Nothing
## ----global_options, include=FALSE--------------------------------------------
knitr::opts_chunk$set(eval = FALSE)
## -----------------------------------------------------------------------------
# library(redlistr)
# library(stringr)
## -----------------------------------------------------------------------------
# # Example directory
# input_dir <- # Path to folder with tif files
# out_dir <- "C:/Users/Username/Desktop"
# # List all files within input_dir that ends with .tif
# input_list <- list.files(input_dir, pattern = '.tif$')
# # Option to save shapefiles or not
# saveSHP <- T
## -----------------------------------------------------------------------------
# # set up data capture
# results_df <- data.frame (
# # Name of the raster
# in.raster = NA,
# # Estimated area of ecosystem
# eco.area.km2 = NA,
# # Spatial resolution of data
# eco.grain = NA,
# # EOO of ecosystem
# eoo.area.km2 = NA,
# # AOO of ecosystem
# aoo.no = NA,
# # AOO of ecosystem with at least 1% in each grid cell
# aoo.1pc = NA,
# # Time taken for the analysis to complete
# time.taken = NA)
## -----------------------------------------------------------------------------
# for (i in seq_along(input_list)){
# # Prints out a message showing progress
# message (paste("working on number... ", i, " of ", length(input_list)))
# start_time <- proc.time()
# filename <- input_list[i]
# input_string <- paste(input_dir, "\\", input_list[i], sep="")
# rast = raster(input_string)
# NAvalue(rast) <- 0
# eco.area.km2 <- getArea(rast)
# message (paste("... area of ecosystem is", eco.area.km2, "km^2"))
# eco.grain <- paste(res(rast)[1], 'x', res(rast)[2])
# eoo.shp <- makeEOO(rast)
# eoo.area.km2 <- getAreaEOO(eoo.shp)
# message (paste("... area of EOO is", eoo.area.km2, "km^2"))
# aoo.no <- getAOO(rast, 10000, FALSE)
# message (paste("... number of occupied grid cells is", aoo.no, "10 x 10-km cells"))
# aoo.1pc <- getAOO(rast, 10000, TRUE)
# message (paste("... number of AOO 1% grid cells is", aoo.1pc, "10 x 10-km cells"))
# time_taken <- proc.time() - start_time
# message (paste("file", i, "completed in ", time_taken))
#
# # Saving the results into the data frame
# results_df$in.raster[i] <- filename
# results_df$eco.area.km2[i] = eco.area.km2
# results_df$eco.grain[i] = eco.grain
# results_df$eoo.area.km2[i] = eoo.area.km2
# results_df$aoo.no[i] = aoo.no
# results_df$aoo.1pc[i] = aoo.1pc
# results_df$time.taken[i] = time_taken
#
# # Saving shapefiles
# if(saveShps == TRUE){
# shapefile(eoo.shp, paste0(out_dir, filename, "eoo"), overwrite=TRUE)
# aoo.shp <- makeAOOGrid (rast, 10000, one.percent.rule = FALSE)
# shapefile(aoo.shp, paste0(out_dir, filename, "aoo"), overwrite=TRUE)
# aoo1.shp <- makeAOOGrid (rast, 10000, one.percent.rule = TRUE)
# shapefile(aoo1.shp, paste0(out_dir, filename, "aoo1"), overwrite=TRUE)
# }
# }
#
# # Printing a message when everything is completed
# message ("Analysis complete.")
#
# # Saving the outputs as a csv file
# write.csv(results_df, paste(out_dir, "redlistr_analysis.csv"))
## -----------------------------------------------------------------------------
# library(redlistr)
# library(stringr)
## -----------------------------------------------------------------------------
# # Example directory
# input_rast <- # raster(...)
# out_dir <- "C:/Users/Username/Desktop"
# # Option to save shapefiles or not
# saveSHP <- T
## -----------------------------------------------------------------------------
# # set up data capture
# results_df <- data.frame (
# # Name of the raster
# raster.class = NA,
# # Estimated area of ecosystem
# eco.area.km2 = NA,
# # Spatial resolution of data
# eco.grain = NA,
# # EOO of ecosystem
# eoo.area.km2 = NA,
# # AOO of ecosystem
# aoo.no = NA,
# # AOO of ecosystem with at least 1% in each grid cell
# aoo.1pc = NA,
# # Time taken for the analysis to complete
# time.taken = NA)
## -----------------------------------------------------------------------------
# val_table <- freq(input_rast, useNA = "no") # get class values from raster
# vals <- val_table[,1] # convert table of values to vector
# message('Raster has >>> ', length(vals) , ' <<< classes' )
#
# for (val in vals){
# # Prints out a message showing progress
# message (paste("working on class", val))
# start_time <- proc.time()
# # Create temporary raster where values are the current class
# rast <- input_rast == i
# values(rast)[values(rast) == 0] <- NA
# NAvalue(rast) <- 0
# eco.area.km2 <- getArea(rast)
# message (paste("... area of ecosystem is", eco.area.km2, "km^2"))
# eco.grain <- paste(res(rast)[1], 'x', res(rast)[2])
# eoo.shp <- makeEOO(rast)
# eoo.area.km2 <- getAreaEOO(eoo.shp)
# message (paste("... area of EOO is", eoo.area.km2, "km^2"))
# aoo.no <- getAOO(rast, 10000, FALSE)
# message (paste("... number of occupied grid cells is", aoo.no, "10 x 10-km cells"))
# aoo.1pc <- getAOO(rast, 10000, TRUE)
# message (paste("... number of AOO 1% grid cells is", aoo.1pc, "10 x 10-km cells"))
# time_taken <- proc.time() - start_time
# message (paste("file", i, "completed in ", time_taken))
#
# # Saving the results into the data frame
# temp_df <- data.frame(
# eco.class = val,
# eco.area.km2 = eco.area.km2,
# eco.grain = eco.grain,
# eoo.area.km2 = eoo.area.km2,
# aoo.no = aoo.no,
# aoo.1pc = aoo.1pc,
# time_taken = time_taken)
# results_df <- rbind(results_df, temp_df)
# # Saving shapefiles
# if(saveSHP == TRUE){
# shapefile(eoo.shp, paste0(out_dir, filename, "eoo"), overwrite=TRUE)
# aoo.shp <- makeAOOGrid (rast, 10000, one.percent.rule = FALSE)
# shapefile(aoo.shp, paste0(out_dir, filename, "aoo"), overwrite=TRUE)
# aoo1.shp <- makeAOOGrid (rast, 10000, one.percent.rule = TRUE)
# shapefile(aoo1.shp, paste0(out_dir, filename, "aoo1"), overwrite=TRUE)
# }
# }
#
# # Printing a message when everything is completed
# message ("Analysis complete.")
#
# # Saving the outputs as a csv file
# write.csv(results_df, paste(out_dir, "redlistr_analysis.csv"))
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