problems with raster histograms and classification

Discussion created by ronsuther on Sep 26, 2013
Latest reply on Nov 26, 2013 by amfeadan
Hi there,

I'm having some strange problems with classifying certain raster images for display purposes. The histograms that show up under properties/symbology/classify just don't match the actual raster, and as a result, the classify options don't work very well. In particular, I'd love to be able to use quantiles to display the raster in 10 evenly balanced colors (each color representing 10% of the raster cells). But the quantiles function fails and instead the raster shows up as 95% one color (the lowest values) and then only a tiny fraction for the other colors. This is a grid file (but I'm having similar issues with a tiff), so the sampling is I believe automatically set at full (no skips).

Even though the classification stats should be based on the full raster, the mean and standard deviation listed on the classify window don't come close to matching the mean and standard deviation of the raster in the properties/source tab. I am inclined to believe the classify #'s are the wrong ones, the mean is way too low. The histogram shows up as a single bar at the extreme low end of the scale.

Any ideas what is going on? Are these rasters just corrupted somehow? Am I missing some key setting where I could readjust the sampling of the Grid and/or re-do the statistics (I did try Calculate Statistics, didn't change anything that I could see)?

The files are large (673 MB), floating point Grid and tiff rasters. I'm running 10.1, on a 32 bit Windows 7 machine (though we get similar results on 64-bit). 

One other oddity - when I try to manually classify the images, and type in break points in the window on the right side of the box, every time I type in a new value, it shows up twice in the list. So if there are 8 breaks, for example, by the time I type in 4 new ones, I end up with 4 pairs of identical breaks! I'm assuming this could somehow be related to the above?

Any help would be appreciated!

ps just did a test where I converted the raster to an integer file instead of floating point, the classification problems persisted unfortunately...