During Hurricane Irma instead of hopping on a plane and leaving South Florida, I chose to stay in Miami to help my family, many of whom decided to stay. While gathering water and awaiting the storm I noticed that most of the maps about the storm were terrible. Instead of using cutting-edge maps most maps were like images that were hand drawn by crayons. My siblings who are 7 and 13 asked me if the area where they lived was under evacuation. Like many, the heard from friends and school that this hurricane wasn’t anything to play with.
Instead of telling them I wanted to show them myself. The best way I found was through creating a map and letting them search for themselves where the place they lived ranked in terms of areas that should be evacuated. To help me make a map that could answer all their questions I asked, “What do you want to know?”
Some of the biggest questions they had:
- What were all the shelters in Miami?
- What place can we take our pet too?
- Where can mom park here car so it won’t get flooded?
In the map below I collected their questions and turned it into a GIS map using CartoDB and SQL. The map has evacuation zones and you can type your address in the search field to find where your home is in the zones. Any area with EVACUATE next to it are places where you should leave and anything with Pet-Friendly is where you can bring your pets. For clarity, only a few areas in Zone C were supposed to evacuate. Later on days later all shelters reported to accept pets via Local 10 WPLG.
For this map, I used a dataset on Flooding Zones within an area and then marked the data by zone areas. From there I imported the data and used SQL to select the needed columns for this particular map. Other data sets like shelters and municipal garages were scraped from PDFS or online using Python. I then compiled this data and added these as layers on top of the current data.
To visualize areas, I shaded it in by color and for the locations I used dots. All together this didn’t take very long and the hardest part was making sure the data was accurate and up to date. The idea was to make this better not worse than the maps shared at the time which were static images. If I had more time I would add places that lost electricity but at the time of writing this article that was hard to get – especially because we lost electricity ourselves.
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