-
+
+
03:00
+
+
Explore and plot by vector layer attributes
Challenge 2: π 3 mins
+Challenge 2: π 3 mins
Explore the attributes associated with the point_Delft and boundary_Delft spatial objects.
- How many attributes does each have? @@ -398,7 +487,7 @@
- Create a new object that only contains the motorways in Delft.
- How many features does the new object have? @@ -418,15 +520,35 @@
- make the lines where bicycles are not allowed THINNER than the roads where bicycles are allowed. +
- Make the lines where bicycles are not allowed THINNER than the roads where bicycles are allowed.
- Be sure to add a title and legend to your map.
- You might consider a color palette that has all bike-friendly roads displayed in a bright color. All other lines can be black.
- Use the data located in your data folder:
nl-gemeenten.shp.
@@ -471,12 +621,24 @@ color each point by the leisure type.
+Color each point by the leisure type.
Overlay this layer on top of the
lines_Delftlayer (the streets).Create a custom legend that applies line symbols to lines and point symbols to the points.
Extra: Modify the previous plot. Tell R to plot each point, using a different symbol of shape value.
- Import
nl-gemeenten.shpand filter only the municipalities in South Holland.
@@ -518,13 +702,26 @@
Challenge 2: π 3 mins
β£ A) location B) leisure C) osm_id
-
+
+
@@ -406,9 +495,22 @@
03:00
Challenge 2: π 3 mins
+
+
Challenge 3: π 5 mins
+Challenge 3: π’ 5 mins
Challenge 3: π 5 mins
-
+
+
05:00
+
+
+
+levels(factor(lines_Delft$highway))
+
+motorway_Delft <- lines_Delft %>%
+ filter(highway == "motorway")
+
+motorway_Delft %>%
+ mutate(length = st_length(.)) %>%
+ select(everything(), geometry) %>%
+ summarise(total_length = sum(length))
+
+nrow(motorway_Delft)
+
+ggplot(data = motorway_Delft) +
+ geom_sf(size = 1.5) +
+ ggtitle("Mobility network of Delft", subtitle = "Motorways") +
+ coord_sf()Challenge 4: β° 3 mins
+Challenge 4: π 3 mins
In the previous example, we set the line widths to be 1, 0.75, 0.5, and 0.25. In our case line thicknesses are consistent with the hierarchy of the selected road types, but in some cases we might want to show a different hierarchy.
Letβs create another plot where we show the different line types with the following thicknesses:
-
@@ -437,32 +559,60 @@
Challenge 4: β° 3 mins
-
+
+
03:00
+
+
+
+levels(factor(lines_Delft$highway))
+
+line_widths <- c(0.25, 0.75, 0.5, 1)
+
+ggplot(data = lines_Delft_selection) +
+ geom_sf(aes(size = highway)) +
+ scale_size_manual(values = line_widths) +
+ labs(size = "Road Size") +
+ ggtitle("Mobility network of Delft", subtitle = "Roads & Cycleways - Line width varies") +
+ coord_sf()Challenge 5: π° 5 mins
+Challenge 5: π‘ 5 mins
Create a plot that emphasizes only roads where bicycles are allowed, as follows:
-
-
-
+
+
05:00
+
+
+
+levels(factor(lines_Delft_selection$highway))
+
+lines_Delft_bicycle <- lines_Delft %>%
+ filter(highway == "cycleway")
+
+ggplot() +
+ geom_sf(data = lines_Delft) +
+ geom_sf(data = lines_Delft_bicycle, color = "magenta", size = 2) +
+ ggtitle("Mobility network of Delft", subtitle = "Roads dedicated to bikes") +
+ coord_sf()Challenge 6: π 3 mins
+Challenge 6: π 3 mins
Create a map of the municipal boundaries in the Netherlands, as follows:
Challenge 6: π 3 mins
-
+
+
03:00
+
+
+
+municipal_boundaries_NL <- st_read(here("episodes", "data", "nl-gemeenten.shp"))
+str(municipal_boundaries_NL)
+levels(factor(municipal_boundaries_NL$ligtInPr_1))
+
+ggplot(data = municipal_boundaries_NL) +
+ geom_sf(aes(color = ligtInPr_1), size = 1) +
+ ggtitle("Contiguous NL Municipal Boundaries") +
+ coord_sf()Plot multiple shapefiles
Challenge 7: π 5 mins
+Challenge 7: π 5 mins
Create a map of leisure locations only including playground and picnic_table:
-
-
-
+
+
05:00
+
+
+
+leisure_locations_selection <- st_read(here("episodes", "data", "delft-leisure.shp")) %>%
+ filter(leisure %in% c("playground", "picnic_table"))
+
+blue_orange <- c("cornflowerblue", "darkorange")
+
+p <- ggplot() +
+ geom_sf(data = lines_Delft_selection, aes(color = highway)) +
+ scale_color_manual(name = "Line Type", values = road_colors) +
+ ggtitle("Road network and leisure")
+
+p +
+ geom_sf(data = leisure_locations_selection, aes(fill = leisure), shape = 21) +
+ scale_fill_manual(name = "Leisure Type", values = blue_orange)
+
+p +
+ geom_sf(data = leisure_locations_selection, aes(fill = leisure, shape = leisure), size = 3) +
+ scale_fill_manual(name = "Leisure Type", values = blue_orange) +
+ scale_shape_manual(name = "Leisure Type", values = c(21, 22))Handle spatial projections
+Handling spatial projections
Challenge 8: π 3 mins
+Challenge 8: π° 3 mins
Create a map of the South Holland, as follows:
Challenge 8: π 3 mins
-
+
03:00
+
diff --git a/instructors/2-vector-slides.qmd b/instructors/2-vector-slides.qmd
index 11224511..bf668f22 100644
--- a/instructors/2-vector-slides.qmd
+++ b/instructors/2-vector-slides.qmd
@@ -46,19 +46,23 @@ knitr::opts_chunk$set(
```
-## `sf` package for spatial vector data
+# Intro to Geospatial Concepts
+
+# Geospatial Vector Data in R
+
+## The `sf` package
{fig-align="center"}
-## `sf` package for spatial vector data
+## The `sf` package
- `sf` provides [simple features access](https://en.wikipedia.org/wiki/Simple_Features) to R
-- represents simple features as records in a `data.frame` or `tibble` with a `geometry` column
+- represents simple features as records in a data frame with a `geometry` column
- function names start with a prefix `st_` ("st" stands for spatial type), which is also handy for auto-completion in RStudio
# Open and Plot Shapefiles
-## Challenge 1: `r emo::ji("clock")` **3 mins**
+## Challenge 1: `r emo::ji("clock")` **5 mins**
Read in `delft-streets.shp` and `delft-leisure.shp` and call them `lines_Delft` and `point_Delft` respectively.
@@ -80,13 +84,13 @@ countdown::countdown(minutes = 3)
```{r}
#| label: ch-1
#| eval: false
-#| include: false
+#| include: true
lines_Delft <- st_read(here("episodes", "data", "delft-streets.shp"))
point_Delft <- st_read(here("episodes", "data", "delft-leisure.shp"))
-class(lines_Delft)
-class(point_Delft)
+st_geometry_type(lines_Delft)
+st_geometry_type(point_Delft)
st_crs(lines_Delft)
st_crs(point_Delft)
@@ -121,7 +125,7 @@ countdown::countdown(minutes = 3)
```{r}
#| label: ch-2
#| eval: false
-#| include: false
+#| include: true
ncol(point_Delft)
ncol(boundary_Delft)
@@ -152,7 +156,7 @@ countdown::countdown(minutes = 5)
```{r}
#| label: ch-3
#| eval: false
-#| include: false
+#| include: true
levels(factor(lines_Delft$highway))
@@ -170,16 +174,6 @@ ggplot(data = motorway_Delft) +
geom_sf(size = 1.5) +
ggtitle("Mobility network of Delft", subtitle = "Motorways") +
coord_sf()
-
-pedestrian_Delft <- lines_Delft %>%
- filter(highway == "pedestrian")
-
-nrow(pedestrian_Delft)
-
-ggplot(data = pedestrian_Delft) +
- geom_sf() +
- ggtitle("Slow mobility network of Delft", subtitle = "Pedestrian") +
- coord_sf()
```
## Challenge 4: `r emo::ji("clock")` **3 mins**
@@ -203,7 +197,7 @@ countdown::countdown(minutes = 3)
```{r}
#| label: ch-4
#| eval: false
-#| include: false
+#| include: true
levels(factor(lines_Delft$highway))
@@ -221,7 +215,7 @@ ggplot(data = lines_Delft_selection) +
Create a plot that emphasizes only roads where bicycles are allowed, as follows:
-- make the lines where bicycles are not allowed THINNER than the roads where bicycles are allowed.
+- Make the lines where bicycles are not allowed THINNER than the roads where bicycles are allowed.
- Be sure to add a title and legend to your map.
- You might consider a color palette that has all bike-friendly roads displayed in a bright color. All other lines can be black.
@@ -235,9 +229,7 @@ countdown::countdown(minutes = 5)
```{r}
#| label: ch-5
#| eval: false
-#| include: false
-
-class(lines_Delft_selection$highway)
+#| include: true
levels(factor(lines_Delft_selection$highway))
@@ -267,9 +259,9 @@ countdown::countdown(minutes = 3)
. . .
```{r}
-#| label: ch-6
+#| label: ch-6-1
#| eval: false
-#| include: false
+#| include: true
municipal_boundaries_NL <- st_read(here("episodes", "data", "nl-gemeenten.shp"))
str(municipal_boundaries_NL)
@@ -287,7 +279,7 @@ ggplot(data = municipal_boundaries_NL) +
Create a map of leisure locations only including `playground` and `picnic_table`:
-- color each point by the leisure type.
+- Color each point by the leisure type.
- Overlay this layer on top of the `lines_Delft` layer (the streets).
- Create a custom legend that applies line symbols to lines and point symbols to the points.
@@ -303,39 +295,29 @@ countdown::countdown(minutes = 5)
```{r}
#| label: ch-7
#| eval: false
-#| include: false
+#| include: true
-leisure_locations_selection <- st_read(here("data", "delft-leisure.shp")) %>%
+leisure_locations_selection <- st_read(here("episodes", "data", "delft-leisure.shp")) %>%
filter(leisure %in% c("playground", "picnic_table"))
-levels(factor(leisure_locations_selection$leisure))
-
blue_orange <- c("cornflowerblue", "darkorange")
-ggplot() +
+p <- ggplot() +
geom_sf(data = lines_Delft_selection, aes(color = highway)) +
- geom_sf(data = leisure_locations_selection, aes(fill = leisure),
- shape = 21, show.legend = 'point') +
- scale_color_manual(name = "Line Type", values = road_colors,
- guide = guide_legend(override.aes = list(linetype = "solid", shape = NA))) +
- scale_fill_manual(name = "Soil Type", values = blue_orange,
- guide = guide_legend(override.aes = list(linetype = "blank", shape = 21, colour = NA))) +
- ggtitle("Traffic and leisure") +
- coord_sf()
+ scale_color_manual(name = "Line Type", values = road_colors) +
+ ggtitle("Road network and leisure")
-ggplot() +
- geom_sf(data = lines_Delft_selection, aes(color = highway), size = 1) +
- geom_sf(data = leisure_locations_selection, aes(fill = leisure, shape = leisure), size = 3) +
- scale_shape_manual(name = "Leisure Type", values = c(21, 22)) +
- scale_color_manual(name = "Line Type", values = road_colors) +
- scale_fill_manual(name = "Leisure Type", values = rainbow(15),
- guide = guide_legend(override.aes = list(linetype = "blank", shape = c(21, 22),
- color = "black"))) +
- ggtitle("Road network and leisure") +
- coord_sf()
+p +
+ geom_sf(data = leisure_locations_selection, aes(fill = leisure), shape = 21) +
+ scale_fill_manual(name = "Leisure Type", values = blue_orange)
+
+p +
+ geom_sf(data = leisure_locations_selection, aes(fill = leisure, shape = leisure), size = 3) +
+ scale_fill_manual(name = "Leisure Type", values = blue_orange) +
+ scale_shape_manual(name = "Leisure Type", values = c(21, 22))
```
-# Handle spatial projections
+# Handling spatial projections
## Challenge 8: `r emo::ji("clock")` **3 mins**
@@ -357,7 +339,7 @@ countdown::countdown(minutes = 3)
```{r}
#| label: ch-8
#| eval: false
-#| include: false
+#| include: true
boundary_ZH <- municipal_boundary_NL %>%
filter(ligtInPr_1 == "Zuid-Holland")
diff --git a/instructors/2-vector-slides_files/figure-revealjs/ch-6-2-1.png b/instructors/2-vector-slides_files/figure-revealjs/ch-6-2-1.png
new file mode 100644
index 00000000..7777697c
Binary files /dev/null and b/instructors/2-vector-slides_files/figure-revealjs/ch-6-2-1.png differ
+
+
boundary_ZH <- municipal_boundary_NL %>%
+ filter(ligtInPr_1 == "Zuid-Holland")
+
+ggplot() +
+ geom_sf(data = boundary_ZH, aes(color ="color"), show.legend = "line") +
+ scale_color_manual(name = "", labels = "Municipal Boundaries", values = c("color" = "gray18")) +
+ geom_sf(data = boundary_Delft, aes(shape = "shape"), color = "purple", fill = "purple") +
+ scale_shape_manual(name = "", labels = "Municipality of Delft", values = c("shape" = 19)) +
+ ggtitle("Delft location in South Holland") +
+ theme(legend.background = element_rect(color = NA)) +
+ coord_sf()Geospatial Data Carpentry for Urbanism