Christa's GIS Archive

Module 1 covered a brief introduction to Cartography, its history, and map design principles. I grew up Catholic, so hearing about the 20 Tufteisms instantly made me think of this being the Cartographer's 20 Commandments. Haha! Anyways, this week's lab required students to find 2 maps, one deemed well-designed and the other poorly designed, and critique them. I spun around several ideas in my head. At first, I really did want to do a map from my childhood, like something in a video game; however, I couldn't find a decent enough example that I wanted to go through with. The map I chose, which is well-designed, is one that I see quite frequently when I want to go on a nice stroll. And that is Cascades Park in Tallahassee, Florida. Cascades Park in Tallahassee, FL. It features all the points of interest that visitors can visit, as well as amenities, parking, and additional information such as hours of operation and rules. The Cascades Park map above is quite beautiful! I love ...

Back again with another GIS course -- this time it's Computer Cartography! After taking a management course, I feel excited to continue learning more about GIS. For the start of the Computer Cartography class, we're going through the motions of orientation week, which includes creating this blog post and a Story Map. This would be my 2nd official Story Map, and it covers some highlights of my life. To give a brief summary about me, my name is Christa Dizon. I work full-time as a GIS Engineering Specialist for the Florida Department of Environmental Protection. I maintain various GIS data and curate maps for the programs throughout. I joined UWF's master's program in GIS Administration because my colleagues on my team had graduated from the same program, and I wanted to challenge myself further by growing in GIS and developing my skills. I hope to merge my love of health education and promotion with GIS in the future. However, I'm happy and proud of the work I am abl...

Life got the better of me, and I forgot to upload my maps to my final project last semester. It wasn't a requirement to make a blog post for the final; however, I'd still like to archive my maps here at least before I forget again. The maps below are my LULC maps of Pebbledale Mine, showing changes from 2010 to 2019. I went with supervised classification to give myself the most control and to also challenge myself. There are definitely improvements to be made and drawbacks, which I outlined further in my final paper; but due to the time limitations and having personal plans that required me to finish this project a week ahead of time, I will hopefully be able to improve if I have to do a similar project or task in the future. Overall, still very proud of what I was able to accomplish and enjoy my maps!

This week's module covered all things classification from unsupervised to supervised. In ERDAS, we got to see how the two differed and how to preform each. It was really cool to see how the program would classify pixel areas for you based on what you essentially feed into it. Since unsupervised classification has users classify after the program categorized pixel values, it felt much easier and quicker; however, accuracy may not be as high when compared to supervised. Supervised classification took me much longer with all the steps we had to go through to identify to the program the classes/features themselves, although it was the most rewarding trying to wrap my head around everything. After learning how to preform both, the map deliverable this time around involved us taking a raster image from Germantown, Maryland and classifying its land use/land cover based on supervised classification. By the time we got to this image, I figured out that ERDAS had some nice preset color theme...

This week's module was on Spatial Enhancement, Multispectral Data, and Band Indices. I've never had to alter imagery when it comes to its spatial or spectral resolution, so this was very intriguing to learn but also a bit overwhelming at times trying to take it in for the first time. I'm sure in time, as I get exposed to these concepts more, I will become more confident doing these kind of image enhancements or alterations in the future. We first began by learning how to retrieve aerial imagery. I find that this can sometimes be the hardest part of a project. Locating the data or imagery needed can truly be half the battle. I am grateful that this lab gives us those resources and walks us through how to download imagery. If we don't have the data or images needed to conduct an analysis, then accomplishing the goal or finishing a project would be impossible. I will definitely be keeping these sources in mind for future projects, including the final for this course! Addit...

Oh we meet again, ERDAS Imagine. I haven't touched that program in quite some time -- probably at least a year or two at this point. We seldom use it for work; we mostly rely on it for creating and cleaning up large mosaics, like in the countywide historical aerial initiative that the GIS team was working towards a while back. Frankly, we haven't been keeping up with that legacy project, due to the workload and overall demand for GIS support increasing; however, I will admit my time with ERDAS was not the most pleasant back then when I first joined the GIS team. Lots of crashing and confusion occurred back then, especially when compared to ArcGIS Pro, the primary program that is utilized in our workflows. Thankfully, I was grateful for the kind and easy to digest introduction into ERDAS Imagine this second time around. Taking this course, I'm definitely seeing other ways of analyzing and processing imagery through this program, which is really cool! I've warmed back up ...