Examining thermokarst initiation with random forest models

• Main Author: Spicer, Rawser W.
• Other Authors: Bolton, W. Robert, Lawlor, Orion, Chappell, Glenn
• Format: Other/Unknown Material
• Language: English
• Published: 2020
• Subjects: Fairbanks; Thermokarst; Alaska
• Online Access: http://hdl.handle.net/11122/11879

Master's Project (M.S.) University of Alaska Fairbanks, 2020 This project examines thermokarst initiation through the application of random forest models. Thermokarst initiation marks the start of the formation of thermokarst features. Changes in landscape, due to the thermokarst process, can result in changes in wildlife habitat, as well as energy, carbon and water fluxes. Random forests are an ensemble learning technique that combines the results of many independent decision trees to create results that avoid the overfitting in regular decision trees. Random forests were trained against an existing thermokarst initiation model. Results showed that random forests were useful in this context. Random forest hyperparameters were also examined through a multiparameter sensitivity analysis.