Hi Thiago -
Here is an approach using 'mapply' and 'reclassify'. I changed your example
raster stack so the values range from 1:100 rather than 1:ncell(r) since that
is what you stated in your problem:
# Create raster stack
r <- raster(ncol=50, nrow=50)
s <- stack(lapply(1:10, function(x) setValues(r, rep(1:100,
each=(ncell(r)/100)))))
# Create lookup table
m <- as.data.frame(matrix(sample(100, 100*10, TRUE), 100, 10))
# create new stack with lookup
new.stack <- stack(mapply(FUN = function(x, y) {
lookup <- matrix(cbind(1:length(y), y), ncol=2)
reclassify(x, lookup)
}, x = as.list(s), y = m))
plot(s); plot(new.stack)
Cheers,
Cotton
-----Original Message-----
From: R-sig-Geo [mailto:[email protected]] On Behalf Of
Kilpatrick, Katherine A
Sent: Tuesday, April 10, 2018 11:44 AM
To: Thiago V. dos Santos <[email protected]>
Cc: R-sig-geo Mailing List <[email protected]>
Subject: Re: [R-sig-Geo] Substitute raster stack values based on matrix index
Maybe something along this line…..assuming I understood the problem properly
for (i in 1:nlayers(stackr)) {
layer <- stackr[[i]] # get a layer from the stack
ID_layer<- 1:ncell(layer[[1]]) # create cell ids for the layer
for (j in 1:nrow(tablem)) {
x <- rep(j,ncell(layer)) # LUT row number to test match
replace <- layer[ID_Raster] == x # test if cell value matches LUT row
number
layer[ID_Raster[replace]] <- tablem[j,i]
}
stackr[[i]] <- layer # put the update layer back in the stack }
---------------------------------------------------------------------
Katherine (Kay) Kilpatrick
Oceanographer
University of Miami Rosenstiel School for Marine and Atmospheric Science
Satellite Remote Sensing Laboratory
On Apr 10, 2018, at 12:45 PM, Thiago V. dos Santos via R-sig-Geo
<[email protected]<mailto:[email protected]>> wrote:
I have a large (7000x7000, 10-layered) raster stack whose values range from 0
to 100.
I need to modify the raster values using the a "lookup table" consisted of a
matrix which is 100 rows long by 10 cols wide, where the number of rows is
associated with the 0-100 value range of the raster and the number of columns
relates to the number of layers of the raster stack.
The following code creates a toy example of my dataset:
# Create raster stackr <- raster(ncol=50, nrow=50)s <- stack(lapply(1:10,
function(x) setValues(r, 1:ncell(r))))
# Create lookup tablem <- matrix(sample(100, 100*10, TRUE), 100, 10)
Therefore, I need to loop through each cell of the raster and check its value.
For example, if the cell value is `20`, then the new value will be reassigned
from the 20th line and 1st column in the matrix.
And so on for the 2nd raster stack layer and 2nd matrix column. And so on for
the remaining raster stack layers and matrix columns.
Any ideas on how to do that?
I know this sounds a bit cumbersome, but that's how a few ISRIC-WISE's soil
datasets are organized!
Greetings, -- Thiago V. dos Santos
Postdoctoral Research FellowDepartment of Climate and Space Science and
EngineeringUniversity of Michigan
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