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I'll explain my aim first: I am trying to create a single raster to represent vegetation resilience, I am doing this via change detection.

So far I have created 5 Change detection images, where 2000 is a reference image. I have done nothing to these except to display them with the classify tool with 1 st dev.

My problem is what is the best way to combine these images to demonstrate resilience. I'm assuming it's just a raster calculation.

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  • Should mention I'm working on a method from: Washington-Allen, R. A., R. Ramsey, N. E. West and B. E. Norton (2008). "Quantification of the ecological resilience of drylands using digital remote sensing." Ecology and Society 13(1): 33. and it's the final equation I'm having trouble with not sure how to convert it for arcmap Sep 4, 2013 at 16:08
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    Please edit your question to either provide a link to the paper or reproduce the equation (with explanations of its symbols).
    – whuber
    Sep 4, 2013 at 20:14
  • Direct link to the pdf can be found here: tinyurl.com/mxnt7y6 the equation is number 7. where ij are row and coloumn of a given pixel A is your difference image and R your reference image. I've consider using linear regression on the 5 NDVI images instead as a measure of resilience, however I'm not sure how to approach that method as my dates are not consecutive. Sep 4, 2013 at 21:33
  • There's no problem doing regression on non-consecutive dates unless there is a large gap at one end or the other (for then the result depends too heavily on the lone isolated raster). One efficient way to do this is shown at gis.stackexchange.com/questions/52502. Although R code is given the procedure works pretty easily with Spatial Analyst: the formula for the slope will be a weighted (linear) combination of the five images and you can work out the weights based on the dates alone.
    – whuber
    Sep 4, 2013 at 21:36
  • Equation (7) in the paper makes no sense: it is a combination of scalars and an apparent vector. You will need to contact the authors and inquire concerning what they intended this stuff to say.
    – whuber
    Sep 4, 2013 at 21:42

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