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I've tried changing GCS and PCS multiple ways but can't seem to figure out how to get the Near (from Proximity tools) to output the Near_DIST in feet. All it outputs is what looks like decimal degrees. Here is my data:

Data frame: NAD_1983_StatePlane_Texas_North_FIPS_4201_Feet

Input features (points): GCS_North_American_1927

Near features: GCS_North_American_1983

I'm not fond of the Data frame features but it's for my geographic area and ensures that when I draw buffer circles they actually look like circles and are not skewed to appear oblong. Based on the tool, it says the output Near_DIST will return units of measure based on the Input features. I'm not sure what I should change to get it to return the distance in feet.

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    Are you sure your input features are in NAD27? I ask because that was the default projection long ago, before folks paid attention to coordinate systems. Either way, you'll need to project both to the data frame projection before running Near if you want the units in the data frame projection. Please edit the question to detail the ways you have changed the input layers (the data frame doesn't count). – Vince Dec 11 '15 at 15:49
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    @Vince - you should post the content of your comment as an answer. It will be important for OP to make sure that he knows what CS his original data is in so that he can project both. Per ESRI tool help: "The (NEAR_DIST) value is in the linear unit of the input features coordinate system, or Meters when the Method parameter is set to GEODESIC and the input is in a geographic coordinate system." – JWallace Dec 11 '15 at 16:38
  • Yeah, the input features are points that I created from long/lats based on NAD27 so I set it to that when I created the shapefile. So if my data frame is in 'X' State Plane (US feet) and my input feature is my NAD27 shapefile am I correct to understand that I need to use the toolbox to do a GCS transformation on it and into the 'X' State Plane (US feet) in order for my Near_DIST to output in feet? – Chris Dec 11 '15 at 21:00
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Agree with above, need to reproject to match your data frame or vise versa... Don't know if this is large or small scale analysis, but if it's large.. you need a non ancient transverse Mercator projection to preserve conformality and eliminate scene based anomalies that would be present with a geographic projection. Either way.. match those projections

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