A decade of topographic transformation: Statewide elevation differencing from public LiDAR data and the relationship to landscape patterns

Abstract

Researchers have used elevation models to study the Earth’s landscapes and landforms for over a century, and technological advancements, namely light detection and ranging (LiDAR), have provided increasingly detailed models and maps. As this technology matures, opportunities for multitemporal LiDAR topographic data collection are possible. However, the fundamental components and nuances of LiDAR and the implications for data interpretation are underacknowledged. When comparing multitemporal collections, understanding the errors that arise from creating elevation models from LiDAR data is vital. In this thesis, I seek to bridge the knowledge gaps in LiDAR technologies and provide a historical context for the technology and its surrounding ecosystem. I also evaluate several techniques for comparing multitemporal LiDAR collections statewide. Finally, I provide transferable methods that can be used in future research as more LiDAR data becomes available and discuss the limitations and usability of such datasets.