About this tutorial

Here you can find a quick tutorial how to create an overview map of an Area of Interst (AOI) on Svalbard with a Digital Elevation Model (DEM) as basemap.

The final plot can be saved and used in presentations, reports etc.

1. Setup packages

Install required packages

This is only necessary once, when the packages have never been installed before.

#install.packages("terra")
#install.packages("sf")
#install.packages("ggplot2")

Load required packages

These are the packages that are needed to create the maps

library(terra) #process raster data
library(sf) #process vector data
library(ggplot2) #create plots

2. Download and load DEM

A DEM is usually a large file therefore it has to be downloaded on you personal laptop for this tutorial. Here we use the DEM of Svalbard provided by the Norsk Polar institude. You can download it here.

# input data
dem_path <- "C:/Users/ronja/Documents/EAGLE/Svalbard/Data/Basemap/NP_S0_DTM20/S0_DTM20.tif" #path to dem

# load input data
dem_raster <- rast(dem_path) #Load DEM using the Terra package.

3. Create aoi layer

For our AOI we create a bounding box indicating the corners of our area of interest (AOI). We have to assign a coordinate system matching the one of the DEM. The coordinate system most commonly used in Svalbard is UTM zone 33N, so we define this first and assign it to the bounding box of our AOI.

# Define UTM zone and bounding box (Example: UTM Zone 33N)
utm_zone <- 33  # Change based on your location
utm_crs <- paste0("+proj=utm +zone=", utm_zone, " +datum=WGS84 +units=m +no_defs")

# Define bounding box for bjorndalen in UTM (Easting, Northing) 
utm_bbox <- st_sfc(st_polygon(list(matrix(c(
  505000 , 8676038,  # Bottom-left (E, N)
  509000 , 8676038,  # Bottom-right (E, N)
  509000 , 8684990,  # Top-right (E, N)
  505000 , 8684990, # Top-left (E, N)
  505000 , 8676038  #close polygon
), ncol = 2, byrow = TRUE))), crs = utm_crs)

4. Create a map of the AOI on Svalbard

We can first map Svalbard without the AOI.

To save processing time we crop the DEM to the exact extent of Svalbard, as well as aggregate it so reduce the resolution by the factor 5.

Note: GGplot only uses dataframes as input so we create a new variable with as.data.frame().

# Aggregate using mean (for continuous data)
# Define the cropping extent (xmin, xmax, ymin, ymax)
crop_extent <- ext(xmin(dem_raster), 775254 , 8473192, ymax(dem_raster))  # Define exact extent Svalbard

# Crop the raster
r_cropped <- crop(dem_raster, crop_extent) #crop the DEM to the extent defined earlier
r_agg <- aggregate(r_cropped, fact = 5, fun = mean) #aggregate pixels of DEM to reduce resolution and decrease processing time
dem_df <- as.data.frame(r_agg, xy = T)

Now we plot! More infos about ggplot and plotting rasters can be found here. You can change parameters like scale_fill_viridis_c(option = "E") or title and axis labeling.

gg_map_svalbard <- ggplot(data = dem_df) +
  geom_raster(aes(x = x, y = y, fill = S0_DTM20)) +
  scale_fill_viridis_c(option = "E") +
  theme_light() +
  theme(legend.position = "right") +
  labs(
    title = "DEM of Svalbard",
    x = "Longitude",
    y = "Latitude"
  ) +
  coord_sf(crs = st_crs(25833))

gg_map_svalbard

At last we add our AOI to the map that we just created and we can use ggsave() to save it as a image file.

gg_map_svalbard_box <- gg_map_svalbard +
    geom_sf(data=utm_bbox, colour = "red", fill = NA)

gg_map_svalbard_box

ggsave("gg_map_svalbard_box.png", plot = gg_map_svalbard_box, width = 8, height = 6, dpi = 300)


Using the function sessionInfo() gives insight into the R version, platform, packages and local settings to increase reproducibility and is good practice to include at the end of scripts.

sessionInfo() 
## R version 4.4.1 (2024-06-14 ucrt)
## Platform: x86_64-w64-mingw32/x64
## Running under: Windows 11 x64 (build 22631)
## 
## Matrix products: default
## 
## 
## locale:
## [1] LC_COLLATE=German_Germany.utf8  LC_CTYPE=German_Germany.utf8   
## [3] LC_MONETARY=German_Germany.utf8 LC_NUMERIC=C                   
## [5] LC_TIME=German_Germany.utf8    
## 
## time zone: Europe/Berlin
## tzcode source: internal
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] ggplot2_3.5.1 sf_1.0-18     terra_1.7-83 
## 
## loaded via a namespace (and not attached):
##  [1] sass_0.4.9         generics_0.1.3     class_7.3-22       KernSmooth_2.23-24
##  [5] digest_0.6.36      magrittr_2.0.3     evaluate_1.0.1     grid_4.4.1        
##  [9] fastmap_1.2.0      jsonlite_1.8.8     e1071_1.7-16       DBI_1.2.3         
## [13] viridisLite_0.4.2  scales_1.3.0       codetools_0.2-20   textshaping_0.4.0 
## [17] jquerylib_0.1.4    cli_3.6.3          rlang_1.1.4        units_0.8-5       
## [21] munsell_0.5.1      withr_3.0.2        cachem_1.1.0       yaml_2.3.10       
## [25] tools_4.4.1        dplyr_1.1.4        colorspace_2.1-1   vctrs_0.6.5       
## [29] R6_2.5.1           proxy_0.4-27       lifecycle_1.0.4    classInt_0.4-10   
## [33] ragg_1.3.3         pkgconfig_2.0.3    pillar_1.10.1      bslib_0.8.0       
## [37] gtable_0.3.6       glue_1.7.0         Rcpp_1.0.12        systemfonts_1.1.0 
## [41] xfun_0.49          tibble_3.2.1       tidyselect_1.2.1   highr_0.11        
## [45] rstudioapi_0.17.1  knitr_1.48         farver_2.1.2       htmltools_0.5.8.1 
## [49] rmarkdown_2.29     labeling_0.4.3     compiler_4.4.1