--- title: "Exercises 1" subtitle: "Medium level" format: html --- E1. Programmatically download borders of Germany. E2. Read the median (P50) global snow cover monthly values for December 2019 from https://zenodo.org/record/6011200/. E3. Limit the snow cover data extent to the area of Germany. E4. Transform the Germany borders and the Germany snow cover data to a local projection. E5. Create a map of the median (P50) Germany snow cover monthly values for December 2019 using the {tmap} package. Customize map colors, add a scale bar, north arrow, graticule lines, and a map title. E6. Save the map created in the previous exercise to a .png file. E7. Use the {supercells} package to create superpixels of similar snow cover monthly values for December 2019. Next, apply the `kmeans()` algorithm to derive six categories of superpixels. Visualize the results. E8: Dissolve the borders between superpixels belonging to the same category. Visualize the results. E9: Bonus 1: Download elevation data for Germany using the {elevatr} package. Visualize the previous results on top of a hillshade map. E10: Bonus 2: Derive clusters of superpixels again, but this time based on a raster time-series of the median (P50) Germany snow cover monthly values for every December between 2000 and 2019. Visualize the results.