demo/spacetime.R

In stars: Spatiotemporal Arrays, Raster and Vector Data Cubes

library(stars)

# wind:
library(gstat)
data(wind)
library(sp)
library(sf)

wind.loc$y = as.numeric(char2dms(as.character(wind.loc[["Latitude"]])))
wind.loc$x = as.numeric(char2dms(as.character(wind.loc[["Longitude"]])))
locs = st_as_sf(wind.loc, coords = c("x", "y"), crs = st_crs(4326))


# match order:

data = as.data.frame(t(wind[,-c(1:3)]))
data$geom = st_geometry(locs[match(names(wind)[-c(1:3)], locs$Code),])
wind_ = st_sf(data)
wind.st = merge(st_as_stars(wind_), times = ISOdate(wind$year+1900, wind$month, wind$day, 0))
plot(wind.st)

# Produc:
data(Produc, package = "plm")

library(maps)
states = st_as_sf(map('state', plot=FALSE, fill=TRUE))[-8,]
yrs = 1970:1986
#time = as.POSIXct(paste(yrs, "-01-01", sep=""), tz = "GMT")

Pr = lapply(Produc[order(Produc[2], Produc[1]),-(1:3)], matrix, nrow = nrow(states))
(Produc.st = st_as_stars(Pr, 
	dimensions = st_dimensions(sfc = st_geometry(states[-8]), times = yrs)))

plot(Produc.st[1], max.plot = 17)
plot(Produc.st[2], max.plot = 17)

# gridded example:
library(gstat)
example(krigeST)
library(stars)
s = st_as_stars(DE_kriged)
stplot(DE_kriged,scales=list(draw=T))
plot(s, axes = TRUE)
f = as(s, "STFDF")
# roundtrip:
summary(f@data - DE_kriged@data)