In NINAnor/oneimpact: Tools for the assessment of the cumulative impacts of anthropogenic features in ecological studies

knitr::opts_chunk$set(echo = TRUE,
                      dpi = 300)
knitr::opts_knit$set(root.dir = rprojroot::find_rstudio_root_file())

# libraries
library(rgrass7)
library(raster)
library(terra)

library(NinaR)
library(dplyr)
library(purrr)

library(viridis)

library(oneimpact)

Connect to GRASS.

# start GRASS and connect to my mapset
grassdir <- system("grass78 --config path", intern = T)
gisDB <- "/data/grass"
loc <- "ETRS_33N/"
ms <- "u_bb_cuminf"
# initGRASS(gisBase = grassdir,
#           home = tempdir(), 
#           override = T,
#           gisDbase = gisDB,
#           location = loc, 
#           mapset = ms)

# more directly within NINA
NinaR::grassConnect(mapset = ms)

rgrass7::use_sp()
rgrass7::use_sf()

# copy test region vector and map of private cabins

# check region
gmeta() # g.copy is not affected by the region

# copy region vector
rgrass7::execGRASS("g.copy", parameters = list(vector = "region_test_influence@u_bernardo.brandao,region_test_influence"),
                   flags = c("overwrite"))
# copy private cabins
rgrass7::execGRASS("g.copy", parameters = list(raster = "private_cabins_rast@u_bernardo.brandao,private_cabins_rast"),
                   flags = c("overwrite"))

# define region

# I defined a region_test_influence through the GRASS GUI and using v.in.region output=region_test_influence
rgrass7::execGRASS("g.region", parameters = list(vector = "region_test_influence", align = "private_cabins_rast"),
          flags = "p")

# create a new small map for the current region, just to ease visualization in R
rgrass7::execGRASS("r.mapcalc", expression = "private_cabins_sub = if(!isnull(private_cabins_rast), 1, null())",
          flags = c("overwrite", "quiet"))

Retrieve input raster data to R

# show input map and region here
rgrass7::use_sp()
cabins <- rgrass7::readRAST(c("private_cabins_rast_sub")) %>% 
  raster::raster() %>% 
  terra::rast()

terra::plot(cabins, col = "black")

Exponential decay filter

Single scale

# R
expR <- calc_influence_cumulative(x = cabins, zoi = 500, type = "exp_decay")
plot(expR)

# GRASS
name_var <- "private_cabins_sub"

# first we binarize the input map
# binarize
cabins_bin_name <- util_binarize_GRASS(name_var, null = 0, overwrite = T)

# visualize
cabins_bin <- rgrass7::readRAST(cabins_bin_name) %>% 
  raster::raster() %>% 
  terra::rast()
plot(cabins_bin, main = "Binarized map of cabins")

# now we calculate cumulative influence
expG_name <- calc_influence_cumulative(x = cabins_bin_name, zoi = 500, type = "exp_decay",
                                       where = "GRASS", quiet = T, overwrite = T)
# visualize
expG <- rgrass7::readRAST(expG_name) %>% 
  raster::raster() %>% 
  terra::rast()

terra::plot(c(expR, expG), 
            main = paste("Exponential decay filter - ", 
                         c("R", "GRASS")))




# normalization
# no: 0 to 100 cabins
# in the end: sum = 1
# before the end: where we have max number of cabins = 1

# expG_name <- calc_influence_cumulative_GRASS(x = name_var, zoi = 1000, type = "exp_decay",
#                                              overwrite = T, quiet = F)
# 
# expG_name2 <- calc_influence_cumulative_GRASS(x = name_var, zoi = c(1000, 2000), type = "exp_decay",
#                                              overwrite = T, quiet = F)

Multiple scales

# ZoI
zoi_vals <- c(500, 1000, 1500, 2000)

# R
expR <- calc_influence_cumulative(x = cabins, zoi = zoi_vals, type = "exp_decay")
plot(expR)

# GRASS

# binarized map
cabins_bin_name <- "private_cabins_sub_bin"

expG_name <- calc_influence_cumulative(x = cabins_bin_name, zoi = zoi_vals, type = "exp_decay",
                                       where = "GRASS", quiet = T, overwrite = T)
# visualize
expG <- rgrass7::readRAST(expG_name) %>% 
  raster::stack() %>% 
  terra::rast()

terra::plot(expG, main = paste("Exponential decay cum. influence, ZoI = ", zoi_vals))

Bartlett

Single scale

# R
expR <- calc_influence_cumulative(x = cabins, zoi = 500, type = "bartlett")
plot(expR)

# GRASS

# binarized map
cabins_bin_name <- "private_cabins_sub_bin"

# calculate cumulative influence
expG_name <- calc_influence_cumulative(x = cabins_bin_name, zoi = 500, type = "bartlett",
                                       where = "GRASS", quiet = F, overwrite = T)
# visualize
expG <- rgrass7::readRAST(expG_name) %>% 
  raster::raster() %>% 
  terra::rast()

terra::plot(c(expR, expG), 
            main = paste("Bartlett decay filter - ", 
                         c("R", "GRASS")))

Multiple scales

# ZoI
zoi_vals <- c(500, 1000, 1500, 2000)

# R
expR <- calc_influence_cumulative(x = cabins, zoi = zoi_vals, type = "bartlett")
plot(expR)

# GRASS

# binarized map
cabins_bin_name <- "private_cabins_sub_bin"

expG_name <- calc_influence_cumulative(x = cabins_bin_name, zoi = zoi_vals, type = "bartlett",
                                       where = "GRASS", quiet = T, overwrite = T)
# visualize
expG <- rgrass7::readRAST(expG_name) %>% 
  raster::stack() %>% 
  terra::rast()

terra::plot(expG, main = paste("Bartlett decay cum. influence, ZoI = ", zoi_vals))

Circle window

Single scale

# R
expR <- calc_influence_cumulative(x = cabins, zoi = 500, type = "circle")
plot(expR)

# GRASS

# binarized map
cabins_bin_name <- "private_cabins_sub_bin"

# calculate cumulative influence
expG_name <- calc_influence_cumulative(x = cabins_bin_name, zoi = 500, type = "threshold",
                                       where = "GRASS", quiet = F, overwrite = T)
# visualize
expG <- rgrass7::readRAST(expG_name) %>% 
  raster::raster() %>% 
  terra::rast()

terra::plot(c(expR, expG), 
            main = paste("Threshold filter - ", 
                         c("R", "GRASS")))

Multiple scales

# ZoI
zoi_vals <- c(500, 1000, 1500, 2000)

# R
expR <- calc_influence_cumulative(x = cabins, zoi = zoi_vals, type = "circle")
plot(expR)

# GRASS

# binarized map
cabins_bin_name <- "private_cabins_sub_bin"

expG_name <- calc_influence_cumulative(x = cabins_bin_name, zoi = zoi_vals, type = "circle",
                                       where = "GRASS", quiet = T, overwrite = T)
# visualize
expG <- rgrass7::readRAST(expG_name) %>% 
  raster::stack() %>% 
  terra::rast()

terra::plot(expG, main = paste("Bartlett decay cum. influence, ZoI = ", zoi_vals))

Rectangular window

Single scale

# R
expR <- calc_influence_cumulative(x = cabins, zoi = 500, type = "rectangle")
plot(expR)

# GRASS

# binarized map
cabins_bin_name <- "private_cabins_sub_bin"

# calculate cumulative influence
expG_name <- calc_influence_cumulative(x = cabins_bin_name, zoi = 500, type = "rectangle",
                                       where = "GRASS", quiet = F, overwrite = T)
# visualize
expG <- rgrass7::readRAST(expG_name) %>% 
  raster::raster() %>% 
  terra::rast()

terra::plot(c(expR, expG), 
            main = paste("Rectangle filter - ", 
                         c("R", "GRASS")))

Multiple scales

# ZoI
zoi_vals <- c(500, 1000, 1500, 2000)

# R
expR <- calc_influence_cumulative(x = cabins, zoi = zoi_vals, type = "rectangle")
plot(expR, main = paste("Rectangle-window cum. influence, ZoI = ", zoi_vals))

# GRASS

# binarized map
cabins_bin_name <- "private_cabins_sub_bin"

expG_name <- calc_influence_cumulative(x = cabins_bin_name, zoi = zoi_vals, type = "rectangle",
                                       where = "GRASS", quiet = T, overwrite = T)
# visualize
expG <- rgrass7::readRAST(expG_name) %>% 
  raster::stack() %>% 
  terra::rast()

terra::plot(expG, main = paste("Rectangle-window cum. influence, ZoI = ", zoi_vals))

Gaussian window

Single scale

# R
expR <- calc_influence_cumulative(x = cabins, zoi = 250, type = "Gauss")
plot(expR)

# GRASS

# binarized map
cabins_bin_name <- "private_cabins_sub_bin"

# calculate cumulative influence
expG_name <- calc_influence_cumulative(x = cabins_bin_name, zoi = 250, type = "Gauss",
                                       where = "GRASS", quiet = F, overwrite = T)
# visualize
expG <- rgrass7::readRAST(expG_name) %>% 
  raster::raster() %>% 
  terra::rast()

terra::plot(c(expR, expG), 
            main = paste("Gaussian filter - ", 
                         c("R", "GRASS")))

Multiple scales

# ZoI
zoi_vals <- c(500, 1000, 1500, 2000)

# R
expR <- calc_influence_cumulative(x = cabins, zoi = zoi_vals, type = "Gauss")
plot(expR, main = paste("Gaussian-window cum. influence, ZoI = ", zoi_vals))

# GRASS

# binarized map
cabins_bin_name <- "private_cabins_sub_bin"

expG_name <- calc_influence_cumulative(x = cabins_bin_name, zoi = zoi_vals, type = "Gauss",
                                       where = "GRASS", quiet = T, overwrite = T)
# visualize
expG <- rgrass7::readRAST(expG_name) %>% 
  raster::stack() %>% 
  terra::rast()

terra::plot(expG, main = paste("Rectangle-window cum. influence, ZoI = ", zoi_vals))

User-defined window

Single scale

my_filter <- create_filter(r = 100, zoi = 5000, method = "exp_decay", zoi_hl_ratio = 5)

# R
expR <- calc_influence_cumulative(x = cabins, zoi = my_filter, type = "mfilter")
plot(expR)

# GRASS

# binarized map
cabins_bin_name <- "private_cabins_sub_bin"

# calculate cumulative influence
expG_name <- calc_influence_cumulative(x = cabins_bin_name, zoi = my_filter, type = "mfilter",
                                       where = "GRASS", quiet = F, overwrite = T)
# visualize
expG <- rgrass7::readRAST(expG_name) %>% 
  raster::raster() %>% 
  terra::rast()

terra::plot(c(expR, expG), 
            main = paste("User-defined filter - ", 
                         c("R", "GRASS")))

Multiple scales

# ZoI
zoi_vals <- c(2000, 3000, 4000, 5000)
my_filters <- purrr::map(zoi_vals, create_filter, r = 100, zoi_hl_ratio = 5)

# R
expR <- calc_influence_cumulative(x = cabins, zoi = my_filters, type = "mfilter")
plot(expR, main = paste("User-defined-window cum. influence, ZoI = ", zoi_vals))

# GRASS

# binarized map
cabins_bin_name <- "private_cabins_sub_bin"

expG_name <- calc_influence_cumulative(x = cabins_bin_name, zoi = my_filters, type = "mfilter",
                                       where = "GRASS", quiet = T, overwrite = T)
# visualize
expG <- rgrass7::readRAST(expG_name) %>% 
  raster::stack() %>% 
  terra::rast()

terra::plot(expG, main = paste("User-defined-window cum. influence, ZoI = ", zoi_vals))

NINAnor/oneimpact documentation built on June 14, 2025, 12:27 a.m.