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Improving Sinkhole Mapping Using Lidar Data And Locating Sinkhole Hotspots In Johnson City, Tn, Kingsley Fasesin
Improving Sinkhole Mapping Using Lidar Data And Locating Sinkhole Hotspots In Johnson City, Tn, Kingsley Fasesin
Electronic Theses and Dissertations
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 …
Fm Radio Signal Propagation Evaluation And Creating Statistical Models For Signal Strength Prediction In Differing Topographic Environments, Timothy Land
Electronic Theses and Dissertations
Radio wave signal strength and associated propagation models are rarely analyzed across individual geographic provinces. This study evaluates the effectiveness of the Radio Mobile model to predict radio wave signal strength in the Blue Ridge and Valley and Ridge physiographic provinces. A spectrum analyzer was used on 19 FM transmitters to determine model accuracy. Statistical analysis determined the significance between different terrain factors and signal strength. Field signal strength was found to be related to test site elevation, transmitter azimuth, elevation angle, transmitter elevation, path loss, and distance. Using 76 signal strength receiver sites, Ordinary Least Square regression models predicted …