map_urban_cooling: map_urban_cooling

In AlbyDR/rSCOPE: Run SCOPE model through R

map_urban_cooling

Description

This function map greening cooling services based on the SCOPE outputs according to a selected period.

Usage

map_urban_cooling(
  dataset,
  date_hottest,
  function_var = list(max, sum),
  output_vars = c("ET", "Tsave", "Tcave"),
  input_raster,
  NA_cells,
  Input_vector,
  veg_fraction,
  extract_fun = "max"
)

Arguments

dataset	a data.frame with SCOPE outputs, a datetime variable and pixel numbers (timestamp, id_pixel) from the get_prediction function
date_hottest	to define the day to calculate the indices
output_vars	variables to map, default c("ET", "Tsave"),
input_raster	the grip template (raster object, the same as the interpolation)
NA_cells	a vector the raster grid id_pixel masked and excluded from the SCOPE run
Input_vector	name of the sf polygon map object
veg_fraction	name of the vegetation fraction variable
extract_fun	get the max ET form the 1km grid, default = 'max', faster and suitable in case of coarse grid

Value

It will save the split files in the SCOPE directory.

Examples

Map greening cooling services indices based on the SCOPE predictions
Cooling_maps_2000 <- map_urban_cooling(dataset = Berlin2020_pred,
                                      date_hottest = "2020-08-08",
                                      input_raster = krg_grid,
                                      NA_cells = cellNA,
                                      Input_vector = Green_vol,
                                      veg_fraction = "vegproz",
                                      output_vars = c("ET", "Tsave"),
                                      extract_fun = 'max')

summary(Cooling_maps_2000)

plot(Cooling_maps_2000[c(3,4,5)], border = "transparent", nbreaks=11,
    pal=RColorBrewer::brewer.pal('RdYlBu', n = 11), reset=FALSE)

AlbyDR/rSCOPE documentation built on Dec. 19, 2024, 7:29 p.m.