Danger Zones

TL; DR

I’ve built a map of the location updates from the Ministry of Works and Transport of Trinidad and Tobago based on flooding and where was/is impassable. You van view it here.

“Technical” details

That tweet above is kind of how I got the idea in my head to build out an example of the approach.

When I sat down to do create a version of a good approach, I had all kinds of options in my mind. Should it be rendered on the client or server side? React or Angular? Should I use Google Maps, Leaflet & MapBox or something else? How would I generate the data?  Should I try and parse some tweets? What’s the fastest way to get data? Who has the data?

Since I didn’t want to spend all evening in analysis paralysis, I just dove in and began pulling things together. I had recently set up a new dev environment, so my regular tools for some ideas weren’t restored yet. No node, npm or React was set up. So I started downloading packages, installers and tools.

And then I remembered glitch! I literally paused mid environment setup and jumped onto searching in glitch. Glitch is like online development environment that comes prepackaged with the resources you need to get up and running with with minimal fuss. Now, you have to have a sense of what you want to build and what tech to use. Which I did. A few searches later, I found a great starting point, something that already had the Leaflet stuff built in.

Having the base I wanted, I needed to get the content of these tweets represented as geojson:

Again, numerous options, parsers to write and just ideas swirling around. But while spelunking online for stuff to use, I found geojson.io – a WYSIWIG for generating geojson. I had to handcode the stuff, switching between Google Maps, Open Streetmaps and Waze but I just wanted an early result.

And I got it: a map that presents the information that @mowtgovtt tweeted about the state of impassable regions in the country.

 

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