Geospatial Analytics Utilities
gisr
is not on CRAN, so you will have to install it directly from rOpenSci or GitHub using the code found below.
## SETUP
# Pre-requisits - gisr user rnaturalearthdata and rnaturalearthhires
remotes::install_github("ropensci/rnaturalearth")
remotes::install_github("ropensci/rnaturalearthhires")
#install from rOpenSci
install.packages('gisr', repos = c('https://usaid-oha-si.r-universe.dev', 'https://cloud.r-project.org'))
#alt: install from GitHub using pak
#install.packages("pak")
#pak::pak("USAID-OHA-SI/gisr")
#load the package
library(gisr)
## LIST TYPES OF STYLES INCLUDED WITH PACKAGE
ls("package:gisr")
Admin boundaries + neighbor countries data from Natural Earth Data
library(tidyverse)
library(sf)
library(gisr)
zambia0 <- get_admin0("Zambia")
zambia1 <- get_admin1("Zambia")
zambia_neighbors <- geo_neighbors("Zambia")
ggplot(data = zambia_neighbors) +
geom_sf(fill = NA) +
geom_sf(data = zambia1, fill = gray(.92), lty = "dashed") +
geom_sf(data = zambia0, fill = NA) +
geom_sf_text(aes(label = sovereignt), size = 3) +
theme_void()
Create a terrain map with vector + raster data from local DEM Tiff file
library(tidyverse)
library(sf)
library(gisr)
dem_dir <- "./GIS"
z_map1 <- terrain_map("Zambia", terr_path = dir_terr)
print(z_map1)
z_map2 <- terrain_map("Zambia", terr_path = dir_terr, add_neighbors = TRUE)
print(z_map2)
Create an administrative map with vector data from RNaturalEarth
library(systemfonts)
library(tidyverse)
library(sf)
library(glitr)
library(gisr)
z_map1 <- admins_map("Zambia")
print(z_map1)
z_map2 <- admins_map("Zambia", add_neighbors = TRUE)
print(z_map2)
Create an administrative map with vector data from RNaturalEarth and apply SI Style
library(systemfonts)
library(tidyverse)
library(gisr)
library(sf)
library(glitr)
sfdf <- gisr::get_admin1("Nigeria") %>%
select(name) %>%
mutate(value = runif(nrow(.), 0, 1))
ggplot() +
geom_sf(data = sfdf,
aes(fill = value),
color = grey10k,
size = .1) +
scale_fill_si(palette = "genoas",
discrete = FALSE,
limits = c(0, 1),
labels = scales::percent) +
labs(title = "NIGERIA - % OF PLHIV BY STATE",
subtitle = "States from XYZ Region are the most hit by HIV/AIDS",
caption = base::paste0("Produced by OHA/SIEI/SI, ON ", base::Sys.Date())) +
si_style_map()
Disclaimer: The findings, interpretation, and conclusions expressed herein are those of the authors and do not necessarily reflect the views of United States Agency for International Development. All errors remain our own.