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(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)

# 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"))

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

a <- rgrass7::execGRASS("r.category", map = "patches", flags = "quiet")
attributes(a)$resOut
rgrass7::execGRASS("g.list", type = "raster")

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

Euclidean distance

# R
cabins_dist_r <- calc_influence_nearest(cabins, where = "R")

# GRASS
name_var <- "private_cabins_sub"
cabins_dist_names <- calc_influence_nearest(name_var, where = "GRASS", quiet = F, overwrite = T)

# visualize
cabins_dist_grass <- readRAST(cabins_dist_names) %>% 
  raster::raster() %>% 
  terra::rast()

terra::plot(c(cabins_dist_r, cabins_dist_grass), 
            main = paste("Euclidean distance from private cabins - ", 
                         c("R", "GRASS")))

Log distance

# R
cabins_logdist_r <- calc_influence_nearest(cabins, transform = "log", log_base = 10, where = "R")

# GRASS
name_var <- "private_cabins_sub"
cabins_logdist_names <- calc_influence_nearest(name_var, transform = "log", log_base = 10, 
                                               where = "GRASS", quiet = F, overwrite = T)

# visualize
cabins_logdist_grass <- readRAST(cabins_logdist_names) %>% 
  raster::raster() %>% 
  terra::rast()

terra::plot(c(cabins_logdist_r, cabins_logdist_grass), 
            main = paste("Log-distance from private cabins - ", 
                         c("R", "GRASS")))

Square root distance

# R
cabins_sqrtdist_r <- calc_influence_nearest(cabins, transform = "sqrt", where = "R")

# GRASS
name_var <- "private_cabins_sub"
cabins_sqrtdist_names <- calc_influence_nearest(name_var, transform = "sqrt", 
                                               where = "GRASS", quiet = F, overwrite = T)

# visualize
cabins_sqrtdist_grass <- readRAST(cabins_sqrtdist_names) %>% 
  raster::raster() %>% 
  terra::rast()

terra::plot(c(cabins_sqrtdist_r, cabins_sqrtdist_grass), 
            main = paste("Sqrt-distance from private cabins - ", 
                         c("R", "GRASS")))

Exponental decay influence

Example with ZoI = 1000m

# R
cabins_exp_decay_r <- calc_influence_nearest(cabins, transform = "exp_decay", 
                                             zoi = 1000, where = "R")

# GRASS
name_var <- "private_cabins_sub"
cabins_exp_decay_names <- calc_influence_nearest(name_var, transform = "exp_decay",
                                                 zoi = 1000, where = "GRASS", 
                                                 quiet = F, overwrite = T)

# visualize
cabins_exp_decay_grass <- readRAST(cabins_exp_decay_names) %>% 
  raster::raster() %>% 
  terra::rast()

terra::plot(c(cabins_exp_decay_r, cabins_exp_decay_grass), 
            main = paste("Exp-decay influence from private cabins - ", 
                         c("R", "GRASS")))

Bartlett decay

Example with ZoI = 1000m

# R
cabins_bartlett_r <- calc_influence_nearest(cabins, transform = "bartlett",
                                            zoi = 1000, where = "R")

# GRASS
name_var <- "private_cabins_sub"
cabins_bartlett_names <- calc_influence_nearest(name_var, transform = "bartlett",
                                                zoi = 1000, where = "GRASS",
                                                quiet = F, overwrite = T)

# visualize
cabins_bartlett_grass <- readRAST(cabins_bartlett_names) %>% 
  raster::raster() %>% 
  terra::rast()

terra::plot(c(cabins_bartlett_r, cabins_bartlett_grass), 
            main = paste("Linear-decay influence from private cabins - ", 
                         c("R", "GRASS")))

Half-normal (Gaussian) decay influence

Example with ZoI = 1000m

# R
cabins_hnorm_decay_r <- calc_influence_nearest(cabins, transform = "half_norm",
                                               zoi = 1000, where = "R")

# GRASS
name_var <- "private_cabins_sub"
cabins_hnorm_decay_names <- calc_influence_nearest(name_var, transform = "half_norm",
                                                   zoi = 1000, where = "GRASS",
                                                   quiet = T, overwrite = T)

# visualize
cabins_exp_decay_grass <- readRAST(cabins_hnorm_decay_names) %>% 
  raster::raster() %>% 
  terra::rast()

terra::plot(c(cabins_hnorm_decay_r, cabins_exp_decay_grass), 
            main = paste("Halfnormal influence from private cabins - ", 
                         c("R", "GRASS")))

# Euclidean distance
# name_var <- "private_cabins_sub"
# execGRASS("r.resamp.filter", input = name_var, output = "test_neighborhood", filter = "gauss,box", radius = c(500,1500))
# 
# execGRASS("r.mapcalc", expression = "private_cabins_binary = if(isnull(private_cabins_sub), 0, 1)", flags = "overwrite")
# 
# execGRASS("r.neighbors", input = "private_cabins_binary", output = "test_neighborhood", size = 5, flags = "overwrite")
# 
# Zone of Influence
# cumulative zone of influence
# cumulative affected area
# landcape effect, cumulative weight - "Miguet et al"
# Perceived disturbance
# 
# multiply two layers referreing to two different scales of a variable density
# 
# # visualize
# cabins_dens <- readRAST("test_neighborhood") %>% 
#   raster::raster() %>% 
#   terra::rast()
# 
# terra::plot(cabins_dens, main = "Density")
# 
# threshold = 0.05
# execGRASS("r.mapcalc", expression = "areas = if(test_neighborhood > 0.05, 1, 0)", flags = "overwrite")
# 
# cabins_areas_affected <- readRAST("areas") %>% 
#   raster::raster() %>% 
#   terra::rast()
# 
# terra::plot(cabins_areas_affected, main = "areas affected")
# 
# #
# execGRASS("g.extension", extension = "r.area")
# 
# execGRASS("r.clump", input = "areas", output = "patches", flags = "overwrite")
# 
# cabins_areas_patches <- readRAST("patches") %>% 
#   raster::raster() %>% 
#   terra::rast()
# 
# terra::plot(cabins_areas_affected, main = "patch areas affected")

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