Extract raster by a list of SpatialPolygonsDataFrame objects in R









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I am trying to extract summed raster cell values from a single big file for various SpatialPolygonsDataFrames (SPDF) objects in R stored in a list, then add the extracted values to the SPDF objects attribute tables. I would like to iterate this process, and have no idea how to do so. I have found an efficient solution for multiple polygons stored in a single SPDF object (see: https://gis.stackexchange.com/questions/130522/increasing-speed-of-crop-mask-extract-raster-by-many-polygons-in-r), but do not know how to apply the crop>mask>extract procedure to a LIST of SPDF objects, each containing multiple polygons. Here is a reproducible example:



library(maptools) ## For wrld_simpl
library(raster)

## Example SpatialPolygonsDataFrame
data(wrld_simpl) #polygon of world countries
bound <- wrld_simpl[1:25,] #country subset 1
bound2 <- wrld_simpl[26:36,] #subset 2

## Example RasterLayer
c <- raster(nrow=2e3, ncol=2e3, crs=proj4string(wrld_simpl), xmn=-180,
xmx=180, ymn=-90, ymx=90)
c <- 1:length(c)

#plot, so you can see it
plot(c)
plot(bound, add=TRUE)
plot(bound2, add=TRUE, col=3)

#make list of two SPDF objects
boundl<-list()
boundl[[1]]<-bound1
boundl[[2]]<-bound2

#confirm creation of SPDF list
boundl


The following is what I would like to run for the entire list, in a forloop format. For a single SPDF from the list, the following series of functions seem to work:



clip1 <- crop(c, extent(boundl[[1]])) #crops the raster to the extent of the polygon, I do this first because it speeds the mask up
clip2 <- mask(clip1, boundl[[1]]) #crops the raster to the polygon boundary
extract_clip <- extract(clip2, boundl[[1]], fun=sum)
#add column + extracted raster values to polygon dataframe
boundl[[1]]@data["newcolumn"] = extract_clip


But when I try to isolate the first function for the SPDF list (raster::crop), it does not return a raster object:



crop1 <- crop(c, extent(boundl[[1]])) #correctly returns object class 'RasterLayer'
cropl <- lapply(boundl, crop, c, extent(boundl)) #incorrectly returns objects of class 'SpatialPolygonsDataFrame'


When I try to isolate the mask function for the SPDF list (raster::mask), it returns an error:



maskl <- lapply(boundl, mask, c) 
#Error in (function (classes, fdef, mtable) : unable to find an inherited method for function ‘mask’ for signature ‘"SpatialPolygonsDataFrame", "RasterLayer"’


I would like to correct these errors, and efficiently iterate the entire procedure within a single loop (i.e., crop>mask>extract>add extracted values to SPDF attribute tables. I am really new to R and don't know where to go from here. Please help!










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  • bound1 is not defined.
    – Florian
    Nov 12 at 3:33














up vote
0
down vote

favorite












I am trying to extract summed raster cell values from a single big file for various SpatialPolygonsDataFrames (SPDF) objects in R stored in a list, then add the extracted values to the SPDF objects attribute tables. I would like to iterate this process, and have no idea how to do so. I have found an efficient solution for multiple polygons stored in a single SPDF object (see: https://gis.stackexchange.com/questions/130522/increasing-speed-of-crop-mask-extract-raster-by-many-polygons-in-r), but do not know how to apply the crop>mask>extract procedure to a LIST of SPDF objects, each containing multiple polygons. Here is a reproducible example:



library(maptools) ## For wrld_simpl
library(raster)

## Example SpatialPolygonsDataFrame
data(wrld_simpl) #polygon of world countries
bound <- wrld_simpl[1:25,] #country subset 1
bound2 <- wrld_simpl[26:36,] #subset 2

## Example RasterLayer
c <- raster(nrow=2e3, ncol=2e3, crs=proj4string(wrld_simpl), xmn=-180,
xmx=180, ymn=-90, ymx=90)
c <- 1:length(c)

#plot, so you can see it
plot(c)
plot(bound, add=TRUE)
plot(bound2, add=TRUE, col=3)

#make list of two SPDF objects
boundl<-list()
boundl[[1]]<-bound1
boundl[[2]]<-bound2

#confirm creation of SPDF list
boundl


The following is what I would like to run for the entire list, in a forloop format. For a single SPDF from the list, the following series of functions seem to work:



clip1 <- crop(c, extent(boundl[[1]])) #crops the raster to the extent of the polygon, I do this first because it speeds the mask up
clip2 <- mask(clip1, boundl[[1]]) #crops the raster to the polygon boundary
extract_clip <- extract(clip2, boundl[[1]], fun=sum)
#add column + extracted raster values to polygon dataframe
boundl[[1]]@data["newcolumn"] = extract_clip


But when I try to isolate the first function for the SPDF list (raster::crop), it does not return a raster object:



crop1 <- crop(c, extent(boundl[[1]])) #correctly returns object class 'RasterLayer'
cropl <- lapply(boundl, crop, c, extent(boundl)) #incorrectly returns objects of class 'SpatialPolygonsDataFrame'


When I try to isolate the mask function for the SPDF list (raster::mask), it returns an error:



maskl <- lapply(boundl, mask, c) 
#Error in (function (classes, fdef, mtable) : unable to find an inherited method for function ‘mask’ for signature ‘"SpatialPolygonsDataFrame", "RasterLayer"’


I would like to correct these errors, and efficiently iterate the entire procedure within a single loop (i.e., crop>mask>extract>add extracted values to SPDF attribute tables. I am really new to R and don't know where to go from here. Please help!










share|improve this question























  • bound1 is not defined.
    – Florian
    Nov 12 at 3:33












up vote
0
down vote

favorite









up vote
0
down vote

favorite











I am trying to extract summed raster cell values from a single big file for various SpatialPolygonsDataFrames (SPDF) objects in R stored in a list, then add the extracted values to the SPDF objects attribute tables. I would like to iterate this process, and have no idea how to do so. I have found an efficient solution for multiple polygons stored in a single SPDF object (see: https://gis.stackexchange.com/questions/130522/increasing-speed-of-crop-mask-extract-raster-by-many-polygons-in-r), but do not know how to apply the crop>mask>extract procedure to a LIST of SPDF objects, each containing multiple polygons. Here is a reproducible example:



library(maptools) ## For wrld_simpl
library(raster)

## Example SpatialPolygonsDataFrame
data(wrld_simpl) #polygon of world countries
bound <- wrld_simpl[1:25,] #country subset 1
bound2 <- wrld_simpl[26:36,] #subset 2

## Example RasterLayer
c <- raster(nrow=2e3, ncol=2e3, crs=proj4string(wrld_simpl), xmn=-180,
xmx=180, ymn=-90, ymx=90)
c <- 1:length(c)

#plot, so you can see it
plot(c)
plot(bound, add=TRUE)
plot(bound2, add=TRUE, col=3)

#make list of two SPDF objects
boundl<-list()
boundl[[1]]<-bound1
boundl[[2]]<-bound2

#confirm creation of SPDF list
boundl


The following is what I would like to run for the entire list, in a forloop format. For a single SPDF from the list, the following series of functions seem to work:



clip1 <- crop(c, extent(boundl[[1]])) #crops the raster to the extent of the polygon, I do this first because it speeds the mask up
clip2 <- mask(clip1, boundl[[1]]) #crops the raster to the polygon boundary
extract_clip <- extract(clip2, boundl[[1]], fun=sum)
#add column + extracted raster values to polygon dataframe
boundl[[1]]@data["newcolumn"] = extract_clip


But when I try to isolate the first function for the SPDF list (raster::crop), it does not return a raster object:



crop1 <- crop(c, extent(boundl[[1]])) #correctly returns object class 'RasterLayer'
cropl <- lapply(boundl, crop, c, extent(boundl)) #incorrectly returns objects of class 'SpatialPolygonsDataFrame'


When I try to isolate the mask function for the SPDF list (raster::mask), it returns an error:



maskl <- lapply(boundl, mask, c) 
#Error in (function (classes, fdef, mtable) : unable to find an inherited method for function ‘mask’ for signature ‘"SpatialPolygonsDataFrame", "RasterLayer"’


I would like to correct these errors, and efficiently iterate the entire procedure within a single loop (i.e., crop>mask>extract>add extracted values to SPDF attribute tables. I am really new to R and don't know where to go from here. Please help!










share|improve this question















I am trying to extract summed raster cell values from a single big file for various SpatialPolygonsDataFrames (SPDF) objects in R stored in a list, then add the extracted values to the SPDF objects attribute tables. I would like to iterate this process, and have no idea how to do so. I have found an efficient solution for multiple polygons stored in a single SPDF object (see: https://gis.stackexchange.com/questions/130522/increasing-speed-of-crop-mask-extract-raster-by-many-polygons-in-r), but do not know how to apply the crop>mask>extract procedure to a LIST of SPDF objects, each containing multiple polygons. Here is a reproducible example:



library(maptools) ## For wrld_simpl
library(raster)

## Example SpatialPolygonsDataFrame
data(wrld_simpl) #polygon of world countries
bound <- wrld_simpl[1:25,] #country subset 1
bound2 <- wrld_simpl[26:36,] #subset 2

## Example RasterLayer
c <- raster(nrow=2e3, ncol=2e3, crs=proj4string(wrld_simpl), xmn=-180,
xmx=180, ymn=-90, ymx=90)
c <- 1:length(c)

#plot, so you can see it
plot(c)
plot(bound, add=TRUE)
plot(bound2, add=TRUE, col=3)

#make list of two SPDF objects
boundl<-list()
boundl[[1]]<-bound1
boundl[[2]]<-bound2

#confirm creation of SPDF list
boundl


The following is what I would like to run for the entire list, in a forloop format. For a single SPDF from the list, the following series of functions seem to work:



clip1 <- crop(c, extent(boundl[[1]])) #crops the raster to the extent of the polygon, I do this first because it speeds the mask up
clip2 <- mask(clip1, boundl[[1]]) #crops the raster to the polygon boundary
extract_clip <- extract(clip2, boundl[[1]], fun=sum)
#add column + extracted raster values to polygon dataframe
boundl[[1]]@data["newcolumn"] = extract_clip


But when I try to isolate the first function for the SPDF list (raster::crop), it does not return a raster object:



crop1 <- crop(c, extent(boundl[[1]])) #correctly returns object class 'RasterLayer'
cropl <- lapply(boundl, crop, c, extent(boundl)) #incorrectly returns objects of class 'SpatialPolygonsDataFrame'


When I try to isolate the mask function for the SPDF list (raster::mask), it returns an error:



maskl <- lapply(boundl, mask, c) 
#Error in (function (classes, fdef, mtable) : unable to find an inherited method for function ‘mask’ for signature ‘"SpatialPolygonsDataFrame", "RasterLayer"’


I would like to correct these errors, and efficiently iterate the entire procedure within a single loop (i.e., crop>mask>extract>add extracted values to SPDF attribute tables. I am really new to R and don't know where to go from here. Please help!







r polygon spatial raster






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edited Nov 10 at 21:02

























asked Nov 10 at 18:05









Dorothy

577




577











  • bound1 is not defined.
    – Florian
    Nov 12 at 3:33
















  • bound1 is not defined.
    – Florian
    Nov 12 at 3:33















bound1 is not defined.
– Florian
Nov 12 at 3:33




bound1 is not defined.
– Florian
Nov 12 at 3:33












1 Answer
1






active

oldest

votes

















up vote
2
down vote



accepted










One approach is to take what is working and simply put the desired "crop -> mask -> extract -> add" into a for loop:



for(i in seq_along(boundl)) 
clip1 <- crop(c, extent(boundl[[i]]))
clip2 <- mask(clip1, boundl[[i]])
extract_clip <- extract(clip2, boundl[[i]], fun=sum)
boundl[[i]]@data["newcolumn"] <- extract_clip



One can speed-up the loop with parallel execution, e.g., with the R package foreach. Conversely, the speed gain of using lapply() instead of the for loop will be small.



Why the error occurs:



cropl <- lapply(boundl, crop, c, extent(boundl)) 


applies the function crop() to each element of the list boundl. The performed operation is



tmp <- crop(boundl[[1]], c)
## test if equal to first element
all.equal(cropl[[1]], tmp)
[1] TRUE


To get the desired result use



cropl <- lapply(boundl, function(x, c) crop(c, extent(x)), c=c)
## test if the first element is as expected
all.equal(cropl[[1]], crop(c, extent(boundl[[1]])))
[1] TRUE


Note:



Using c to denote an R object is a bade choice, because it can be easily confused with c().






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    1 Answer
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    active

    oldest

    votes








    1 Answer
    1






    active

    oldest

    votes









    active

    oldest

    votes






    active

    oldest

    votes








    up vote
    2
    down vote



    accepted










    One approach is to take what is working and simply put the desired "crop -> mask -> extract -> add" into a for loop:



    for(i in seq_along(boundl)) 
    clip1 <- crop(c, extent(boundl[[i]]))
    clip2 <- mask(clip1, boundl[[i]])
    extract_clip <- extract(clip2, boundl[[i]], fun=sum)
    boundl[[i]]@data["newcolumn"] <- extract_clip



    One can speed-up the loop with parallel execution, e.g., with the R package foreach. Conversely, the speed gain of using lapply() instead of the for loop will be small.



    Why the error occurs:



    cropl <- lapply(boundl, crop, c, extent(boundl)) 


    applies the function crop() to each element of the list boundl. The performed operation is



    tmp <- crop(boundl[[1]], c)
    ## test if equal to first element
    all.equal(cropl[[1]], tmp)
    [1] TRUE


    To get the desired result use



    cropl <- lapply(boundl, function(x, c) crop(c, extent(x)), c=c)
    ## test if the first element is as expected
    all.equal(cropl[[1]], crop(c, extent(boundl[[1]])))
    [1] TRUE


    Note:



    Using c to denote an R object is a bade choice, because it can be easily confused with c().






    share|improve this answer
























      up vote
      2
      down vote



      accepted










      One approach is to take what is working and simply put the desired "crop -> mask -> extract -> add" into a for loop:



      for(i in seq_along(boundl)) 
      clip1 <- crop(c, extent(boundl[[i]]))
      clip2 <- mask(clip1, boundl[[i]])
      extract_clip <- extract(clip2, boundl[[i]], fun=sum)
      boundl[[i]]@data["newcolumn"] <- extract_clip



      One can speed-up the loop with parallel execution, e.g., with the R package foreach. Conversely, the speed gain of using lapply() instead of the for loop will be small.



      Why the error occurs:



      cropl <- lapply(boundl, crop, c, extent(boundl)) 


      applies the function crop() to each element of the list boundl. The performed operation is



      tmp <- crop(boundl[[1]], c)
      ## test if equal to first element
      all.equal(cropl[[1]], tmp)
      [1] TRUE


      To get the desired result use



      cropl <- lapply(boundl, function(x, c) crop(c, extent(x)), c=c)
      ## test if the first element is as expected
      all.equal(cropl[[1]], crop(c, extent(boundl[[1]])))
      [1] TRUE


      Note:



      Using c to denote an R object is a bade choice, because it can be easily confused with c().






      share|improve this answer






















        up vote
        2
        down vote



        accepted







        up vote
        2
        down vote



        accepted






        One approach is to take what is working and simply put the desired "crop -> mask -> extract -> add" into a for loop:



        for(i in seq_along(boundl)) 
        clip1 <- crop(c, extent(boundl[[i]]))
        clip2 <- mask(clip1, boundl[[i]])
        extract_clip <- extract(clip2, boundl[[i]], fun=sum)
        boundl[[i]]@data["newcolumn"] <- extract_clip



        One can speed-up the loop with parallel execution, e.g., with the R package foreach. Conversely, the speed gain of using lapply() instead of the for loop will be small.



        Why the error occurs:



        cropl <- lapply(boundl, crop, c, extent(boundl)) 


        applies the function crop() to each element of the list boundl. The performed operation is



        tmp <- crop(boundl[[1]], c)
        ## test if equal to first element
        all.equal(cropl[[1]], tmp)
        [1] TRUE


        To get the desired result use



        cropl <- lapply(boundl, function(x, c) crop(c, extent(x)), c=c)
        ## test if the first element is as expected
        all.equal(cropl[[1]], crop(c, extent(boundl[[1]])))
        [1] TRUE


        Note:



        Using c to denote an R object is a bade choice, because it can be easily confused with c().






        share|improve this answer












        One approach is to take what is working and simply put the desired "crop -> mask -> extract -> add" into a for loop:



        for(i in seq_along(boundl)) 
        clip1 <- crop(c, extent(boundl[[i]]))
        clip2 <- mask(clip1, boundl[[i]])
        extract_clip <- extract(clip2, boundl[[i]], fun=sum)
        boundl[[i]]@data["newcolumn"] <- extract_clip



        One can speed-up the loop with parallel execution, e.g., with the R package foreach. Conversely, the speed gain of using lapply() instead of the for loop will be small.



        Why the error occurs:



        cropl <- lapply(boundl, crop, c, extent(boundl)) 


        applies the function crop() to each element of the list boundl. The performed operation is



        tmp <- crop(boundl[[1]], c)
        ## test if equal to first element
        all.equal(cropl[[1]], tmp)
        [1] TRUE


        To get the desired result use



        cropl <- lapply(boundl, function(x, c) crop(c, extent(x)), c=c)
        ## test if the first element is as expected
        all.equal(cropl[[1]], crop(c, extent(boundl[[1]])))
        [1] TRUE


        Note:



        Using c to denote an R object is a bade choice, because it can be easily confused with c().







        share|improve this answer












        share|improve this answer



        share|improve this answer










        answered Nov 12 at 4:04









        Florian

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