Merge pull request #1100 from babayoshihiko/main

Some typos

01-introduction.Rmd

@@ -101,7 +101,7 @@ Geocomputation\index{geocomputation} implies working with geographic data in a r
 
 Early geographers used a variety of tools including barometers, compasses and [sextants](https://en.wikipedia.org/wiki/Sextant) to advance knowledge about the world [@wulf_invention_2015]. 
 It was only with the invention of the marine [chronometer](https://en.wikipedia.org/wiki/Marine_chronometer) in 1761 that it became possible to calculate longitude at sea, enabling ships to take more direct routes, for example.
-Before the turn of the century, there was an accute shortage of data and tools for geographic analysis.
+Before the turn of the century, there was an acute shortage of data and tools for geographic analysis.
 <!-- Using a sextant was a difficult-to-learn but essential tool for navigation in the 18th century.
 Likewise, learning to program and write and share reproducible code can be hard, but is a key skill for modern geocomputation. -->
 <!-- Maps were predominantly hand-drawn until modern computing enabled digitisation, a process which only become widespread in the 1990s and which is still ongoing [@gold_outsidein_1996; @auffret_histmapr_2017]. -->
@@ -380,7 +380,7 @@ The **mapsf** package (successor of **cartography**) was re-written to reduce de
 
 In late 2021, the planned retirement of **rgdal**, **rgeos** and **maptools** [was announced](https://stat.ethz.ch/pipermail/r-sig-geo/2021-September/028760.html) and in October 2023 they were archived on CRAN.
 This retirement at the end of 2023 has had a large impact on existing workflows applying these packages, but also [influenced the packages that depend on them](https://geocompx.org/post/2023/rgdal-retirement/). 
-Modern R packages such as **sf** and **terra**, described in \@ref(spatial-class) provide a strong and future-proof foundation for geocomputation that we build on in this book.
+Modern R packages such as **sf** and **terra**, described in Chapter \@ref(spatial-class) provide a strong and future-proof foundation for geocomputation that we build on in this book.
 
 ## Exercises
 

_09-ex.Rmd

@@ -55,7 +55,8 @@ mf_map(x = africa, var = "HDI", type = "choro")
 ```
 
 E2. Extend the **tmap** created for the previous exercise so the legend has three bins: "High" (`HDI` above 0.7), "Medium" (`HDI` between 0.55 and 0.7) and "Low" (`HDI` below 0.55).
-    - Bonus: improve the map aesthetics, for example by changing the legend title, class labels and color palette.
+
+- Bonus: improve the map aesthetics, for example by changing the legend title, class labels and color palette.
 
 ```{r}
 library(tmap)