Thursday, April 19, 2018

GIS Portfolio

This is it, my final post for my final assignment of my GIS certificate! It has been quite a ride, and I have learned so much in the process. It has been really interesting to look back through all of my assignments and see how much my work has improved throughout the year. Maps that I thought were great from my first semester, I can now quickly spot ways to improve them and make them more eye-catching and professional. I chose some of my favorite maps, as well as some of my favorite assignments for my portfolio, and I also included a large project from my internship. If you would like to take a look at it, you can find it here. I am very impressed with the certificate program here at UWF, and would definitely recommend it to anyone interested in learning about GIS!

Friday, March 23, 2018


This week's assignment was a fun one. I decided to keep my GIS day celebration close to home and share some of the fun things that GIS can do with my family and coworkers. I live with my boyfriend and his two daughters, and they were especially interested in seeing what I was learning to do (and what took so much of my time for the past year). I showed them a variety of projects that I had worked on for my classes and internship and talked about the different things that GIS could do. I also talked to my coworkers about GIS and some of the neat analysis that it can do. The "event" was multi-pronged and took place at my house, my job site, and another family member's house. They were all informal and just meant to inspire others about all that GIS can do besides just make pretty maps. It was a good lesson about working hard and paying attention to details for the girls, and some of my coworkers were inspired as well. I even think one of our employees will go through the certificate program through UWF in the near future. It was definitely a lot of fun to share event a portion of what I have learned through the program so far.

Thursday, December 14, 2017

Lab 4 - Open Sourced Project - Report Week

This week was our final lab exercise for the Special Topics course. We finished up our open source project by conducting a food desert study on data from an area of our choosing with QGIS, created a webmap for it using mapbox, and shared it publicly with leaflet. You can view my webmap for my project on the southern portion of Walton County here. We also had to create a powerpoint presentation complete with audio to share our process and the results of the study. I don't want to spoil the final results, so if you are interested in the learning the percent of southern Walton County residents that live in a food desert area, you can watch my powerpoint here.

Saturday, December 2, 2017

Lab 4 - Open Sourced Project - Analyze Week 2

     For this week's lab we worked more on QGIS, Mapbox, and Leaflet to create food desert data and maps with our chosen study area. I chose to complete this project on my hometown area, the South Walton area of Florida. I downloaded US Census Bureau Tiger data from FGDL for Walton County that was organized by the census tracts. There was not available data for grocery stores, so I created data for the grocery store point layer. I located all grocery stores within the study area on google maps and created point graphics on the map, then converted the graphics to a feature layer of the grocery store points to edit the symbology and export. I included all named grocery stores in the data as well as permanent farmers markets, and made sure to exclude convenience stores that did not sell a variety of fresh produce. The data includes all grocery store locations that I could find, but may not be entirely conclusive if there is a newer store that has not been established online yet. The data depicts census tracts where a food desert exists. This refers to areas where the nearest grocery store is over 1 mile away, limiting accessibility to fresh produce for individuals without reliable transportation. Most of the South Walton census tracts are food desert areas, with the exception of the tract in the most populated area, that has three grocery stores. I used data from my local area, and I did expect similar results. There are not many grocery stores or farmer’s markets in the central to northern part of the county. The Santa Rosa Beach area does have more access to grocery stores however, and was the only census tract that was not a food desert area.

     Many map hosting websites use tiling to expedite the loading process of webmaps. This process refers to breaking the maps into separate squares or tiles so they load quicker and can hold more details than original maps were loaded all at once. This allows webmaps to be much more detailed and aesthetically pleasing without having to worry about download speed. This process allows us to include more plugins, a legend, and a geocoder and the map will still load quickly. It has been very interesting learning about map hosting and html code.

Monday, November 27, 2017

Lab 4 - Open Sourced Project - Analyze Week

Our lab this week was a new adventure into coding as well as in using mapbox to create a webmap. First, we created a webmap using our food deserts and grocery stores layers and learned how to customize and symbolize the layers. We had to duplicate the food desert layer for each class and edit the data content and symbolization to mimic a graduated color symbolization that GIS mapping programs would create. We then learned some basics about writing html code language and what each line represents to host our food desert map online through leaflet. We edited existing code to show our map, a legend of the map, a circle in a non food desert area, a polygon within a food desert area, a label and marker for Pensacola, and a geocoder. To view my final map, click here. Overall it was slightly less daunting than I was expecting, but still had some intricate parts.

Friday, November 17, 2017

Lab 4 - Open Sourced Project - Prepare Week

This week's lab was our first introduction to open sourced GIS programs. We explored QGIS and recreated the "Own Your Map" lab to learn the basic settings then furthered our knowledge by learning how to complete some analysis in QGIS. We were taught how to do basic clip analysis, use the selection tool, and use the layout options to create our final map outputs. We learned about food deserts, which are urban areas where the nearest grocery store is over 1 mile away, leading to a lack of fresh produce and healthy food options for many residents. We used QGIS to map the food desert areas in Southern Escambia county, and selected the area where we will be conducting our own food desert analysis. The QGIS program offers a nice free alternative to ArcGIS if funds are limited, but definitely has a few more glitches than ArcMap. It offers a wonderful color selection and it is nice to have the layout in a separate window, but some of the other features are much trickier than in ArcMap.

Wednesday, November 15, 2017

Lab 10 - Supervised Classification

This week's lab taught us about how to conduct a supervised classification in ERDAS Imagine. We learned different ways to create spectral signatures in the AOI layer, including manually drawing the polygon as well as using the grow tool to grow the polygon from "seed' or from a certain pixel. We also learned how to examine the histograms and mean plot chart to see where the most spectral confusion existed and to determine which bands to use for the display. We completed the process for an example map before conducting our own supervised classification of an area in Germantown, Maryland. I enjoyed learning about this method, but believe that my skills need some refining as my roads signature was too close to my urban areas signature and more of the area was diverted to roads than what exists in the image.