Revision b6f62053
Added by Benoit Parmentier over 11 years ago
| climate/research/oregon/interpolation/covariates_production_temperatures.R | ||
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# -24 LST layers: "climatology" produced from MOD11A1, LST (mean and obs) using script in step 1 of workflow |
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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: 06/20/2013
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#DATE: 08/05/2013
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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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screening_val_r_stack_fun<-function(list_val_range,r_stack){
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#Screening values for raster stack |
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#Screening values for a raster stack by providing a valid range. Values outside the valid |
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#range are assigned NA. Layers in the stack/brick are only screened if a name valid range is provided. |
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#input: list_val_range: list of character strings comma separated |
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# e.g.: "mm_12,-15,50","mm_12,-15,50" |
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# variable name, min value, max value |
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#The user must include the name of the variable matching the names in the raster brick/stack. |
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#Values are assigned NA if they are less than the mini value or greater than the maximum value. |
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#Output: stack with screened values. Note that the original order of layer names is not preserved!!! |
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## Parameters: parsing |
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tab_range_list<-do.call(rbind,as.list(list_val_range)) |
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| ... | ... | |
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val_rst<-vector("list",nrow(tab_range)) #list of one row data.frame
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for (k in 1:nrow(tab_range)){
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avl<-c(-Inf,tab_range$vmin[k],NA, tab_range$vmax[k],+Inf,NA) #This creates a input vector...val 1 are -9999, 2 neg, 3 positive |
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rclmat<-matrix(avl,ncol=3,byrow=TRUE) |
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#avl<-c(-Inf,tab_range$vmin[k],NA, tab_range$vmax[k],+Inf,NA) #This creates a input vector...val 1 are -9999, 2 neg, 3 positive |
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#avl<-c(tab_range$vmin[k],tab_range$vmax[k],NA) #This creates a input vector...val 1 are -9999, 2 neg, 3 positive |
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#rclmat<-matrix(avl,ncol=3,byrow=TRUE) |
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#s_raster_r<-raster(r_stack,match(tab_range$varterm[k],names(r_stack))) #select relevant layer from stack |
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s_raster_r<-raster(r_stack,match(tab_range$varname[k],names(r_stack))) |
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s_raster_r<-reclassify(s_raster_r,rclmat) #now reclass values |
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#s_raster_r<-reclassify(s_raster_r,rclmat) #now reclass values |
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#s_raster_r<-reclassify(s_raster_r,rclmat,include.lowest=TRUE,right=FALSE) #now reclass values |
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#s_raster_r<-reclassify(s_raster_r,rclmat,include.lowest=FALSE,right=FALSE) #now reclass values |
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#s_raster_r<-reclassify(s_raster_r,rclmat,include.lowest=TRUE,right=TRUE) #now reclass values |
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#s_raster_r<-reclassify(s_raster_r,rclmat,include.lowest=FALSE,right=TRUE) #now reclass values |
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#r_stack<-dropLayer(r_stack,match(tab_range$varname[k],names(r_stack))) |
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s_raster_r[s_raster_r < tab_range$vmin[k]] <- NA #Assign NA if less than the minimum value in the valid range |
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s_raster_r[s_raster_r > tab_range$vmax[k]] <- NA #Assign NA if greater than the maxim value in the valid range |
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names(s_raster_r)<-tab_range$varname[k] #Loss of layer names when using reclass |
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val_rst[[k]]<-s_raster_r |
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} |
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proj4string(ref_rast) <- CRS_interp #Assign given reference system from master script... |
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} |
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out_suffix_lst <-paste(out_suffix,".tif",sep="") |
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mean_lst_list_outnames<-change_names_file_list(mean_m_list,out_suffix_lst,"reg_",".tif",out_path=out_path) |
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nobs_lst_list_outnames<-change_names_file_list(nobs_m_list,out_suffix_lst,"reg_",".tif",out_path=out_path) |
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lc_list <- c(infile_elev,infile_canheight,infile_distoc) #, lc_list #15 layers to reproject... |
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out_suffix_l <-paste(out_suffix,".tif",sep="") |
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lc_list_outnames<-change_names_file_list(lc_list,out_suffix_l,"reg_",".tif",out_path=out_path) |
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j<-1 |
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list_param_create_region<-list(j,raster_name=lc_list,reg_ref_rast=ref_rast,out_rast_name=lc_list_outnames) |
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list_covar_layers <- mclapply(1:3, list_param=list_param_create_region, create__m_raster_region,mc.preschedule=FALSE,mc.cores = 3) #This is the end bracket from mclapply(...) statement |
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| ... | ... | |
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r2<-raster(terrain_rast,layer=pos) #Select layer from stack |
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N<-cos(r1) |
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E<-sin(r1) |
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Nw<-sin(r2)*cos(r1) #Adding a variable to the dataframe
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Ew<-sin(r2)*sin(r1) #Adding variable to the dataframe.
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Nw<-sin(r2)*cos(r1) #Calculating Northness weighted by the slope
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Ew<-sin(r2)*sin(r1) #Calculating Eastness weighted by the slope
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################################ |
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#6) X-Y coordinates and LAT-LONG: do not keep in memory? |
Also available in: Unified diff
covariates script, modification of screening function related to CANHEIGHT and LC