Hi.
I think there's been a misunderstand, maybe I'm not being clear.
I did some quick analysis of the data & current OSM data. There are
about 622 trees which are inside a building. about 300 which are <1m
from the centre line of a road.
For example there are some trees-inside-buildings around here (
https://www.openstreetmap.org/#map=17/45.39017/-75.75801 ) and (
https://www.openstreetmap.org/#map=16/45.4187/-75.7007 ). My JOSM
validator didn't flag "tree inside building", so you can't rely on that
to figure it out.
There are "trees very close to road centreline" around here (
https://www.openstreetmap.org/#map=18/45.28647/-75.70499 ) or (
https://www.openstreetmap.org/#map=18/45.40001/-75.75015 )
For a dataset of 150k, these numbers are pretty good.
When doing an import, it's important that someone does this sort of
work. That's part of the process of doing an import, to learn more about
the accuracy of the data you have, and to check how it would look after
you import it. You shouldn't just presume everything will fit together
100%, someone needs to do this sort of analysis.
I suggest you filter out the small number of suspicious trees, and
either manually enter them, change the OSM data, and/or contact the City
of Ottawa to tell them about possible errors in their data.
BTW I noticed there are lots of address interpolation ways from a 2011
CanVec import, and then lots of buildings with address tags from a
building import this year. The old address lines weren't removed, so I
think there are thousands (hundreds of thousands) of duplicate addresses
in Ottawa? Have you noticed this? This is a danger of doing an import
without looking at the existing OSM data.
Doing some data analysis isn't a "mechanical edit", you're looking at
the data, not editing it.
Rory
On 28/06/17 17:13, James wrote:
Other than MANUALLY VERIFYING EACH AND EVERY TREE, there is no way to
give a statistical analysis of the accuracy of the entire dataset. If we
did it programatically we'd have to prove how the method of analysis is
correct and would be probably be brushed off as being a "mechanical
edit" thus invalid. If the need to verify each tree is not on a
road/water/building this could be accomplished during the import(what I
like to call a manual import: where the data is validated at the time of
the importation of data as to the accuracy of the location and not just
a massive dump of data in one pass)
On Wed, Jun 28, 2017 at 11:02 AM, Rory McCann
<r...@technomancy.org
<mailto:r...@technomancy.org>> wrote:
On 28/06/17 16:53, Kyle Nuttall wrote:
I am still a little confused by what you mean. Obviously if
there's a
tree in the middle of a building, that means something is not
right.
But what I was trying to say was that the trees in this dataset will
only appear where an actual tree is in real life. There shouldn't be
any cases of rogue trees in the middle of rivers or buildings
because
a tree just wouldn't be there in real life.
What if OSM data is wrong? What if OSM says "The river bank goes up to
here" and it doesn't, and that would make the tree in the river.
Sometimes people just upload data into OSM without checking for things
like this, and you get these weird data problems. You should try to
figure where (if at all) this happens, and see if the problem is OSM or
the official data.
You're also presuming the official data is 100% guaranteed to have the
correct location. If they are 99.9% accurate, then there are 150 wrong
locations. 99.99% accurate, 15 wrong locations.
If you do this sort of analysis you can find out just how accurate the
official data is, and also prevent making the map be full of these
mistakes.
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