Hello. I have a project where I need to make acreage calculations for hundreds of thousands of polygons spread across the U.S. I have 2 goals for this analysis: 1) minimize regional bias in acreage calculations, 2) generate acreage totals for many different subsets of polygons that are as close to true acreage as possible. These are my only goals, so my focus is on accurate area calculation only. In other words, I’m fine if the method I use distorts shape or distance and I don’t need to make any calculations across zones (if I stitch projections together).
It seems to me like accuracy would be highest if the acreage of each polygon was calculated with it projected to the exact state plane zone it is within. Nice idea, but pragmatically, this seems like a nightmare. In my fantasy world, there is already some sort of stitched together projection like this that covers the US where each location is projected to the correct state plane zone. I know this would wreak havoc around zone boundaries, it would look Frankensteinian, and cross-boundary inference would be nonsensical, but for my objectives, I think this would be ok. Does anyone know of an existing resource like this?
Alternatively, I wonder if there are any existing tools or workflows that could take a single feature class containing all of my polygons and somehow “batch project” them so that each individual polygon is projected to the appropriate state plane zone. Can anyone make recommendations about something like this? if anyone has a different solution to this problem entirely, I’m all ears.
Please note that I’ve already compared acreage measurements using Albers Equal Area Conic and Lambert Conformal conic with acreage estimates from the same polygons projected to UTM zones. Across this large dataset, both of the single projections had too many biased acreage calculations and the UTM based calculations had unacceptable amounts of inaccuracy for polygons that were farthest from central meridians. This is what led me to the idea of using state plane zones, since they cover smaller areas and have fewer problems with distortion. It’s just… there are so many of them that I’m finding this analysis quite daunting. I’m hoping someone here has some advice for me. I’m guessing that others have worked through this problem before. Thanks in advance for any sage advice you can provide.
