Final Project: Bobwhite-Manatee Transmission Line

The Final Project finally came! For our last assignment, we were to run an analysis on whether or not the location of the Bobwhite-Manatee Transmission Line was viable. The objectives were to make sure the surrounding communities, land owners, and environmental lands were impacted as minimally as possible. After collecting the data, producing maps, and analyzing multiple queries and selections, I deduced that the location was definitely in an ideal location. Please check out my powerpoint and read the transcript below to get a more in depth interpretation of this project. Thank you!

Powerpoint Link
https://drive.google.com/open?id=1XsPi3kEvjDej-EzFN1T-VzZX_Zjgndtc

Transcript Link
https://drive.google.com/open?id=1K2PB1fpjq7ry4sOKYcB9Viq7CTFhK9hH

Geocoding and Model Builder

This week we focused on geocoding and did an ESRI training exercise about Model Builders. The Model Builder used tools to input data and create output data in a diagram. It taught another way to create buffers. We learned how to make a route analysis and geocode addresses by using the geocoding tool and the network analyst tool. Below is a description of the steps I took:

1.       TOC > EMS Table > Geocode Addresses > MyAddressLocator > Geocoding_Result > Geocoding Options > Minimum match score = 75 and minimum candidate score = 10 > rematch

2.       From here, I had the Lake County, FL  EMS Stations site opened, and I highlighted each unmatched station in sequential order. I added an aerial basemap to ArcMap, and viewed each address on the stations website in satellite view. This made the process go by much quicker as I was able to use surrounding features that stood out to orient myself and locate where each station was.  When I was positive I had the location on ArcMap, I would Pick Address From the Map, and click directly on the map. Then, I would press rematch to clear it out of my list in the rematch window. I followed this process until everything was geocoded!

Week 13 Lab: Georeferencing

This week's lab we took a journey into georeferencing distorted raster images and editing point and polygon features on a map. We started by adding control points by determining the most easily identifiable buildings (polygons) to begin the hunt for a low Root Mean Square (RMS) error. The RMS is an indicator of spatial accuracy and our goal was to get that number as low as possible-but definitely lower than 15! I found this process to be fairly quick and easy and got a 7.62963 on my first attempt! I did have to delete about 3 control points along the way but it was not frustrating in the least. We were introduced to the editor toolbar and used this to create a polygon over one of the campus buildings and to create a polyline for a section of road by following the centerline. Again, this was very quick and easy for me. But, I do this at work so I have had some practice. The subject of the map was creating a conservation zone for an Eagle's Nest and to do this we created a protection buffer using the Multiple Ring Buffer in the toolbar. The following was the process:

1. When I created the hyperlink, I had to save the EaglesNest.jpg to my student Google Drive. From there, I copied the shareable link. When I inputed it into the attribute table, it would not accept more than 65 characters. To solve this problem, I went to bit.ly.com and shortened the url link. When I updated the attribute table, the link now worked.

2. TOC > EaglesNest > Properties > HTML popup > check Show Content > Choose As a url radio button > select Picture Field > OK. From here, when you click on EaglesNest with the identify tool, an attribute window pops up and the lightning bolt is a clickable link to the picture.

3. Customize > Customize Mode > Commands > search Multiple Ring Buffer > selected and dragged to editor toolbar > right click and selected Image and Text.

Below are the two map deliverables. One is a 3 dimensional map we created in ArcScene!

UWF Eagle's Nest Conservation

 UWF Campus-3D

Week 10: Vector Analysis 2

This week we completed the second portion of the Vector Analysis series for lab. We learned how to use the buffer and overlay tools. We were finally introduced to Python and creating basic script writing by running a buffer. Below are the steps I took:

1.       TOC > Water_Buffer > Open Attribute Table > Add Field > short integer type > “insd_wbuf”

2.       Keeping the attribute table open, right click on “insd_wbuf” > Field Calculator > 1 > for every feature in the layer

3.       The same process was repeated for the “roadsbuff300m” except the field was named “insd_rbuf”

4.       TOC > roadsbuff300m > Open Attribute Table > Add Field > short integer type > “buffdist”

5.       Keeping the attribute table open, right click on “roadsbuff300m” > Field Calculator > 300 > for every feature in the layer

6.       Next, I ran a Union Overlay by: Arc Toolbox > Analysis Tool > Overlay > Union…then for input features, I selected Water_Buffer and roadsbluff300m. I named the output feature class as S:/Intro2GIS/10_Vector2/V2Data.gdb/Union_Buffer.shp. I joined attributes as ALL and left the Gaps allowed option checked and selected ok.

7.       Select by Attributes > insd_rbuf = 1 AND insd_wbuf  = 1. Then I exported the selected features from TOC > Union_Buffer > Data > Export Data to a new feature class called buffer_union_export

8.       When this new layer was added to the map, I only selected this layer, the Roads layer, and the Water layer to appear on the map.

In this lab, we used the union tool to create the buffer needed to isolate the parameters for our campsites. Below is a map of potential campground sites with the buffers and overlays created.

Potential Campground Sites

Weeks 7 & 8 Lab: Data Search

This week's lab was part scavenger hunt, part learning a new stitch-lot's of start over and repeats!      First, I went on the search for data. I went to the Saint Johns County, Florida website. They provided most of my data. They have a Data Depot Section with tons of free, downloadable data available. I downloaded their creek data file for my hydrography. I went this route instead of downloading major rivers, as I didn’t really see any in the county. I also downloaded their city data verse FGDL.org. Well, I downloaded FGDL.org too, but after adding that data set to my first map, and trying to build a query to only include cities in St John’s county, I decided there was too much useless data that made the map messy. I also chose the county layer from the Data Depot, to save time from having to clip the county boundary from the entire state of Florida. They also provided an already clipped DEM Raster layer which totally saved my life…or a lot of time, anyways. I did use the major highways data file from FGDL.org. I was not fond of the roads file that the Data Depot provided-it was all streets, all 14,000 of them. I only wanted major highway systems to keep my map cleaner. I downloaded the NW quadrant of St Augustine for my second map from the Labins website. I chose the Transverse_Mercator projections for Maps 1 and 2. It saved a lot of time just clipping the data layers to the county boundary. Of course, I spent a lot of time on my first map figuring that out. But hey, isn’t that part of the GIS learning process??!! The one area I ran into huge trouble and just could not figure out was the Land Cover Raster-I followed the Raster Project data tool steps to a T, and it clipped it-just not to any county boundary I added…it was noticeably larger. Thus, I decided to just go with the Basin Catchment layer that good ole’ St Johns County GIS Data Depot provided. This counts as land cover, right? One could argue? I feel like I am on the precipice of getting this whole Projections game down but I am not quite there yet. Practice makes almost perfect, though! Here are the maps I projected!

Map 1: Conservation Parks, Creeks, & Wetlands

 Map 2: Aerial View of Saint Augustine, Florida

 Map 3: Topography & Basin Catchments of St Johns County

Map Projections: Part 2

This week's lab was a continuation of displaying data in the same projections. This was definitely the most challenging lab to date. I learned how to project different data files. I chose Pensacola, Florida for my aerials, created a shapefile of petroleum storage tank monitoring sites in Escambia County, and displayed the data over quad index and the counties of Florida. From the labins.org website, I learned how to navigate and searched for data files containing aerial images in Florida. From the 2004 RGB State Plane Units: FT MrSID link, I determined the file name by accessing the Geographic Profile>Quad>Dep Name and selected Pensacola, since it was a city in Escambia County, Florida. The quad number was 5258. I downloaded the file and saved to my data file. From fgdl.org, I searched Major Roads, and selected the MAJRDS_JAN18 file from the Florida Department of Transportation. I projected the data from Albers to NAD_1983_2011_StatePlane_Florida_North_FIPS_0903_Ft_US. FGDL.org is also where I obtained the quad index, and I selected the file USGS 1:24,000 Quarter-Quad Index. I also searched for county boundaries here and downloaded the cntbnd_sept15 file. I projected this file from Albers to NAD_1983_2011_StatePlane_Florida_North_FIPS_0903_Ft_US with the NAD_1983_To_Harn_Florida transformation. I accessed the EscambiaSTCM file from the R file and added two columns, the Ycoord and the Xcoord, in the excel spreadsheet. I added the XY Data on my map and transformed the data there. I did run into an issue here where the data points were thousands of miles away from Escambia county. It turned out that I needed to add a negative sign to my Y coordinates. This fixed the issue! The geographic coordinate sytem used for the shapefile created from the excel data was GCS_WGS_1984. When I had all the necessary data, shapefiles created, and projections finished, I was ready to create the map. I added the layers in this order to display so everything was viewable on the map: EscambiaSTMD_SO (excel shapefile), Major Roads, the quad file, the county layer, and the 4 aerial images. I made the quad file 40% transparent so both the quad layer and the county layer could be seen. I have included screenshots of my data and the data frame properties below. Enjoy!

Petroleum Storage Tank Monitoring Sites in Pensacola, FL

Map Projections: Part 1

Map projections are used to display 3 dimensional  areas in a 2 dimensional manner. This week we learned how to present the same dataset in three different map projections, so we could see the variation in area of each projection arranged. Different map projections vary in size and distortion. Understanding what each projection looks like and what data you are using it important in choosing which projection to use for your map. Uniformity in map projection choice is essential in making a map that is clean and represents the area and the data you are conveying. The map below shows 3 different map projections, Albers, UTM 16 N, and State Plane N, of four counties in Florida. There is a table provided with the square area in miles for each county in each projection.  According to the data in the  table referenced on the map, Miami-Dade County has the most deviation in comparison by area, followed by Polk County, Alachua County, and Escambia County. This is because the counties that are closest to the UTM 16 N and State Plane N zone display less of a difference in variation. UTM 16 N and State Plane N are limited to a smaller portion of the Florida panhandle and thusly will be more accurate showing the counties within their boundaries. Because of this, Albers, which is a global projection, is best used to signify Florida state. This week, the biggest challenge was formatting the table as neatly as possible. I chose to insert an Excel table in Microsoft Word and format it to an appropriate size and without gridlines. Then, I just copied and pasted in ArcMap. It was my favorite outcome of presenting the data, so I went with it! Projections has been the most challenging lab thus far. I hope I get comfortable with it soon, considering choosing the right ones dictates how well your map reads!

Albers, UTM, State Plane N Projections of Alachua, Escambia, Miami-Dade, and Polk Counties in Florida