Combining data with different scales

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12-18-2015 07:04 AM
anayoung
New Contributor III

Hello,

I have two feature classes that I want to combine into one feature class but they were created in two different scales. My thought was that I simply loaded both into one feature class and call it done; however, I realize there might be a better way to get this done. Any suggestions?

Thanks,

Ana

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17 Replies
DanPatterson_Retired
MVP Emeritus

Just be aware of the boundaries.  I would symbolize one of the layers with just an outline and have a look at the edges.  You don't want to cut out part of the old layer if the new layer has changed borders.  And symmetrical difference isn't what you want, it would be a union which would keep all the good bits and fiddly bits and enable you to decide what to keep and what to discard.  Also check intersect and other tools in the Overlays tools An overview of the Overlay toolset—Help | ArcGIS for Desktop

anayoung
New Contributor III

Thank you, Dan. Good advice. I will do as you suggest.

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ChadKopplin
Occasional Contributor III

Also, keep in mind that you are setting your scale to the broader of the 2 datasets, when you combine them.  This could affect the accuracy of your final product, and any other analysis that you may use the product in.

anayoung
New Contributor III

That is my greater concern. I apologize I wasn't able to communicate it properly initially. Is there a way to cut down on any possible issues?

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katherinehannaford
New Contributor III

As an addendum to this interesting discussion:

If your cities do not share boundaries, then your boundary issues shouldn't be a problem in a combined dataset.  If they do share boundaries, then, as previously stated, you will have to be careful or decide if you are going to change the adjacent Census city boundary.  And, if you ever spatially nest Census tracts or blocks onto your cities (such as on a map) then the boundary differences will also be problematic.

If you do combine the census and local sources I would recommend populating a new attribute to keep a record of the source (census2010, CityA, CountyX, etc).  How you actually combine the datasets will depend a lot on what attributes you want to keep from each set, so you'll want to keep an eye on that.  And, whatever you do, make sure you're editing in a new dataset or a copy of an existing one, just to be on the safe side.

Good luck.

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anayoung
New Contributor III

Hello Katherine,

Thank you for your thoughtful response.

I made sure to get local data for those cities that share boundaries from one source e.g. Regional planning commissions. So, that shouldn't be a problem. I also created a new feature class with a source (of data) field. However, I am concerned about the differences in scale between the Census data and local data as the Census is created at a much smaller scale. Thank you for your insight on creating a map with this combined data and census tracts and blocks.

Ana

Sent from my iPhone

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katherinehannaford
New Contributor III

Ana,

The scale differences per se aren’t a problem – the scale of your combined dataset is the smaller scale of the census data. However, interpretation problems could come up if the boundary description is different.

As an aside, I will mention that Census does try to elicit boundary files from local government, such as county or regional planning organizations in the run-up to the decennial census (PSAP). Theoretically, they should be the same, although I know from personal experience that this is not always the case.

Good luck with your work,

Kathi

Kathi Hannaford

SEDA-COG GIS

570-522-7288

khannaford@seda-cog.org<mailto:khannaford@seda-cog.org>

“Start where you are. Use what you have. Do what you can.”

Arthur Ashe

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anayoung
New Contributor III

Thank you, Kathi. I've combined data sets with different scales before and had no problems. However, I wasn't considering the fact that the combined set might be used in advanced analyses. So, I needed some confirmation that the data would be okay should it be used for more than just display and identification of attributes. I think you have put my worries to rest.

With much appreciation,

Ana

Sent from my iPhone

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