Stretched exhibits your reported bug and "Unique Values" just doesn't show anything. (You should just be able to use your original raster as the mask) Step 3, run the Nibble tool. This identifies the areas to be filled (NoData). Use Classified - The Classified symbology method seems to display both NoData types properly (i.e.e as the same thing) so use that if possible and you don't want to alter the data. You could use the following raster calculator statement to generate an input: Con (IsNull ('yourraster'),0,'yourraster') Step 2, create a Nibble mask. I tried in ArcGIS (reclass, copy raster). Some other tool may be able to re-render it while keeping the data as 32bit floats. I don't know why, but I think it is because I have nodata value in Variable (slope image, elevation image, distance to roads) and I don't know how I can remove these values. On the downside this converts it to 8 bit data (0-255). I tried using the value as well in Set Null and the Raster Calculator, no luck. Ran the function, and I still get the same result shown in image 1. Use the raster calculator to construct a binary raster which can be symbolized as blue or transparent and overlain on the bedrock elevation map. If you don't tick the use-renderer your new file will have the same issues. Raster Calculator (image 2) Set Null (image 3) I have also gone to (Windows / image analysis), selected one of the files, added a function, and computed the 'NoData' values. However, there are a couple of possible workarounds:Įxport the data - If you export the data being sure to "use renderer" it will start working correctly. I have absolutely no idea whats happening in the data (but my guess would be that there are two different "noData" values being used behind the scenes, one may be "null" the other "-9999" for instance) but would be interested to know, maybe someone else can enlighten us. You're right in that ArcGIS shows two different types of NoData even though the attributes both show the same thing.
There's definitely something very funky going on with that file/data. Its a very flexible and versatile algorithm that can be used for many different calculations, and one that will soon become an important part of your toolbox.
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