Extract spectral regeneration data using Google Earth Engine
The following workflow can be used to extract a time series of Landsat Normalized Burn Ratio (NBR) using Google Earth Engine and the LandTrendr change detection algorithm.1 See (1.1) for a definitions of the spectral change metrics extracted via Landtrendr.
The workflow presented was developed and provided to me by Jen Hird (University of Calgary | Alberta Biodiversity Monitoring Institute, 2020). I adapted it for chapter 3 of my PhD thesis.
|preDistMean||For each polygon, the average NBR value for the 5 years pre-disturbance|
|yod_mean||Year of disturbance|
|eoc_year||year when NBR values started to increase|
|totDistb||Difference between pre-disturbance NBR and the NBR at the start of regeneration|
|relDistbVal_mean||(totDistb)/SQRT(ABS(preDistMean/1000)) Calculation from @MillerThode2007|
|regen5yr, regen10yr, regen15yr, regen20yr||Percent of totDistb values regained after 5, 10, 15, and 20 years after the disturbance|
|yrTo30, yrTo50, yrTo80, yrTo100||Time taken for 30%, 50%, 80%, and 100% of thetotDistb to be regained|
|regen_survey||Percent of totDistb values regained at the year of the bird survey.|
|lengthDistb||time between yod and eoc|
|length of Regen||end year - eocYr|
|TOT_PIXELS||number of pixels used for change detection (Landsat has a 30m resolution)|
|PERC_UNMSKD||percent of pixels not masked by clouds or atmospheric conditions|