Guiding mapping priorities in Nepal with seismological data

To better guide Nepal mapping efforts we used Turf, TileReduce, and seismological data from the USGS to calculate approximate impact levels for each building and road in OpenStreetMap. Combined with the latest imagery, this damage analysis can help to better target where mapping is needed most.

Earthquake intensity mapped to OpenStreetMap data. Red corresponds to stronger shocks (source: USGS, OpenStreetMap contributors) — fullscreen.

The color of the features is determined by the interpolated Peak Ground Acceleration at each location with red for the areas experiencing the strongest shocks. The northern region of Kathmandu had ground acceleration readings as high as 0.8 Gs; the ground was essentially falling in the wrong direction at the center of an area with 1 million residents and a population density higher than San Francisco.

You can use this data now for mapping. Here is an example of an area at the most violent epicenter of the earthquake that is in need of additional mapping.

High priority area: map data is in red, features are missing (source: USGS, OpenStreetMap contributors, DigitalGlobe) — fullscreen.

I made a mashup with our post-earthquake satellite imagery ready to go for your OpenStreetMap editor of choice.

To use this data in JOSM, follow the JOSM documentation. To overlay this layer in iD editor, copy the URL below and follow the steps in the gif.

https://{switch:a,b,c,d}.tiles.mapbox.com/v4/morganherlocker.f762d746/{zoom}/{x}/{y}.jpg?access_token=pk.eyJ1IjoibW9yZ2FuaGVybG9ja2VyIiwiYSI6Ii1zLU4xOWMifQ.FubD68OEerk74AYCLduMZQ