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Raster used available here: https://www.dropbox.com/s/xn7hdll2op5zcc9/MAP_global.tif?dl=0.

INTRODUCTION: The resolution of a raster is commonly related in degrees, e.g.:

 library(raster) r <- raster("/CALL/IN/RASTER/FILE") print(r) class : RasterLayer dimensions : 720, 1440, 1036800 (nrow, ncol, ncell) *resolution : 0.25, 0.25 (x, y)* extent : -180, 180, -90, 90 (xmin, xmax, ymin, ymax) crs : +proj=longlat +datum=WGS84 +no_defs source : MAP_global.tif names : MAP_global values : 2.561833, 10341.26 (min, max)

At the equator, x = 0.25 degrees is ~27.75km, so, a 0.25 x 0.25 cell would have a horizontal area of ~770.06km^2. While the resolution (in units of degree) will remain constant as a function of latitude, the grid cell's area will shrink with distance from the equator.

QUESTION:

Can the area of a 0.25 x 0.25 degree grid cell be calculated as a function of latitude, and then be stored as a variable in that raster? If so, could someone please provide that script? Or provide me the information needed to proceed with coding it myself?

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2 Answers 2

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It's the raster packages "area" function!

Make a sample lat-long raster (1 degree here but any lat-long raster should work):

> r = raster() > r class : RasterLayer dimensions : 180, 360, 64800 (nrow, ncol, ncell) resolution : 1, 1 (x, y) extent : -180, 180, -90, 90 (xmin, xmax, ymin, ymax) crs : +proj=longlat +datum=WGS84 +no_defs

and area gives us:

> area(r) class : RasterLayer dimensions : 180, 360, 64800 (nrow, ncol, ncell) resolution : 1, 1 (x, y) extent : -180, 180, -90, 90 (xmin, xmax, ymin, ymax) crs : +proj=longlat +datum=WGS84 +no_defs source : memory names : layer values : 107.7756, 12308.62 (min, max)

a raster where each cell is the area in km^2, approximately. See the help for details of the approximation.

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Just a little remark: {terra} seems to handle things a little bit differently in comparison to {raster} since area() was removed from the package. expanse() is now what you are looking for:

library(terra) #> terra 1.6.33 # init raster r <- rast(resolution = 0.25) # insert some unique values to remove NAs values(r) <- 1:ncell(r) r #> class : SpatRaster #> dimensions : 720, 1440, 1 (nrow, ncol, nlyr) #> resolution : 0.25, 0.25 (x, y) #> extent : -180, 180, -90, 90 (xmin, xmax, ymin, ymax) #> coord. ref. : lon/lat WGS 84 #> source(s) : memory #> name : lyr.1 #> min value : 1 #> max value : 1036800 # area per grid cell res <- expanse(r, unit = "km", byValue = TRUE) summary(res[, 3]) #> Min. 1st Qu. Median Mean 3rd Qu. Max. #> 1.701 298.578 547.647 491.961 711.836 769.316
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  • Thank you for the solution employing terra. It is an interesting alternative to the one suggested by SpacedMan. Unfortunately, I can only choose one solution as the 'answer', else I would flag both your's and SpacedMan's solutions. Because SpacedMan provided a solution first, I'm flagging that solution the answer. That said, I do appreciate your time and have certainly learned something - thanks! Commented Oct 30, 2022 at 14:49
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    No worries, just wanted to provide some additional info to the existing answer. Commented Oct 30, 2022 at 16:00

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