Degree Name

MS (Master of Science)

Program

Geosciences

Date of Award

12-2018

Committee Chair or Co-Chairs

Dr. Ingrid Luffman

Committee Members

Dr. Eileen Ernenwein, Dr. Arpita Nandi

Abstract

Predicting infrastructure damage and economic impact of sinkholes requires high accuracy mapping distribution and development. The study mapped sinkholes and sinkhole hotpsots in Johnson City, TN using LiDAR-derived Digital Elevation Model (DEM) and a database of known sinkholes which were matched to LiDAR-derived depressions. For all matched depressions (n = 404), three metrics were calculated: circularity index, ratio of length to width of the Minimum Bounding Rectangle (MBR) and percent coverage of the MBR by the depression, and 3,634 new sinkholes were identified. Newly developed hotspots were identified in north Johnson City and other areas in the south near the Johnson City Medical Center. The methodology developed can be applied to identify hotspots in other small metropolitan cities and the hotspot map produced can be employed in hazard mitigation planning, resource allocation, and made available publicly to property owners and insurance companies.

Document Type

Thesis - Withheld

Copyright

Copyright by the authors.

Available for download on Saturday, November 12, 2022

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