Final Project: Bobwhite-Manatee Transmission Line

For the final project, I had to design and perform an analysis of a preferred corridor for the Bobwhite-Manatee Transmission Line. This was a real-world case study that happened around 10-15 years ago. FPL needed to build a line to connect a power station with a substation and had to find a route that had minimal impacts on the community.

I started with designing a cartographic model to describe the problem and criteria, and then lay out the analysis steps, data required, and outputs. From there, I began the analysis. First was using the pairwise intersect tool to figure out which conservation lands and wetlands were in the corridor. Next I created a 400ft buffer around the corridor. I heads up digitized houses based on aerials then used select by location to determine which were in the corridor and which were in the buffer. I also used this tool with the "within" setting to find parcels in the corridor and buffer. The third analysis involved geocoding school locations with a locator I created with Census data, and then determining if any of these were within the corridor or buffer. Finally I measured the corridor.

I realized in the process that I've learned a lot this semester! But I still have a few things to figure out. I stumbled through creating the new feature class and had to reproject it when it was in the wrong projection. I realized at the end that the aerials were in a slightly different variant of Albers Conical Equal Area and had to reproject the rasters. And I spent a lot of time copying and pasting layers to sort out the best way to make different maps with slightly different data. Below are a few of the maps I created. You can also check out the presentation and a transcription.

This map shows all the environmental data - I used the intersect tool to make these layers, and then calculated the geometry of each polygon to find the area for conservation land, uplands, and wetlands.

This map shows the houses and parcels that are within or intersect the corridor. Select by Location and Attribute tools were particularly helpful to find and symbolize this data.

This map shows no schools are within the corridor and it's buffer! I used the Geocoding tool to make all of those dots and feel pretty accomplished to turn cvs data into something spatial.

Georeferencing, Editing and my first taste of LiDAR data

 

This week, we covered georeferencing raster files, editing vectors to digitize features from the rasters, and playing with LiDAR point clouds. First step: georeferencing rasters! I used control points to georeference these two images of the UWF campus and a survey drawing to vector layers of the buildings and roads on campus. I did well the first two images but got a little turned around with the survey. I realized I was clicking the wrong layer first (the vector instead of the survey raster) and had to delete all my points several times. But I figured it out in the end. The control points are a lot like controls points I use in 3D processing software to match features in images and scans, so it clicked really well in my mind. Next step: editing layers! I drew a polygon for the UWF gym and a line for a road segment. Saving is an important step! We did a few extra steps in here to add a hyperlinked image to a point representing an eagles nest, as well as creating a multi-ring buffer around said point. And lastly, I opened up a LiDAR point cloud in a 3D Scene. There are some pretty cool filtering tools that helped cut through the noise of trees and buildings to see the surface elevation. I created a DEM from this data and made another map with this data. Manipulating the 3D imagery was a little difficult as I'm used to 3D software, but I finally managed to make a decent layout.

Here's the first digital surface model I made in ArcGIS during this lab. Manipulating the map in the layout was tricky, so it's not the best view. I just need to keep playing!

Geocoding School Locations

Here's a preview of the online map. Be sure to check it out at the link below!

This week, we learned how to use csv data to create feature layers in ArcGIS Pro. Part of this included gathering locations of schools in Manatee County from the Florida Department of Educations website and geocoding the locations using data from the US Census. First I copied the school locations from the website and created a nice excel document with the school name, type of school, address, and phone number. Then I created the ArcGIS database with the census data (which I reprojected into State Plane projections). I used the Geocoding tool in the software to calculate the locations based on the addresses. A few didn't work because they had PO boxes, addresses outside of the county, or the process didn't recognize the road. I found the locations for these and assigned them manually. Instead of sharing the map as an image, we shared the maps to ArcGIS online. My map can be viewed here.

Vector Analysis

During lab this week, we learned how to use buffers and overlays to help define areas that met certain criteria. We had to find areas within the De Soto National Forest that were within 300m from roads, 500m from rivers and 150m from lakes, and that also do not fall within the designated conservation areas. The buffer tools helped to define the areas near roads and waterways. We had to join this data using the Union tool and then use overlay tool to exclude the areas within the conservation zones. To finish up, we split out each parcel and calculated the area for each, then visualizing these numbers using a gradient scale. I choose to show the possible camp site locations based on calculated area, using 5 different classes based on the data itself. I broke the groups down into up to 10ha, 10.01-50ha, 50.01-100ha, 100.01-300ha, and 300ha and above. I used a color scale from dark blue to yellow, with the darker colors representing the smaller parcels as this made them easier to see on the map. When I created the map layout, I created a polygon around the area of analysis to show in the inset map so viewers would know exactly where in the park the analysis took place.