GIS5100 Module 5: Hazards - Damage Assessement

 

    

Hurricane Sandy (2012) path

    This week’s lab in Applications in GIS allowed us to assess damage from Hurricane Sandy in Ocean County, New Jersey. To do so we used provided pre- and post- Hurricane Sandy rasters and compared both to each out using the Swipe tool. This allowed us to see the damage and determine where each parcel would fall under in categories of Structure Damage, Wind Damage, Inundation, and Structure Type. 

ArcGIS Pro screenshot of structure damage in an area of Ocean County, New Jersey

I created a new feature class “Structure Damage” as a point feature and digitized each parcel with a point indicating level of damage.

I then created a new feature class “Coastline” as a line feature and digitized the coastline parallel to the study area.

I used the Multiple Ring Buffer tool to create a buffer around the Coastline feature class with parameters to determine structures impacted within 100 meters, 200 meters, and 300 meters.

Then I used the Spatial Join tool to determine the count of structures within certain distances from the coastline using the and determined how many structures were within 100 meters, 200 meters, or 300 meters using Select By Attributes.

These steps allowed us to determine the below data:

Structure Damage Category	Count of Structures 0-100 m from coastline	Count of Structures 100-200 m from coastline	Count of Structures 200-300 m from coastline
No Damage	0	0	0
Affected	6	1	2
Minor Damage	0	0	7
Major Damage	0	32	33
Destroyed	4	7	0
Totals	12	40	42

 

 

 

 

 

 

               The results indicate that the closer structures are to the coastline, the more damage structures obtained. There were (12) structures between 0-100 meters, (4) structures were destroyed. Out of (12) building structures, (4) were parking lots – so  those are outliers if we are trying to determine building damage. Less buildings are closer to the coast within 0-100 meters, so this also affects the results if we were to graph the data.

              This information is not reliable enough to extrapolate nearby areas, in my opinion. We would need more information and a larger study area to more reliable extrapolate data in a more accurate way. For example, this lab indicated we should be incorporating each parcel – but not every parcel housed a building structure. This would impact the results depending if we wanted to specify building damage.

StoryMap: https://arcg.is/0n9a4i0