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How to calculate % of population that overlaps another polygon?

KathrynAngleton

I am trying to figure out what percentage of my City's population falls within a certain distance of their parks. I created a 10-min walkshed via network analyst, but my population data is limited. The best I have is Census Block Groups (2014-5 year estimates). Since I don't have points for population or even just household points with household sizes in the attribute table, I'm relying on the BG polygon. I know I can intersect the BG poly with the parks network analyst output poly, but how do I calculate the percentage of the population (a field within the BG attribute table) overlaps with the parks output? Is there a better way to do this? Any ideas, input, or advice is greatly appreciated. Also, I do not have BAO or BA Desktop, I know those tools can generate population numbers based on polygon inputs.

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RobertScheitlin__GISP

Kathryn

Calculation the percentage of the original polygon that intersects the parks walk distance polygon is not to hard (clip the bg poly using the park polygon and some math to determine clipped portions SqFt vs the original BG poly SqFt), but then the population number (say 43) is assigned to that polygon so you would have to assume even distribution and divide that pop by the percentage of the BG poly that intersects.

DanPatterson_Retired

An approach which is similar to Robert's clip and calculate is to do a Split—Help | ArcGIS for Desktop but it requires an Advanced License, but it does it all at once

MicahBabinski

Hi Kathryn,

Expanding on that idea, you could consider pre-processing your block groups by erasing water and right of way polygons (if you can get them). Then, you could try to obtain address points or building footprints for your area. You could divide the block group population by number of buildings and assign each building that amount of people.

It just depends on what data you have available and how sophisticated an estimate you want to go for. I'd recommend you set up your process in Python script or ModelBuilder so you can evaluate results and refine your estimate.

Good luck! I did a similar project in my first GIS job and it was a lot of fun.

KathrynAngleton

Hi Dan,

Thanks for the advice. Would I want to have use ratio policy enabled on the population field within the BG attribute table? What I had originally done was had that enabled before I intersected the two polygons, but the percentage of pop I got back didn't seem right to me knowing the city and parks.

KathrynAngleton

Thanks for the tip! If split doesn't work for me, I will try this.

KathrynAngleton

Hi Micah,

This is an interesting approach. I do have building footprints, address points, ROW polygons, and waterways. My concern about using addresses or footprints is that I would be putting residents in non-residential buildings. Land uses are mixed/integrated here, so I couldn't rely on assuming certain BGs would be 100% residential.

To add, my Python skills are limited and I've never used model builder. Should I stay away from those processes then? I usually do more cartography than actual geography or heavy geoprocessing.

KathrynAngleton

Dan, I have advanced. Split only works with string fields. Since population is numerical, how would split do what I want? I've tried tabulate intersection as an alternative.

KathrynAngleton

Robert, would you say tabulate intersection does this for me? It appears to have created the output I was looking for.

RobertScheitlin__GISP

Kathryn,

That sounds like exactly what you need. Back years ago (the last time I had to do this) that tool did not exist.

Robert_LeClair

Another workflow is to use Modelbuilder to do the analysis. There is a tool - Make Feature Layer that uses a ratio policy - basically a percentage split on the population field based upon an intersect.

KathrynAngleton

Hey Robert, I actually tried that originally and wasn't entirely confident in the results that came back. It was probably more so the data I was using rather than the process itself. I realized I should have been using 2010 census data rather than the 2014 estimates. What I ended up doing was selecting by location having their centroids within. May not be as fancy, but the results came back closer to what I was expecting. Thanks for the input, though!

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