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Revision 4adca9a2

Added by Benoit Parmentier over 11 years ago

data preparation, modifications to run anywhere, Queensland test

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climate/research/oregon/interpolation/Database_stations_covariates_processing_function.R
94 94
  #Read in GHCND database station locations
95 95
  dat_stat <- read.fwf(infile_ghncd_data, 
96 96
                       widths = c(11,9,10,7,3,31,4,4,6),fill=TRUE)
97
  colnames(dat_stat)<-c("STAT_ID","lat","lon","elev","state","name","GSNF","HCNF","WMOID")
98
  coords<- dat_stat[,c('lon','lat')]
97
  colnames(dat_stat)<-c("STAT_ID","latitude","longitude","elev","state","name","GSNF","HCNF","WMOID")
98
  coords<- dat_stat[,c('longitude','latitude')]
99 99
  coordinates(dat_stat)<-coords
100 100
  proj4string(dat_stat)<-CRS_locs_WGS84 #this is the WGS84 projection
101 101
  #proj4string(dat_stat)<-CRS_interp
......
131 131
  
132 132
  #Transform the subset data frame in a spatial data frame and reproject
133 133
  data_reg<-data_table                               #Make a copy of the data frame
134
  coords<- data_reg[c('lon','lat')]              #Define coordinates in a data frame: clean up here!!
134
  coords<- data_reg[c('longitude','latitude')]              #Define coordinates in a data frame: clean up here!!
135 135
  coordinates(data_reg)<-coords                      #Assign coordinates to the data frame
136 136
  proj4string(data_reg)<-CRS_locs_WGS84                #Assign coordinates reference system in PROJ4 format
137 137
  data_reg<-spTransform(data_reg,CRS(CRS_interp))     #Project from WGS84 to new coord. system
......
168 168
  s_raster<-brick(infile_covariates)                   #read in the data stack
169 169
  names(s_raster)<-covar_names               #Assigning names to the raster layers: making sure it is included in the extraction
170 170
  stat_val<- extract(s_raster, data_reg)        #Extracting values from the raster stack for every point location in coords data frame.
171
  #stat_val_test<- extract(s_raster, data_reg,def=TRUE)
171 172
  
172 173
  #create a shape file and data_frame with names
173 174
  
......
223 224
  #Save the query data here...
224 225
  data_m<-merge(data_m, stat_reg, by.x="station", by.y="STAT_ID")   #Inner join all columns are retained
225 226
  #Extracting covariates from stack for the monthly dataset...
226
  coords<- data_m[c('lon','lat')]              #Define coordinates in a data frame
227
  coords<- data_m[c('longitude','latitude')]              #Define coordinates in a data frame
227 228
  coordinates(data_m)<-coords                      #Assign coordinates to the data frame
228 229
  proj4string(data_m)<-CRS_locs_WGS84                  #Assign coordinates reference system in PROJ4 format
229 230
  data_m<-spTransform(data_m,CRS(CRS_interp))     #Project from WGS84 to new coord. system
......
258 259
  }
259 260
  
260 261
  #Extracting covariates from stack for the monthly dataset...
261
  coords<- dst[c('lon','lat')]              #Define coordinates in a data frame
262
  #names(dst)[5:6] <-c('latitude','longitude')
263
  coords<- dst[c('longitude','latitude')]              #Define coordinates in a data frame
264
  
262 265
  coordinates(dst)<-coords                      #Assign coordinates to the data frame
263 266
  proj4string(dst)<-CRS_locs_WGS84                  #Assign coordinates reference system in PROJ4 format
264 267
  dst_month<-spTransform(dst,CRS(CRS_interp))     #Project from WGS84 to new coord. system
......
292 295
  
293 296
  outfiles_obj<-list(outfile1,outfile2,outfile3,outfile4,outfile5,outfile6)
294 297
  names(outfiles_obj)<- c("loc_stations","loc_stations_ghcn","daily_query_ghcn_data","daily_covar_ghcn_data","monthly_query_ghcn_data","monthly_covar_ghcn_data")
298
  save(outfiles_obj,file= file.path(out_path,paste("met_stations_outfiles_obj_",interpolation_method,"_", out_prefix,".RData",sep="")))
299
  
295 300
  return(outfiles_obj)
296 301
  
297 302
  #END OF FUNCTION # 

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