```{r 08-ex-e0, message=FALSE}

library(sf)

library(terra)

```

E1. List and describe three types of vector, raster, and geodatabase formats.

```{asis 08-ex-e0-asis}

Vector formats: Shapefile (old format supported by many programs), GeoPackage (more recent format with better support of attribute data) and GeoJSON (common format for web mapping).

Raster formats: GeoTiff, Arc ASCII, ERDAS Imagine (IMG).

Database formats: PostGIS, SQLite, FileGDB.

```

E2. Name at least two differences between the **sf** functions `read_sf()` and `st_read()`.

```{asis 08-ex-e2-asis}

`read_sf()` is simply a 'wrapper' around `st_read()`, meaning that it calls `st_read()` behind the scenes. The differences shown in the output of the `read_sf` are `quiet = TRUE`, `stringsAsFactors = FALSE`, and `as_tibble = TRUE`:

- `read_sf()` outputs are `quiet` by default, meaning less information printed to the console.

- `read_sf()` outputs are tibbles by default, meaning that they are data frames with some additional features.

- `read_sf()` does not convert strings to factors by default.

The differences can be seen by running the following commands `nc = st_read(system.file("shape/nc.shp", package="sf"))` and `nc = read_sf(system.file("shape/nc.shp", package="sf"))` from the function's help (`?st_read`).

```

```{r 08-ex-e2}

read_sf

nc = st_read(system.file("shape/nc.shp", package="sf"))

nc = read_sf(system.file("shape/nc.shp", package="sf"))

```

E3. Read the `cycle_hire_xy.csv` file from the **spData** package as a spatial object (Hint: it is located in the `misc` folder).

What is a geometry type of the loaded object?

```{r 08-ex-e3}

c_h = read.csv(system.file("misc/cycle_hire_xy.csv", package = "spData")) |>

st_as_sf(coords = c("X", "Y"))

c_h

```

E4. Download the borders of Germany using **rnaturalearth**, and create a new object called `germany_borders`.

Write this new object to a file of the GeoPackage format.

```{r 08-ex-e4}

library(rnaturalearth)

germany_borders = ne_countries(country = "Germany", returnclass = "sf")

plot(germany_borders)

st_write(germany_borders, "germany_borders.gpkg")

```

E5. Download the global monthly minimum temperature with a spatial resolution of 5 minutes using the **geodata** package.

Extract the June values, and save them to a file named `tmin_june.tif` file (hint: use `terra::subset()`).

```{r 08-ex-e5}

library(geodata)

gmmt = worldclim_global(var = "tmin", res = 5, path = tempdir())

names(gmmt)

plot(gmmt)

gmmt_june = terra::subset(gmmt, "wc2.1_5m_tmin_06")

plot(gmmt_june)

writeRaster(gmmt_june, "tmin_june.tif")

```

E6. Create a static map of Germany's borders, and save it to a PNG file.

```{r 08-ex-e6}

png(filename = "germany.png", width = 350, height = 500)

plot(st_geometry(germany_borders), axes = TRUE, graticule = TRUE)

dev.off()

```

E7. Create an interactive map using data from the `cycle_hire_xy.csv` file.

Export this map to a file called `cycle_hire.html`.

```{r 08-ex-e7, eval=FALSE}

library(mapview)

mapview_obj = mapview(c_h, zcol = "nbikes", legend = TRUE)

mapshot(mapview_obj, file = "cycle_hire.html")

```