[Talk-ca] [Imports] Ottawa, Canada Tree Import

James james2432 at gmail.com
Thu Jun 29 12:19:59 UTC 2017

We are aware of the Canvec interpolations and cleaning them up(residential
areas with 100% coverage, we keep them in vast areas where new buildings
might be built as to not miss any potential areas) so that process is on

On Thu, Jun 29, 2017 at 8:01 AM, Rory McCann <rory at technomancy.org> wrote:

> 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 <rory at technomancy.org
>> <mailto:rory at 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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>>     <mailto:Imports at openstreetmap.org>
>>     https://lists.openstreetmap.org/listinfo/imports
>>     <https://lists.openstreetmap.org/listinfo/imports>
>> --
>> 外に遊びに行こう!
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