Green Means Go

Where in the United States could government imports improve OpenStreetMap?

A map of 1km×1km squares covering the continental United States. Green squares show places where data imports are unlikely to interfere with community mapping. Any attempt to import new data into OSM should follow the import guidelines; see caveats section below.

Jump to: New York, Chicago, D.C./Baltimore, Atlanta, Florida, Dallas/Ft. Worth, Denver, Los Angeles, San Francisco, Seattle.

Methodology & Caveats

I performed a simple linear sum of highway lengths on two datasets to generate the green “improvement” areas, comparing TIGER/Line 2007 to 2012 and generating darker greens based on relative lengths. The white areas are based on a count of unique OSM user ID’s on a recent copy of the OpenStreetMap dataset from October 2012, and may not reflect editors whose work has been covered up by other editors, or improvements to the TIGER/Line import consisting of junk data removal. Any attempt to import new data into OSM should follow the import guidelines.

Patterns

Densely populated area with strong local community of mappers.

Attempt no import here.

Small city or town with existing local community and very little activity at the edge of town. Contact the local community.

Sporadic local mapping, primarily along major roads. Find out if the mappers are local, check non-obvious data such as route relations and work with OSM-US mailing list plan import.

There’s not much data here to speak of.

Source Data

Raw data for this visualization can be found in these raster images:

Each is a 1km resolution GeoTIFF file, Float32 format, gzip-compressed in Albers Equal-Area projection:

Generated by Michal Migurski, Oct 2012-Jan 2013. Inspired by Martijn van Exel’s work on TIGER Deserts and Dennis Zielstra’s data imports case study. Thanks Ian Dees for feedback.