At this point in my entry-level upskilling project, the ground work has been done. I have a polygon of the Chesapeake Bay laid over an OpenStreetMap layer and I know how to change the color of it. Going back to the initial post, my hope with this project is to show change over time in the crab population of the Bay. As a complete novice, I don’t even know if there’s a way for me to do that in QGIS, or if I’m going to make 15 different maps with the 15 years of data and turn images of them into a .gif. So, I went back to ChatGPT for guidance.
It also told me I could use style changes by time attribute, the TimeManager Plugin, or the manual process I had considered doing with turning a series of images into a .gif.
I’ll be using the Temporal Controller since it was the first option. I asked ChatGPT for a step-by-step guide of how to do this.
Before getting bogged down in the process of creating the visualization, it’s important to have my data prepped and ready to go. I asked ChatGPT how it needed to be set up in order to use the temporal controller function.
In this case, I’ve decided to not do the thing that ChatGPT says is easier. The “Join External Time Data to Polygon” option seems to involve more data preparation work and be a better process to know for future projects. I began by taking a screen capture of the data table from the Maryland DNR’s Winter Dredge Survey history, uploaded it into ChatGPT, and had it use its OCR capabilities to make a table that I could paste into Excel and save as a .csv.
Step 1.
Step 2.
Step 3.
After looking back at some of the steps in the process of using the temporal controller (Step 2 above), the final product ended up looking like this. I went into the attribute table of the polygon and saw that it already had an assigned ID of “2250”, so I added that column. Additionally, the geometry type is a polygon so that was added, as well.
With that, data preparation was complete and now I’m ready to move on to joining the data table to the polygon and creating the visualization.
