Last updated: 2021-04-24
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Knit directory: wildlife-bacteria/
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ozmaps#ozmaps data not on CRAN
#devtools::install_github("mdsumner/ozmaps.data")Load libraries
pkgs <- c("ozmaps", "sf", "sp", "dplyr", "rgdal",
"raster", "ggplot2", "viridis", "readr",
"paletteer", "rmapshaper", "ggrepel",
"tidyverse", "ozmaps.data", "readxl")
lapply(pkgs, require, character.only = TRUE)Import data
site_map <- read_excel("data/site_map.xlsx")
site_map_lab = column_to_rownames(site_map, var = "Site name")site_map <- read_excel(“data/site_map.xlsx”, col_types = c(“text”, “text”, “numeric”, “numeric”, “text”, “numeric”))
OzmapsSimple Aus map
ozmap()Plot of states
sf_oz <- ozmap_data("states")
if (utils::packageVersion("paletteer") < '1.0.0') {
pal <- paletteer::paletteer_d(package = "ochRe", palette = "namatjira_qual")
} else {
pal <- paletteer::paletteer_d(palette = "ochRe::namatjira_qual")
}
mycols = c("#a19a11", "#D3D3D3", "#D3D3D3", "#D3D3D3", "#D3D3D3", "#D3D3D3", "#D3D3D3", "#365350", "#a19a11", "#3f4482")
opal <- colorRampPalette(pal)
nmjr <- opal(nrow(sf_oz))
plot(st_geometry(sf_oz), col = mycols)Plot the ABS layers (from 2016).
ozmap("abs_ced", col = opal(nrow(abs_ced)))Plot of map with city regions abs_gccsa
citycols = c("#D3D3D3", "#3f4482", "#D3D3D3", "#D3D3D3", "#D3D3D3", "#D3D3D3", "#D3D3D3", "#D3D3D3", "#3f4482", "#D3D3D3", "#D3D3D3", "#D3D3D3", "#D3D3D3", "#D3D3D3", "#D3D3D3", "#D3D3D3")
plot(st_transform(abs_gccsa, LCC), main = "Greater Capital City Statistical Areas", col = citycols)Enlarge northern beaches
library(dplyr)
kbor <- abs_lga %>% dplyr::filter(grepl("Northern Beaches", NAME))
bb <- st_bbox(kbor)
layout(matrix(c(1, 1, 1, 2, 2, 2, 2, 2, 2), nrow = 3))
plot(kbor, reset = FALSE, main = "Northern Beaches (NSW)")
rect(bb["xmin"], bb["ymin"], bb["xmax"], bb["ymax"])
library(mapdata)
#> Loading required package: maps
par(mar = rep(0, 4))
plot(c(110, 160), c(-45, -5), type = "n", asp = 1/cos(mean(bb[c(2, 4)]) * pi/180), axes = FALSE, xlab = "", ylab = "")
plot = maps::map(database = "worldHires", regions = "australia", xlim = c(110, 160), ylim = c(-45, -5), add = TRUE)
rect(bb["xmin"], bb["ymin"], bb["xmax"], bb["ymax"])
buffer <- 0.11
min_lon <- 110
max_lon <- 160
min_lat <- -45
max_lat <- -5
geo_bounds <- c(left = min_lon, bottom = min_lat, right = max_lon, top = max_lat)oz_states <- ozmaps::ozmap_states
ggplot(oz_states) +
geom_sf() +
coord_sf()
oz_states <- ozmaps::ozmap_states %>% filter(NAME != "Other Territories")
oz_votes <- rmapshaper::ms_simplify(ozmaps::abs_ced)
ggplot() +
geom_sf(data = oz_states, mapping = aes(fill = NAME), show.legend = FALSE) +
geom_sf(data = oz_votes, fill = NA) +
coord_sf()
# large map
map1 = ggplot() +
geom_sf(data = oz_votes) +
geom_sf(data = oz_states, colour = "black", fill = "NA") +
geom_point(data = site_map_lab, mapping = aes(x = lon, y = lat, color = Site, shape=Site, size= Size)) +
coord_sf() + theme_classic() + theme(legend.position = "none", axis.title.x = element_blank(), axis.title.y = element_blank()) + scale_color_manual(values=c("#E69F00", "#56B4E9")) + scale_shape_manual(values=c(8, 16)) + xlim (114,155)
# base map for inserts
map2 = ggplot() +
geom_sf(data = oz_votes) +
geom_sf(data = oz_states, colour = "black", fill = "NA") +
geom_point(data = site_map_lab, mapping = aes(x = lon, y = lat, color = Site, shape=Site, size= Size)) +
coord_sf() + theme_classic() + theme(legend.position = "none", axis.title.x = element_blank(), axis.title.y = element_blank()) + scale_color_manual(values=c("#999999", "#E69F00"))
# zoom in on Sydney region
map3 = map2 + coord_sf(xlim = c(150, 152), ylim = c(-35, -33.0)) + theme(legend.position = "none") + theme(axis.title.x = element_blank(), axis.title.y = element_blank())
map4 = map2 + coord_sf(xlim = c(115, 117), ylim = c(-32.5, -31)) + theme(legend.position = "none") + theme(axis.title.x = element_blank(), axis.title.y = element_blank())
ggsave("map_base.pdf", plot = map1, path = "output/plots", width = 30, height = 15, units = "cm")
ggsave("map_NSW.pdf", plot = map3, path = "output/plots", width = 10, height = 10, units = "cm")
ggsave("map_WA.pdf", plot = map4, path = "output/plots", width = 10, height = 10, units = "cm")Capital cities
oz_capitals <- tibble::tribble(
~city, ~lat, ~lon,
"Sydney", -33.8688, 151.2093,
"Melbourne", -37.8136, 144.9631,
"Brisbane", -27.4698, 153.0251,
"Adelaide", -34.9285, 138.6007,
"Perth", -31.9505, 115.8605,
"Hobart", -42.8821, 147.3272,
"Canberra", -35.2809, 149.1300,
"Darwin", -12.4634, 130.8456,
)Following tutorial at this link
Load libraries
pkgs <- c("sp", "dplyr", "rgdal",
"raster", "ggplot2", "readxl",
"viridis", "readr")
lapply(pkgs, require, character.only = TRUE)Load your point data file
site_map <- read_excel("data/site_map.xlsx")Create buffer around your data points
# Make boundaries
buffer <- 0.11
min_lon <- 110
max_lon <- 160
min_lat <- -45
max_lat <- -5
geo_bounds <- c(left = min_lon, bottom = min_lat, right = max_lon, top = max_lat)
# Now map with boundaries
Sites.grid <- expand.grid(lon_bound = c(geo_bounds[1], geo_bounds[3]),
lat_bound = c(geo_bounds[2], geo_bounds[4]))
coordinates(Sites.grid) <- ~ lon_bound + lat_boundLoad mapping files Downloaded from GEODATA COAST 100K 2004 shapefiles available here
Aus <- readOGR(dsn = "~/Documents/Programs/R/Maps/Rpackage_Geodata-coast/australia",layer = "cstauscd_r")Remove coastline clutter from map
Aus_coast <- subset(Aus, FEAT_CODE != "sea")
plot <- plot(Aus_coast)Now apply boundaries to the map without coastline
Aus_crop <- crop(Aus_coast, extent(Sites.grid))
plot(Aus_crop)Plot map with axis
aus_plot1 <- ggplot() +
geom_polygon(data = Aus_crop, aes(x=long, y=lat, group=group), fill = "gray98", colour="black") +
coord_equal() +
labs(x="Longitude", y="Latitude") +
theme_classic()
aus_plot2 = aus_plot1 + geom_point(data = site_map, aes (x=lon, y=lat, color=Site, stroke=1)) +
geom_text(label=(site_map$Site)) + scale_color_brewer(palette = "Set1") + theme_classic()
ggsave("aus_plot2.pdf", plot = aus_plot2, path = "output/plots", width = 15, height = 15, units = "cm")# load library
library(OpenStreetMap)
# extract map
AustraliaMap <- openmap(c(-8,110),
c(-45,160),
# type = "osm",
# type = "esri",
type = "nps",
minNumTiles=7)
plot(AustraliaMap)
library(DT)
opt <- c("osm", "osm-bw","maptoolkit-topo", "waze", "bing", "stamen-toner", "stamen-terrain", "stamen-watercolor", "osm-german", "osm-wanderreitkarte", "mapbox", "esri", "esri-topo", "nps", "apple-iphoto", "skobbler", "hillshade", "opencyclemap", "osm-transport", "osm-public-transport", "osm-bbike", "osm-bbike-german")
opt <- data.frame(opt)
# extract map
queensland1 <- openmap(c(-8,135),
c(-30,160),
type = "osm",
minNumTiles=6)
queensland2 <- openmap(c(-8,135),
c(-30,160),
type = "esri",
minNumTiles=6)
# plot maps
par(mfrow = c(1, 2)) # display plots in 1 row/2 columns
plot(queensland1); plot(queensland2); par(mfrow = c(1, 1)) # restore original settingsLeaflet here
# load package
library(leaflet)
# load library
m <- leaflet() %>% setView(lng = 153.05, lat = -27.45, zoom = 12)
# display map
m %>% addTiles()
# add ERSI theme
esri <- grep("^Esri", providers, value = TRUE)
m %>% addTiles() %>% addLayersControl(baseGroups = names(esri))
leaflet(data = site_map) %>% addTiles() %>%
addMarkers(~lon, ~lat, icon=oceanIcons)