Module 4 - Hazards: Coastal Flooding

    This week, in the fourth Applications in GIS lab, was about Hazard with concerns for Coastal Flooding.

    In this lab, we primarily looked at the before and after of storm surges with Lidar, as well used the tools we learned in order to make maps with a certain height of water from a storm surge. In this post, I will go over all three parts of the lab.

    In the first part of the lab we focused primary on Mantoloking New Jersey from when it was hit by Sandy in 2012. This involved us downloading LiDAR data once more and transforming it with new tools, Spatial ETL tool, from a .laz file to a .las file. Once this was done we then observed the area to see the difference between pre and post sally. Next we then made the raster you see below. This was done by changing the lidar data to tin, to raster, and then subtracting pre from post. This then allowed us to see with our new color ramp from red to blue where the high areas of erosion are. As you can see in the map below, there are a fair few areas where the storm washed away houses and eroded the land

    In the second part of lab, we used our tools and knowledge to reclassify a raster to obtain data for flooded cells of 2 meters or less. This was also done for another part of New Jersey where once we obtained these 2 meters or less of flooded cells, we calculated how much of Cape May County might be effected by a 2 meter storm surge. This part of the lab was a bit shorter but was provided in order to reaffirm the use of tools used previously. 

    In the third part of lab, we then compared the use of LiDAR and USGS elevation models in order to see which determined impacted buildings. This first started with us assuring that the values were both in meters before then going through the process to make the data into a polygon after erasing disconnected areas in the Lidar data (though with my process I may have made an error and still have a few of the disconnected rasters). Once that was done, we then used spatial join and select by attributes in order to determine how many of the featured buildings were flooded with either LiDAR or USGS. This then escalated to where we would see which were only effected by LiDAR with error omission and only effected by USGS with error of commission. All of which can be seen below. I will admit due to my error of using a wrong tool earlier with the deletion of disconnected raster area, my data may be a bit wrong on the LiDAR side. Despite this I carried on to do the rest of the lab the best I could.

    Overall this lab was a bit more challenging than what I am used too, but it did help me try to problem solve on my own more. This did result in some minor errors with my LiDAR data in the the third part of the lab, but it helped me reach the end. I hope in the next lab I am able to understand what needs to be done more and complete it as well as this one.

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