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Full-Text Articles in Physical Sciences and Mathematics
Application Of Remote Sensing And Machine Learning Modeling To Post-Wildfire Debris Flow Risks, Priscilla Addison
Application Of Remote Sensing And Machine Learning Modeling To Post-Wildfire Debris Flow Risks, Priscilla Addison
Dissertations, Master's Theses and Master's Reports
Historically, post-fire debris flows (DFs) have been mostly more deadly than the fires that preceded them. Fires can transform a location that had no history of DFs to one that is primed for it. Studies have found that the higher the severity of the fire, the higher the probability of DF occurrence. Due to high fatalities associated with these events, several statistical models have been developed for use as emergency decision support tools. These previous models used linear modeling approaches that produced subpar results. Our study therefore investigated the application of nonlinear machine learning modeling as an alternative. Existing models …
Probing The Precambrian Geodynamo: Analysis Of The Geomagnetic Field Behavior And Calibration Of Pseudo-Thellier Paleointensity Method For Mesoproterozoic Rocks, Marine Foucher
Dissertations, Master's Theses and Master's Reports
Understanding the geomagnetic field direction and strength (e.g., paleomagnetism and paleointensity, respectively) recorded by Precambrian rocks is essential to obtain insight into the nature and evolution of the Earth’s early geodynamo and for constraining models of planetary evolution. Major milestones of our planet’s history, such as beginning of plate tectonics, development of the atmosphere and life, took place during the first four billion years. However, the available data on the Earth’s magnetic field in the Precambrian are very limited, especially the information about the field intensity which represents one of the most challenging aspect of paleomagnetic research. Many Precambrian rocks …