I have a Google Earth KMZ file which shows ground movements after an earthquake, arranged into discrete classes:
From the KMZ file I'm able to download the original PNG images, which are multi-band (RGBA). I used the mosaic tool to create a single, seamless raster over my area of interest. I need to reclassify this image to match the legend above.
The problem is that while there are 13 discrete classes in the legend, there is a far greater range of values in the mosaicked raster.
I believe this has occurred due to resampling and smoothing of the images (which occurred before the data provider gave them to me) which has resulted in interpolation between the known values. Here is a screenshot of the cells at close magnification:
For example, the yellow in the legend corresponds to RGB values of 255,255,0 but the yellows in the mosaicked raster vary considerably (eg 239,239,15 or 246,246,8, etc).
Is it feasible to "resurrect" the mosaicked image, and convert it into something approximating the values in the legend?
I realise that this approach isn't ideal, and that it would be far better to start with the original source dataset - but this isn't possible in this case.