Great stuff. I assume you are aware of woeids from Yahoo which have
some interesting boundaries derived from crowd sourced data in Flickr
and other places. Details here.
http://developer.yahoo.com/geo/geoplanet/guide/concepts.html#woeids
It would be a great project to match up boundaries from yahoo woeids
with Wikipedia articles for UK places, OSM place names and Traveline
NatGaz database and also I guess the Cycle Streets DB. Note that we
still haven't imported the NatGaz DB (with 50,000 place names in a
hierarchy) into OSM and are probably missing many places on the map in
more obscure parts of the country as a result.
Regards,
Peter
On 23 Feb 2010, at 14:18, Peter Reed wrote:
As the weather improves we are all going to be out and about tracing
roads for OSM. So there are various discussions, and work under way
to help find, prioritise and then fill the most important gaps in
the map. Larger towns and bigger areas that need attention are
fairly well known, but experience suggests that it can be more
difficult to find smaller and more local places where a short
session could make a difference quickly.
So this is an attempt to help, at a bit more of a micro-level
–http://www.reedhome.org.uk/Documents/osmembed.html?kml=KML/osmcategory.kml
(to view the same thing on Google maps use this http://maps.google.co.uk/maps?f=q&source=s_q&hl=en&geocode=&q=http:%2F%2Fwww.reedhome.org.uk%2FDocuments%2FKML%2Fosmcategory.kml&sll=51.525483,-0.746802&sspn=0.01287,0.033023&ie=UTF8&z=6
)
Broadly – green areas look as though they are already fairly well
covered, red areas look as though they would benefit from some
attention, and the rest are grey.
WARNINGS
This is very much a first cut, pre-beta, etc. We know there are
places missing, some gaps in the data, and we are aware that it
doesn’t always get things right (we think it does often enough to
be useful).
It really cannot tell how well an area is mapped from the data. It
can only try to find areas that look a bit thin - and some areas
look thin when they are not.
At the moment we are concentrating on roads, not the full list of
features in areas that are most thoroughly mapped.
As a result this sometimes flags up an area as “poor” when in
reality it has been perfectly well mapped. For example, there are
two areas near here that a lot of work has gone into, where the
classification is not right. So if your favourite areas shows up
wrongly, please don’t take it personally.
Still, it seems to point in the right direction quite a lot of the
time, and it’s offered up on that basis. In my own area (which is
already fairly well covered) it has flagged up some towns that I
already knew were a bit thin, and another half dozen options that I
can reach fairly easily, but didn’t know about.
If it looks as though it will prove useful then future plans will
address some of the current limitations by refining the borders,
filling gaps, correcting errors in the underlying measures, and
tweaking the arithmetic.
However, some mis-classification will always be inevitable. Read on
to see why.
THIS IS HOW IT WORKS:
We start with a list of about 1,600 UK settlements, and a figure for
the population that lives there. Baring a few errors and omissions,
the settlements are the same ones that Cyclestreets uses for local
areas -http://www.cyclestreets.net/area/
We then try to find a boundary for each of these settlements. This
is based either on the local authority admin area where there is
one, the naptan pay-scale area if there is one, or if all else
fails, a guesstimate of how big the settlement must be based on
population density.
(FWIW we already realise that some of the pre-defined areas are too
big, some of guesstimates are off-centre, or the wrong size, and the
guesstimates don’t work well on the coastline. But it’s a start, and
most settlements don’t look too far out.)
Where we know the actual length of roads in a settlement from
Department for Transport data we use that to classify the area, but
this only works for bigger towns and cities, so for the rest we are
trying to figure out how well they are covered without knowing the
true length of roads on the ground.
At the moment we do this using various ratios. Within each
settlement boundary we measure the length of roads in the OSM
database, and from that we calculate three measures: the length of
roads per sq km (the road density within the settlement), the length
of road per head of population ,and the proportion of roads that are
major (primary, secondary and motorway).
The underlying hypothesis is that a thoroughly mapped area should
have a relatively high road density, plenty of road per head of
population, and a relatively low proportion of major roads (because
it’s the unclassified and residential roads that tend to be missing,
not the major roads).
However, there are anomalies - some areas are thinly populated, some
are at the intersection of a lot of major roads, some have more
tightly packed houses (so a high road density), while others have
big gardens (and hence a low road density). So inevitably our
hypothesis sometimes breaks down.
To avoid tripping over some of the more extreme cases, we therefore
highlight as “good” only those areas that fall into the top quartile
on at least two of the ratios, and to be classified as “poor” we
pick only those areas that fall into the bottom quartile on at least
two ratios. Everywhere else is in the middle.
That covers complete settlements. On top of that we have plotted all
the bigger residential areas (landuse = residential) where there
don’t seem to be many roads. We can’t know the population of these
areas so we just highlight those with a low road density (road
length / area). If the road density in a residential area is above
the threshold, or if it is a very small residential area (where the
measures can be unreliable), then we just ignore it. We have only
plotted the bigger, low density residential areas.
One final caveat – the base data on which this is all based was
extracted several weeks ago, so it’s a little bit out of date. An
updated version will follow when time permits.
IN CONCLUSION
We have several ideas on how this can be improved, based on earlier
suggestions. We welcome more comments and ideas.
Even more importantly, we welcome more roads on the map.
So most of all we hope this helps members of the community find some
handy places where they can quickly make a difference by plugging a
few gaps. Remember that it’s all a bit hit-and-miss though. It’s
probably a good idea to check some other sources as well before
rushing out with the GPS.
_______________________________________________
Talk-GB mailing list
[email protected]
http://lists.openstreetmap.org/listinfo/talk-gb
_______________________________________________
Talk-GB mailing list
[email protected]
http://lists.openstreetmap.org/listinfo/talk-gb
