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Aha! I think I found the problem, and it's NOT with Cell Statistics. As I mentioned, most of the out-of range data were in Florida. The data are projected minimum January temperatures, and of course, in the US, South Florida is among the hottest places in January. The Cell Statistics Data are correct, but the statistics in the Symbology classifier are wrong. See the image below. I selected an especially hot year (2072); the classifier says that the maximum value is 284.7843018 (ok, these temperature data are Kelvin BTW, not Celsius. Otherwise we would be in deep doo-doo). So I classified into two groups, with 284 as the cutoff. The classifier says there are 6 elements above my cut-off value. But, if you look at the partial image of Florida, You will see a lot of 6 cells colored red. And if you look at the "identify" box, you will see that the pixel I have identified has a value of 285.128021, well outside the range that the classifier says exists in the raster. I clicked around in the red area, and there are more than 6 unique values. Stack up 30 rasters (years) and South Florida will show lots of these "out of range" values. So, I am convinced that the Cell Statistics values are correct, and there is something wrong with the Symbology classifier. Which does not bother me right this moment. If anyone can shed light on this problem, I'd be happy to hear your input.
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07-15-2016
09:44 AM
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Thanks. Yuck, BTW. I have 30 rasters in two time periods from each of three global climate models, so that's 180 rasters to convert or integerize. Did I mention I'm not much of a batch processor? I'd love to hear any updates on the fix for Cell Statistics in 10.4 and if there is a patch for 10.3. Gah. Oh, and one option in X. Wang's suggestion to the other question was to convert their rasters to floating point, which is what my rasters already are. Any light you can shed on that?
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07-14-2016
09:59 AM
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Thanks, Dan. Here is where I found the reference to a bug, nearly to the end of the post (Right above, but post-dating a comment by you, actually!) https://community.esri.com/thread/173734?q=cell%20statistics%20Arc And thanks for the suggestion, but I'm afraid it has reached beyond my abilities. Never used numpy arrays or masked arrays or nanmeans. I did try using a mask in the Cell Stats run, but that did not seem to help, either.
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07-14-2016
09:26 AM
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I am using Cell Statistics (Spatial analyst/Local) to calculate mean values for a set of 32 bit floating point rasters; all the same size and source (a NetCDF), identical cell size, and numbers of rows and columns. The resulting overall mean raster has high values that are greater than ANY of the input rasters for which I want the mean value. All of the high values are near or somewhat near NoData values (but some are in the center of Florida, not near the raster edges). I've tried checking and unchecking the ignore no data option. Any help with this? I've seen some older posts about a bug that 10.4 has addressed, but that is not an option for me. Thanks.
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07-14-2016
08:55 AM
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