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vignettes/examples_topo_Africa.Rmd

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+---
+title: "tmap example: topographic map (Africa)"
+output: 
+  bookdown::html_vignette2:
+pkgdown:
+  as_is: true
+template:
+  math-rendering: mathjax
+bibliography: '`r system.file("tmap.bib", package="tmap")`'
+csl: "`r system.file('ieee.csl', package = 'tmap')`"
+editor_options: 
+  chunk_output_type: console
+---
+
+```{r, include = FALSE}
+knitr::opts_chunk$set(
+  collapse = TRUE,
+  out.width = "100%",
+  dpi = 300,
+  fig.width = 7.2916667,
+  comment = "#>"
+)
+hook_output <- knitr::knit_hooks$get("output")
+knitr::knit_hooks$set(output = function(x, options) {
+   lines <- options$output.lines
+   if (is.null(lines)) {
+     return(hook_output(x, options))  # pass to default hook
+   }
+   x <- unlist(strsplit(x, "\n"))
+   more <- "..."
+   if (length(lines)==1) {        # first n lines
+     if (length(x) > lines) {
+       # truncate the output, but add ....
+       x <- c(head(x, lines), more)
+     }
+   } else {
+     x <- c(more, x[lines], more)
+   }
+   # paste these lines together
+   x <- paste(c(x, ""), collapse = "\n")
+   hook_output(x, options)
+ })
+
+```
+
+```{r, message = FALSE}
+library(tmap)
+library(dplyr)
+library(sf)
+tmap_options(scale = 0.75)
+```
+
+
+## About the data
+
+We use several spatial data object that are contained in tmap. The first is called `World`, which we only use for country borders. We'll only select the African countries:
+
+```{r}
+metroAfrica = sf::st_intersection(metro, World[World$continent == "Africa", ])
+Africa = World[World$continent == "Africa", ]
+```
+
+The second is `land` which is a `stars` object that contains land cover. The third object is `metro` an `sf` object with metropolitan areas. The fourth and final ovject is `World_rivers`.
+
+## Topographic map
+
+```{r, fig.height = 6}
+tm_shape(land) +
+  tm_raster("cover_cls",
+    col.legend = tm_legend("Land use")) +
+tm_shape(World_rivers) +
+  tm_lines(
+  	lwd = "strokelwd", 
+  	lwd.scale = tm_scale_asis(values.scale = .5),
+    col = "#A6CEE3") +
+tm_shape(Africa, is.main = TRUE) +
+  tm_borders() +
+tm_shape(metroAfrica) +
+  tm_symbols(fill = "red", shape = "pop2020", size = "pop2020",
+    size.scale = tm_scale_intervals(
+      breaks = c(1, 2, 5, 10, 15, 20, 25) * 1e6,
+      values.range = c(0.2,2)
+    ),
+    size.legend = tm_legend("Population in 2020"),
+    shape.scale = tm_scale_intervals(
+      breaks = c(1, 2, 5, 10, 15, 20, 25) * 1e6,
+      values = c(21, 23, 22, 21, 23, 22)
+    ),
+    shape.legend = tm_legend_combine("size")) +
+  tm_labels("name") +
+tm_credits("United Nations, Department of Economic and Social Affairs, Population Division (2014). World Urbanization Prospects.\nProduction of Global Land Cover Data - GLCNMO2008.", position = tm_pos_out("center", "bottom"))
+```
+
+## Breaking down in layers
+
+If this code chunk is overwhelming, let's that a look at the layer groups:
+
+### Land use layer
+
+```{r, fig.height = 3.5}
+tm = 
+tm_shape(land) +
+  tm_raster("cover_cls",
+    col.legend = tm_legend("Land use"))
+tm
+```
+
+
+### Adding rivers
+
+```{r, fig.height = 3.5}
+tm = tm + 
+tm_shape(World_rivers) +
+  tm_lines(
+  	lwd = "strokelwd", 
+  	lwd.scale = tm_scale_asis(values.scale = .5),
+    col = "#A6CEE3")
+tm
+```
+
+### African countries
+
+Note that the first two layers are from a global data set (so not just Africa). 
+Note that in the final plot this raster is cropped to the bounding box of Africa.
+We'll use `is.main` for the the spatial object `Africa` to do the actual cropping.
+
+```{r, fig.height = 6}
+tm = tm +
+tm_shape(Africa, is.main = TRUE) +
+  tm_borders()
+tm
+```
+
+### African cities
+
+```{r, fig.height = 6}
+tm = tm +
+tm_shape(metroAfrica) +
+  tm_symbols(fill = "red", shape = "pop2020", size = "pop2020",
+    size.scale = tm_scale_intervals(
+      breaks = c(1, 2, 5, 10, 15, 20, 25) * 1e6,
+      values.range = c(0.2,2)
+    ),
+    size.legend = tm_legend("Population in 2020"),
+    shape.scale = tm_scale_intervals(
+      breaks = c(1, 2, 5, 10, 15, 20, 25) * 1e6,
+      values = c(21, 23, 22, 21, 23, 22)
+    ),
+    shape.legend = tm_legend_combine("size")) +
+  tm_labels("name")
+tm
+```
+
+See the [vigette about scale](https://r-tmap.github.io/tmap/articles/basics_scales) and [about legends](https://r-tmap.github.io/tmap/articles/basics_legends).