OpenStreetMap
Tools I wish I had: smarter paved vs unpaved road defaults.
Posted by CloCkWeRX on 7 October 2016 in English. Last updated on 10 October 2016.OpenStreetMap has a few assumptions about road surfaces, based on the fact most western cities have paved roads.
From https://wiki.openstreetmap.org/wiki/Key:surface
For roads for motor vehicles there there is normally an assumption that the surface is surface=paved unless otherwise stated. Paved in OpenStreetMap is non-specific and may cover sealed, tarmac, asphalt, bitumen. surface=unpaved is treated as the opposite of paved. More specific tags can used used for surfaces which are normally classified into paved or unpaved for routing purposes. Navigation software should assume that roads-that-are-not-paved will have slower driving speed (and therefore longer driving time) and may be impassable in some weather conditions.
In South America (Rural), Rural Australia, Africa, Haiti and more this is not the default. During activities like a HOT activation, quite a lot of road data gets added without specific surface tags.
In places like South America, Strava route building a big thing - but knowing if you can go on a road bike or a mountain bike is not something routing engines can answer with much certainty.
Alternatively, knowing if you are likely to need a 4WD vehicle in disaster relief is another use case which can’t be easily answered by a routing engine.
In an idea world, it’d be great if:
- ID had some notion of ‘rural’ vs ‘metropolitan’ mapping profiles; and allowed you to create a number of roads with the same surface properties as the last few you’ve traced.
- QA tools (maproulette? similar?) existed that looked at specific countries, finding highway=unclassified and highway=residential without explicit surface tags; plus a relationship to any bounding residential landuse to suggest a value (Big city? Its more likely to be paved residential roads)
- Something like DeepOSM that could guess the difference between “light, sandy coloured road” and “Dark, asphalt road” to suggest an appropriate classification.
Even if these tools weren’t used to write out lots of surface data back into OSM, it would be interesting to see if they could be used to generate a likely profile of an area for routing engines - ie; better answering if a certain section of the planet is likely to be unpaved roads.
Discussion
Comment from Warin61 on 7 October 2016 at 08:04
I have a ‘local road’ with concrete sections. The concrete is there to stop erosion when the creek floods or, on the hills, when it rains hard .. and the concrete has a very rough surface. So even the surface=concrete does not tell the complete story. So the surface tag is only one consideration.
Some unpaved roads can be used by sports cars at speed - smooth and hard surface. Some unpaved roads are not usable by some 4WD vehicles - the alloy diff housings break on rocks.
A ‘light coloured’ road can be either concrete or white sand.
A grey road can be either loose gravel or asphalt.
You cannot beat local knowledge and experience. A map helps for planing .. but you do need that local knowledge, especially for most disasters and these effect what were ‘good’ roads.
Comment from CloCkWeRX on 7 October 2016 at 08:26
@Warin61, yes but right now the majority of roads default to paved when they are not, unless a mapper takes extra steps in certain areas.
If a routing engine sends you on unpaved, non compacted roads because it assumed they were sealed… that can be particularly unsettling with some modes of transport.
Of course local knowledge works best… but right now the implied default is often the wrong thing; so an easy way to make things explicit would be more useful than not.
Comment from Richard on 7 October 2016 at 08:36
cycle.travel’s routing does this to some extent: it has different surface assumptions in urban vs rural areas. In particular, in the US, it assumes that highway=residential, tiger:reviewed=no is paved in urban areas, but not in rural areas. But yes, getting more roads explicitly tagged would be a big win.
Comment from SK53 on 9 October 2016 at 12:51
I now have fairly complete urban shapefiles derived from OSM for the whole world. I have not yet processed them to identify false positives, and in some undermapped areas some urban areas will be missing. However, I believe that a) these are more accurate than Natural Earth; b) have fewer false positives; and c) can be readily split along existing OSM boundary lines to add as a means of incorporating into a country extract. More soon/