Plot Multiple Shapefiles in R

Overview

Teaching: 40 min
Exercises: 20 min

Questions

• How can I create map compositions with custom legends using ggplot?

• How can I plot raster and vector data together?

Objectives

• Plot multiple shapefiles in the same plot.

• Apply custom symbols to spatial objects in a plot.

• Create a multi-layered plot with raster and vector data.

Things You’ll Need To Complete This Episode

See the lesson homepage for detailed information about the software, data, and other prerequisites you will need to work through the examples in this episode.

This episode builds upon the previous episode to work with shapefile attributes in R and explores how to plot multiple shapefiles. It also covers how to plot raster and vector data together on the same plot.

Load the Data

To work with vector data in R, we can use the sf library. The raster package also allows us to explore metadata using similar commands for both raster and vector files. Make sure that you have these packages loaded.

We will continue to work with the three shapefiles that we loaded in the Open and Plot Shapefiles in R episode. The three shapefiles are:

• aoi_boundary_HARV layer of the “data/vector/HarClip_UTMZ18.shp”
• lines_HARV layer of the “data/vector/HARV_roads.shp”
• point_HARV layer of the “data/vector/HARVtower_UTM18N.shp”

Plotting Multiple Shapefiles

In the previous episode, we learned how to plot information from a single shapefile and do some plot customization including adding a custom legend. However, what if we want to create a more complex plot with many shapefiles and unique symbols that need to be represented clearly in a legend?

Now, let’s create a plot that combines our tower location (point_HARV), site boundary (aoi_boundary_HARV) and roads (lines_HARV) spatial objects. We will need to build a custom legend as well.

To begin, we will create a plot with the site boundary as the first layer. Then layer the tower location and road data on top using +.

ggplot() + 
  geom_sf(data = aoi_boundary_HARV) +
  geom_sf(data = lines_HARV) +
  geom_sf(data = point_HARV) +
  ggtitle("NEON Harvard Forest Field Site") + 
  coord_sf()

Now that we have a basic plot, we can customize it by changing the symbology, or the look of the data by changing the fill and the color. We will change the aoi_boundary_HARV to be solid gray. Because we want to show the different types of paths at this site, we will also have the color of the lines_HARV data be set according to the TYPE attribute. Doing this will also create a legend for our plot. And finally, because we also want to includ tower location in the legend, we will have the fill of the point_HARV data be set according to the Sub_type attribute.

ggplot() + 
  geom_sf(data = aoi_boundary_HARV, fill = "grey", color = "grey") +
  geom_sf(data = lines_HARV, aes(color = TYPE)) +
  geom_sf(data = point_HARV, aes(fill = Sub_Type)) +
  ggtitle("NEON Harvard Forest Field Site") + 
  coord_sf()

Next, let’s build a custom legend using the symbology (the colors and symbols) that we used to create the plot above. We will use ggplot2 functions to specify the symbology and change the names of the legends. We will add lines for the color or the lines and the fill of the points. We will also adjust the legend titles by passing a name to the respective color and fill palettes.

ggplot() + 
  geom_sf(data = aoi_boundary_HARV, color = "gray", fill = "grey") +
  geom_sf(data = lines_HARV, aes(color = TYPE)) +
  geom_sf(data = point_HARV, aes(fill = Sub_Type), color = "black") +
  scale_color_manual(values = road_colors, name = "Path Type") +
  scale_fill_manual(values = "black", name = "Tower Location") +
  ggtitle("NEON Harvard Forest Field Site") + 
  coord_sf()

Finally, it might be better if the points were symbolized as a symbol. We can customize this using shape parameters in our call to geom_sf: 16 is a point symbol, 15 is a box.

Data Tip

To view a short list of shape symbols, type ?pch into the R console.

ggplot() + 
  geom_sf(data = aoi_boundary_HARV, color = "gray", fill = "grey") +
  geom_sf(data = lines_HARV, aes(color = TYPE)) +
  geom_sf(data = point_HARV, aes(fill = Sub_Type), color = "black", shape = 15) +
  scale_color_manual(values = road_colors, name = "Path Type") +
  scale_fill_manual(values = "black", name = "Tower Location") +
  ggtitle("NEON Harvard Forest Field Site") + 
  coord_sf()

Challenge: Plot Polygon by Attribute

1. Using the PlotLocations_HARV.shp shapefile, create a map of study plot locations, with each point colored by the soil type (soilTypeOr). How many different soil types are there at this particular field site? Overlay this layer on top of the lines_HARV layer (the roads). Create a custom legend that applies line symbols to lines and point symbols to the points.

2. Modify the plot above. Tell R to plot each point, using a different symbol of shape value.

Answers

If the CHM data are not already loaded from previous episodes, load the raster and convert to a data frame. You will need the raster package to do this.

library(raster) CHM_HARV <- raster(“data/raster/HARV_chmCrop.tif”) CHM_HARV_df <- as.data.frame(CHM_HARV, xy = TRUE) First we need to read in the data and see how many unique soils are represented in the soilTypeOr attribute.

plot_locations <- st_read("data/vector/PlotLocations_HARV.shp")

Reading layer `PlotLocations_HARV' from data source `/home/travis/build/UW-Madison-DataScience/r-raster-vector-geospatial/_episodes_rmd/data/vector/PlotLocations_HARV.shp' using driver `ESRI Shapefile'
Simple feature collection with 21 features and 25 fields
geometry type:  POINT
dimension:      XY
bbox:           xmin: 731405.3 ymin: 4712845 xmax: 732275.3 ymax: 4713846
CRS:            32618

unique(plot_locations$soilTypeOr)

[1] "Inceptisols" "Histosols"  

Next we can create a new color palette with one color for each soil type.

blue_green <- c("lightblue", "darkgreen")

Finally, we will create our plot.

ggplot() + 
  geom_sf(data = lines_HARV, aes(color = TYPE)) + 
  geom_sf(data = plot_locations, aes(fill = soilTypeOr), shape = 21) + 
  scale_color_manual(name = "Line Type", values = road_colors) + 
  scale_fill_manual(name = "Soil Type", values = blue_green) + 
  ggtitle("NEON Harvard Forest Field Site") + 
  coord_sf()

If we want each soil to be shown with a different symbol, we can give multiple values to the scale_shape_manual() argument.

ggplot() + 
  geom_sf(data = lines_HARV, aes(color = TYPE)) + 
  geom_sf(data = plot_locations, aes(fill = soilTypeOr, shape = soilTypeOr)) + 
  scale_color_manual(name = "Line Type", values = road_colors) + 
  scale_fill_manual(name = "Soil Type", values = blue_green) +
  scale_shape_manual(name = "Soil Type", values = c(21, 22)) +
  ggtitle("NEON Harvard Forest Field Site") + 
  coord_sf()

Challenge: Plot Raster & Vector Data Together

You can plot vector data layered on top of raster data using the + to add a layer in ggplot. Create a plot that uses the NEON AOI Canopy Height Model HARV_chmCrop.tif as a base layer. On top of the CHM, please add:

• The study site AOI
• Roads
• The tower location

Be sure to give your plot a meaningful title.

Answers

ggplot() +
  geom_raster(data = CHM_HARV_df, aes(x = x, y = y, fill = HARV_chmCrop)) +
  geom_sf(data = lines_HARV, color = "black") +
  geom_sf(data = aoi_boundary_HARV, color = "grey20", size = 1) +
  geom_sf(data = point_HARV, pch = 8) +
  ggtitle("NEON Harvard Forest Field Site w/ Canopy Height Model") + 
  coord_sf()

Key Points

• Use the + operator to add multiple layers to a ggplot.

• Multi-layered plots can combine raster and vector datasets.

• Use the show.legend argument to set legend symbol types.

• Use the scale_fill_manual() function to set legend colors.