Semester

Fall

Date of Graduation

2020

Document Type

Thesis

Degree Type

MS

College

Eberly College of Arts and Sciences

Department

Geology and Geography

Committee Chair

J. Steven Kite

Committee Co-Chair

Timothy A. Warner

Committee Member

James Thompson

Abstract

The purpose of this thesis was to determine if the surficial geology of Bluestone National Scenic River (BLUE) and New River Gorge National River (NERI), two areas of similar geology, can be mapped using visual interpretation methods applied to digital elevation models (DEMs) derived from light detection and ranging (LiDAR) data. Surficial geology in BLUE was field mapped using GPS, following definitions and characterizations for surficial geology units established with the guidance of Dr. J. Steven Kite. A 2m x 2m LiDAR-derived DEM was used for BLUE and most of NERI using US Army Corps of Engineers (USCOE) LiDAR data, and a 1m x 1m DEM was created using West Virginia Department of Environmental Protection’s (WVDEP) Division of Mining and Reclamation LiDAR data for Babcock State Park, which is located within NERI and not included in the USCOE LiDAR dataset. The DEM was used to create a slope shade map and hillshade maps. The surficial geology was manually digitized at a 1:3,000 scale based on visual interpretation of image texture, slope steepness, and slope position. The digital mapping methods and definitions established at BLUE were then applied to mapping surficial geology at NERI. Surficial geology units defined and mapped at BLUE and NERI were: disturbed areas, river channels, floodplains, rock floored floodplains, terraces, alluvial fans, tributary deposits, bouldery tributary deposits, fluvial channels, colluvial fans, colluvial aprons, colluvial veneers, colluvial mantles, blocky mantles, landslides, rock cities, and residuum. The surficial geology units were then assessed based on the bedrock units in which they were associated spatially. LiDAR-based DEMs were found to be useful for understanding the dynamics between bedrock stratigraphy and landscape development. LiDAR-derived DEMs were effective in significantly reducing field work and in identifying and delineating surficial geology landforms.

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