M6

 


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About Me

  My name is Reese and I am in my third set of courses in this GIS program at UWF. I work full time as an Environmental Specialist for a local municipality, which is what my story map is all about (  https://storymaps.arcgis.com/stories/4cf090796d3f4682a018a53db55ee664 Links to an external site.  ). I have helped with lots of GIS projects in my environmental career, and taken one GIS course in my Environmental Science bachelors degree before I started this program. I absolutely love geography, history, and maps in general. Because I have done so much GIS work in the environmental and natural resource field already, I decided that I wanted to become even more skilled in this realm, which is why I joined the GIS program here. My goal in going through this program is to be as valuable to my city in environmental and geographic information science as possible. I also want to be the person who is looked to when any complex questions could be answered through GIS.   I...
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M4

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  For this project, I conducted a geospatial analysis of coastal flooding and storm surge impacts using LiDAR and USGS DEM datasets. The study focused on the aftermath of Hurricane Sandy, particularly in Mantoloking, NJ, and Collier County, FL. Using ArcGIS Pro, I processed pre- and post-storm LiDAR to detect elevation changes and map erosion. I also analyzed storm surge impacts using reclassified DEMs to identify affected buildings. One major takeaway was the stark difference in flood predictions between high-resolution LiDAR data and traditional USGS DEMs, highlighting substantial errors of omission and commission when using lower-quality datasets. I learned how DEM resolution and assumptions about storm surge height can significantly affect spatial analysis outcomes. Challenges included aligning datasets collected years apart, accounting for reconstructed areas, and simplifying assumptions like uniform surge height, which limit real-world accuracy. Nonetheless, this study emphas...
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M2

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  In this project, I created several raster maps from a LiDAR dataset to analyze forest structure and biomass. First, I generated a Digital Elevation Model (DEM) and a Digital Surface Model (DSM) by filtering the LAS dataset to isolate ground and non-ground points, respectively. Using these rasters, I calculated a Height raster to estimate tree heights by subtracting the DEM from the DSM. Then, I created a Canopy Density raster to assess vegetation density by comparing vegetation and ground return counts. One of the main challenges I ran into was locating the “Filters” option for the LAS dataset. Initially, I didn’t see it in the Contents pane and struggled to isolate ground points. I eventually realized that I needed to use a LAS Dataset (.lasd) file and switch to the Appearance tab in the 3D Scene view to access point classification filters like Ground or Vegetation. Once that was resolved, I was able to proceed with creating the DEM and DSM accurately. Another minor issue was un...
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