My Geographic Information Journal

  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...

   My name is Reese and I am in my fourth 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...

 

  We were tasked with writing a script that creates a geodatabase, copies all feature classes from a data folder into it, then populates a dictionary with the names and populations of New Mexico county seat cities. This was by far the largest and most complicated script project I have done so far. It was without direction so I had to outline what I was thinking and try lines of commands to see if they would work and put it all together in the outline. One of the main issues I was toward the beginning of my process. I didn’t really understand what setting arcpy.env.workspace was doing. I thought it was just setting a default folder, but it actually controls where ArcPy looks for data and sometimes even affects how tools behave. When it was pointing to the wrong folder, ListFeatureClasses() just returned nothing, and I had no idea why. I also had so many issues with file paths like forgetting to use raw strings (r""), accidentally adding extra slashes, or copying paths from Win...

  These are the Notebook script output results from this weeks lab pt 2. These results are telling me that my script successfully ran AddXY, Buffer, and Dissolve tools to a hospitals shapefile that I had in a map on ArcGIS Pro.  This was a bit of a difficult task for me. I had to sit and just consider the task at hand for a while. At first, I was just thinking about what I already had, and where I needed to get it, in terms of ArcGIS Pro tools and functions. I am pretty skilled with ArcGIS Pro, so doing these tasks would be pretty easy if I were not scripting it. However, I was trying to keep in mind not only all of the scripting language rules, but also whether I needed to use try-except statements to run through the script and catch issues. I then broke my individual tasks down and focused on each separately. First was addxy coordinates. I understand this function in Arc Pro, but how do I script it in python? I went back into my notes and the textbook and found the main comm...

  This weeks lab we expanded on debugging problems in a script. The first two parts felt pretty natural, like common sense. Making cases of text match each other, being consistent, proper spelling, etc. The third part felt a bit more uncomfortable. We had to find where we thought there was an error and use try-except statements to wrap around the script so the interpreter would catch potential issues, run the script anyways, and tell us where the issues were. This task took me a while to get correct. I had to run some different ideas and go back to the module resources and drawing boards before I finally got this to work right.