Physical Sciences and Mathematics Commons^™

Truck Trailer Classification Using Side-Fire Light Detection And Ranging (Lidar) Data, Olcay Sahin

Civil & Environmental Engineering Theses & Dissertations

Classification of vehicles into distinct groups is critical for many applications, including freight and commodity flow modeling, pavement management and design, tolling, air quality monitoring, and intelligent transportation systems. The Federal Highway Administration (FHWA) developed a standardized 13-category vehicle classification ruleset, which meets the needs of many traffic data user applications. However, some applications need high-resolution data for modeling and analysis. For example, the type of commodity being carried must be known in the freight modeling framework. Unfortunately, this information is not available at the state or metropolitan level, or it is expensive to obtain from current resources.

Nevertheless, using …

Mapping Surficial Geology In The New River Gorge National River And Bluestone National Scenic River, West Virginia, Using Lidar-Derived Digital Elevation Data, Marla K. Denicola

Graduate Theses, Dissertations, and Problem Reports

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, …

Predictive Geohazard Mapping Using Lidar And Satellite Imagery In Missouri And Oklahoma, Usa, Olufeyisayo B. Ilesanmi

Doctoral Dissertations

”Light Detection and Ranging (LiDAR) and satellite imagery have become the most utilized remote sensing technologies for compiling inventories of surficial geologic conditions. Point cloud data obtained from multi-spectral remote sensing methods provide a detailed characterization of the surface features, in particular, the detailed surface manifestations of underlying geologic structures. When combined, point clouds eliminate bias from visual inconsistencies and/or statistical values. This research explores the competence of point clouds derived from LiDAR and Unmanned Aerial Systems (UAS) as a predictive tool in evaluating various geohazards. It combines these data sets with other remote sensing techniques to evaluate the sensitivity …