I want to calculate the Crop Water Requirements and for this I need NDVI values for a period of time.

Because I have Sentinel 2 images and the temporal resolution is 5 days, I need also the values for NDVI for days when the satellite don't take the images.

Do you know a software that can interpolate/fill the gaps where I don't have NDVI values? I need to obtain just NDVI values for each day.

closed as primarily opinion-based by Vince, whyzar, Fran Raga, ahmadhanb, PolyGeo May 31 at 4:03

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  • 1
    Do you need raster layers for each day or do you need just values? Please add this information editing your question – aldo_tapia May 29 at 12:49
  • Sorry, I did not mention. I need just values for each days. – Cristina Mihalache May 30 at 18:53
  • Since you need just NDVI values, you can use from excel to almost any statistical software. In terms of R processing, with zoo() and na.approx() you can do it easily. Are you working with ET0 to compute CWR? – aldo_tapia May 30 at 19:21
  • I am working with ET0 to compute ETc and after these to compute CWR, GIWR and NIWR. – Cristina Mihalache May 31 at 8:16
  • You can check the work of UCLM related to this topic and Irrisat, a very interesting tool mounted in GEE – aldo_tapia May 31 at 12:30

You can use R for this purpose. A really small example:

Given some rasters (where values are (ndvi*100) + 100):


d1 <- raster('ndvi_2019-79.tif')
d2 <- raster('ndvi_2019-94.tif')
d3 <- raster('ndvi_2019-104.tif')

s <- stack(d1,d2,d3)


enter image description here

Create a date object with rasters names and an empty object with days in period:

dates <- names(s) # extract names
dates <- as.Date(dates, format = 'ndvi_%Y.%j')

dips <- dip(from = dates[1], to = dates[3])
zoo_ <- zoo(NA, order.by = dips)
idx <- which(dips %in% dates)

A function for fill gaps for those days:

fillGaps <- function(x){
  temp <- zoo_
  temp[idx] <- x

s2 <- calc(s, fillGaps)

And voila:

names(s2) <- dips

enter image description here

A small area to see date differences (BTW, are Sentinel-2 ndvi product):

enter image description here

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