[Imports] Fwd: Importing West Virginia State Forests Boundary

[Attila Kun]

Yes, you didn't misread it, it's about a Boundary import aka 
boundary=protected_area.

As it reads in the dataset description, "Last Revised in 2020 for USGS's 
Protected Areas Database, a subset of the National Gap Analysis 
project." So it means I'm gonna work with pretty decent data which is a 
good thing, and i checked the quality of the dataset, I only need to do 
some minor multipolygon editing, i already set up the tagging, so yeah, 
i'm not gonna import it like an idiot but like i have proper knowledge 
how to, after some research of how the taggings work. The taggings of 
the dataset is based on the PAD US scheme, for which WV GIS TC provided 
a PDF file to explain what tag does what.

I haven't started it yet, but i guess you all say that i should be good 
to go if I do it carefully, but that's why I wanted to hear from you.

I created a separate account 
<https://www.openstreetmap.org/user/ottwiz_import>just for the import 
itself so it's distinguished from my main one.

On 8/12/2021 4:52 PM, Adam Franco wrote:
>
>     > On 12 Aug 2021, at 08:38, Mateusz Konieczny via Imports
>     <imports at openstreetmap.org <mailto:imports at openstreetmap.org>> wrote:
>     I disagree. For simple polygons (few nodes), overlapping ways
>     might be the easiest to maintain representation, but as an editor
>     I would always prefer a multipolygon to tens or hundreds of
>     reused/overlapping nodes in overlapping ways.
>
> As a heavy land-cover mapper I agree that multipolygons are vastly 
> easier to improve over time than to try to disconnect overlapping ways.
>
> That said, unless I'm misreading the wiki the import being discussed 
> <https://wiki.openstreetmap.org/wiki/Import/West_Virginia_State_Forests_Import> 
> is about State Forest (protected area) boundaries not 
> land-cover/land-use. I'd rather not have folks doing 
> land-cover/land-use imports from poor data, but I'm of the opinion 
> that protected area boundaries are often a very good candidate for 
> [careful] importing if the data are of good quality.
>
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