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Reading hdf files in R and converting them to geoTIFF rasters

I try to read MODIS 17 data files in R, manipulate them (cropping, etc.) and then save them as geoTIFF. Data files come in a format .hdfand there seems to be no easy way to read them in R.

Compared to other topics, there aren't many tips here, and most of them are already a few years old. Some of them also advise using additional programs, but I want to use only R.

What packages / files are used by people to work with .hdffiles in R?

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4 answers

, hdf MODIS hdf4, hdf5. , MODIS -, . HDFView, .

R hdf4, (, rgdal) hdf5. rgdal , , MAC Unix, Windows.

gdal_translate gdalUtils - , hdf4 R. hdf4 geoTIFF, R. , , , - , ( MODIS - Reverb), .

:

library(gdalUtils)

# Provides detailed data on hdf4 files but takes ages

gdalinfo("MOD17A3H.A2000001.h21v09.006.2015141183401.hdf")

# Tells me what subdatasets are within my hdf4 MODIS files and makes them into a list

sds <- get_subdatasets("MOD17A3H.A2000001.h21v09.006.2015141183401.hdf")
sds

[1] "HDF4_EOS:EOS_GRID:MOD17A3H.A2000001.h21v09.006.2015141183401.hdf:MOD_Grid_MOD17A3H:Npp_500m"   
[2] "HDF4_EOS:EOS_GRID:MOD17A3H.A2000001.h21v09.006.2015141183401.hdf:MOD_Grid_MOD17A3H:Npp_QC_500m"

# I'm only interested in the first subdataset and I can use gdal_translate to convert it to a .tif

gdal_translate(sds[1], dst_dataset = "NPP2000.tif")

# Load and plot the new .tif

rast <- raster("NPP2000.tif")
plot(rast)

# If you have lots of files then you can make a loop to do all this for you

files <- dir(pattern = ".hdf")
files

 [1] "MOD17A3H.A2000001.h21v09.006.2015141183401.hdf" "MOD17A3H.A2001001.h21v09.006.2015148124025.hdf"
 [3] "MOD17A3H.A2002001.h21v09.006.2015153182349.hdf" "MOD17A3H.A2003001.h21v09.006.2015166203852.hdf"
 [5] "MOD17A3H.A2004001.h21v09.006.2015099031743.hdf" "MOD17A3H.A2005001.h21v09.006.2015113012334.hdf"
 [7] "MOD17A3H.A2006001.h21v09.006.2015125163852.hdf" "MOD17A3H.A2007001.h21v09.006.2015169164508.hdf"
 [9] "MOD17A3H.A2008001.h21v09.006.2015186104744.hdf" "MOD17A3H.A2009001.h21v09.006.2015198113503.hdf"
[11] "MOD17A3H.A2010001.h21v09.006.2015216071137.hdf" "MOD17A3H.A2011001.h21v09.006.2015230092603.hdf"
[13] "MOD17A3H.A2012001.h21v09.006.2015254070417.hdf" "MOD17A3H.A2013001.h21v09.006.2015272075433.hdf"
[15] "MOD17A3H.A2014001.h21v09.006.2015295062210.hdf"

filename <- substr(files,11,14)
filename <- paste0("NPP", filename, ".tif")
filename

[1] "NPP2000.tif" "NPP2001.tif" "NPP2002.tif" "NPP2003.tif" "NPP2004.tif" "NPP2005.tif" "NPP2006.tif" "NPP2007.tif" "NPP2008.tif"
[10] "NPP2009.tif" "NPP2010.tif" "NPP2011.tif" "NPP2012.tif" "NPP2013.tif" "NPP2014.tif"

i <- 1

for (i in 1:15){
  sds <- get_subdatasets(files[i])
  gdal_translate(sds[1], dst_dataset = filename[i])
}

.tif R, , , raster . , QGIS, , , , . Loïc Dutrieux !

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script , 36 , . , . , ArcGIS "Make NetCDF Raster Layer tool", +, C Kelvin, : RasterValue * 0.02 - 273.15. R , , ArcGIS , R .

library(gdalUtils)
library(raster)

setwd("D:/Users/szynisze/Google Drive/Gates Project/Data/Climate/MODIS")

# Get a list of sds names
sds <- get_subdatasets('MOD11C3.A2009001.006.2016006051904.hdf')
# Isolate the name of the first sds
name <- sds[1]
filename <- 'Rasterinr.tif'

gdal_translate(sds[1], dst_dataset = filename)
# Load the Geotiff created into R
r <- raster(filename)

# Identify files to read:
rlist=list.files(getwd(), pattern="hdf$", full.names=FALSE)


# Substract last 5 digits from MODIS filename for use in a new .img filename
substrRight <- function(x, n){
        substr(x, nchar(x)-n+1, nchar(x))
}

filenames0 <- substrRight(rlist,9)
# Suffixes for MODIS files for identyfication:
filenamessuffix <- substr(filenames0,1,5)

listofnewnames <- c("2009.01.MODIS_","2009.02.MODIS_","2009.03.MODIS_","2009.04.MODIS_","2009.05.MODIS_",
                    "2009.06.MODIS_","2009.07.MODIS_","2009.08.MODIS_","2009.09.MODIS_","2009.10.MODIS_",
                    "2009.11.MODIS_","2009.12.MODIS_",
                    "2010.01.MODIS_","2010.02.MODIS_","2010.03.MODIS_","2010.04.MODIS_","2010.05.MODIS_",
                    "2010.06.MODIS_","2010.07.MODIS_","2010.08.MODIS_","2010.09.MODIS_","2010.10.MODIS_",
                    "2010.11.MODIS_","2010.12.MODIS_",
                    "2011.01.MODIS_","2011.02.MODIS_","2011.03.MODIS_","2011.04.MODIS_","2011.05.MODIS_",
                    "2011.06.MODIS_","2011.07.MODIS_","2011.08.MODIS_","2011.09.MODIS_","2011.10.MODIS_",
                    "2011.11.MODIS_","2011.12.MODIS_")

# Final new names for converted files:
newnames <- vector()
for (i in 1:length(listofnewnames)) {
        newnames[i] <- paste0(listofnewnames[i],filenamessuffix[i],".img")
}

# Loop converting files to raster from NetCDF
for (i in 1:length(rlist)) {
        sds <- get_subdatasets(rlist[i])
        gdal_translate(sds[1], dst_dataset = newnames[i])
}
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HEG, NASA hdf geotiff, (, "" ) . hdf.

: https://newsroom.gsfc.nasa.gov/sdptoolkit/HEG/HEGHome.html

Take a look at the NASA products supported here: https://newsroom.gsfc.nasa.gov/sdptoolkit/HEG/HEGProductList.html

Hope this helps.

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The following worked for me. This is a short program and just takes the name of the input folder. Make sure you know what supporting data you want. I was interested in supporting data 1.

library(raster)
library(gdalUtils)

inpath <- "E:/aster200102/ast_200102"

setwd(inpath)

filenames <- list.files(,pattern=".hdf$",full.names = FALSE)

for (filename in filenames)
{
     sds <- get_subdatasets(filename)
     gdal_translate(sds[1], dst_dataset=paste0(substr(filename, 1, nchar(filename)-4) ,".tif"))
}
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