Date of Award
2025
Document Type
Open Access Dissertation
Degree Name
Doctor of Philosophy in Civil Engineering (PhD)
Administrative Home Department
Department of Civil, Environmental, and Geospatial Engineering
Advisor 1
Jae Sung Kim
Committee Member 1
Bo Xiao
Committee Member 2
Chiung-Shiuan Fu
Committee Member 3
Quang Tran
Abstract
Lava flows have severe impacts on the Earth’s surface, communities, and natural habitats. Accurate modeling of lava flow paths is crucial for volcanic hazard assessment and risk mitigation. This research integrated remote sensing, geographic information systems, geomorphological techniques, and hydrologic analysis to numerically determine the optimal ground sample distance (GSD) of digital elevation models (DEMs) for delineating lava flow paths. Two volcanic regions were analyzed: the Afar Region of Ethiopia (Alu, Dalaffilla, and Erta Ale volcanoes) and the Reykjanes Peninsula of Iceland (Fagradalsfjall volcano). Forward and backward modeling methods were used to simulate potential lava flow paths. Remote sensing data, including multispectral and thermal images as well as DEMs, were utilized for analysis. A large-scale mean-shift image segmentation method was applied to identify lava objects and extract the main centerline for analysis. The forward model was applied to the fissures between the Alu and Dalaffilla volcanoes. The main lava centerline was derived from a 2008 ASTER image, while flow paths were simulated using the 2000 SRTM DEM. An optimal GSD of 35 m resulted in the lowest root mean square error (RMSE) of 146.89 m. This was validated using the 2017 Erta Ale eruption, confirming 35 m as a suitable GSD for delineating a major lava polygon. In the backward model, hydrologic analysis on resampled DEMs using TauDEM identified an optimal GSD of 38 m with an RMSE of 123.44 m. In the study of the Fagradalsfjall volcano, an optimal GSD of 71 m with an RMSE of 98.84 m was obtained, while the backward model yielded an optimal GSD of 33 m with an RMSE of 173.56 m. Statistical analyses were conducted to validate the results. This research contributed to volcanic hazard assessment by providing a framework that integrated geospatial technologies into lava flow modeling. Initiating simulation from the observed lava outlet, the forward model addressed a key limitation of the backward model. Results indicate that lava flow path accuracy was sensitive to the GSD of a DEM. The findings further demonstrate that the forward model may aid emergency response planning and risk mitigation strategies in volcanic regions.
Recommended Citation
Ayo, Oluwatosin Oluyemisi, "ANALYSIS OF LAVA FLOW PATHS USING REMOTE SENSING AND GEOMORPHOLOGICAL TECHNIQUES", Open Access Dissertation, Michigan Technological University, 2025.