Revision 661e6ef0
Added by Benoit Parmentier over 11 years ago
| climate/research/oregon/interpolation/covariates_production_temperatures.R | ||
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# -MODIS LST: mean and obs |
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#3) The output is a multiband file in tif format with projected covariates for the processing region/tile. |
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#AUTHOR: Benoit Parmentier |
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#DATE: 03/21/2013
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#DATE: 05/14/2013
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#PROJECT: NCEAS INPLANT: Environment and Organisms --TASK#363-- |
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##Comments and TODO: |
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} |
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create_raster_region <-function(raster_name,reg_ref_rast){
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#This functions returns a subset of tiles from the modis grdi. |
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#This functions returns a subset of tiles from the modis grdid.
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#Arguments: raster name of the file,reference file with |
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#Output: spatial grid data frame of the subset of tiles |
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covariates_production_temperature<-function(list_param){
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#This functions produce covariates used in the interpolation of temperature. |
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#It requires 15 arguments: |
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# |
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#1) var : interpolated variable: TMIN, TMAX, (PRCP?) |
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#2) out_path : output directory |
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#3) lc_path |
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#4) infile_modis_grid |
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#5) infile_elev : this is the global file: replace later with the input produced by the DEM team |
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#6) infile_canheight : Canopy height |
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#7) list_tiles_modis : tile for Venezuela and surrounding area |
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#8) infile_reg_outline : input region outline defined by polygon |
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#9) CRS_interp : local projection system |
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#10) CRS_locs_WGS84 : CRS_locs_WGS84 # |
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#11) out_region_name : generated on the fly |
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#12) out_suffix : added to the covariates stack/brick |
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#13) ref_rast_name: local raster name defining resolution, exent, local projection--. set on the fly?? |
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#14) hdfdir: directory where the LST averages are stored... |
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#15) out_suffix_modis : suffix used in producing LST climatology |
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#16) covar_names : names of covariates |
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# |
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# |
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out_region_name<-list_param$out_region_name #generated on the fly |
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out_suffix<-list_param$out_suffix |
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ref_rast_name<-list_param$ref_rast_name #local raster name defining resolution, exent, local projection--. set on the fly?? |
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hdfdir <- list_param$hdfdir |
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out_suffix_modis <- list_param$out_suffix_modis |
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covar_names<-list_param$covar_names |
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##### SET UP STUDY AREA #### |
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setwd(in_path) |
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#setwd(in_path) |
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setwd(out_path) |
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list_tiles_modis <- unlist(strsplit(list_tiles_modis,",")) # transform string into separate element in char vector |
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filename<-sub(".shp","",basename(infile_modis_grid)) #Removing path and the extension from file name.
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#modis_grid<-readOGR(".", filename) #Reading shape file using rgdal library
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modis_grid<-readOGR(dsn=dirname(infile_modis_grid), filename) #Reading shape file using rgdal library |
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filename<-sub(".shp","",infile_modis_grid) #Removing the extension from file.
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modis_grid<-readOGR(".", filename) #Reading shape file using rgdal library
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#filename<-sub(".shp","",infile1) #Removing the extension from file.
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#world_countries<-readOGR(".", filename) #Reading shape file using rgdal library
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#outfile1<-file.path(out_path,paste("stations","_",out_prefix,".shp",sep=""))
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#writeOGR(stat_reg,dsn= dirname(outfile1),layer= sub(".shp","",basename(outfile1)), driver="ESRI Shapefile",overwrite_layer=TRUE)
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if (infile_reg_outline!=""){
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filename<-sub(".shp","",infile_reg_outline) #Removing the extension from file.
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reg_outline<-readOGR(".", filename)
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filename<-sub(".shp","",basename(infile_reg_outline)) #Removing path and the extension from file name.
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reg_outline<-readOGR(dsn=dirname(infile_reg_outline), filename)
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} |
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if (infile_reg_outline==""){
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reg_outline<-create_modis_tiles_region(modis_grid,list_tiles_modis) #problem...this does not |
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#align with extent of modis LST!!! |
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writeOGR(reg_outline,dsn= ".",layer= paste("outline",out_region_name,"_",out_suffix,sep=""),
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writeOGR(reg_outline,dsn= out_path,layer= paste("outline",out_region_name,"_",out_suffix,sep=""),
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driver="ESRI Shapefile",overwrite_layer="TRUE") |
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} |
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| ... | ... | |
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lst_pat<-"LST_Night_1km" |
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} |
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if (var=="TMAX"){
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lst_pat<-"" #for the time being change at later stage... |
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#day_pat<-"LST_Day_1km" |
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lst_pat<-"LST_Day_1km" #for the time being change at later stage... |
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} |
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#Get list of files containing the LST averages |
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pat_str2 <- glob2rx(paste("nobs","*",lst_pat,"*.tif",sep=""))
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tmp_str2<- mixedsort(list.files(pattern=pat_str2)) |
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pat_str1 <- glob2rx(paste("mean","*",lst_pat,"*.tif",sep=""))
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tmp_str1<- mixedsort(list.files(pattern=pat_str1)) |
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#pat_str2 <- glob2rx(paste("nobs","*",lst_pat,"*.tif",sep=""))
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pat_str2 <- glob2rx(paste("nobs","*",lst_pat,"*",out_suffix_modis,"*.tif",sep=""))
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#mixedsort(list.files(path=hdfdir,pattern=".*tif")) |
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tmp_str2 <- mixedsort(list.files(path=hdfdir,pattern=pat_str2)) #note that this assumes the LST averages are stored in hdfdir |
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#pat_str1 <- glob2rx(paste("mean","*",lst_pat,"*.tif",sep=""))
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pat_str1 <- glob2rx(paste("mean","*",lst_pat,"*",out_suffix_modis,"*.tif",sep=""))
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tmp_str1 <- mixedsort(list.files(path=hdfdir,pattern=pat_str1)) |
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#add lines using grep to select tiles... |
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#Format list for mosaicing: mosaic for every month the relevant number of files |
Also available in: Unified diff
covariates preparation script, modifications to handle LST inputs and output directory