R/tmunpackr.r
In jdbcode/LandsatLinkr: Tools to spectrally link Landsat data
Defines functions
tmunpackr
Documented in
tmunpackr
#' Decompress, stack, and reproject TM/ETM+ SR images
#'
#' Decompress, stack, and reproject TM/ETM+ SR images
#' @param file character. full path name of the surface reflectance file
#' @param proj character. PROJ.4 projection definition.
#' @param overwrite logical. True will overwrite the file if it already exists, False will skip processing if output file exists.
#' @import raster
#' @import gdalUtils
#' @import rgdal
#' @export
tmunpackr = function(file, proj="default", overwrite=F){
# http://earthexplorer.usgs.gov/ Landsat CDR TM and ETM+ images
check = file_check(file,"ledaps.tif",overwrite)
if(check == 0){return(0)}
#set new directories
randomstring = paste(sample(c(0:9, letters, LETTERS), 6, replace=TRUE),collapse="")
tempdir = file.path(dirname(file),randomstring) #temp
dir.create(tempdir, recursive=T, showWarnings=F)
#decompress the image
untar(file, exdir=tempdir, tar="internal") #decompress the file
files = list.files(tempdir, full.names=T)
#are there files in the decompressed archive
if(length(files) == 0){
unlink(tempdir, recursive=T, force=T)
stop(paste('There were no files found in the decompressed archive:', file))
}
#are these sr files
filesBname = basename(files)
srFilesTest = grep("_sr_", filesBname, value=T)
if(length(srFilesTest) == 0){
unlink(tempdir, recursive=T, force=T)
stop(paste('There were no USGS ESPA Surface Reflectance files found in the decompressed archive:', file))
}
#is this collection 1 or pre-collection
name = filesBname[1]
isCollection = substr(filesBname[1], 5,5) == '_'
#get the sr bands
bands = sort(grep("band", files, value=T))
if(isCollection){
#new version: LXSS_LLLL_PPPRRR_YYYYMMDD_yyyymmdd_CX_TX_prod_band.ext
year = substr(name,18,21)
pieces = unlist(strsplit(dirname(file), "/")) #break up the directory and unlist so the pieces can be called by index
len = length(pieces)-1 #get the ending index for "scene"
newpieces = paste(pieces[1:len], collapse = "/") #subset the directory pieces so the last piece is the scene
outdir = file.path(newpieces, "images", year)
dir.create(outdir, recursive=T, showWarnings=F)
# create the mask
pixelqafile = grep("pixel_qa.tif", files, value=T)
pixelqar = getValues(raster(pixelqafile))
#mask = as.numeric(pixelqar == 322 | pixelqar == 386 | pixelqar == 324 | pixelqar == 388 | pixelqar == 836 | pixelqar == 900)
shadow = bitwAnd(pixelqar, 8) == 0 # shadow
snow = bitwAnd(pixelqar, 16) == 0 # snow
clouds = bitwAnd(pixelqar, 32) == 0 # clouds
mask = shadow*snow*clouds
clouds = snow = shadow = pixelqar = 0 #clear memory
# make the basename for final output files
mtlfile = grep("MTL.txt", files, value=T)
tbl = unlist(read.delim(mtlfile, header=F, skipNul=T))
string = as.character(grep("LANDSAT_SCENE_ID = ", tbl, value=T))
pieces = unlist(strsplit(string, " "))
sceneid = pieces[length(pieces)]
outbase = substr(sceneid,1,16)
} else{
#name = 'LC80380292015214LGN00.xml'
outbase = substr(name,1,16) # need to get this from the filename, because pre-collection does not include an mtl file
year = substr(name,10,13)
pieces = unlist(strsplit(dirname(file), "/")) #break up the directory and unlist so the pieces can be called by index
len = length(pieces)-1 #get the ending index for "scene"
newpieces = paste(pieces[1:len], collapse = "/") #subset the directory pieces so the last piece is the scene
outdir = file.path(newpieces, "images", year)
dir.create(outdir, recursive=T, showWarnings=F)
#decompress the image and get/set files names
untar(file, exdir=tempdir, tar="internal") #decompress the file
files = list.files(tempdir, full.names=T)
bands = sort(grep("band", files, value=T))
shadow = grep("cloud_shadow_qa.tif", files, value=T) #0 okay, 255 bad
cloud = grep("sr_cloud_qa.tif", files, value=T) #0 okay, 255 bad
snow = grep("sr_snow_qa.tif", files, value=T) #0 okay, 255 bad
fmask = grep("cfmask.tif", files, value=T) # <= 1 okay background 255
#make a composite cloudmask
s = as.matrix(raster(shadow))
c = as.matrix(raster(cloud))
sn = as.matrix(raster(snow))
f = as.matrix(raster(fmask))
check = s[1,1] # if is.na(check) == T new else old
if(is.na(check) == T){s = is.na(s)} else {s = !is.na(s)}
check = c[1,1] # if is.na(check) == T new else old
if(is.na(check) == T){c = is.na(c)} else {c = !is.na(c)}
check = sn[1,1] # if is.na(check) == T new else old
if(is.na(check) == T){sn = is.na(sn)} else {sn = !is.na(sn)}
f = f <= 1
mask = s*c*f*sn
s=c=sn=f=0
}
#mask = setValues(ref,mask)
#plot(mask)
#writeRaster(mask, "D:/work/proj/llr_dev/collection1/tm/wrs2/032033/test.tif")
# create outfile paths
tempstack = file.path(tempdir,paste(outbase,"_tempstack.tif",sep=""))
tempvrt = sub("tempstack.tif", "tempstack.vrt", tempstack)
tempmask = sub("tempstack", "tempmask", tempstack)
projstack = sub("tempstack", "projstack", tempstack)
projmask = sub("tempstack", "projmask", tempstack)
finalstack = file.path(outdir,paste(outbase,"_ledaps.tif", sep=""))
finalmask = file.path(outdir,paste(outbase,"_cloudmask.tif", sep=""))
tcfile = file.path(outdir,paste(outbase,"_tc.tif", sep=""))
tcafile = file.path(outdir,paste(outbase,"_tca.tif", sep=""))
outprojfile = file.path(outdir,paste(outbase,"_proj.txt", sep=""))
# set a reference raster for setting values and getting projection
ref = raster(bands[1])
origproj = projection(ref)
#stack the image bands and write out
gdalbuildvrt(gdalfile=bands, output.vrt = tempvrt, separate=T) #, tr=c(reso,reso)
gdal_translate(src_dataset=tempvrt, dst_dataset=tempstack, of = "GTiff", co="INTERLEAVE=BAND")
# write the mask out
mask = setValues(ref,mask)
mask = as(mask, "SpatialGridDataFrame") #convert the raster to SGHF so it can be written using GDAL (faster than writing it with the raster package)
writeGDAL(mask, tempmask, drivername = "GTiff", type = "Byte", mvFlag = 255, options="INTERLEAVE=BAND")
mask=0 #clear the memory
#reproject the image #need to add in writing proj file for default
if(proj == "default"){proj = origproj}
write(proj, outprojfile)
gdalwarp(srcfile=tempstack, dstfile=projstack,
s_srs=origproj, t_srs=proj, of="GTiff",
r="bilinear", srcnodata=-9999, dstnodata=-32768, multi=T, #"near"
tr=c(30,30), co="INTERLEAVE=BAND")
#project the mask
gdalwarp(srcfile=tempmask, dstfile=projmask,
s_srs=origproj, t_srs=proj, of="GTiff",
r="mode", srcnodata=255, dstnodata=255, multi=T,
tr=c(30,30), co="INTERLEAVE=BAND")
#trim the na rows and cols
trim_na_rowcol(projstack, finalstack, projmask, finalmask)
#tasseled cap
b1 = as.matrix(raster(finalstack, 1))
b2 = as.matrix(raster(finalstack, 2))
b3 = as.matrix(raster(finalstack, 3))
b4 = as.matrix(raster(finalstack, 4))
b5 = as.matrix(raster(finalstack, 5))
b6 = as.matrix(raster(finalstack, 6))
bcoef = c(0.2043, 0.4158, 0.5524, 0.5741, 0.3124, 0.2303)
gcoef = c(-0.1603, -0.2819, -0.4934, 0.7940, -0.0002, -0.1446)
wcoef = c(0.0315, 0.2021, 0.3102, 0.1594,-0.6806, -0.6109)
bright = (b1*bcoef[1])+(b2*bcoef[2])+(b3*bcoef[3])+(b4*bcoef[4])+(b5*bcoef[5])+(b6*bcoef[6])
green = (b1*gcoef[1])+(b2*gcoef[2])+(b3*gcoef[3])+(b4*gcoef[4])+(b5*gcoef[5])+(b6*gcoef[6])
wet = (b1*wcoef[1])+(b2*wcoef[2])+(b3*wcoef[3])+(b4*wcoef[4])+(b5*wcoef[5])+(b6*wcoef[6])
b1=b2=b3=b4=b5=b6=0
tcb = matrix_to_raster(finalstack,bright)
tcg = matrix_to_raster(finalstack,green)
tcw = matrix_to_raster(finalstack,wet)
wet=0
tca = atan(green/bright) * (180/pi) * 100
bright=green=0
tca = matrix_to_raster(finalstack,tca)
temptcb = file.path(tempdir,paste(outbase,"_temptcb.tif",sep=""))
temptcg = file.path(tempdir,paste(outbase,"_temptcg.tif",sep=""))
temptcw = file.path(tempdir,paste(outbase,"_temptcw.tif",sep=""))
projection(tcb) = set_projection(tcfile)
projection(tcg) = set_projection(tcfile)
projection(tcw) = set_projection(tcfile)
tc = as(tcb, "SpatialGridDataFrame")
tcb=0
writeGDAL(tc, temptcb, drivername = "GTiff", type = "Int16", mvFlag = -32768, options="INTERLEAVE=BAND")
tc = as(tcg, "SpatialGridDataFrame")
tcg=0
writeGDAL(tc, temptcg, drivername = "GTiff", type = "Int16", mvFlag = -32768, options="INTERLEAVE=BAND")
tc = as(tcw, "SpatialGridDataFrame")
tcw=0
writeGDAL(tc, temptcw, drivername = "GTiff", type = "Int16", mvFlag = -32768, options="INTERLEAVE=BAND")
bands = c(temptcb,temptcg,temptcw)
temptcs = file.path(tempdir,paste(outbase,"_temptcstack.vrt",sep=""))
gdalbuildvrt(gdalfile=bands, output.vrt = temptcs, separate=T) #, tr=c(reso,reso)
gdal_translate(src_dataset=temptcs, dst_dataset=tcfile, of = "GTiff", co="INTERLEAVE=BAND")
projection(tca) = set_projection(tcfile)
tc = as(tca, "SpatialGridDataFrame")
tca=0
writeGDAL(tc, tcafile, drivername = "GTiff", type = "Int16", mvFlag = -32768, options="INTERLEAVE=BAND")
#delete temporary files
unlink(tempdir, recursive=T, force=T)
}
jdbcode/LandsatLinkr documentation built on July 14, 2021, 6:35 p.m.
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Defines functions tmunpackr
Documented in tmunpackr
#' Decompress, stack, and reproject TM/ETM+ SR images
#'
#' Decompress, stack, and reproject TM/ETM+ SR images
#' @param file character. full path name of the surface reflectance file
#' @param proj character. PROJ.4 projection definition.
#' @param overwrite logical. True will overwrite the file if it already exists, False will skip processing if output file exists.
#' @import raster
#' @import gdalUtils
#' @import rgdal
#' @export
tmunpackr = function(file, proj="default", overwrite=F){
# http://earthexplorer.usgs.gov/ Landsat CDR TM and ETM+ images
check = file_check(file,"ledaps.tif",overwrite)
if(check == 0){return(0)}
#set new directories
randomstring = paste(sample(c(0:9, letters, LETTERS), 6, replace=TRUE),collapse="")
tempdir = file.path(dirname(file),randomstring) #temp
dir.create(tempdir, recursive=T, showWarnings=F)
#decompress the image
untar(file, exdir=tempdir, tar="internal") #decompress the file
files = list.files(tempdir, full.names=T)
#are there files in the decompressed archive
if(length(files) == 0){
unlink(tempdir, recursive=T, force=T)
stop(paste('There were no files found in the decompressed archive:', file))
}
#are these sr files
filesBname = basename(files)
srFilesTest = grep("_sr_", filesBname, value=T)
if(length(srFilesTest) == 0){
unlink(tempdir, recursive=T, force=T)
stop(paste('There were no USGS ESPA Surface Reflectance files found in the decompressed archive:', file))
}
#is this collection 1 or pre-collection
name = filesBname[1]
isCollection = substr(filesBname[1], 5,5) == '_'
#get the sr bands
bands = sort(grep("band", files, value=T))
if(isCollection){
#new version: LXSS_LLLL_PPPRRR_YYYYMMDD_yyyymmdd_CX_TX_prod_band.ext
year = substr(name,18,21)
pieces = unlist(strsplit(dirname(file), "/")) #break up the directory and unlist so the pieces can be called by index
len = length(pieces)-1 #get the ending index for "scene"
newpieces = paste(pieces[1:len], collapse = "/") #subset the directory pieces so the last piece is the scene
outdir = file.path(newpieces, "images", year)
dir.create(outdir, recursive=T, showWarnings=F)
# create the mask
pixelqafile = grep("pixel_qa.tif", files, value=T)
pixelqar = getValues(raster(pixelqafile))
#mask = as.numeric(pixelqar == 322 | pixelqar == 386 | pixelqar == 324 | pixelqar == 388 | pixelqar == 836 | pixelqar == 900)
shadow = bitwAnd(pixelqar, 8) == 0 # shadow
snow = bitwAnd(pixelqar, 16) == 0 # snow
clouds = bitwAnd(pixelqar, 32) == 0 # clouds
mask = shadow*snow*clouds
clouds = snow = shadow = pixelqar = 0 #clear memory
# make the basename for final output files
mtlfile = grep("MTL.txt", files, value=T)
tbl = unlist(read.delim(mtlfile, header=F, skipNul=T))
string = as.character(grep("LANDSAT_SCENE_ID = ", tbl, value=T))
pieces = unlist(strsplit(string, " "))
sceneid = pieces[length(pieces)]
outbase = substr(sceneid,1,16)
} else{
#name = 'LC80380292015214LGN00.xml'
outbase = substr(name,1,16) # need to get this from the filename, because pre-collection does not include an mtl file
year = substr(name,10,13)
pieces = unlist(strsplit(dirname(file), "/")) #break up the directory and unlist so the pieces can be called by index
len = length(pieces)-1 #get the ending index for "scene"
newpieces = paste(pieces[1:len], collapse = "/") #subset the directory pieces so the last piece is the scene
outdir = file.path(newpieces, "images", year)
dir.create(outdir, recursive=T, showWarnings=F)
#decompress the image and get/set files names
untar(file, exdir=tempdir, tar="internal") #decompress the file
files = list.files(tempdir, full.names=T)
bands = sort(grep("band", files, value=T))
shadow = grep("cloud_shadow_qa.tif", files, value=T) #0 okay, 255 bad
cloud = grep("sr_cloud_qa.tif", files, value=T) #0 okay, 255 bad
snow = grep("sr_snow_qa.tif", files, value=T) #0 okay, 255 bad
fmask = grep("cfmask.tif", files, value=T) # <= 1 okay background 255
#make a composite cloudmask
s = as.matrix(raster(shadow))
c = as.matrix(raster(cloud))
sn = as.matrix(raster(snow))
f = as.matrix(raster(fmask))
check = s[1,1] # if is.na(check) == T new else old
if(is.na(check) == T){s = is.na(s)} else {s = !is.na(s)}
check = c[1,1] # if is.na(check) == T new else old
if(is.na(check) == T){c = is.na(c)} else {c = !is.na(c)}
check = sn[1,1] # if is.na(check) == T new else old
if(is.na(check) == T){sn = is.na(sn)} else {sn = !is.na(sn)}
f = f <= 1
mask = s*c*f*sn
s=c=sn=f=0
}
#mask = setValues(ref,mask)
#plot(mask)
#writeRaster(mask, "D:/work/proj/llr_dev/collection1/tm/wrs2/032033/test.tif")
# create outfile paths
tempstack = file.path(tempdir,paste(outbase,"_tempstack.tif",sep=""))
tempvrt = sub("tempstack.tif", "tempstack.vrt", tempstack)
tempmask = sub("tempstack", "tempmask", tempstack)
projstack = sub("tempstack", "projstack", tempstack)
projmask = sub("tempstack", "projmask", tempstack)
finalstack = file.path(outdir,paste(outbase,"_ledaps.tif", sep=""))
finalmask = file.path(outdir,paste(outbase,"_cloudmask.tif", sep=""))
tcfile = file.path(outdir,paste(outbase,"_tc.tif", sep=""))
tcafile = file.path(outdir,paste(outbase,"_tca.tif", sep=""))
outprojfile = file.path(outdir,paste(outbase,"_proj.txt", sep=""))
# set a reference raster for setting values and getting projection
ref = raster(bands[1])
origproj = projection(ref)
#stack the image bands and write out
gdalbuildvrt(gdalfile=bands, output.vrt = tempvrt, separate=T) #, tr=c(reso,reso)
gdal_translate(src_dataset=tempvrt, dst_dataset=tempstack, of = "GTiff", co="INTERLEAVE=BAND")
# write the mask out
mask = setValues(ref,mask)
mask = as(mask, "SpatialGridDataFrame") #convert the raster to SGHF so it can be written using GDAL (faster than writing it with the raster package)
writeGDAL(mask, tempmask, drivername = "GTiff", type = "Byte", mvFlag = 255, options="INTERLEAVE=BAND")
mask=0 #clear the memory
#reproject the image #need to add in writing proj file for default
if(proj == "default"){proj = origproj}
write(proj, outprojfile)
gdalwarp(srcfile=tempstack, dstfile=projstack,
s_srs=origproj, t_srs=proj, of="GTiff",
r="bilinear", srcnodata=-9999, dstnodata=-32768, multi=T, #"near"
tr=c(30,30), co="INTERLEAVE=BAND")
#project the mask
gdalwarp(srcfile=tempmask, dstfile=projmask,
s_srs=origproj, t_srs=proj, of="GTiff",
r="mode", srcnodata=255, dstnodata=255, multi=T,
tr=c(30,30), co="INTERLEAVE=BAND")
#trim the na rows and cols
trim_na_rowcol(projstack, finalstack, projmask, finalmask)
#tasseled cap
b1 = as.matrix(raster(finalstack, 1))
b2 = as.matrix(raster(finalstack, 2))
b3 = as.matrix(raster(finalstack, 3))
b4 = as.matrix(raster(finalstack, 4))
b5 = as.matrix(raster(finalstack, 5))
b6 = as.matrix(raster(finalstack, 6))
bcoef = c(0.2043, 0.4158, 0.5524, 0.5741, 0.3124, 0.2303)
gcoef = c(-0.1603, -0.2819, -0.4934, 0.7940, -0.0002, -0.1446)
wcoef = c(0.0315, 0.2021, 0.3102, 0.1594,-0.6806, -0.6109)
bright = (b1*bcoef[1])+(b2*bcoef[2])+(b3*bcoef[3])+(b4*bcoef[4])+(b5*bcoef[5])+(b6*bcoef[6])
green = (b1*gcoef[1])+(b2*gcoef[2])+(b3*gcoef[3])+(b4*gcoef[4])+(b5*gcoef[5])+(b6*gcoef[6])
wet = (b1*wcoef[1])+(b2*wcoef[2])+(b3*wcoef[3])+(b4*wcoef[4])+(b5*wcoef[5])+(b6*wcoef[6])
b1=b2=b3=b4=b5=b6=0
tcb = matrix_to_raster(finalstack,bright)
tcg = matrix_to_raster(finalstack,green)
tcw = matrix_to_raster(finalstack,wet)
wet=0
tca = atan(green/bright) * (180/pi) * 100
bright=green=0
tca = matrix_to_raster(finalstack,tca)
temptcb = file.path(tempdir,paste(outbase,"_temptcb.tif",sep=""))
temptcg = file.path(tempdir,paste(outbase,"_temptcg.tif",sep=""))
temptcw = file.path(tempdir,paste(outbase,"_temptcw.tif",sep=""))
projection(tcb) = set_projection(tcfile)
projection(tcg) = set_projection(tcfile)
projection(tcw) = set_projection(tcfile)
tc = as(tcb, "SpatialGridDataFrame")
tcb=0
writeGDAL(tc, temptcb, drivername = "GTiff", type = "Int16", mvFlag = -32768, options="INTERLEAVE=BAND")
tc = as(tcg, "SpatialGridDataFrame")
tcg=0
writeGDAL(tc, temptcg, drivername = "GTiff", type = "Int16", mvFlag = -32768, options="INTERLEAVE=BAND")
tc = as(tcw, "SpatialGridDataFrame")
tcw=0
writeGDAL(tc, temptcw, drivername = "GTiff", type = "Int16", mvFlag = -32768, options="INTERLEAVE=BAND")
bands = c(temptcb,temptcg,temptcw)
temptcs = file.path(tempdir,paste(outbase,"_temptcstack.vrt",sep=""))
gdalbuildvrt(gdalfile=bands, output.vrt = temptcs, separate=T) #, tr=c(reso,reso)
gdal_translate(src_dataset=temptcs, dst_dataset=tcfile, of = "GTiff", co="INTERLEAVE=BAND")
projection(tca) = set_projection(tcfile)
tc = as(tca, "SpatialGridDataFrame")
tca=0
writeGDAL(tc, tcafile, drivername = "GTiff", type = "Int16", mvFlag = -32768, options="INTERLEAVE=BAND")
#delete temporary files
unlink(tempdir, recursive=T, force=T)
}
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