Assessing Coastal Resilience to Sea-Level Rise, Flooding and Extreme Weather Events Using Spatial Data and Big Data Analysis on the United Coast Gulf Coasts

Coastal resilience to sea-level rise, flooding, and extreme weather events is a critical focus for safeguarding communities, ecosystems, and infrastructure along the United States Gulf Coasts. These regions are particularly vulnerable due to their low-lying geography, dense populations, and economic dependence on industries like tourism, fishing, and energy production. Climate change exacerbates these vulnerabilities, increasing the frequency and intensity of extreme weather events and accelerating sea-level rise. Effective resilience planning necessitates a comprehensive understanding of these dynamics, which can be achieved through advanced spatial data and big data analysis techniques. This study examines the application of spatial data analytics and big data frameworks to assess coastal resilience. Using geospatial data, including satellite imagery and LiDAR, combined with historical weather patterns and socioeconomic datasets, we model and visualize the potential impacts of rising sea levels and extreme weather. Predictive modelling, machine learning, and simulation techniques are utilized to identify at-risk areas and evaluate the effectiveness of mitigation strategies. Furthermore, we integrate social vulnerability indices to ensure equitable resilience planning for communities disproportionately affected by these threats. The findings underscore the importance of data-driven approaches in coastal resilience planning. By leveraging spatial and big data analytics, this study provides actionable insights into vulnerability hotspots and mitigation priorities. These insights support policymakers, urban planners, and environmental organizations in designing adaptive strategies to minimize risks and ensure long-term sustainability. This integrative approach offers a blueprint for enhancing coastal resilience across other vulnerable regions globally.