Date of Graduation

5-2025

Document Type

Thesis

Degree Name

Master of Science in Geography (MS)

Degree Level

Graduate

Department

Geosciences

Advisor/Mentor

Tullis, Jason A.

Committee Member

Davidson, Fiona M.

Second Committee Member

Skinner, Vaughn

Keywords

3D imagery; aerial survey; airborne; Comparison; Digital Terrain Model; lidar

Abstract

Light detection and ranging (lidar) laser scanners are prominent remote sensing tools to produce high resolution three-dimensional (3D) imagery of the Earth’s surface. These laser scanners combined with global navigation satellite systems (GNSS) and real-time kinematic (RTK) reference stations can generate some of the most accurate ground surface imagery and elevation data for terrain mapping and related applications. Lidar aerial survey is an important tool in industries such as architecture, civil engineering, forestry, geology, geography, and agriculture where digital terrain models (DTMs) can be used to examine the geographical landscape and urban industry. Currently, there are three different common laser scanning systems: traditional airborne lidar, terrestrial laser scanners (TLS), and small unmanned aircraft systems (sUAS)-based lidar. As the integration of sUAS and lidar is in a phase of rapid development, there are ongoing questions regarding the comparative precision and reliability of sUAS versus traditional airborne platforms. In this study, aerial lidar datasets collected on two distinct platforms were compared for benefits to quality and sensitivity to how the data is collected and post-processed. The lidar datasets collected were analyzed and processed using Esri’s ArcGIS Pro software and LAStools produced by Rapidlasso GmbH to generate two DTMs representing ground surface terrain. The DTMs were evaluated based on geomorphological identification, quality assessment, and lidar intensity returns. The results of the DTMs’ Pearson correlation coefficient and relative accuracy indicate strong similarities. However, the dataset collected using traditional airborne lidar was found to be a better representation of the terrain, with vegetation more identifiable in the DTM derived from sUAS lidar. The traditional airborne lidar also benefited from being captured during the “leaf-off” season and was previously post-processed with ground control points (GCPs), resulting in a more accurate point cloud of the bare earth. Future research of sUAS lidar may indicate that a more accurate DTM is possible with the application of GCPs, more analysis of intensity measurements to classify vegetation, manual classification, and evaluation of industry use. As it stands, sUAS derived lidar is more cost-effective than traditional airborne lidar and is linked to more dynamic and versatile remote sensing technologies.

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