This code ingests binary GIMMS FAPAR and LAI data and converts them to GeoTIFFs. The data was produced by the Climate and Vegetation Research Group of Boston University. The GIMMS data are available from: http://cliveg.bu.edu/modismisr/lai3g-fpar3g.html

GIMMS3g_LAI_FPAR_Binary2Geotiff.r

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# This code ingests binary GIMMS FAPAR and LAI data and converts them to GeoTIFFs. 
# The data was produced by the Climate and Vegetation Research Group of Boston University. 
# The GIMMS data are available from: http://cliveg.bu.edu/modismisr/lai3g-fpar3g.html

# title         : GIMMS3g_LAI_FPAR_Binary2Geotiff.r
# purpose       : Converts binary GIMMS FAPAR/LAI to GeoTIFFs
# author        : Abdulhakim Abdi (@HakimAbdi)
# input         : Binary 8-bit unsigned integer with ieee-be byte order
# output        : Georeferenced TIFF, ArcGIS-ready files

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# install the necessary packages if you don't already have them
install.packages(c("rgdal" "sp", "raster"), repos='http://cran.r-project.org')

# load required libraries and set working directory
library(sp, rgdal, raster)

# specify temporal parameters
year = 1982:2011
month = list("01","02","03","04","05","06","07","08","09","10","11","12")
month.name = list("jan", "feb","mar","apr","may","jun","jul","aug",
              "sep","oct","nov","dec")

# set to loop through years and months within each year
for (i in 1:length(1982:2011)){
  year
  for (j in 1:12){
    month
    
    ### process "a"-lettered files
        letter = 'a'
    
    # set name format and read binary file
    file.name = paste("J:/GIMMS/avhrrbulai_v01/AVHRRBUVI01.",year[i],
                      month.name[j], letter, '.abl', sep="")
    binread = readBin(con=file.name, what="integer", n=9331200, size=1, signed=F, endian="little")
    
    # covert binary object into a matrix using specifications from the metadata
    mtrx = matrix(binread, nrow=2160, ncol=4320, byrow=F)
    
    # convert to matrix to a raster object
    rstr = raster(mtrx)

    # specify extent and projection
    extent(rstr) <- extent(c(-180, 180, -90, 90))
    projection(rstr) <- "+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs"
    
    # set NA values (according to the metadata n=250 is a NULL value)
    rstr[rstr == 250] <-- NA

    # multiplication by 0.1 for LAI and 0.01 for FAPAR sets the actual value
    rstr = rstr*0.1
    rstr.name = paste("LAI", "_", year[i], "_", month[j], "_", letter, sep="")
    
    # write to file
    writeRaster(rstr, filename=paste("J:/GIMMS/avhrrbulai_v01_Gtiffs_TEST/",rstr.name,".tif", sep=""), 
	format="GTiff", overwrite=TRUE)

    # free memory
    rm(letter,file.name,mtrx,rstr,rstr.name)
    
    ### process "b"-lettered files
        letter = 'b'
    
    # set name format and read binary file
    file.name = paste("J:/GIMMS/avhrrbulai_v01/AVHRRBUVI01.",year[i],
                      month.name[j], letter, '.abl', sep="")
    
    binread = readBin(con=file.name, what="integer", n=9331200, size=1, signed=F, endian="little")
    
    # covert binary object into a matrix using specifications from the metadata
    mtrx = matrix(binread, nrow=2160, ncol=4320, byrow=F)

    # convert to matrix to a raster object
    rstr = raster(mtrx)

    # specify extent and projection
    extent(rstr) <- extent(c(-180, 180, -90, 90))
    projection(rstr) <- "+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs"
    
    # set NA values (according to the metadata n=250 is a NULL value)
    rstr[rstr == 250] <-- NA
    
    # multiplication by 0.1 for LAI and 0.01 for FAPAR sets the actual value
    rstr = rstr*0.1
    rstr.name = paste("LAI", "_", year[i], "_", month[j], "_", letter, sep="")
    
    # write to file
    writeRaster(rstr, filename=paste("J:/GIMMS/avhrrbulai_v01_Gtiffs_TEST/",rstr.name,".tif", sep=""), 
	format="GTiff", overwrite=TRUE)

    # free memory
    rm(letter,file.name,mtrx,rstr,rstr.name)
    
  }
}

# clear memory
rm(list=ls())

# End of script