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Feature overlay to identify parcels/polygons

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Message 1 of 3
Anonymous
398 Views, 2 Replies

Feature overlay to identify parcels/polygons

Problem/Scenario

 

I have identified manually a few hundred dwelling locations from aerial imagery. I have then downloaded a property title layer, which then places these identified dwellings inside a property parcel. I have also downloaded a street address layer, that consists of point geometry with an address attached.

 

What I wish to do is to tag known dwellings with a street address. My aim was to utilise a feature overlay that would retain the whole property title parcel of any identified dwellings (polygons), and then with these remaining parcels, run another analysis which would identify any address points within these parcels and "wham-o", I have addresses for all my dwellings.

 

Sadly, I am failing.

 

So in the below pic, the squares are my hand drawn dwellings (exported to [polygons). I need to then try to identify all [blue/grey] polygons that have a square inside, and delete the rest. I would then need to identify all orange points that sit within remaing polygons and recover there addresses...then I'm done 🙂

 

Sounds doable?

 

Any help gratefully appreciated

 

 Capture.JPG

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Message 2 of 3
parkr4st
in reply to: Anonymous

Please post the data so members can work on the problem.

 

dave

Message 3 of 3
Anonymous
in reply to: parkr4st

Sorry Dave

 

Here is the sdf/shp files. I did not include a dwg as I think the links to data files have to be absolute? EPSG is 2193 [NZTM]

 

The "prim pcl" shape file is the polygon that should provide boundaries that I need to tie in "nz-street-address" to "house4datanew" p[olygons. So wherever a house has been identified, I want the corresponding address/addresses that fall within that polygon.

 

Note here: Ive just gone ahead and done it manually. So if no one feels like putting time into this, fair enough. But from a learning point of view, I would be interested in knowing if this was achievable in an automated fashion.

 

Thanks

Mark

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