Module 4: Coastal Flooding

 In this lab, I explored how GIS can be used to model and analyze the impacts of coastal flooding caused by storm surge, using real-world data from Hurricane Sandy in New Jersey and simulated flooding in Collier County, Florida. By working with elevation models (DEMs) and building footprint data, I was able to map potential flood zones and estimate which buildings would be affected by a 1-meter surge.

The process involved reclassifying elevation rasters to identify low-lying areas, filtering out isolated depressions not connected to open water, and using spatial joins to determine which buildings intersected the predicted flood areas. One major takeaway was understanding how different data sources (like high-resolution LiDAR vs. traditional USGS DEMs) can lead to different impact estimates—and how those differences can be measured through errors of omission and commission.

This lab highlighted how GIS is not just about mapping, but also about making data-driven decisions in emergency management and urban planning. It also raised important questions about the assumptions we make when modeling natural disasters and how refining those assumptions can improve real-world preparedness.


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