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Workshop.R
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library(sf)
library(rgdal)
australia <- st_read("data/Australia/Australia_proj.shp")
australia
plot(australia)
plot(australia[2])
aus <- readOGR("data/Australia/Australia_proj.shp")
plot(australia$geometry)
plot(st_geometry(australia), axes = TRUE)
koala <- read.csv("data/koala.csv")
head(koala)
koala_sf <- st_as_sf(koala,
coords = c("Longitude", "Latitude"),
crs = 4326)
plot(koala_sf)
# load from packages ------------------------------------------------------
library(maps)
library(tidyverse)
data(world.cities)
world.cities
cities <- st_as_sf(world.cities,
coords = c("long", "lat"),
crs = 4326)
cities_aus <- filter(cities, country.etc == "Australia")
cities <- st_as_sf(world.cities,
coords = c("long", "lat"),
crs = 4326) %>%
filter(country.etc == "Australia") %>%
filter(pop > 1e6)
plot(cities["pop"], cex = cities$pop / 1e6)
# projection --------------------------------------------------------------
plot(australia$geometry)
plot(koala_sf, add = TRUE)
st_crs(australia)
st_crs(koala_sf)
koala_proj <- st_transform(koala_sf, crs = st_crs(australia))
plot(australia$geometry, axes = TRUE)
plot(koala_proj, add = TRUE)
# clipping maps -----------------------------------------------------------
st_bbox(koala_proj)
aus <- st_crop(australia, st_bbox(koala_proj))
plot(aus)
library(raster)
plot(australia$geometry, axes = TRUE)
ext <- drawExtent()
aus <- st_crop(australia, ext)
plot(aus$geometry)
# buffers -----------------------------------------------------------------
buf <- st_buffer(koala_proj, dist = 1.5e5)
plot(st_geometry(australia))
plot(koala_proj, add = TRUE, pch = 16, cex = 0.5)
plot(st_geometry(buf), add = TRUE, border = "red")
buf <- st_buffer(koala_proj, dist = 1.5e5) %>%
st_union()
plot(st_geometry(australia))
plot(koala_proj, add = TRUE, pch = 16, cex = 0.5)
plot(st_geometry(buf), add = TRUE, border = "red")
# intersection ------------------------------------------------------------
koala_sts <- st_intersection(koala_proj, australia)
plot(koala_sts["STATE"])
table(koala_sts$STATENAME)
# distance ----------------------------------------------------------------
costline <- st_union(australia) %>%
st_cast("MULTILINESTRING")
plot(costline)
koala_proj$dist <- as.numeric(st_distance(koala_proj, costline))
plot(costline$geometry)
plot(koala_proj["dist"], add = TRUE)
# self-distance
koala_dist <- st_distance(koala_proj, koala_proj)
head(koala_dist)
mindist <- function(x) {
mindis <- vector(mode = "numeric", length = nrow(x))
for(i in 1:nrow(x)){
mindis[i] <- min(x[i, -i])
}
return(mindis)
}
koala_proj$ndist <- mindist(koala_dist)
plot(koala_proj["ndist"])
# writing spatial ---------------------------------------------------------
st_write(koala_proj, "data/new_koala.gpkg")
st_read("data/new_koala.gpkg")
############## Rasters in R ################
library(rgdal)
library(raster)
library(tidyverse)
library(sf)
library(maps)
library(rgeos)
####################
r <- matrix(0,nrow =3 , ncol=3)
r[,1] <- c(1,2,3)
r[,2] <- c(5,6,7)
r[,3] <- c(8:10)
rr <- raster(r)
plot(rr)
res(rr)
ncol(rr)
nrow(rr)
ncell(rr)
crs(rr)
dim(rr)
range(values(rr))
cellStats(rr,mean)
#### read in a raster
au <- raster("data/australia.tif")
plot(au)
rasterlist_t <- list.files("data/wc_tavg",
pattern = ".tif$",
full.names = TRUE)
t_stack <- stack(rasterlist_t)
plot(t_stack)
rasterlist_p <- list.files("data/wc_prec",
pattern = ".tif$",
full.names = TRUE)
p_stack <- stack(rasterlist_p)
plot(p_stack)
t_stack_crop <- crop(t_stack, au)
plot(t_stack_crop[[1]])
t_stack_crop_mask <- mask(t_stack_crop,au)
plot(t_stack_crop_mask[[1]])
t_stack_au <- crop(t_stack, au) %>%
mask(au)
p_stack_au <- crop(p_stack, au) %>%
mask(au)
plot(p_stack_au[[1]])
plot(t_stack_au[[1]])
pmean <- mean(p_stack_au)
tmean <- mean(t_stack_au)
plot(pmean)
writeRaster(tmean, "tmean.tif",
format = "GTiff",
overwrite = TRUE)
test <- rr + rr
plot(test)
tcat <- matrix(0, nrow = 4, ncol = 3)
cellStats(tmean, quantile)
tcat[,1] <- c(4,19,22,25)
tcat[,2] <- c(19,22,25,30)
tcat[,3] <- c(1:4)
tcat_au <- reclassify(tmean,
tcat,
right=FALSE,
overwrite=TRUE)
plot(tcat_au)
pcat <- matrix(0, nrow = 2, ncol = 3)
cellStats(pmean, max)
pcat[,1] <- c(0,40)
pcat[,2] <- c(40,380)
pcat[,3] <- c(1:2)
pcat_au <- reclassify(pmean,
pcat,
right=FALSE,
overwrite=TRUE)
plot(pcat_au)
###### make categories combinations
climate_au <- tcat_au + (pcat_au *10)
plot(climate_au)
###### interactions
states <- st_read("data/AU_states.shp")
states1 <- as(states, "Spatial") #readOGR("data/AU_states.shp")
head(koala)
crs(koala_sf)
crs(climate_au)
crs(states)
crs(climate_au) <- crs("+proj=longlat +datum=WGS84 +no_defs")
st_crs(koala_sf) <- crs("+proj=longlat +datum=WGS84 +no_defs")
koala_climate <- raster::extract(climate_au,
koala_sf,
na.rm = TRUE)
hist(koala_climate)
table(koala_climate)
states_pr <- st_transform(states,
crs(climate_au))
crs(states_pr)
state_climate <- raster::extract(climate_au,
states_pr,
factors = TRUE,
df=TRUE,
na.rm = TRUE)
class.counts <- table(state_climate$ID,
state_climate$layer) %>%
as.matrix.data.frame() %>%
as.data.frame() %>%
setNames(paste0("class", c(11,12,13,14,21,22,23,24)))
class.counts$OBJECTID <- as.numeric(rownames(class.counts))
states_pr <- left_join(states_pr, class.counts, by = "OBJECTID")
plot(states_pr["class12"])
### plotting
par(mar = c(2,2,2,2))
plot(climate_au, legend = FALSE)
colors <- c("white", "yellow", "lightgreen", "darkgreen",
"lightblue", "blue", "purple", "red")
breaks <- c(10,11,12,13,14,21,22,23,24)
plot(climate_au, col = colors, breaks= breaks)
plot(states1, add = TRUE, border = "red", col = NA )
plot(koala_sf, add = TRUE, pch = 10)
maps::map.scale(120,-40, relwidth = 0.25,
metric = TRUE, ratio = false,
cex = 0.6)
par(xpd = NA)
leg <- c("dry cold", "dry cool", "dry warm", "dry hot",
"wet cold", "wet cool", "wet warm", "wet hot")
legend(155, y=-15, legend = leg, fill = colors)
# ggplot plotting --------------------------------------------------------
library(tidyverse)
library(viridis)
ncell(tmean)
sam <- sampleRegular(tmean, 5e5, asRaster = TRUE) %>%
as.data.frame(xy = TRUE, na.rm = TRUE)
head(sam)
ggplot(data = sam, aes(x = x, y = y, fill = layer)) +
geom_raster() +
scale_fill_viridis(option = "A") +
labs(x = "Longitude", y = "Latitude",
fill = "Temperature") +
coord_sf(crs = 4326) +
theme_bw()
ggplot() +
geom_sf(data = australia) +
geom_sf(data = koala_proj, alpha = 0.5,
aes(fill = as.factor(Species)), show.legend = "point") +
labs(x = "Longitude", y = "Latitude", fill = "Koala") +
theme_bw() +
theme(panel.background = element_rect(fill = "deepskyblue3"))
esquisse::esquisser()
library(mapview)
mapview(koala_sf)
library(mapedit)
editMap(mapview(koala_sf))
ggplot(data = wmap) +
geom_sf()