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Showing posts from October, 2024

M1 Lab: Visual Interpretation

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  This map layout was created to assist in learning how to identify areas/objects from an image based on traits, such as shape, size, shadows, patterns, and associations. I took an old image from Pensacola Beach and found various features based on these different traits. For example, I chose the pier for shape, as it was very distinct. I chose the ocean for pattern because the ripples of the water was how i could tell what it was. I chose the water tower for shadows because the shadow is the only way I could distinguish it. I chose the beach sand for association because it would be hard to tell what it is without being next to the ocean. The categories of traits are color coordinated to easily tell what traits I used to choose the objects in the image. This was a new skill for me, so it took me some time to get used to doing it. 

Final Proejct

Transcript link: https://docs.google.com/document/d/159daNb5ytSLFVpiSvWUdv-fK7UYOWlAG/edit?usp=drive_link&ouid=107434086861039984206&rtpof=true&sd=true PPT link: https://docs.google.com/presentation/d/1PVbeyJJYVJxHel-eS4AInq_naRA2YJSX/edit?usp=drive_link&ouid=107434086861039984206&rtpof=true&sd=true This project was to analyze the impacts of a new transmission line on surrounding areas, including homes, schools, and environmentally sensitive areas. The ppt presents multiple Map Layouts and describes how they were done, as well as descriptive analysis of findings. The transcript is more detailed than the ppt but does not have any visual models. This project was much more demanding of time and attention than I expected. There are some amazing things one can do with GIS to analyze problems for people or agencies. I would like to give myself a lot more time on future projects so that I can more deeply analyze the data and make a more interwoven presentation. 

M6 Georeferencing

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  During this module we learned how to georeference images into ArcGIS layers that were already existing, as well as editing these images. The georeferencing took some time to get used to. I found out after a while that the best way to get the smallest possible error was to zoom in on the images as closely as possible when choosing the reference points for the image to attach to. When editing a new building and road onto my layer, I found some of the editing tools to have a learning curve. It was very easy to make a line look wonky and I had to redo them multiple times, especially with the curves tool that goes around turns. Eventually I got used to it and it went smoothly. When I was turning this into a layout map, I had to play around with the transparency of different layers so that the entire map looked smooth, while still showing all of the information necessary. 

M5 Lab

https://arcg.is/8Pnzv The geocoding lab was not too difficult for me to comprehend. I was not very familiar with cleaning data on an Excel sheet before this, but once I grasped what was going on, it came very easily. We took data from a webpage and copied it into an Excel sheet. We then made the data useable in an ArcGIS Pro Map by deleting unnecessary cells and organizing all the necessary data. Once we put the Excel data into an ArcGIS Pro map, we had to use various tools, such as Address Locator and Geocoding to further sort out our data so that every data point was on the map and accounted for. Using Geoprocessing tools in ArcGIS Pro is not too difficult for me, in comparison with other things we have learned. I feel like maybe address matching would be pretty confusing in the future when I don't have instructions in front of me, but that is why we practice! This map ended up showing a baselayer Imagery Hybrid, FL Counties, Manatee County, and our Data points.