Skip to main content
deleted 8 characters in body; edited title
Source Link
PolyGeo
  • 65.4k
  • 29
  • 114
  • 345

R: count Counting raster values using another raster as mask in R?

I would like to count the frequency of values in one raster, using another raster (different resolution) as the zonal condition.

The premise is that the coarser resolution raster represents the area that I would like to count the frequency of the finer resolution raster;

# make 2 rasters of the same extent, different resolutions
ext <- extent(0,1000,0,1000)
r1 <- raster(nrows=1000, ncols=1000,ext)
r1[] <- sample(seq(from = 1, to = 6, by = 1), size = 1000000, replace = TRUE)
r2 <- raster(nrows=10, ncols=10,ext)
r2[] <- sample(seq(from = 0, to = 1, by = 0.05), size = 100, replace = TRUE)
# create areas of interest in coarser raster
r2[r2 < 0.9] <- NA

Now i can't seem to find a function (might be blind) that will tell me what i want to know straight off - i thought zonal{raster} might have but it wont return a count function. So this is my work around:

# disaggregate the coarser raster to the same res as the finer raster
r2 <- disaggregate(r2,fact=c(100,100))
# mask the fine by the coarse 
r3 <- mask(r1,r2)
# and return a frequency table of the finer resolution
freq(r3,useNA="no")

But this seems a little round the houses.

ISSUE 1: Is there a function to zonal count in R with differing resolution rasters?

ISSUE 2: I up-scaled the above method to 2 very large rasters but got the error "Error: Failure during raster IO", why so? ## FIXED: issue with PC, not R ##

ISSUE 3: what if I change each cell in the coarser resolution to have an ID instead of a value and I want to count the frequency of values in the finer res raster per ID?

(have also tried changing coarse res raster to binary 1/NA and multiplying but also get the same error as Issue 2 - im using a powerful computer that has worked with bigger data in big stacks, so the issue is not that)

thanks.

R: count raster values using another raster as mask

I would like to count the frequency of values in one raster, using another raster (different resolution) as the zonal condition.

The premise is that the coarser resolution raster represents the area that I would like to count the frequency of the finer resolution raster;

# make 2 rasters of the same extent, different resolutions
ext <- extent(0,1000,0,1000)
r1 <- raster(nrows=1000, ncols=1000,ext)
r1[] <- sample(seq(from = 1, to = 6, by = 1), size = 1000000, replace = TRUE)
r2 <- raster(nrows=10, ncols=10,ext)
r2[] <- sample(seq(from = 0, to = 1, by = 0.05), size = 100, replace = TRUE)
# create areas of interest in coarser raster
r2[r2 < 0.9] <- NA

Now i can't seem to find a function (might be blind) that will tell me what i want to know straight off - i thought zonal{raster} might have but it wont return a count function. So this is my work around:

# disaggregate the coarser raster to the same res as the finer raster
r2 <- disaggregate(r2,fact=c(100,100))
# mask the fine by the coarse 
r3 <- mask(r1,r2)
# and return a frequency table of the finer resolution
freq(r3,useNA="no")

But this seems a little round the houses.

ISSUE 1: Is there a function to zonal count in R with differing resolution rasters?

ISSUE 2: I up-scaled the above method to 2 very large rasters but got the error "Error: Failure during raster IO", why so? ## FIXED: issue with PC, not R ##

ISSUE 3: what if I change each cell in the coarser resolution to have an ID instead of a value and I want to count the frequency of values in the finer res raster per ID?

(have also tried changing coarse res raster to binary 1/NA and multiplying but also get the same error as Issue 2 - im using a powerful computer that has worked with bigger data in big stacks, so the issue is not that)

thanks

Counting raster values using another raster as mask in R?

I would like to count the frequency of values in one raster, using another raster (different resolution) as the zonal condition.

The premise is that the coarser resolution raster represents the area that I would like to count the frequency of the finer resolution raster;

# make 2 rasters of the same extent, different resolutions
ext <- extent(0,1000,0,1000)
r1 <- raster(nrows=1000, ncols=1000,ext)
r1[] <- sample(seq(from = 1, to = 6, by = 1), size = 1000000, replace = TRUE)
r2 <- raster(nrows=10, ncols=10,ext)
r2[] <- sample(seq(from = 0, to = 1, by = 0.05), size = 100, replace = TRUE)
# create areas of interest in coarser raster
r2[r2 < 0.9] <- NA

Now i can't seem to find a function (might be blind) that will tell me what i want to know straight off - i thought zonal{raster} might have but it wont return a count function. So this is my work around:

# disaggregate the coarser raster to the same res as the finer raster
r2 <- disaggregate(r2,fact=c(100,100))
# mask the fine by the coarse 
r3 <- mask(r1,r2)
# and return a frequency table of the finer resolution
freq(r3,useNA="no")

But this seems a little round the houses.

ISSUE 1: Is there a function to zonal count in R with differing resolution rasters?

ISSUE 2: I up-scaled the above method to 2 very large rasters but got the error "Error: Failure during raster IO", why so? ## FIXED: issue with PC, not R ##

ISSUE 3: what if I change each cell in the coarser resolution to have an ID instead of a value and I want to count the frequency of values in the finer res raster per ID?

(have also tried changing coarse res raster to binary 1/NA and multiplying but also get the same error as Issue 2 - im using a powerful computer that has worked with bigger data in big stacks, so the issue is not that).

update on issue
Source Link
Sam
  • 1.6k
  • 2
  • 16
  • 37

I would like to count the frequency of values in one raster, using another raster (different resolution) as the zonal condition.

The premise is that the coarser resolution raster represents the area that I would like to count the frequency of the finer resolution raster;

# make 2 rasters of the same extent, different resolutions
ext <- extent(0,1000,0,1000)
r1 <- raster(nrows=1000, ncols=1000,ext)
r1[] <- sample(seq(from = 1, to = 6, by = 1), size = 1000000, replace = TRUE)
r2 <- raster(nrows=10, ncols=10,ext)
r2[] <- sample(seq(from = 0, to = 1, by = 0.05), size = 100, replace = TRUE)
# create areas of interest in coarser raster
r2[r2 < 0.9] <- NA

Now i can't seem to find a function (might be blind) that will tell me what i want to know straight off - i thought zonal{raster} might have but it wont return a count function. So this is my work around:

# disaggregate the coarser raster to the same res as the finer raster
r2 <- disaggregate(r2,fact=c(100,100))
# mask the fine by the coarse 
r3 <- mask(r1,r2)
# and return a frequency table of the finer resolution
freq(r3,useNA="no")

But this seems a little round the houses.

ISSUE 1: Is there a function to zonal count in R with differing resolution rasters?

ISSUE 2: I up-scaled the above method to 2 very large rasters but got the error "Error: Failure during raster IO", why so? ## FIXED: issue with PC, not R ##

ISSUE 3: what if I change each cell in the coarser resolution to have an ID instead of a value and I want to count the frequency of values in the finer res raster per ID?

sadly my code above wont work for the actual problem due to issue 2 :/

(have also tried changing coarse res raster to binary 1/NA and multiplying but also get the same error as Issue 2 - im using a powerful computer that has worked with bigger data in big stacks, so the issue is not that)

thanks

I would like to count the frequency of values in one raster, using another raster (different resolution) as the zonal condition.

The premise is that the coarser resolution raster represents the area that I would like to count the frequency of the finer resolution raster;

# make 2 rasters of the same extent, different resolutions
ext <- extent(0,1000,0,1000)
r1 <- raster(nrows=1000, ncols=1000,ext)
r1[] <- sample(seq(from = 1, to = 6, by = 1), size = 1000000, replace = TRUE)
r2 <- raster(nrows=10, ncols=10,ext)
r2[] <- sample(seq(from = 0, to = 1, by = 0.05), size = 100, replace = TRUE)
# create areas of interest in coarser raster
r2[r2 < 0.9] <- NA

Now i can't seem to find a function (might be blind) that will tell me what i want to know straight off - i thought zonal{raster} might have but it wont return a count function. So this is my work around:

# disaggregate the coarser raster to the same res as the finer raster
r2 <- disaggregate(r2,fact=c(100,100))
# mask the fine by the coarse 
r3 <- mask(r1,r2)
# and return a frequency table of the finer resolution
freq(r3,useNA="no")

But this seems a little round the houses.

ISSUE 1: Is there a function to zonal count in R with differing resolution rasters?

ISSUE 2: I up-scaled the above method to 2 very large rasters but got the error "Error: Failure during raster IO", why so?

ISSUE 3: what if I change each cell in the coarser resolution to have an ID instead of a value and I want to count the frequency of values in the finer res raster per ID?

sadly my code above wont work for the actual problem due to issue 2 :/

(have also tried changing coarse res raster to binary 1/NA and multiplying but also get the same error as Issue 2 - im using a powerful computer that has worked with bigger data in big stacks, so the issue is not that)

thanks

I would like to count the frequency of values in one raster, using another raster (different resolution) as the zonal condition.

The premise is that the coarser resolution raster represents the area that I would like to count the frequency of the finer resolution raster;

# make 2 rasters of the same extent, different resolutions
ext <- extent(0,1000,0,1000)
r1 <- raster(nrows=1000, ncols=1000,ext)
r1[] <- sample(seq(from = 1, to = 6, by = 1), size = 1000000, replace = TRUE)
r2 <- raster(nrows=10, ncols=10,ext)
r2[] <- sample(seq(from = 0, to = 1, by = 0.05), size = 100, replace = TRUE)
# create areas of interest in coarser raster
r2[r2 < 0.9] <- NA

Now i can't seem to find a function (might be blind) that will tell me what i want to know straight off - i thought zonal{raster} might have but it wont return a count function. So this is my work around:

# disaggregate the coarser raster to the same res as the finer raster
r2 <- disaggregate(r2,fact=c(100,100))
# mask the fine by the coarse 
r3 <- mask(r1,r2)
# and return a frequency table of the finer resolution
freq(r3,useNA="no")

But this seems a little round the houses.

ISSUE 1: Is there a function to zonal count in R with differing resolution rasters?

ISSUE 2: I up-scaled the above method to 2 very large rasters but got the error "Error: Failure during raster IO", why so? ## FIXED: issue with PC, not R ##

ISSUE 3: what if I change each cell in the coarser resolution to have an ID instead of a value and I want to count the frequency of values in the finer res raster per ID?

(have also tried changing coarse res raster to binary 1/NA and multiplying but also get the same error as Issue 2 - im using a powerful computer that has worked with bigger data in big stacks, so the issue is not that)

thanks

added 175 characters in body
Source Link
Sam
  • 1.6k
  • 2
  • 16
  • 37

I would like to count the frequency of values in one raster, using another raster (different resolution) as the zonal condition.

The premise is that the coarser resolution raster represents the area that I would like to count the frequency of the finer resolution raster;

# make 2 rasters of the same extent, different resolutions
ext <- extent(0,1000,0,1000)
r1 <- raster(nrows=1000, ncols=1000,ext)
r1[] <- sample(seq(from = 1, to = 6, by = 1), size = 1000000, replace = TRUE)
r2 <- raster(nrows=10, ncols=10,ext)
r2[] <- sample(seq(from = 0, to = 1, by = 0.05), size = 100, replace = TRUE)
# create areas of interest in coarser raster
r2[r2 < 0.9] <- NA

Now i can't seem to find a function (might be blind) that will tell me what i want to know straight off - i thought zonal{raster} might have but it wont return a count function. So this is my work around:

# disaggregate the coarser raster to the same res as the finer raster
r2 <- disaggregate(r2,fact=c(100,100))
# mask the fine by the coarse 
r3 <- mask(r1,r2)
# and return a frequency table of the finer resolution
freq(r3,useNA="no")

But this seems a little round the houses.

ISSUE 1: Is there a function to zonal count in R with differing resolution rasters?

ISSUE 2: I up-scaled the above method to 2 very large rasters but got the error "Error: Failure during raster IO", why so?

ISSUE 3: what if I change each cell in the coarser resolution to have an ID instead of a value and I want to count the frequency of values in the finer res raster per ID?

sadly my code above wont work for the actual problem due to issue 2 :/

(have also tried changing coarse res raster to binary 1/NA and multiplying but also get the same error as Issue 2 - im using a powerful computer that has worked with bigger data in big stacks, so the issue is not that)

thanks

I would like to count the frequency of values in one raster, using another raster (different resolution) as the zonal condition.

The premise is that the coarser resolution raster represents the area that I would like to count the frequency of the finer resolution raster;

# make 2 rasters of the same extent, different resolutions
ext <- extent(0,1000,0,1000)
r1 <- raster(nrows=1000, ncols=1000,ext)
r1[] <- sample(seq(from = 1, to = 6, by = 1), size = 1000000, replace = TRUE)
r2 <- raster(nrows=10, ncols=10,ext)
r2[] <- sample(seq(from = 0, to = 1, by = 0.05), size = 100, replace = TRUE)
# create areas of interest in coarser raster
r2[r2 < 0.9] <- NA

Now i can't seem to find a function (might be blind) that will tell me what i want to know straight off - i thought zonal{raster} might have but it wont return a count function. So this is my work around:

# disaggregate the coarser raster to the same res as the finer raster
r2 <- disaggregate(r2,fact=c(100,100))
# mask the fine by the coarse 
r3 <- mask(r1,r2)
# and return a frequency table of the finer resolution
freq(r3,useNA="no")

But this seems a little round the houses.

ISSUE 1: Is there a function to zonal count in R with differing resolution rasters?

ISSUE 2: I up-scaled the above method to 2 very large rasters but got the error "Error: Failure during raster IO", why so?

sadly my code above wont work for the actual problem due to issue 2 :/

(have also tried changing coarse res raster to binary 1/NA and multiplying but also get the same error as Issue 2 - im using a powerful computer that has worked with bigger data in big stacks, so the issue is not that)

thanks

I would like to count the frequency of values in one raster, using another raster (different resolution) as the zonal condition.

The premise is that the coarser resolution raster represents the area that I would like to count the frequency of the finer resolution raster;

# make 2 rasters of the same extent, different resolutions
ext <- extent(0,1000,0,1000)
r1 <- raster(nrows=1000, ncols=1000,ext)
r1[] <- sample(seq(from = 1, to = 6, by = 1), size = 1000000, replace = TRUE)
r2 <- raster(nrows=10, ncols=10,ext)
r2[] <- sample(seq(from = 0, to = 1, by = 0.05), size = 100, replace = TRUE)
# create areas of interest in coarser raster
r2[r2 < 0.9] <- NA

Now i can't seem to find a function (might be blind) that will tell me what i want to know straight off - i thought zonal{raster} might have but it wont return a count function. So this is my work around:

# disaggregate the coarser raster to the same res as the finer raster
r2 <- disaggregate(r2,fact=c(100,100))
# mask the fine by the coarse 
r3 <- mask(r1,r2)
# and return a frequency table of the finer resolution
freq(r3,useNA="no")

But this seems a little round the houses.

ISSUE 1: Is there a function to zonal count in R with differing resolution rasters?

ISSUE 2: I up-scaled the above method to 2 very large rasters but got the error "Error: Failure during raster IO", why so?

ISSUE 3: what if I change each cell in the coarser resolution to have an ID instead of a value and I want to count the frequency of values in the finer res raster per ID?

sadly my code above wont work for the actual problem due to issue 2 :/

(have also tried changing coarse res raster to binary 1/NA and multiplying but also get the same error as Issue 2 - im using a powerful computer that has worked with bigger data in big stacks, so the issue is not that)

thanks

Source Link
Sam
  • 1.6k
  • 2
  • 16
  • 37
Loading