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Physical Sciences and Mathematics Commons

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Full-Text Articles in Physical Sciences and Mathematics

Regional Scale Dryland Vegetation Classification With An Integrated Lidar-Hyperspectral Approach, Hamid Dashti, Andrew Poley, Nancy Glenn, Nayani Ilangakoon, Lucas Spaete, Dar Roberts, Et. Al. Sep 2019

Regional Scale Dryland Vegetation Classification With An Integrated Lidar-Hyperspectral Approach, Hamid Dashti, Andrew Poley, Nancy Glenn, Nayani Ilangakoon, Lucas Spaete, Dar Roberts, Et. Al.

Michigan Tech Publications

The sparse canopy cover and large contribution of bright background soil, along with the heterogeneous vegetation types in close proximity, are common challenges for mapping dryland vegetation with remote sensing. Consequently, the results of a single classification algorithm or one type of sensor to characterize dryland vegetation typically show low accuracy and lack robustness. In our study, we improved classification accuracy in a semi-arid ecosystem based on the use of vegetation optical (hyperspectral) and structural (lidar) information combined with the environmental characteristics of the landscape. To accomplish this goal, we used both spectral angle mapper (SAM) and multiple endmember spectral …


Lidar-Based Sinkhole Detection And Mapping In Knox County, Tennessee, J Clint Shannon, David Moore, Yingkui Li, Cathy Olsen Jul 2019

Lidar-Based Sinkhole Detection And Mapping In Knox County, Tennessee, J Clint Shannon, David Moore, Yingkui Li, Cathy Olsen

Pursuit - The Journal of Undergraduate Research at The University of Tennessee

Sinkholes are one of the major causes of damage to roads, buildings, and other infrastructure throughout the US. Sinkholes near or on roads are especially costly and occasionally deadly. Knox County and much of East Tennessee are located within karst areas (comprised of porous and soluble limestone and dolomite), deeming it at risk for sinkholes. Currently, Knox County uses contour maps to manually identify sinkholes. Supported by a geographic information system (GIS), we developed a streamlined model to identify the locations and extents of potential sinkholes using 1.3-ft resolution LiDAR (Light Detection and Ranging) data and applied it to the …