morphology are controlled by hydrogeological and geological factors; therefore, by inverse analogy, cave type and morphology could be used to determine the hydrogeological and geological conditions under which the caves developed. Euclidian metrics have traditionally been used to quantify and compare cave morphologies, even though caves have irregular and complex shapes. Caves have been shown to possess characteristics that identify them as fractals within certain ranges, so the use of Euclidean-based metrics alone to define and characterize them may be a limitation in morphometric analyses. Other factors that limit full morphometric analyses of caves include focus on two-dimensional cave data, as these are typically what are available, and exploration bias, as cave exploration and documentation are limited to spaces that are humanly passable or of immediate interest to the explorer, epitomizing the subjective nature of anthropogenic-based measurements. This research involves a proof-of-concept study that uses fractal indices as a means for identifying and classifying cave morphology and distinguishing genetic cave types. The fractal indices used are fractal dimension, which quantifies the complexity of a pattern, and lacunarity, which quantifies the texture of a pattern. Three-dimensional cave survey data were used to generate cave models that were converted to cave pattern image files and analyzed with image-processing software. Fractal indices were calculated for digital patterns of a limited subset of known cave types that included tafoni, littoral caves, stream caves, flank margin caves, and continental hypogene caves. The quantitative morphological distinctions in cave patterns as identified by fractal dimension and lacunarity proved to be statistically significant within the subset of cave types analyzed for this study. Similarities in geological and/or hydrogeological processes or overprinting by such processes can skew fractal indices, so geological and hydrogeological context is critical when interpreting fractal indices. The results of this study demonstrate that cave morphometry as defined by fractal indices can be used to augment the identification of cave type, which provides insight into the geological and hydrogeological controls on development of the cave type and its cavernous porosity and permeability.

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