sdc: Swiss Data Cube

#' ---
#' title: "Create Corine land cover data for Switzerland"
#' author: "RS-eco"
#' ---

# Downloaded from https://land.copernicus.eu/pan-european/corine-land-cover

# Specify file directory
filedir <- "/home/matt/Documents/Corine/DATA/"

# Load packages
library(raster); library(dplyr)

# Load outline of Switzerland
#che <- getData('GADM', country='CHE', level=0)
load("data/che.rda")

# Load files
cha_files <- list.files(filedir, pattern=".*_CHA.*\\.tif$", full.names=T)
clc_files <- list.files(filedir, pattern=".*_CLC.*\\.tif$", full.names=T)
clc_dat <- lapply(clc_files, raster::raster)
cha_dat <- lapply(cha_files, raster::raster)
clc_dat
cha_dat

# Re-project outline data
che <- sp::spTransform(che, crs(clc_dat[[1]]))

# Crop data
clc_dat <- lapply(clc_dat, function(x) mask(crop(x, che), che))
clc_dat <- stack(clc_dat)
cha_dat <- lapply(cha_dat, function(x) mask(crop(x, che), che))
cha_dat <- stack(cha_dat)

# Plot data
plot(clc_dat[[1]])
plot(che, add=T)

plot(cha_dat[[2]])
plot(che, add=T)

# Turn into data.frame
corine_lc_che <- clc_dat %>% raster::rasterToPoints() %>% as.data.frame()
colnames(corine_lc_che) <- c("x", "y", 1990, 2000, 2006, 2012, 2018)
cha_layers <- c("9000_00", "9000_90", "0006_00", "0006_06", "0612_06", "0612_12", "1218_12", "1218_18")
corine_cha_che <- as.data.frame(raster::rasterToPoints(cha_dat))
colnames(corine_cha_che) <- c("x", "y", cha_layers)

head(corine_lc_che)
unique(corine_lc_che$`1990`)
unique(corine_lc_che$`2000`)
unique(corine_lc_che$`2006`)
unique(corine_lc_che$`2012`)
unique(corine_lc_che$`2018`)

# See labels and color code in clc_legend_qgis_raster.qml

# Define categories
corine_lc_che <- corine_lc_che %>%
  mutate_at(vars(-c(x,y)), factor, levels = c(1:44, 48), 
            labels=c("Continuous urban fabric","Discontinuous urban fabric","Industrial or commercial units",
                     "Road and rail networks and associated land","Port areas","Airports","Mineral extraction sites","Dump sites",
                     "Construction sites","Green urban areas","Sport and leisure facilities","Non-irrigated arable land",
                     "Permanently irrigated land", "Rice fields", "Vineyards", "Fruit trees and berry plantations", "Olive groves",
                     "Pastures", "Annual crops associated with permanent crops", "Complex cultivation patterns",
                     "Land principally occupied by agriculture with significant areas of natural vegetation",
                     "Agro-forestry areas","Broad-leaved forest", "Coniferous forest", "Mixed forest", "Natural grasslands",
                     "Moors and heathland", "Sclerophyllous vegetation", "Transitional woodland-shrub", "Beaches dunes sands",
                     "Bare rocks", "Sparsely vegetated areas", "Burnt areas", "Glaciers and perpetual snow", "Inland marshes",
                     "Peat bogs", "Salt marshes", "Salines", "Intertidal flats", "Water courses", "Water bodies",
                     "Coastal lagoons", "Estuaries", "Sea and ocean", "NODATA"))

library(ggplot2)
corine_lc_che %>% ggplot() + geom_tile(aes(x=x, y=y, fill=`2000`)) + coord_sf() + 
  theme(legend.position="bottom")
#ggsave("corine_lc_che.png", width=10, height=10, dpi=600)

# Save to file
save(corine_lc_che, file="data/corine_lc_che.rda", compress="xz")

head(corine_cha_che)
tail(corine_cha_che)
corine_cha_che <- corine_cha_che %>% mutate_at(vars(-c(x,y)), function(x) factor(x, levels = c(1:44, 48, 128), 
                                                                labels=c("Continuous urban fabric","Discontinuous urban fabric","Industrial or commercial units",
                                                                         "Road and rail networks and associated land","Port areas","Airports","Mineral extraction sites","Dump sites",
                                                                         "Construction sites","Green urban areas","Sport and leisure facilities","Non-irrigated arable land",
                                                                         "Permanently irrigated land", "Rice fields", "Vineyards", "Fruit trees and berry plantations", "Olive groves",
                                                                         "Pastures", "Annual crops associated with permanent crops", "Complex cultivation patterns",
                                                                         "Land principally occupied by agriculture with significant areas of natural vegetation",
                                                                         "Agro-forestry areas","Broad-leaved forest", "Coniferous forest", "Mixed forest", "Natural grasslands",
                                                                         "Moors and heathland", "Sclerophyllous vegetation", "Transitional woodland-shrub", "Beaches dunes sands",
                                                                         "Bare rocks", "Sparsely vegetated areas", "Burnt areas", "Glaciers and perpetual snow", "Inland marshes",
                                                                         "Peat bogs", "Salt marshes", "Salines", "Intertidal flats", "Water courses", "Water bodies",
                                                                         "Coastal lagoons", "Estuaries", "Sea and ocean", "NODATA", "NA")))
corine_cha_che <- corine_cha_che[rowSums(corine_cha_che=="NA")<8,]
head(corine_cha_che)
save(corine_cha_che, file="data/corine_cha_che.rda", compress="xz")
rm(list=ls()); gc()