A/B Street is both a game and a very powerful tool that allows you to download a detailed street map of an area and test out changes to the configuration of roads:
It uses OpenStreetMap as a data source. OSM has impressively rich data on things like the number of lanes a street has, where bike lanes and turn restrictions go, and so on, but one thing it lacks is detailed elevation data. The developers noticed that it was suggesting absurd routes for cyclists in Seattle, including routes that no-one who’s actually tried cycling would ever repeat because of the hills involved. So they brought me in to figure out how to add elevation data.
I wrote a simple Python tool that reads in paths as plain lists of coordinates, and writes out statistics for each one: the start and elevations, and cumulative elevation gain and loss along each path. A/B Street incorporates this into a data load by exporting each road segment as a series of points every metre along the way, getting as fine-grained a picture of a route’s hilliness as the source data allows.
By default, elevation_lookups uses data from the Shuttle Radar Topography Mission, because that source provides fairly high quality data for most of the world’s land. I learned about SRTM while making this tool, and I’m still sort of star-struck that we have a global dataset like this, freely available to anyone who has a use for it. But it is also relatively low resolution, so I built in the ability to override the data source with higher resolution sources where known. It comes preconfigured with examples of both raster (LIDAR source) and vector (contour source) datasets for the Seattle area.
This is an open-source project. I hope it can be useful for other applications, and I have more ideas for it then I have time to implement. I’d love contributions from anyone this appeals to, and have some suggested starting points (not all requiring programming skills!).
