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###################################################################################
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###  R code to aquire and process MOD35_L2 cloud data from the MODIS platform
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# Redirect all warnings to stderr()
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#options(warn = -1)
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#write("2) write() to stderr", stderr())
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#write("2) write() to stdout", stdout())
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#warning("2) warning()")
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## import commandline arguments
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library(getopt)
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## load libraries
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require(reshape)
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require(geosphere)
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require(raster)
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require(rgdal)
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require(spgrass6)
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require(RSQLite)
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## get options
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opta <- getopt(matrix(c(
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                        'date', 'd', 1, 'character',
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                        'tile', 't', 1, 'character',
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                        'verbose','v',1,'logical',
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                        'help', 'h', 0, 'logical'
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                        ), ncol=4, byrow=TRUE))
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if ( !is.null(opta$help) )
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  {
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       prg <- commandArgs()[1];
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          cat(paste("Usage: ", prg,  " --date | -d <file> :: The date to process\n", sep=""));
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          q(status=1);
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     }
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## default date and tile to play with  (will be overwritten below when running in batch)
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date="20010410"
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tile="h11v08"
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platform="pleiades" 
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verbose=T
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## now update using options if given
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date=opta$date  
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tile=opta$tile 
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verbose=opta$verbose  #print out extensive information for debugging?
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outdir=paste("daily/",tile,"/",sep="")  #directory for separate daily files
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## get year and doy from date
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year=format(as.Date(date,"%Y%m%d"),"%Y")
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doy=format(as.Date(date,"%Y%m%d"),"%j")
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if(platform=="pleiades"){
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  ## location of MOD06 files
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  datadir=paste("/nobackupp4/datapool/modis/MOD06_L2.005/",year,"/",doy,"/",sep="")
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  ## path to some executables
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  ncopath="/nasa/sles11/nco/4.0.8/gcc/mpt/bin/"
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  swtifpath="/nobackupp1/awilso10/software/heg/bin/swtif"
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  ## path to swath database
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  db="/nobackupp4/pvotava/DB/export/swath_geo.sql.sqlite3.db"
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  ## specify working directory
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  setwd("/nobackupp1/awilso10/mod06")
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  gisBase="/u/armichae/pr/grass-6.4.2/"
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  ## path to MOD11A1 file for this tile to align grid/extent
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  gridfile=list.files("/nobackupp4/datapool/modis/MOD11A1.005/2006.01.27",pattern=paste(tile,".*[.]hdf$",sep=""),recursive=T,full=T)[1]
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  td=readGDAL(paste("HDF4_EOS:EOS_GRID:\"",gridfile,"\":MODIS_Grid_Daily_1km_LST:Night_view_angl",sep=""))
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  projection(td)="+proj=sinu +lon_0=0 +x_0=0 +y_0=0 +a=6371007.181 +b=6371007.181 +units=m +no_defs +datum=WGS84 +ellps=WGS84 "
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}
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if(platform=="litoria"){  #if running on local server, use different paths
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  ## specify working directory
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  setwd("~/acrobates/projects/interp")
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  gisBase="/usr/lib/grass64"
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   ## location of MOD06 files
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  datadir="~/acrobates/projects/interp/data/modis/mod35"
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  ## path to some executables
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  ncopath=""
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  swtifpath="sudo MRTDATADIR=\"/usr/local/heg/data\" PGSHOME=/usr/local/heg/TOOLKIT_MTD PWD=/home/adamw /usr/local/heg/bin/swtif"
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  ## path to swath database
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  db="/home/adamw/acrobates/projects/interp/data/modis/mod06/swath_geo.sql.sqlite3.db"
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  ## get grid file
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  td=raster(paste("~/acrobates/projects/interp/data/modis/mod06/summary/MOD06_",tile,".nc",sep=""),varname="CER")
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  projection(td)="+proj=sinu +lon_0=0 +x_0=0 +y_0=0 +a=6371007.181 +b=6371007.181 +units=m +no_defs +datum=WGS84 +ellps=WGS84 "
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}
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### print some status messages
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if(verbose) print(paste("Processing tile",tile," for date",date))
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## load tile information and get bounding box
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load(file="modlandTiles.Rdata")
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tile_bb=tb[tb$tile==tile,] ## identify tile of interest
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upleft=paste(tile_bb$lat_max,tile_bb$lon_min) #northwest corner
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lowright=paste(tile_bb$lat_min,tile_bb$lon_max) #southeast corner
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## vars to process
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vars=as.data.frame(matrix(c(
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  "Cloud_Mask",              "CM",
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  "Quality_Assurance",       "QA"),
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  byrow=T,ncol=2,dimnames=list(1:2,c("variable","varid"))),stringsAsFactors=F)
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## vector of variables expected to be in final netcdf file.  If these are not present, the file will be deleted at the end.
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finalvars=c("CLD","CLD2")
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#####################################################
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##find swaths in region from sqlite database for the specified date/tile
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if(verbose) print("Accessing swath ID's from database")
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con=dbConnect("SQLite", dbname = db)
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fs=dbGetQuery(con,paste("SELECT * from swath_geo
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            WHERE east>=",tile_bb$lon_min," AND
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                  west<=",tile_bb$lon_max," AND
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                  north>=",tile_bb$lat_min," AND
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                  south<=",tile_bb$lat_max," AND
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                  year==",format(as.Date(date,"%Y%m%d"),"%Y")," AND
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                  day==",as.numeric(format(as.Date(date,"%Y%m%d"),"%j"))
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  ))
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con=dbDisconnect(con)
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fs$id=substr(fs$id,7,19)
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## find the swaths on disk (using datadir)
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swaths=list.files(datadir,pattern=paste(fs$id,collapse="|"),recursive=T,full=T)
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if(verbose) print(paste(nrow(fs)," swath IDs recieved from database and ",length(swaths)," found on disk"))
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############################################################################
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############################################################################
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### Use the HEG tool to grid all available swath data for this date-tile
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for(file in swaths){
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  ## Function to generate hegtool parameter file for multi-band HDF-EOS file
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  print(paste("Starting file",basename(file)))
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  outfile=paste(tempdir(),"/",basename(file),sep="")
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  ## First write the parameter file (careful, heg is very finicky!)
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  hdr=paste("NUM_RUNS = ",length(vars$varid),"|MULTI_BAND_HDFEOS:",length(vars$varid),sep="")
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  grp=paste("
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BEGIN
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INPUT_FILENAME=",file,"
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OBJECT_NAME=mod35
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FIELD_NAME=",vars$variable,"|
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BAND_NUMBER = 1
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OUTPUT_PIXEL_SIZE_X=1000
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OUTPUT_PIXEL_SIZE_Y=1000
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SPATIAL_SUBSET_UL_CORNER = ( ",upleft," )
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SPATIAL_SUBSET_LR_CORNER = ( ",lowright," )
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#RESAMPLING_TYPE =",ifelse(grepl("Flag|Mask|Quality",vars),"NN","CUBIC"),"
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RESAMPLING_TYPE =NN
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OUTPUT_PROJECTION_TYPE = SIN
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OUTPUT_PROJECTION_PARAMETERS = ( 6371007.181 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 )
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# projection parameters from http://landweb.nascom.nasa.gov/cgi-bin/QA_WWW/newPage.cgi?fileName=sn_gctp
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ELLIPSOID_CODE = WGS84
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OUTPUT_TYPE = HDFEOS
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OUTPUT_FILENAME = ",outfile,"
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END
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",sep="")
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  ## if any remnants from previous runs remain, delete them
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  if(length(list.files(tempdir(),pattern=basename(file)))>0)
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    file.remove(list.files(tempdir(),pattern=basename(file),full=T))
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  ## write it to a file
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  cat(c(hdr,grp)    , file=paste(tempdir(),"/",basename(file),"_MODparms.txt",sep=""))
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  ## now run the swath2grid tool
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  ## write the gridded file
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  log=system(paste("(",swtifpath," -p ",tempdir(),"/",basename(file),"_MODparms.txt -d ; echo $$)",sep=""),intern=T,ignore.stderr=T)
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  ## clean up temporary files in working directory
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#  file.remove(list.files(pattern=
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#              paste("filetable.temp_",
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#              as.numeric(log[length(log)]):(as.numeric(log[length(log)])+3),sep="",collapse="|")))  #Look for files with PID within 3 of parent process
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  if(verbose) print(log)
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  print(paste("Finished gridding ", file))
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}  #end looping over swaths
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########################
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## confirm at least one file for this date is present.  If not, quit.
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outfiles=paste(tempdir(),"/",basename(swaths),sep="")
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if(!any(file.exists(outfiles))) {
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  print(paste("########################################   No gridded files for region exist for tile",tile," on date",date))
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  q("no",status=0)
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}
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#####################################################
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## Process the gridded files to align exactly with MODLAND tile and produce a daily summary of multiple swaths
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## Identify output file
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  ncfile=paste(outdir,"/MOD06_",tile,"_",date,".nc",sep="")  #this is the 'final' daily output file
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## function to convert binary to decimal to assist in identifying correct values
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## this is helpful when defining QA handling below, but isn't used in processing
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## b2d=function(x) sum(x * 2^(rev(seq_along(x)) - 1)) #http://tolstoy.newcastle.edu.au/R/e2/help/07/02/10596.html
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## for example:
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## b2d(c(T,T))
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  ## set Grass to overwrite
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  Sys.setenv(GRASS_OVERWRITE=1)
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  Sys.setenv(DEBUG=1)
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  Sys.setenv(GRASS_GUI="txt")
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### Extract various SDSs from a single gridded HDF file and use QA data to throw out 'bad' observations
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## make temporary working directory
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  tf=paste(tempdir(),"/grass", Sys.getpid(),"/", sep="")  #temporar
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  if(!file.exists(tf)) dir.create(tf)
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  ## create output directory if needed
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  if(!file.exists(dirname(ncfile))) dir.create(dirname(ncfile),recursive=T)
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  ## set up temporary grass instance for this PID
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  if(verbose) print(paste("Set up temporary grass session in",tf))
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  initGRASS(gisBase=gisBase,gisDbase=tf,SG=as(td,"SpatialGridDataFrame"),override=T,location="mod06",mapset="PERMANENT",home=tf,pid=Sys.getpid())
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  system(paste("g.proj -c proj4=\"",projection(td),"\"",sep=""),ignore.stdout=T,ignore.stderr=T)
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  ## Define region by importing one MOD11A1 raster.
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  print("Import one MOD11A1 raster to define grid")
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  if(platform=="pleiades") execGRASS("r.in.gdal",input=paste("HDF4_EOS:EOS_GRID:\"",gridfile,"\":MODIS_Grid_Daily_1km_LST:Night_view_angl",sep=""),
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            output="modisgrid",flags=c("quiet","overwrite","o"))
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   if(platform=="litoria")
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  execGRASS("r.in.gdal",input=paste("NETCDF:\"/home/adamw/acrobates/projects/interp/data/modis/mod06/summary/MOD06_",tile,".nc\":CER",sep=""),output="modisgrid",flags=c("overwrite","o"))
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system("g.region rast=modisgrid save=roi --overwrite",ignore.stdout=F,ignore.stderr=F)
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system("g.region rast=modisgrid.1 save=roi --overwrite",ignore.stdout=F,ignore.stderr=F)
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## Identify which files to process
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tfs=basename(swaths)
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## drop swaths that did not produce an output file (typically due to not overlapping the ROI)
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tfs=tfs[tfs%in%list.files(tempdir())]
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#tfs=list.files(tempdir(),pattern="temp.*hdf")
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nfs=length(tfs)
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if(verbose) print(paste(nfs,"swaths available for processing"))
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## loop through scenes and process QA flags
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  for(i in 1:nfs){
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     file=paste(tempdir(),"/",tfs[i],sep="")
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     ## Cloud Mask
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     execGRASS("r.in.gdal",input=paste("HDF4_EOS:EOS_GRID:\"",file,"\":mod35:Cloud_Mask_0",sep=""),
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              output=paste("CM1_",i,sep=""),flags=c("overwrite","o")) ; print("")
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    ## extract cloudy and 'probably/confidently clear' pixels
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    system(paste("r.mapcalc <<EOF
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                CM_cloud_",i," =  ((CM1_",i," / 2^0) % 2) == 1  &&  ((CM1_",i," / 2^1) % 2^2) == 0 
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                CM_clear_",i," =  ((CM1_",i," / 2^0) % 2) == 1  &&  ((CM1_",i," / 2^1) % 2^2) >=  2 
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                CM_path_",i," =   ((CM1_",i," / 2^6) % 2^2) 
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                CM_cloud2_",i," = ((CM1_",i," / 2^1) % 2^2) 
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EOF",sep=""))
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    ## QA
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     execGRASS("r.in.gdal",input=paste("HDF4_EOS:EOS_GRID:\"",file,"\":mod35:Quality_Assurance_0",sep=""),
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             output=paste("QA_",i,sep=""),flags=c("overwrite","o")) ; print("")
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   ## QA_CER
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#   system(paste("r.mapcalc <<EOF
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#                 QA_COT_",i,"=   ((QA_",i," / 2^0) % 2^1 )==1
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#                 QA_COT2_",i,"=  ((QA_",i," / 2^1) % 2^2 )>=2
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#                 QA_COT3_",i,"=  ((QA_",i," / 2^3) % 2^2 )==0
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#                 QA_CER_",i,"=   ((QA_",i," / 2^5) % 2^1 )==1
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#                 QA_CER2_",i,"=  ((QA_",i," / 2^6) % 2^2 )>=2
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#EOF",sep="")) 
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#                 QA_CWP_",i,"=   ((QA_",i," / 2^8) % 2^1 )==1
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#                 QA_CWP2_",i,"=  ((QA_",i," / 2^9) % 2^2 )==3
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 } #end loop through sub daily files
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#### Now generate daily averages (or maximum in case of cloud flag)
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  system(paste("r.mapcalc <<EOF
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         CLD_daily=int((max(",paste("if(isnull(CM_cloud_",1:nfs,"),-9999,CM_cloud_",1:nfs,")",sep="",collapse=","),"))) 
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         CLD2_daily=int((min(",paste("if(isnull(CM_cloud2_",1:nfs,"),-9999,CM_cloud2_",1:nfs,")",sep="",collapse=","),"))) 
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EOF",sep=""))
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execGRASS("r.null",map="CLD_daily",setnull="-9999")
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execGRASS("r.null",map="CLD2_daily",setnull="-9999")
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  ### Write the files to a netcdf file
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  ## create image group to facilitate export as multiband netcdf
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    execGRASS("i.group",group="mod06",input=c("CLD_daily","CLD2_daily")) ; print("")
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  if(file.exists(ncfile)) file.remove(ncfile)  #if it exists already, delete it
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  execGRASS("r.out.gdal",input="mod06",output=ncfile,type="Int16",nodata=-32768,flags=c("quiet"),
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#      createopt=c("FORMAT=NC4","ZLEVEL=5","COMPRESS=DEFLATE","WRITE_GDAL_TAGS=YES","WRITE_LONLAT=NO"),format="netCDF")  #for compressed netcdf
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      createopt=c("FORMAT=NC","WRITE_GDAL_TAGS=YES","WRITE_LONLAT=NO"),format="netCDF")
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  system(paste(ncopath,"ncecat -O -u time ",ncfile," ",ncfile,sep=""))
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## create temporary nc file with time information to append to MOD06 data
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  cat(paste("
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    netcdf time {
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      dimensions:
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        time = 1 ;
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      variables:
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        int time(time) ;
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      time:units = \"days since 2000-01-01 00:00:00\" ;
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      time:calendar = \"gregorian\";
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      time:long_name = \"time of observation\"; 
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    data:
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      time=",as.integer(as.Date(date,"%Y%m%d")-as.Date("2000-01-01")),";
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    }"),file=paste(tempdir(),"/time.cdl",sep=""))
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system(paste("ncgen -o ",tempdir(),"/time.nc ",tempdir(),"/time.cdl",sep=""))
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system(paste(ncopath,"ncks -A ",tempdir(),"/time.nc ",ncfile,sep=""))
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## add other attributes
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  system(paste(ncopath,"ncrename -v Band1,CLD -v Band2,CLD2 ",ncfile,sep=""))
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  system(paste(ncopath,"ncatted -a scale_factor,CLD,o,d,1 -a units,CLD,o,c,\"none\" -a missing_value,CLD,o,d,-32768 -a long_name,CLD,o,c,\"Cloud Mask\" ",ncfile,sep=""))
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system(paste(ncopath,"ncatted -a scale_factor,CLD2,o,d,1 -a units,CLD2,o,c,\"none\" -a missing_value,CLD2,o,d,-32768 -a long_name,CLD2,o,c,\"Cloud Mask Flag\" ",ncfile,sep=""))
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                                        #  system(paste(ncopath,"ncatted -a sourcecode,global,o,c,",script," ",ncfile,sep=""))
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### delete the temporary files 
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  unlink_.gislock()
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  system(paste("rm -frR ",tf,sep=""))
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## Confirm that the file has the correct attributes, otherwise delete it
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ntime=as.numeric(system(paste("cdo -s ntime ",ncfile),intern=T))
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## confirm it has all 'final variables as specified above"
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fvar=all(finalvars%in%strsplit(system(paste("cdo -s showvar ",ncfile),intern=T)," ")[[1]])
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  if(ntime!=1|!fvar) {
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      print(paste("FILE ERROR:  tile ",tile," and date ",date," was not outputted correctly, deleting... "))
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      file.remove(ncfile)
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    }
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  ## print out some info
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print(paste(" ###################################################################               Finished ",date,
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"################################################################"))
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## delete old files
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system("cleartemp")
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## quit
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q("no",status=0)
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