Reversing a “combine” function on a raster

Question

I have a raster that I think was "combined" using an arcmap function. I am wondering if there is a way to extract just one raster layer from the combined dataset in order to use it separately, either in R or Arcmap.

If you want to see the data it is available here

It takes this form in R:

class       : RasterLayer 

dimensions  : 10995, 10349, 113787255  (nrow, ncol, ncell)

resolution  : 100, 100  (x, y)

extent      : -446880, 588020, -612570, 486930  (xmin, xmax, ymin, ymax)

coord. ref. : +proj=aea +lat_1=34 +lat_2=40.5 +lat_0=0 +lon_0=-120 +x_0=0 +y_0=-4000000 +datum=NAD27 +units=m +no_defs +ellps=clrk66 +nadgrids=@conus,@alaska,@ntv2_0.gsb,@ntv1_can.dat 

data source : G:\Faculty\Mann\Share\Fire\FRAP_FireThreat\FireThreat.tif 

names       : FireThreat 

values      : 0, 255  (min, max)

attributes
     fields : ID Rowid   COUNT FUEL_RANK FROTCLASS URBAN THREAT THREAT2PEOPLE
        min :  1     0       1        -1         0     0     -1            -1
        max : 97    96 5360409         3         3     1      4           424

Answer 1

The data slot in sp DataFrame objects can be accessed by simply using @ and a standard column index $ or [,"ColName"]. You do not need to define names in the reclass matrix, it just needs to be three columns (from value, to value, new value) Your code can be consolidated to:

reclass <- matrix(c(fire_threat@data$ID, fire_threat@data$ID, 
                    fire_threat@data$THREAT), ncol=3)
THREAT <- reclassify(fire_threat, reclass)

If you do not need to be memory safe (i.e., plenty of RAM to hold the raster in memory) it would be more efficent to read your raster directly to a sp SpatialGridDataFrame object using readGDAL in the rgdal package. Using the raster package is introducing coercion, which is adding unnecessary overhead. Then, you would not need to reclassify the raster. You could just use writeGDAL and specify the "THREAT" column as the value attribute that is assigned to the output.

Answer 2

I figured it out in R. Used attribute data as a lookup table where ID was the current cell value (and unique lookup for THREAT class)

    >fire_threat = raster('G:\\Fire\\FRAP_FireThreat\\FireThreat.tif')

    > fire_threat

class       : RasterLayer 
dimensions  : 10995, 10349, 113787255  (nrow, ncol, ncell)
resolution  : 100, 100  (x, y)
extent      : -446880, 588020, -612570, 486930  (xmin, xmax, ymin, ymax)
coord. ref. : +proj=aea +lat_1=34 +lat_2=40.5 +lat_0=0 +lon_0=-120 +x_0=0 +y_0=-4000000 +datum=NAD27 +units=m +no_defs +ellps=clrk66 +nadgrids=@conus,@alaska,@ntv2_0.gsb,@ntv1_can.dat 
data source : G:\Faculty\Mann\Share\Fire\FRAP_FireThreat\FireThreat.tif 
names       : FireThreat 
values      : 0, 255  (min, max)
attributes
     fields : ID Rowid   COUNT FUEL_RANK FROTCLASS URBAN THREAT THREAT2PEOPLE
        min :  1     0       1        -1         0     0     -1            -1
        max : 97    96 5360409         3         3     1      4           424


    > lookup = data.frame(slot(fire_threat, "data")@attributes)  # ID is raster value, look up corresponding THREAT
    > head(lookup)

  ID Rowid   COUNT FUEL_RANK FROTCLASS URBAN THREAT THREAT2PEOPLE
1  1     0  740186         1         0     0      1           324
2  2     1  993424        -1         0     0     -1           324
3  3     2 3371876         1         1     0      1           324
4  4     3 2641845         3         1     0      3           324
5  5     4 1060206         3         2     0      3           324
6  6     5  406150         2         0     0      2           324

    > rclass = lookup[,c('ID','THREAT')]
    > head(rclass)

  ID THREAT
1  1      1
2  2     -1
3  3      1
4  4      3
5  5      3
6  6      2

    > names(rclass)=c('is','becomes')
    > head(rclass)



     is becomes
    1  1       1
    2  2      -1
    3  3       1
    4  4       3
    5  5       3
    6  6       2

    >    THREAT = reclassify(fire_threat,rclass)
    > THREAT

class       : RasterLayer 
dimensions  : 10995, 10349, 113787255  (nrow, ncol, ncell)
resolution  : 100, 100  (x, y)
extent      : -446880, 588020, -612570, 486930  (xmin, xmax, ymin, ymax)
coord. ref. : +proj=aea +lat_1=34 +lat_2=40.5 +lat_0=0 +lon_0=-120 +x_0=0 +y_0=-4000000 +datum=NAD27 +units=m +no_defs +ellps=clrk66 +nadgrids=@conus,@alaska,@ntv2_0.gsb,@ntv1_can.dat 
data source : G:\Faculty\Mann\Share\Fire\FRAP_FireThreat\THREAT.tif 
names       : THREAT 
values      : -1, 4  (min, max)