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I need to run a Propensity Score Analysis with forest loss in a given region between 2017 to 2020. I am new to GEE, and I can't seem to find out how to retrieve total loss from 2017-2020 for the ROI. Ultimately I need deforested area per pixel. I am using ArcGIS for data processing after exporting data from GEE. I tried this:

// Select lossyear band from Hansen and the total ROI

var hansen = hansen.select(['lossyear']).clip(intersection)

// Select relevant years and add them up into one image
var loss2017 = hansen.eq(17)
var loss2018 = hansen.eq(18)
var loss2019 = hansen.eq(19)
var loss2020 = hansen.eq(20)

var allyears = loss2017.add(loss2018).add(loss2019).add(loss2020); 

But it didn't seem right when I mapped it. I had used also

var lossImage = hansen.select(['loss']);
var lossAreaImage = lossImage.multiply(ee.Image.pixelArea()); 

in an attempt to export deforested pixels 2000-2020, but I ended up with total areas for every pixel, which I couldn't use.

How can I do this?

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  • Do you want a single value? Like in the study area there were e.g. 500 pixels with forest loss? Or do you want only a mask, where every single pixel is either 0 (no loss) or 1 (loss)?
    – JonasV
    Jul 7, 2021 at 9:56
  • Yes the second one! A mask where every pixel is either 0 or 1 -- because then I need to randomly sample them for inference
    – Julia R.
    Jul 7, 2021 at 14:03

1 Answer 1

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If I correctly understand your question that you want an image containing valid pixels where there was loss between 2017 and 2020, then I believe this would do it:

var hansenLossYear = ee.Image('UMD/hansen/global_forest_change_2020_v1_8').select('lossyear').selfMask()
var loss_2017_2020 = hansenLossYear.gte(ee.Image.constant(17)).and(hansenLossYear.lte(ee.Image.constant(20))).selfMask()

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