Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

Geology

Theses and Dissertations--Earth and Environmental Sciences

Theses/Dissertations

LiDAR

Publication Year

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

Rethinking Karst Hazard Assessment In Kentucky, William P. Pierskalla Jr. Jan 2019

Rethinking Karst Hazard Assessment In Kentucky, William P. Pierskalla Jr.

Theses and Dissertations--Earth and Environmental Sciences

Current karst hazard maps in Kentucky reflect the general lithology of the state and ignore or significantly reduce the impact of the actual sinkholes present within these areas. These maps rely on equal weighting, by area, of the Karst Potential Index (KPI) map and the sinkhole inventory map. The KPI is based on a 1:500,000 geologic map and less than 500 data points of carbonate rocks. The sinkhole inventory is derived from topographic maps updated in the 1970s with approximately 10-foot resolution. This method gives a preferential weighting of the KPI over the sinkhole data. Consequently, the current method is …


Use And Evaluation Of Lidar For Mapping Sinkholes In Royal Spring Groundwater Basin, Fidele Nsonguh Tibouo Jan 2016

Use And Evaluation Of Lidar For Mapping Sinkholes In Royal Spring Groundwater Basin, Fidele Nsonguh Tibouo

Theses and Dissertations--Earth and Environmental Sciences

This study utilizes a digital elevation model of the surface derived from high-resolution LiDAR (Light Detection and Ranging) and aerial-image technologies to map sinkholes in the Royal Spring groundwater basin. Shade-relief maps, with vertical exaggeration, were very helpful in the initial characterization of depressions. Then, aerial-photography sets were likewise helpful in identifying man-made structures such as retention basins, swimming pools, and parking lots, and to identify new sinkholes.

Field checking was necessary to further define depressions into two categories: 1.) potential sinkholes and 2.) probable sinkholes. This study had a lower success rate (50 percent) for identifying sinkholes via LiDAR …