Alternative Title

NCKRI Symposium 2: Proceedings of the Thirteenth Multidisciplinary Conference on Sinkholes and the Engineering and Environmental Impacts of Karst

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Publisher

University of South Florida

Publication Date

May 2013

Abstract

Sinkholes in Winona County, MN have been mapped four times since 1985 using different techniques including field observations, topographic maps, air photos and Global Positioning System (GPS) measurements. As of early 2009, these efforts had identified and inventoried 672 sinkholes in Winona County that are recorded in the Minnesota Karst Feature Database (KFDB) (See the KFDB at: http://deli.dnr.state.mn.us/). The acquisition of one-meter resolution Light Detection and Ranging (LiDAR) images has significantly increased the speed and accuracy of sinkhole mapping. One meter shaded relief LiDAR Digital Elevation Models (DEMs) for Winona County were visually scanned to compare sinkhole locations in the KFDB with the LiDAR images and to find new sinkholes in the LiDAR DEMs. The results of this method indicate that the number of actual sinkholes in Winona County could be as many as four times more sinkholes than identified by the pre-LiDAR surveys. To automate sinkhole detection from LiDAR data at a regional scale, an algorithm was developed in MATLAB(r) based on image processing techniques. The algorithm has three steps. The first part detects potential sinkhole locations as depressions in the DEM using a morphological operation (erosion). The second part of the algorithm delineates sinkhole boundaries by automatically fitting an active contour (snake) around the potential sinkhole locations. In the last step, a pruning process, based on the relationship between depth and area of depressions, was applied to discard shallow depressions. The proposed method was evaluated on selected parts of Winona County. Evaluations of precision and recall returned positive results at 82% and 91% levels, respectively, which are sufficiently accurate to permit regional-scale, reconnaissance sinkhole mapping in complex landscapes. -- Authors Open Access - Permission by Publisher See Extended description for more information.

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1 online resource

Type

Conference Proceeding

Genre

Conference Proceedings; Serials

Format

application/pdf

Identifier

K26-02176

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