Deploy commit: improves style 144b77c

02-spatial-data.md

@@ -36,6 +36,8 @@ install.packages("spData")
 install.packages("spDataLarge", repos = "https://nowosad.r-universe.dev")
 ```
 
+<!-- toDo: explain (maybe also move tmapv4 to main) -->
+
 
 ```r
 remotes::install_github("r-tmap/tmap@v4")
@@ -888,15 +890,6 @@ india_buffer_without_s2 = st_buffer(india, 1)
 #> dist is assumed to be in decimal degrees (arc_degrees).
 ```
 
-
-```
-#> 
-#> Attaching package: 'tmap'
-#> The following object is masked from 'package:datasets':
-#> 
-#>     rivers
-```
-
 <div class="figure" style="text-align: center">
 <img src="02-spatial-data_files/figure-html/s2example-1.png" alt="Example of the consequences of turning off the S2 geometry engine. Both representations of a buffer around India were created with the same command but the purple polygon object was created with S2 switched on, resulting in a buffer of 1 m. The larger light green polygon was created with S2 switched off, resulting in a buffer with inaccurate units of degrees longitude/latitude." width="100%" />
 <p class="caption">(\#fig:s2example)Example of the consequences of turning off the S2 geometry engine. Both representations of a buffer around India were created with the same command but the purple polygon object was created with S2 switched on, resulting in a buffer of 1 m. The larger light green polygon was created with S2 switched off, resulting in a buffer with inaccurate units of degrees longitude/latitude.</p>

03-attribute-operations.md

@@ -16,14 +16,6 @@ library(dplyr)   # tidyverse package for data frame manipulation
 
 ```r
 library(spData)  # spatial data package introduced in Chapter 2
-#> The legacy packages maptools, rgdal, and rgeos, underpinning the sp package,
-#> which was just loaded, will retire in October 2023.
-#> Please refer to R-spatial evolution reports for details, especially
-#> https://r-spatial.org/r/2023/05/15/evolution4.html.
-#> It may be desirable to make the sf package available;
-#> package maintainers should consider adding sf to Suggests:.
-#> The sp package is now running under evolution status 2
-#>      (status 2 uses the sf package in place of rgdal)
 ```
 
 - Also ensure you have installed the **tidyr** package, or the **tidyverse** of which it is a part, if you want to run data 'tidying' operations in Section \@ref(vec-attr-creation).

05-geometry-operations.md

@@ -80,7 +80,6 @@ Therefore, the first step is to project the data into some adequate projected CR
 
 ```r
 us_states2163 = st_transform(us_states, "EPSG:2163")
-us_states2163 = us_states2163
 ```
 
 `st_simplify()` works equally well with projected polygons:

09-mapping.md

@@ -301,7 +301,7 @@ This figure shows four ways of coloring regions in New Zealand depending on medi
 ```r
 tm_shape(nz) + tm_polygons(fill = "Median_income")
 tm_shape(nz) + tm_polygons(fill = "Median_income",
-                           fill.scale = tm_scale(breaks = c(0, 30000, 40000, 50000)))
+                        fill.scale = tm_scale(breaks = c(0, 30000, 40000, 50000)))
 tm_shape(nz) + tm_polygons(fill = "Median_income",
                            fill.scale = tm_scale(n = 10))
 tm_shape(nz) + tm_polygons(fill = "Median_income",
@@ -378,8 +378,10 @@ Sequential palettes can be single (`greens` goes from light to dark blue, for ex
 
 
 ```r
-tm_shape(nz) + tm_polygons("Median_income", fill.scale = tm_scale(values = "greens"))
-tm_shape(nz) + tm_polygons("Median_income", fill.scale = tm_scale(values = "yl_gn_bu"))
+tm_shape(nz) + 
+  tm_polygons("Median_income", fill.scale = tm_scale(values = "greens"))
+tm_shape(nz) + 
+  tm_polygons("Median_income", fill.scale = tm_scale(values = "yl_gn_bu"))
 ```
 
 The third group, diverging palettes, typically range between three distinct colors (purple-white-green in Figure \@ref(fig:colpal)) and are usually created by joining two single-color sequential palettes with the darker colors at each end.
@@ -390,7 +392,8 @@ The reference point's value can be adjusted in **tmap** using the `midpoint` arg
 ```r
 tm_shape(nz) + 
   tm_polygons("Median_income",
-              fill.scale = tm_scale_continuous(values = "pu_gn_div", midpoint = 28000))
+              fill.scale = tm_scale_continuous(values = "pu_gn_div", 
+                                               midpoint = 28000))
 ```
 
 <div class="figure" style="text-align: center">
@@ -433,9 +436,10 @@ Other than that, we can also customize the location of the legend using the `pos
 
 ```r
 map_nza2 = tm_shape(nz) +
-  tm_polygons(fill = "Land_area", fill.legend = tm_legend(title = legend_title,
-                                                          orientation = "landscape",
-                                                          position = tm_pos_out("center", "bottom")))
+  tm_polygons(fill = "Land_area",
+              fill.legend = tm_legend(title = legend_title,
+                                      orientation = "landscape",
+                                      position = tm_pos_out("center", "bottom")))
 ```
 
 The legend position (and also the position of several other map elements in **tmap**) can be customized using one of a few functions.
@@ -1206,15 +1210,6 @@ nz_carto = cartogram_cont(nz, "Median_income", itermax = 5)
 tm_shape(nz_carto) + tm_polygons("Median_income")
 ```
 
-
-```
-#> Warning: Some legend items or map compoments do not fit well (e.g. due to the
-#> specified font size).
-
-#> Warning: Some legend items or map compoments do not fit well (e.g. due to the
-#> specified font size).
-```
-
 <div class="figure" style="text-align: center">
 <img src="09-mapping_files/figure-html/cartomap1-1.png" alt="Comparison of standard map (left) and continuous area cartogram (right)." width="100%" />
 <p class="caption">(\#fig:cartomap1)Comparison of standard map (left) and continuous area cartogram (right).</p>

10-gis.md

@@ -163,28 +163,12 @@ Both polygon datasets are available in the **spData** package, and for both we w
 
 
 ```r
+
 data("incongruent", "aggregating_zones", package = "spData")
 incongr_wgs = st_transform(incongruent, "EPSG:4326")
 aggzone_wgs = st_transform(aggregating_zones, "EPSG:4326")
 ```
 
-
-```
-#> The legacy packages maptools, rgdal, and rgeos, underpinning the sp package,
-#> which was just loaded, will retire in October 2023.
-#> Please refer to R-spatial evolution reports for details, especially
-#> https://r-spatial.org/r/2023/05/15/evolution4.html.
-#> It may be desirable to make the sf package available;
-#> package maintainers should consider adding sf to Suggests:.
-#> The sp package is now running under evolution status 2
-#>      (status 2 uses the sf package in place of rgdal)
-#> 
-#> Attaching package: 'tmap'
-#> The following object is masked from 'package:datasets':
-#> 
-#>     rivers
-```
-
 <div class="figure" style="text-align: center">
 <img src="10-gis_files/figure-html/uniondata-1.png" alt="Illustration of two areal units: incongruent (black lines) and aggregating zones (red borders)." width="100%" />
 <p class="caption">(\#fig:uniondata)Illustration of two areal units: incongruent (black lines) and aggregating zones (red borders).</p>
@@ -938,11 +922,9 @@ library(rstac)
 # and search for images intersecting our AOI
 s = stac("https://earth-search.aws.element84.com/v0")
 items = s |>
-  stac_search(
-    collections = "sentinel-s2-l2a-cogs",
-    bbox = c(7.1, 51.8, 7.2, 52.8),
-    datetime = "2020-01-01/2020-12-31"
-  ) |>
+  stac_search(collections = "sentinel-s2-l2a-cogs",
+              bbox = c(7.1, 51.8, 7.2, 52.8),
+              datetime = "2020-01-01/2020-12-31") |>
   post_request() |>
   items_fetch()
 ```
@@ -1011,36 +993,26 @@ p = processes() # load available processes
 collections = list_collections() # load available collections
 formats = list_file_formats() # load available output formats
 # Load Sentinel-2 collection
-s2 = p$load_collection(
-  id = "SENTINEL2_L2A",
-  spatial_extent = list(
-    west = 7.5, east = 8.5,
-    north = 51.1, south = 50.1
-  ),
-  temporal_extent = list("2021-01-01", "2021-01-31"),
-  bands = list("B04", "B08")
-)
+s2 = p$load_collection(id = "SENTINEL2_L2A",
+                       spatial_extent = list(west = 7.5, east = 8.5,
+                                             north = 51.1, south = 50.1),
+                       temporal_extent = list("2021-01-01", "2021-01-31"),
+                       bands = list("B04", "B08"))
 # Compute NDVI vegetation index
-compute_ndvi = p$reduce_dimension(
-  data = s2, dimension = "bands",
-  reducer = function(data, context) {
-    (data[2] - data[1]) / (data[2] + data[1])
-  }
-)
+compute_ndvi = p$reduce_dimension(data = s2, dimension = "bands",
+                                  reducer = function(data, context) {
+                                      (data[2] - data[1]) / (data[2] + data[1])
+                                  })
 # Compute maximum over time
-reduce_max = p$reduce_dimension(
-  data = compute_ndvi, dimension = "t",
-  reducer = function(x, y) {
-    max(x)
-  }
-)
+reduce_max = p$reduce_dimension(data = compute_ndvi, dimension = "t",
+                                reducer = function(x, y) {
+                                    max(x)
+                                })
 # Export as GeoTIFF
 result = p$save_result(reduce_max, formats$output$GTiff)
 # Login, see https://docs.openeo.cloud/getting-started/r/#authentication
-login(
-  login_type = "oidc", provider = "egi",
-  config = list(client_id = "...", secret = "...")
-)
+login(login_type = "oidc", provider = "egi", 
+      config = list(client_id = "...", secret = "..."))
 # Execute processes
 compute_result(graph = result, output_file = tempfile(fileext = ".tif"))
 ```

16-synthesis.md

@@ -24,14 +24,6 @@ The code chunk below illustrates this by using three functions, covered in Chapt
 
 ```r
 library(spData)
-#> The legacy packages maptools, rgdal, and rgeos, underpinning the sp package,
-#> which was just loaded, will retire in October 2023.
-#> Please refer to R-spatial evolution reports for details, especially
-#> https://r-spatial.org/r/2023/05/15/evolution4.html.
-#> It may be desirable to make the sf package available;
-#> package maintainers should consider adding sf to Suggests:.
-#> The sp package is now running under evolution status 2
-#>      (status 2 uses the sf package in place of rgdal)
 nz_u1 = sf::st_union(nz)
 nz_u2 = aggregate(nz["Population"], list(rep(1, nrow(nz))), sum)
 nz_u3 = dplyr::summarise(nz, t = sum(Population))

404.html

@@ -129,7 +129,7 @@ <h2>Note: Second Edition is under construction 🏗</h2>
 <footer class="bg-primary text-light mt-5"><div class="container"><div class="row">
 
   <div class="col-12 col-md-6 mt-3">
-    <p>"<strong>Geocomputation with R</strong>" was written by Robin Lovelace, Jakub Nowosad, Jannes Muenchow. It was last built on 2023-08-25.</p>
+    <p>"<strong>Geocomputation with R</strong>" was written by Robin Lovelace, Jakub Nowosad, Jannes Muenchow. It was last built on 2023-08-26.</p>
   </div>
 
   <div class="col-12 col-md-6 mt-3">