Utility Programs

To conflate external datasets with OSM, the external data needs to be converted to the OSM tagging schema. Otherwise comparing tags gets very convoluted. Since every dataset uses a different schema, included are a few utility programs for converting external datasets. Currently the only datatsets are for highways. These datasets are available from the USDA, and have an appropriate license to use with OpenStreetMap. Indeed, some of this data has already been imported. The files are available from the FSGeodata Clearinghouse

Most of the fields in the dataset aren't needed for OSM, only the reference number if it has one, and the name. Most of these highways are already in OSM, but it's a bit of a mess, and mostly unvalidated. Most of the problems are related to the TIGER import in 2007. So the goal of these utilities is to add in the TIGER fixup work by updating or adding the name and a reference number. These utilities prepare the dataset for conflation.

There are other fields in the datasets we might want, like surface type, is it 4wd only, etc... but often the OSM data is more up to date. And to really get that right, you need to ground truth it.

mvum.py

This converts the Motor Vehicle Use Map(MVUM) dataset that contains data on highways more suitable for offroad vehicles. Some require specialized offroad vehicles like a UTV or ATV. The data in OSM for these roads is really poor. Often the reference number is wrong, or lacks the suffix. We assume the USDA data is correct when it comes to name and reference number, and this will get handled later by conflation.

roadcore.py

This converts the Road Core vehicle map. This contains data on all highways in a national forest. It's similar to the MVUM dataset.

trails.py

This converts the NPSPublish Trail dataset. These are hiking trails not open to motor vehicles. Currently much of this dataset has empty fields, but the trail name and reference number is useful. This utility is to support the OpenStreetMap US Trails Initiative.

usgs.py

This converts the raw data used to print Topographical maps in the US. This obviously is a direct source when it comes to names if you want to be accurate. Although things do change over time, so you still have to validate it all. The files are available from the National Map. I use the Shapefiles, as the different categories are in separate files inside the zip. Each one covers a 7.5 quad square on a topo map. These have to be merged together into a single file to be practical.

fixnames.py

On the OSM wiki, there is a list of incorrect tagging for forest highway names. Basically the name shouldn't be something like "Forest Service Road 123.4A". That's actually a reference number, not a name. This is primarily a problem with existing OSM data. These would all have to get manually fixed when validating in JOSM, so this program automates the process so you only have to validate, and not edit the feature. After conflation, process the output file with this utility to produce an improved version.