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1

The easiest way is to subtract one raster from the other, if the result is 0, then both images are the same. Also you can see the histogram or plot by color the result.


0

The simplest solution I've found is to compute some summary statistics on the rasters, and compare those. I usually use standard deviation and mean, which are robust to most changes, though it is possible to fool them by intentionally manipulating the data. mean_obj = arcpy.GetRasterProperties(input_raster, 'MEAN') mean = float(mean_obj.getOutput(0)) if ...


3

You could have a try with gdalcompare.py script http://www.gdal.org/gdalcompare.html. The source code of the script is at http://trac.osgeo.org/gdal/browser/trunk/gdal/swig/python/scripts/gdalcompare.py and because it is a python script it should be easy to remove the unnecessary tests and add new ones to suit your current needs. The script seems to do pixel ...


1

I would suggest that you build your raster attribute table for each image, then you can compare the tables. This is not a complete check (like computing the difference between the two), but the probability that your images are different with the same histogram values is very very small. Also it gives you the number of unique values without NoData (from the ...


5

Try converting your rasters to numpy arrays and then check to see if they have the same shape and elements with array_equal. If they are the same, the result should be True: import arcpy, numpy raster1 = r'C:\path\to\raster.tif' raster2 = r'C:\path\to\raster.tif' r1 = arcpy.RasterToNumPyArray(raster1) r2 = arcpy.RasterToNumPyArray(raster2) d = ...


1

I recommend that you review the Help page entitled Managing the performance of ArcGIS map services. In particular I think you should look at the dot point from that page below: Precompute information results when you can do so. For example, you can precompute the maps that are delivered with ArcGIS for Server and use cached map services or basemap ...



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