Question

I opened a netCDF file in R and looked at the header information. Afterwards I used gdalinfo to look at the header information of the same file.

What I found is that there are much-much more information shown by the gdalinfo (time origin , units , etc.). Is there a command to grasp more information of a variable in netCDF file with R?

             f=open.ncdf("C:\\BR_Ban.nc")

              > f
            [1] "file C:\\GF_Guy_6Y.nc has 4 dimensions:"
              [1] "x   Size: 1"
              [1] "y   Size: 1"
              [1] "land   Size: 1"
           [1] "tstep   Size: 105120"
       [1] "double nav_lon[x,y]  Longname:Longitude Missval:1e+30"
       [1] "double nav_lat[x,y]  Longname:Latitude Missval:1e+30"
       [1] "float time[tstep]  Longname:Time axis Missval:1e+30"
     [1] "float timestp[tstep]  Longname:Time step axis Missval:1e+30"

Then read one variable

           A = get.var.ncdf(nc=f,varid="time",verbose=TRUE)
     [1] "vobjtodimname: is a character type varid.  This file has 6 dims"
    [1] "vobjtodimname: no cases found, returning FALSE"
     [1] "get.var.ncdf: isdimvar: FALSE"
      [1] "vobjtovarid: entering with varid=date"
     [1] "Variable named date found in file with varid= 7"
     [1] "vobjtovarid: returning with varid deduced from name; varid= 7"
    [1] "get.var.ncdf: ending up using varid= 7"
     [1] "ndims: 2"
  [1] "get.var.ncdf: varsize:"
    [1]     3 52560
     [1] "get.var.ncdf: start:"
     [1] 1 1
      [1] "get.var.ncdf: count:"
    [1]     3 52560
     [1] "get.var.ncdf: totvarsize: 157680"
     [1] "Getting var of type 3  (1=short, 2=int, 3=float, 4=double, 5=char, 6=byte)"
    [1] "get.var.ncdf: C call returned 0"
    [1] "count.nodegen: 3    Length of data: 157680"     "count.nodegen: 52560    Length of data: 157680"
     [1] "get.var.ncdf: final dims of returned array:"
        [1]     3 52560

Answer 1

In short, because gdalinfo is a program for displaying information about a particular type of data sets, while R is a language designed to analyze all kinds of data sets. If R spammed me with such information every time I import a data set, I would quickly go nuts.

Of course, this information can be accessed in R, you just need to ask for it.

class( f )
dim( f )
summary( f )
plot( f )