I have two raster data layers from cropscape for 2014 and 2015 that have been clipped to Fresno County. I want to look at the change in almonds between these two years (if and where almonds were added or taken out). I used the difference function in the Image Analysis window to obtain the temporary difference/change layer. What I'm unsure how to do, is make this layer useful and classify it so I can see areas of positive/negative change and no change.

I watched a couple video tutorials explaining how to perform change analysis using landsat data, but I'm not sure how to apply this to my cropscape data. For instance, to use the remap function to classify the difference data, I need to know what definition parameters to enter, but I'm not sure of what these would be.

Does anyone have any suggestions or other functions that would be better to use? enter image description here

  • Reclassify first year to 1,0. Second year to 2,0. Find total. 1 = reduction. 2=increase. 3=no changes – FelixIP Jun 17 '16 at 9:30

Do some experimenting with the Raster Calculator. You can call Con or other conditional functions from within the raster calculator, or better yet the python interpreter (if you're comfortable with that).

You will probably want to create an output for each scenario that you are interested in comparing. For example if you want to identify areas that were grassland/pasture (class 176) and are now almonds (class 75):

  1. First create each condition as a new binary raster - Con('CDL_2014' == 176, 1, 0) and Con('CDL_2015' == 75, 1, 0)
  2. Then add those output rasters together - 'CDL_2014_176' + 'CDL_2015_75'
  3. In this new raster, pixel values of 2 will represent areas that changed from Grassland/Pasture to Almond.

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