Module 4 - Damage Assessment

 

Figure 2 - Hurricane Sandy Track 

This lab guided me through mapping Hurricane Sandy’s track, symbolizing the storm intensity, and preparing a layout that highlights affected states and the hurricane’s path. I then create a citizen damage‑assessment survey using Survey123, followed by building pre‑ and post‑storm imagery mosaics for visual comparison. Next, I design attribute domains and a structure‑damage feature class to support consistent data entry. Using these tools, I digitized structures within the study area, assigned damage categories, and symbolized the results. Finally, I digitized a simple coastline, calculated distances from each structure to the shore, and analyzed whether damage patterns correspond to proximity to the coast.

Damage Assessment

To examine patterns in the damage, I first created a simple polyline feature class called Coastline in the geodatabase and digitized the shoreline using the pre‑storm imagery. It didn’t need to be super detailed, just enough to mark where the water meets the beach along the study area. After saving those edits, I used that coastline to measure how far each structure was from the shore. From there, the goal was to figure out which tools would help summarize the number of structures in each damage category within the 0–100 m, 100–200 m, and 200–300 m distance bands. Once the distances were calculated, it was just a matter of organizing the counts into the table so I could see whether any clear patterns showed up in how damage relates to proximity to the coastline.

The damage assessment denoted the following results; the closer the homes were to the coast, the higher the likelihood of being destroyed or experiencing major damage, which is expected since these homes are closest to the shoreline and most likely to experience major wind and water impacts. Although these measurements certainly reveal a trend showing that the closer a structure is to the water, the more destruction and structural damage it will incur, I don’t know if this numerical pattern will always translate across the entire coastline, because different areas experience different building densities, differently sized lots, and other variations. However, if there were a way to standardize these differently sized areas and create a ratio comparison based on area density and similar factors, we could potentially use those numbers to extrapolate conditions in nearby areas.

Table 1- Summary of Structural Damage

Figure 1 - Structural Damage Assessment Features and Attribute Table

To View a Summary of this two-week Coastal Flooding Assessment, please check out my Story Map!

 : https://arcg.is/1qmuC54