[Talk-us-massachusetts] Some observations and preliminary stats on MassGIS address import
Angela Morley
amorley at protonmail.com
Tue Jul 17 18:37:37 UTC 2018
Interesting data.
I've discovered an import process that works using QGIS, JOSM, OpenData plugin and Conflation plugin. I'll go into more detail in a little bit, but in involves using QGIS to modify the all capitals in the shapefile to partially lowercase (yes, this breaks things like McCabe Street, but I think that's acceptable. Community feedback, please?), and JOSM's Conflation plugin to assign the points to the closest building.
There's a lot of little hiccups I'm discovering along the way, like how JOSM won't download town sized maps from the server, and you can't upload changesets greater than 10,000 edits. I'm not sure how to get around those hurdles at the moment.
Another facet -- should one person do the data conversion, and others upload the changesets? (that's fine with me, but it's going to take me some time going through 350 towns of data if I do this)
‐‐‐‐‐‐‐ Original Message ‐‐‐‐‐‐‐
On July 17, 2018 12:57 PM, Yury Yatsynovich <yury.yatsynovich at gmail.com> wrote:
> Thanks for creating the wiki page, Angela!
>
> I did some simple spatial joins of MassGIS address points with existing buildings without addresses (either house number or street name missing) using python (geopandas and osmnx). Here are some stats from such joins by counties:
>
> County OSM buildings w/o addresses MassGIS points Matched points 1-to-1 matches Share of matched points Share of 1-to-1 matches
> Barnstable 188370 192619 157235 121330 0.82 0.77
> Berkshire 89520 79138 62324 39290 0.79 0.63
> Bristol 233590 284883 247625 112776 0.87 0.46
> Dukes 23647 20330 13639 11236 0.67 0.82
> Essex 268122 379036 328679 147073 0.87 0.45
> Franklin 50091 40853 31336 18146 0.77 0.58
> Hampden 206111 225352 198221 100958 0.88 0.51
> Hampshire 78709 73675 60417 34122 0.82 0.56
> Middlesex 429556 779421 594647 219696 0.76 0.37
> Nantucket 14048 12963 8408 6445 0.65 0.77
> Norfolk 361719 337260 302017 147594 0.90 0.49
> Plymouth 233374 244200 207421 134116 0.85 0.65
> Suffolk 118763 457611 426855 36796 0.93 0.09
> Worcester 383670 407001 347611 173147 0.85 0.50
> TOTAL 2679290 3534342 2986435 1302725 0.84 0.44
>
> Most of the address points (84%) lie within boundaries of buildings w/o addresses, almost half of which (44%) are unique address point within the corresponding buildings.
>
> For those 1-to-1 matches the address info can be added directly to the buildings. For the many-to-1 matches (several addresses within one building) the options are either creating separate address points within a building or combining addresses of all such points and adding it to the building (e.g. addr:housenumber = 11,13,15 as suggested in https://wiki.openstreetmap.org/wiki/Addresses#Buildings_with_multiple_house_numbers). It seems that the second approach has been used for the existing addresses in Malden and Boston. If points in the many-to-1 matches have different street names then adding separate address points seems to me the only solution.
>
> Having visualized the data in QGIS I've noticed couple of issues:
> 1) some points lie outside, yet, very close to a building so that it is unambiguous to which building they belong. Maybe creating a small buffer (5-10m) around such points and merging them with unique buildings that these buffers intersect can help match them.
>
> 2) some points, as it was mentioned in previous messages, are assigned to parcels. E.g. there are many cases when a group of buildings (a house and, say, barns) have an address point next to them. It could be possible to identify a house among those building manually and add the address only to it, yet, as there might be several thousands of such cases, it can be very time consuming. So, for parcels I would suggest simply adding an address point in the middle of a parcel (as it is placed in MassGIS) without identifying the exact building to which the address belongs.
>
> --
> Yury Yatsynovich
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