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Revision b345fd0a

Added by Benoit Parmentier over 11 years ago

data preparation, debugging, clean up of input parameters names

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climate/research/oregon/interpolation/Database_stations_covariates_processing_function.R
9 9 
  # 2)  var: the variable of interest - "TMAX","TMIN" or "PRCP"
10 10 
  # 3)  range_years: range of records used in the daily interpolation, note that upper bound year is not included
11 11 
  # 4)  range_years_clim: range of records used in the monthly climatology interpolation, note that upper bound is not included
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  # 5)  infile1: region outline as a shape file - used in the interpolation  stage too
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  # 6)  infile2: ghcnd stations locations as a textfile name with lat-long fields
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  # 5)  infile_reg_outline: region outline as a shape file - used in the interpolation  stage too
13 
  # 6)  infile_ghncd_data: ghcnd stations locations as a textfile name with lat-long fields
14 14 
  # 7)  infile_covarariates: tif file of raser covariates for the interpolation area: it should have a local projection
15 15 
  # 8)  CRS_locs_WGS84: longlat EPSG 4326 used as coordinates reference system (proj4)for stations locations
16 16 
  # 9)  in_path: input path for covariates data and other files, this is also the output?
......
28 28 
  #6) monthly_covar_ghcn_data: ghcn monthly averaged data with covariates for the year range of interpolation (locally projected)
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  #AUTHOR: Benoit Parmentier
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  #DATE: 05/07/2013
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  #DATE: 05/21/2013
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  #PROJECT: NCEAS INPLANT: Environment and Organisms --TASK#363--
33 33 
  #Comments and TODO
34 34 
  #-Add buffer option...
......
72 72 
  year_end <-list_param_prep$range_years[2] #"2011"                 #end year for the query (excluded)
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  year_start_clim <-list_param_prep$range_years_clim[1] #right bound not included in the range!! starting year for monthly query to calculate clime
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  year_end_clim <-list_param_prep$range_years_clim[2] #right bound not included in the range!! starting year for monthly query to calculate clime
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  infile1<- list_param_prep$infile1  #This is the shape file of outline of the study area                                                      #It is an input/output of the covariate script
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  infile2<-list_param_prep$infile2      #"/home/layers/data/climate/ghcn/v2.92-upd-2012052822/ghcnd-stations.txt"                              #This is the textfile of station locations from GHCND
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  infile3<-list_param_prep$infile_covariates #"covariates__venezuela_region__VE_01292013.tif" #this is an output from covariate script
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  infile_reg_outline<- list_param_prep$infile_reg_outline  #This is the shape file of outline of the study area                                                      #It is an input/output of the covariate script
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  infile_ghncd_data<-list_param_prep$infile_ghncd_data      #"/home/layers/data/climate/ghcn/v2.92-upd-2012052822/ghcnd-stations.txt"                              #This is the textfile of station locations from GHCND
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  infile_covariates<-list_param_prep$infile_covariates #"covariates__venezuela_region__VE_01292013.tif" #this is an output from covariate script
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  CRS_locs_WGS84<-list_param_prep$CRS_locs_WGS84 #Station coords WGS84: same as earlier
79 79 
  in_path <- list_param_prep$in_path #CRS_locs_WGS84"/home/parmentier/Data/IPLANT_project/Venezuela_interpolation/Venezuela_01142013/input_data/"
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  out_path <- list_param_prep$out_path #CRS_locs_WGS84"/home/parmentier/Data/IPLANT_project/Venezuela_interpolation/Venezuela_01142013/input_data/"
......
83 83 
  out_prefix<-list_param_prep$out_prefix #"_365d_GAM_fus5_all_lstd_03012013"                #User defined output prefix
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  ## working directory is the same for input and output for this function
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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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  ##### STEP 1: Select station in the study area
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  filename<-sub(".shp","",infile1)             #Removing the extension from file.
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  interp_area <- readOGR(".",filename)
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  filename<-sub(".shp","",infile_reg_outline)             #Removing the extension from file.
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  interp_area <- readOGR(dsn=dirname(filename),basename(filename))
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  CRS_interp<-proj4string(interp_area)         #Storing the coordinate information: geographic coordinates longlat WGS84
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  #Read in GHCND database station locations
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  dat_stat <- read.fwf(infile2,
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  dat_stat <- read.fwf(infile_ghncd_data,
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                       widths = c(11,9,10,7,3,31,4,4,6),fill=TRUE)
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  colnames(dat_stat)<-c("STAT_ID","lat","lon","elev","state","name","GSNF","HCNF","WMOID")
98 98 
  coords<- dat_stat[,c('lon','lat')]
......
164 164 
  ### STEP 4: Extract values at stations from covariates stack of raster images
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  #Eventually this step may be skipped if the covariates information is stored in the database...
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  s_raster<-stack(file.path(in_path,infile3))                   #read in the data stack
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  #s_raster<-stack(file.path(in_path,infile_covariates))                   #read in the data stack
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  s_raster<-brick(infile_covariates)                   #read in the data stack
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  names(s_raster)<-covar_names               #Assigning names to the raster layers: making sure it is included in the extraction
169 170 
  stat_val<- extract(s_raster, data_reg)        #Extracting values from the raster stack for every point location in coords data frame.
170 171

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