Revision f27d277d
Added by Adam Wilson over 11 years ago
| climate/procedures/MOD35_L2_process.r | ||
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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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date="20000410"
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tile="h11v08" |
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platform="pleiades" |
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verbose=T |
| ... | ... | |
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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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setwd("~/acrobates/adamw/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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datadir="~/acrobates/adamw/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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db="~/acrobates/adamw/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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td=raster(paste("~/acrobates/adamw/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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|
| ... | ... | |
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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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finalvars=c("PClear")
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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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fs=dbGetQuery(con,paste("SELECT * from swath_geo6
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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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## 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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if(platform=="pleiades") {
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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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system("g.region rast=modisgrid save=roi --overwrite",ignore.stdout=F,ignore.stderr=F)
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} |
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if(platform=="litoria"){
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execGRASS("r.in.gdal",input=paste("NETCDF:\"/home/adamw/acrobates/adamw/projects/interp/data/modis/mod06/summary/MOD06_",tile,".nc\":CER",sep=""),
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output="modisgrid",flags=c("overwrite","o"))
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system("g.region rast=modisgrid.1 save=roi --overwrite",ignore.stdout=F,ignore.stderr=F)
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} |
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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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## 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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## QA ## extract first bit to keep only "useful" values of cloud mask |
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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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## extract first two bits of cloud mask |
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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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QA_useful_",i," = if((QA_",i," / 2^0) % 2==1,1,0) |
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CM_cloud_",i," = if((CM1_",i," / 2^0) % 2==1,(CM1_",i," / 2^1) % 2^2,-9999) |
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Pclear1_",i," = if(CM_cloud_",i,"==0,0,if(CM_cloud_",i,"==1,66,if(CM_cloud_",i,"==2,95,if(CM_cloud_",i,"==3,99,-9999)))) |
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Pclear_",i," = if(QA_useful_",i,"==1,Pclear1_",i,",-9999) |
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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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execGRASS("r.null",map=paste("Pclear_",i,sep=""),setnull="-9999")
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execGRASS("r.null",map=paste("CM_cloud_",i,sep=""),setnull="-9999")
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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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Pclear_daily=int((min(",paste("if(isnull(Pclear_",1:nfs,"),9999,Pclear_",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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# CLD_daily=int((min(",paste("if(isnull(CM_cloud_",1:nfs,"),9999,CM_cloud_",1:nfs,")",sep="",collapse=","),")))
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## reset null values |
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#execGRASS("r.null",map="CLD_daily",setnull="9999")
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execGRASS("r.null",map="Pclear_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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execGRASS("i.group",group="mod35",input=c("Pclear_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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execGRASS("r.out.gdal",input="mod35",output=ncfile,type="Byte",nodata=255,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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| ... | ... | |
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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,"ncrename -v Band1,PClear ",ncfile,sep="")) |
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system(paste(ncopath,"ncatted -a scale_factor,PClear,o,d,1 -a units,PClear,o,c,\"Probability (%)\" -a missing_value,PClear,o,d,255 -a long_name,PClear,o,c,\"Probability of Clear Sky\" ",ncfile,sep="")) |
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# system(paste(ncopath,"ncatted -a sourcecode,global,o,c,",script," ",ncfile,sep="")) |
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| ... | ... | |
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"################################################################")) |
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## delete old files |
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system("cleartemp")
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#system("cleartemp")
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## quit |
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q("no",status=0)
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Also available in: Unified diff
Simplified MOD35 script and converted output to single band p(Clear) rather than multiple bands