Haha, get it? ‘Cause it’s making maps about Cleveland, and…
Anyway, in my post about the maternal mortality case study, I alluded to another project in R that involved USGS data and interactive maps. This was actually inspired by the Great Lakes Data Watershed. I took some time out to learn how to reproduce most of the functionality of one of their dashboards, and I learned a lot in the process. You can follow along with the GitHub repo here, or check out the demo here.
What are we looking at here?
This program calls the USGS REST API to get near real-time data from water monitoring stations around Cuyahoga county, Ohio. It formats that data to get the flow and stage of rivers around the county, and displays that information on relevant points on the map. Unfortunately, it’s only hosted on GitHub Pages, so it isn’t making regular calls to the USGS. This could be remedied by using real hosting that I am not going to pay for personally. For the curious, I made use of OpenStreetMaps to provide the map data, and Leaflet for the interactive map elements.
What’s next?
I have been trying to get into GIS applications for years, and I never before had the skill with R to explore this environment with that kind of tooling. Because this is the first time I’ve used a REST API to get data of this type, I’m thinking about other scientific datasets that have frequent updates. Something that I have been paying particular attention to is Landsat data and its possible applications to precision agriculture. Early Days!