2009 Portland GSA Annual Meeting (18-21 October 2009)

Paper No. 8
Presentation Time: 9:00 AM-6:00 PM

ADVANCES IN SINKHOLE MAPPING: A LIDAR SURVEY OF HOUSTON COUNTY, MINNESOTA


LARSON, Erik B., Unity College, 42 Murdock Dr, UC Box 322, Unity, ME 04988, ALEXANDER, Scott C., Earth Sciences, Univ of Minnesota, 108 Pillsbury Hall, 310 Pillsbury Dr. SE, Minneapolis, MN 55455, GREEN, Jeffrey A., Division of Ecological and Water Resources, Minnesota Department of Natural Resources, 2300 Silver Creek Rd. NE, Rochester, MN 55906 and ALEXANDER Jr., E. Calvin, Department of Earth Sciences, University of Minnesota, 310 Pillsbury Dr. SE, Minneapolis, MN 55455, erik.b.e.larson@gmail.com

Sinkhole mapping is a useful part of groundwater management in karst aquifers. Over the past 40 years those mapping efforts have progressed from field and air photographic searches through GPS locating to the current web based 1m LiDAR DEMs in GIS systems. This progression has systematically increased the completeness of coverage, accuracy of location attribute information, and public access to information, while decreasing the time and effort required searching a given area.

This abstract reports the first application of LiDAR data to sinkhole mapping in Minnesota. Houston County, in the SE corner of MN, is underlain by karst aquifers developed in Ordovician and Cambrian carbonates. Systematic sinkhole searches had not been conducted in the County but 64 sinkholes had been recorded in the process of geologic mapping and hydrogeologic studies. 1m resolution LiDAR DEMs became available for the area in July 2009.

Two sets of shaded relief maps (with 180° different illumination angles) were generated then visually scanned for sinkholes. In a GIS system air photos and bedrock geology information were also used in conjunction with the shaded relief maps to identify closed depressions. During this initial process 347 potential sinkholes were identified. In addition to sinkholes several other processes produced closed depressions in the LiDAR data. Field checking proved to be both necessary and productive in learning to differentiate the sinkholes from the other closed depressions. The majority of the non-karst depressions proved to be slumps. Cellars of demolished houses, cattle rubs (wallows), constructed cattle crossings under roads, push-up and farm ponds were also recognized. Given the field calibrations contour lines provided additional help in differentiating the different types of depressions. The final number of new sinkholes found using LiDAR data was 227, bringing the total number of sinkholes mapped in Houston County to 291.