R: Interpolation between raster layers of different dates

Question

Let's say I have 4 raster layers with the same length with data from 4 different years: 2006,2008,2010 and 2012:

library(raster) r2006<-raster(ncol=3, nrow=3) values(r2006)<-1:9 r2008<-raster(ncol=3, nrow=3) values(r2008)<-3:11 r2010<-raster(ncol=3, nrow=3) values(r2010)<-5:13 r2012<-raster(ncol=3, nrow=3) values(r2012)<-7:15 

Now I want to create raster layers for each year between 2006 and 2013 (or even longer) by inter- / extrapolation (the linear method should be a good start) of the values ​​of 4 raster layers. The result should look like this:

 r2006<-raster(ncol=3, nrow=3) values(r2006)<-1:9 r2007<-raster(ncol=3, nrow=3) values(r2007)<-2:10 r2008<-raster(ncol=3, nrow=3) values(r2008)<-3:11 r2009<-raster(ncol=3, nrow=3) values(r2009)<-4:12 r2010<-raster(ncol=3, nrow=3) values(r2010)<-5:13 r2011<-raster(ncol=3, nrow=3) values(r2011)<-6:14 r2012<-raster(ncol=3, nrow=3) values(r2012)<-7:15 r2013<-raster(ncol=3, nrow=3) values(r2013)<-8:16 

Using lm() or approxExtrap doesn't help much.

Answer 1

One way to do this is to divide your problem into two parts: 1. First, perform numerical interpolation based on the values ​​of the raster, 2. and apply the interpolated values ​​to the corresponding intermediate raster layers.

Idea . Create a data frame of raster layer values ​​(), the time index that is used for the data frame, and then apply linear interpolation to these numbers. For linear interpolation, I use approxTime from the simecol package.

For your example above,

 library(raster) library(simecol) df <- data.frame("2006" = 1:9, "2008" = 3:11, "2010" = 5:13, "2012"=7:15) #transpose since we want time to be the first col, and the values to be columns new <- data.frame(t(df)) times <- seq(2006, 2012, by=2) new <- cbind(times, new) # Now, apply Linear Interpolate for each layer of the raster approxTime(new, 2006:2012, rule = 2) 

This gives:

 # times X1 X2 X3 X4 X5 X6 X7 X8 X9 #1 2006 1 2 3 4 5 6 7 8 9 #2 2007 2 3 4 5 6 7 8 9 10 #3 2008 3 4 5 6 7 8 9 10 11 #4 2009 4 5 6 7 8 9 10 11 12 #5 2010 5 6 7 8 9 10 11 12 13 #6 2011 6 7 8 9 10 11 12 13 14 #7 2012 7 8 9 10 11 12 13 14 15 

Then you can save this and take each row and apply to the values ​​of this raster object this year.

Note: approxTime does not perform linear extrapolation. It just takes the closest value, so you need to consider this.