This dissertation comprises three interrelated studies exploring the effects of hurricanes on forestlands and the optimization of salvage logging practices. The first study examines land cover changes and salvage logging patterns following Hurricane Michael. It utilizes predictive models to identify key drivers of these changes, exploring the relative influence of storm intensity, forest vulnerability, and economic/operational factors. The second study builds upon these findings, focusing on the agent attribution for land cover change observations leveraging advanced remote sensing tools and relevant spatial data. By distinguishing between wind damage and salvage logging activities, it advances the understanding of post-hurricane land cover dynamics. The third study introduces a novel timber supply model that utilizes robust stochastic optimization to optimize salvage operations under uncertainty. It integrates various data sources to optimize site selection, transportation logistics, and resource allocation under uncertain timber stocks, aiming to enhance salvage operations' efficiency and economic returns. Collectively, these studies provide valuable insights for improved hurricane disturbance management.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-7266 |
| Date | 13 August 2024 |
| Creators | Sartorio, Ian Pereira |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
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