A MORPHOMETRIC COMPARISON OF STATE INVENTORIED AND SEMI-AUTOMATED CATALOGS OF KARST DEPRESSIONS AT APALACHICOLA NATIONAL FOREST AND MAMMOTH CAVE NATIONAL PARK

We compare state inventories and semi-automated LiDAR (Light Detection and Ranging) derived inventories of karst depressions and sinkholes within Apalachicola National Forest and Mammoth Cave National Park. Traditionally, state inventories have relied on coarse resolution topographic data, such as that derived from 7.5-minute topographic quadrangles. With the increased acquisition of high-resolution LiDAR topographic datasets, the ability to employ semi-automated methods to rapidly create a karst depression catalog is now possible. Metrics such as perimeter, area, major and minor axes, and eccentricity are calculated. These metrics are then used to assess the completeness and accuracy of both catalogs and explore the statistical properties of karst landscapes. We conclude that the use of LiDAR data can increase the precision of metrics, increase catalog size, reduce the time required for catalog creation, and reduce subjectivity in classifying karst depressions.