1

Pick a address in Germany and geocode it through OSM. Make sure that the CRS is transformed to EPSG:3035.

If you’re not familiar with German places, you could, for example, choose between these three: - “B2,1 68159 Mannheim” - “Waldspirale, 64289 Darmstadt” - “Gustav-Stresemann-Ring 11, 65189 Wiesbaden” 
bboxing <- function(input_point) {
  sf::st_bbox(
    c(
      xmin = sf::st_coordinates(input_point)[1] - 1000,
      xmax = sf::st_coordinates(input_point)[1] + 1000,
      ymax = sf::st_coordinates(input_point)[2] + 1000,
      ymin = sf::st_coordinates(input_point)[2] - 1000
    ),
    crs = sf::st_crs(3035)
  )
}

2

Apply the bboxing function and store the results in a new object. What do you think is the function doing?

Note that we use a cut-out map of a specific place’s surroundings.

3

Please download data on roads using OpenStreetMap. You can use the “highways” plus “trunk”, “primary”, “secondary”, and “tertiary” as key/value pairs. Again, make sure that the CRS is transformed to EPSG:3035

This task was part of the session this morning. It’s part of this crazy pipe where you first define a bounding box using osmdata::getbb() and so on.

4

Crop the downloaded road data to the extent of the object you created in exercise “2”. We haven’t used the function before, but it’s the same as in the use of cropping raster data – it’s the sf::st_crop() function.

The first argument of the function is your downloaded road data, the second one the – psst! – bounding box from exercise “2”.

Use the following function for shearing and rotating your layers. Run the code first before applying it.

rotate_data <- function(data, x_add = 0, y_add = 0) {
  
  shear_matrix <- function () { 
    matrix(c(2, 1.2, 0, 1), 2, 2) 
  }
  
  rotate_matrix <- function(x) { 
    matrix(c(cos(x), sin(x), -sin(x), cos(x)), 2, 2) 
  }
  
  data %>% 
    dplyr::mutate(
      geometry = 
        .$geometry * shear_matrix() * rotate_matrix(pi/20) + c(x_add, y_add)
    )
}

5

Finally, plot the data as is, and then after or while rotating it with the rotate_data() function.

You can rotate the data either before calling gpplot() and store them in a separate object. Or, you can do that on the fly within the geom_sf() call.