How to extract values from rasterstack with xy coordinates?

Question

I have a rasterstack (5 raster layers) that actually is a time series raster.

r <- raster(nrow=20, ncol=200)
s <- stack( sapply(1:5, function(i) setValues(r, rnorm(ncell(r), i, 3) )) )
s

class       : RasterStack
dimensions  : 20, 200, 4000, 5  (nrow, ncol, ncell, nlayers)
resolution  : 1.8, 9  (x, y)
extent      : -180, 180, -90, 90  (xmin, xmax, ymin, ymax)
coord. ref. : +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0 
names       :   layer.1,   layer.2,   layer.3,   layer.4,   layer.5
min values  : -9.012146, -9.165947, -9.707269, -7.829763, -5.332007
max values  :  11.32811,  11.97328,  15.99459,  15.66769,  16.72236

My objective is to plot each pixel and explore their behavior over time.

How could I extract each pixels together with their x,y coordinates and plot a time series curve?

Solution 1

Thanks a lot @SimonO101 !

This code works.

r <- raster(nrow=10, ncol=10)
s <- stack( sapply(1:5, function(i) setValues(r, rnorm(ncell(r), i, 3) )) )
s[1:3]<-NA

vals <- values(s)

coord <- xyFromCell(s,1:ncell(s))

combine <- cbind(coord,vals)

write.table(combine,"xyvalues.txt") 

Solution 2

You can use extract and pass a vector of cell numbers you wish to extract to return a matrix of values in each pixel. Each row represents a pixel, the columns are layers...

mat <- extract( s , 1:ncell(s) )
head( mat )
#        layer.1  layer.2  layer.3    layer.4   layer.5
#[1,] -0.2138718 3.114061 3.670945  1.2560295  2.881104
#[2,]  3.3580783 5.008205 2.315353  2.3247236 11.539837
#[3,]  3.2173875 2.958985 1.055389  3.1016730  4.064339
#[4,]  4.1113162 4.469828 3.113790  8.5329679  8.771459
#[5,] -2.4011283 4.747527 4.299707  2.2111643  9.457012
#[6,] -2.6159294 5.659211 1.926900 -0.3886837  5.661419

However extract is more useful when trying to get particular pixels. To get all pixels with the x / y coordinates you can just use rasterToPoints...

head( rasterToPoints( s ) )
#          x    y    layer.1  layer.2  layer.3    layer.4   layer.5
#[1,] -179.1 85.5 -0.2138718 3.114061 3.670945  1.2560295  2.881104
#[2,] -177.3 85.5  3.3580783 5.008205 2.315353  2.3247236 11.539837
#[3,] -175.5 85.5  3.2173875 2.958985 1.055389  3.1016730  4.064339
#[4,] -173.7 85.5  4.1113162 4.469828 3.113790  8.5329679  8.771459
#[5,] -171.9 85.5 -2.4011283 4.747527 4.299707  2.2111643  9.457012
#[6,] -170.1 85.5 -2.6159294 5.659211 1.926900 -0.3886837  5.661419