MORPHOMETRIC ANALYSIS OF CAVE PATTERNS USING FRACTAL INDICES

Cave type and morphology are controlled by hydrological and geological factors, so by inverse analogy, these factors could be used to determine the conditions under which caves developed. Caves possess characteristics that identify them as fractals, so the use of Euclidean-based metrics aline to define and characterize caves may limit full morphometric anslyses. Other factors that limit morphometric analyses of caves include focus on two-dimensional data as these are typically what are available, and exploration bias as cave exploration and documentation are limited by spaces that are humanly passable or of immediate interest to the explorer. This research tested a proof-of-concept method using fractal indices to identify and classify cave morphology and distinguish genetic cave types. Fractal indices included fractal dimension and lacunarity, which quantify pattern complexity and texture. Three-dimensional cave data were converted to pattern image files and analyzed with image processing software. Fractal indices were calculated for digital patterns of a subset of known cave types including tafoni, littoral caves, flank margin caves and continental hypogene caves. The quantitative morphological distinctions in cave patterns proved to be statistically significant within the subset of cave types analyzed for this study. Similarities in hydrological and geological processes and/or over-printing by such processes can skew fractal indices so hydrologicsl/geological context are critical when interpreting fractal indices. This study demonstrated that cave morphometry as defined by fractal indices can augment the identification of cave type and provide insight into the hydrological and geological controls on cave development and cavernous porosity and permeability.