Piece of Eden GIS Blog

This week I learned how to utilize ArcGis Pro to make out the pathway of a past hurricane, Hurricane Sandy, along the North East coast of the USA in 2012. Later, I was also able to assess structural damage on the coast of New Jersey from Hurricane Sandy.  Below you can see the map I created of Hurricane Sandy's pathway/timeline. If you look closely, you can see via the symbology what category storm Sandy was along its path along with information on its wind (mph) and pressure (barometer) information.  In the second part of the lab, I assessed the structural damage of Hurricane Sandy in a select area in New Jersey. I created a new point feature class and subsequent domain with categories no damage, affected, minor damage, major damage, and destroyed to categorize each parcel. After creating the points and designating their damage category, I analyzed the data future by determining what damage feel 0-100m, 100-200m, and 200-300m from the coast.  1.       Created a new polyline featur

 For the first part of this module, I compared before and after pictures of the New Jersey coast, pre and post Hurricane Sandy. I created DEM's from lidar data to compare the before and after. Below, you can see the magnitude of erosion and accretion on the Jersey coast due to the Hurrican Sandy in 2012.  In the second portion of this lab, I created a storm surge impact model for Collier County, Fl. This was a very educational assignment and I learned a lot. We not only created a storm surge model for the coast of Florida, but we also did so utilizing both Lidar and USGS DEM data to compare accuracy. I first began by converting the Lidar layer to meters, and then reclassified both to only include data where the elevation is under 1 meter. I used the region group tool to clump together into one large area the land along the coast, and isolated it (via select by attributes) to only analysis this single large connected area. Lastly, converted that large area for both Lidar and USGS to

 This was an interesting module, as I analyzed homicide data in 2017/2018 Chicago. I created three different hotspot analysis maps to anticipate homicide hotspots in Chicago year 2018 using data from 2017. After creating each map, I determined the accuracy of each map by comparing how large a map's hotspot area was to the actual crime density of 2018.  Beginning this portion of the assignment, I first made sure to change the environmental parameters to that of the city of Chicago boundaries.  Below I summarize all the technical steps I took to perform my analysis.  1)       Grid Overlay: a.        Spatial join Chicago grid and 2017 homicides b.       Select attributes greater than zero and make new layer c.        Select attributes in the top 20% and create a new layer d.       Dissolve layer into one polygon                                                                i.       Create a new field in the table                                                              ii.