Date of Award
2024
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Atmospheric and Earth Science
Committee Chair
Udaysankar Nair
Committee Member
Brian Freitag
Committee Member
Abdullahi Salman
Committee Member
Xiaomin Chen
Research Advisor
Udaysankar Nair
Subject(s)
Wetlands-Gulf Coast (U.S.), Hurricane damage, Hurricane Ida 2021, Hurricane Ian 2022
Abstract
This thesis employs data fusion techniques to analyze the damage to US Gulf Coast wetlands caused by Hurricanes Ida and Ian. The relationship between ecosystem damage and wave stress is evaluated using salt marsh classifications derived from PlanetScope imagery and atmospheric and ocean modeling (WRF, ADCIRC+SWAN). Short-term vegetation recovery following Hurricane Ian is assessed using HLS-derived NDVI data. A multi-decadal analysis of salt marsh vegetation off the Louisiana coast is conducted with statistical models incorporating MODIS NDVI and MERRA-2 climate variables. The analysis reveals the following key findings: 1) -38.7% and -93.25% of wetland area changed following the passage of Hurricanes Ida and Ian, respectively; 2) on average, Ian caused a ~14% reduction in wetland NDVI, which recovered within one year; 3) statistical modeling found a multi-decadal decreasing trend in salt marsh NDVI, after accounting for hurricane damage; and 4) wave stress modeling shows potential for predicting wetland damage.
Recommended Citation
Cowan, Trent W., "Data fusion approach to assessing hurricane impacts on US Gulf Coast wetlands: case studies of Hurricanes Ida and Ian" (2024). Theses. 718.
https://louis.uah.edu/uah-theses/718