Module 4 Hazards: Coastal Flooding

In this week's module 4 we worked with analyzing natural disasters. We were given a scenario from Hurricane Sandy that made landfall near the Atlantic City, NJ on 10/29/2012. We were tasked with analyzing the geophysical effects of coastal flooding after a tropical storm, using the data that was provided to us. In the scenario we a GIS Tech working for a university that has been contracted by a private company to measure erosion caused by the tropical storm. Using LiDAR data to create a digital model. Then we will use the DEM raster to measure the erosion.

Some of the learning outcomes from this week's module includes understanding how elevation models are used to delineate coastal flood zones. Being able to perform overlay analysis in vector and raster domains. Becoming familiar with procedures for coastal flooding assessment.

In creating the map displayed below I started off using the Spatial ELT Tool to convert the LAZ file to a LAS file for both the pre and post Sandy files. Then moving on to creating the DEMS starting by converting the LAS files to a TIN using the LAS Dataset to TIN tool for both the pre and post files. Then I used the TIN to Raster tool to change the sampling value. Then using the Raster Calculator I subtracted the pre and post raster layers. Then change the symbology to highlight the change between the two layers. Showing the elevation change between pre and post hurricane Sandy. Then using a provided layer of the buildings on top of this changed layer I was able to see the change done to the neighborhood, such as what is still demolished or what has been rebuilt. This kind of analysis is done by insurance companies. It allows them to cut down on response times for filing and processing claims. This kind of analysis is also useful for government agencies for planning for rebuilding and restoration.

The map below shows the results of the last analysis exercise. We were tasked with comparing a traditional USGS DEM and a DEM derived from LiDAR. Comparing the differences in results between the two elevation models. We were told that we are assuming there was a storm surge of 1 meter.

The LiDAR layer is a high-resolution elevation model for a portion of Collier County, FL units in feet. The USGS layer is a regular elevation model before LiDAR data was available of the same area and its units is in meters. We were tasked to create a new raster for each elevation layer that shows which cells are flooded or that have an elevation of 1m or less. To do this I used the Reclassifying Tool. Classified the two new rasters into 2 areas ≤ 1 meters, and NoData. I also converted the LiDAR data into meters during the reclassification. Using the Region Group Tool I determined which cell value was associated with the regions connected to open water and used the Extract by Attributes tool to extract that area to a separate raster. Then using the Raster to Polygon tool, I converted the new raster of the areas connected to open water to a polygon. Then next I needed to determine the impacted buildings from the storm surge. To do this I used the provided buildings file. I performed a spatial join for each of the USGS and LiDAR flooded layers to determine which buildings were impacted for each layer. I then did A Select by Attributes Tool for each of the joins and made a new layer that contained just the buildings impacted from the flooded areas for each layer. With the new layers I used the Pairwise Intersect Tool to determine which buildings were impacted by both layers and create a new feature class with buildings impacted in both the USGS and LiDAR flooded areas. To create the table shown in the map I used the Select by Attributes Tool and create queries of the feature classes to determine the number of the types of buildings.