LCDB symbology in R

1 Purpose

The goal of lcdb_symbology in my isaacr package is to colour the symbology of the Land Cover Database (LCDB) in a way that is consistent with the Manaaki Whenua Landcare Research (MWLR)’s original symbology. MWLR provide a .lyr file for use with ArcGIS (or with QGIS via a plugin), but this repo provides a way to use the same symbology in R or ggplot2 or other non-GIS software.

2 Usage

To load the LCDB symbology, use the load_lcdb_symbology function. This will return a data frame with the following columns: Class, Colour, and Name. The Class column contains the class code, the Colour column contains the colour in HEX format, and the Name column contains the name of the land cover class.

# install.packages("devtools")
# devtools::install_github("isaacbain/isaacr")
library(isaacr)

# load data 
landcover_df <- load_lcdb_symbology()

3 Table of colours

Here’s a table of the colours used in the LCDB symbology. Extracted from XML in the original .lyr file.

Class Code	Colour	HEX Code	Landcover Class
1	Built-up Area (settlement)	#9c9c9c	Built-up Area (settlement)
6	Surface Mines and Dumps	#704489	Surface Mines and Dumps
5	Transport Infrastructure	#a80000	Transport Infrastructure
2	Urban Parkland/Open Space	#688578	Urban Parkland/Open Space
10	Sand or Gravel	#ffff73	Sand or Gravel
12	Landslide	#ca7af5	Landslide
15	Alpine Grass/Herbfield	#abcd66	Alpine Grass/Herbfield
16	Gravel or Rock	#9cba9c	Gravel or Rock
14	Permanent Snow and Ice	#dbd4ff	Permanent Snow and Ice
20	Lake or Pond	#bee8ff	Lake or Pond
21	River	#bee8ff	River
22	Estuarine Open Water	#d6f5e8	Estuarine Open Water
30	Short-rotation Cropland	#ffd37f	Short-rotation Cropland
33	Orchard Vineyard and Other Perennial Crops	#e69800	Orchard Vineyard and Other Perennial Crops
40	High Producing Exotic Grassland	#beff8c	High Producing Exotic Grassland
41	Low Producing Grassland	#a3d400	Low Producing Grassland
43	Tall Tussock Grassland	#e6e68c	Tall Tussock Grassland
44	Depleted Grassland	#d2d25a	Depleted Grassland
45	Herbaceous Freshwater Vegetation	#c2ffd6	Herbaceous Freshwater Vegetation
46	Herbaceous Saline Vegetation	#def5de	Herbaceous Saline Vegetation
47	Flaxland	#7af5ca	Flaxland
50	Fernland	#705c00	Fernland
51	Gorse and/or Broom	#7d690f	Gorse and/or Broom
52	Manuka and/or Kanuka	#8c7922	Manuka and/or Kanuka
54	Broadleaved Indigenous Hardwoods	#a8994f	Broadleaved Indigenous Hardwoods
55	Sub Alpine Shrubland	#b8ab6a	Sub Alpine Shrubland
56	Mixed Exotic Shrubland	#c4bb89	Mixed Exotic Shrubland
58	Matagouri or Grey Scrub	#d4cdae	Matagouri or Grey Scrub
80	Peat Shrubland (Chatham Is)	#bfcdae	Peat Shrubland (Chatham Is)
81	Dune Shrubland (Chatham Is)	#d4c27a	Dune Shrubland (Chatham Is)
64	Forest - Harvested	#a1ad61	Forest - Harvested
68	Deciduous Hardwoods	#477f00	Deciduous Hardwoods
69	Indigenous Forest	#284600	Indigenous Forest
71	Exotic Forest	#38a800	Exotic Forest
70	Mangrove	#448989	Mangrove
0	Not land	#000000	Not land

4 Examples

4.1 ggplot2

Here’s an example of how to use the LCDB symbology in ggplot2. Let’s make a map of Christchurch, and another one of Blenheim.

library(ggplot2)
library(sf)

# for ggplot2, load named vector
lcdb_colours_vector <- load_lcdb_vector()

# Plot using ggplot2 with scale_fill_manual
ggplot(data = lcdb5_chch) + # lcdb5_chch available in the isaacr package, and it lazy-loads - so just refer to it
  geom_sf(aes(fill = as.factor(Class_2018)), color = NA) +
  scale_fill_manual(values = lcdb_colours_vector) +
  theme_void() +
  theme(legend.position = "none")

# Plot using ggplot2 with scale_fill_manual
ggplot(data = lcdb5_blenheim) +
  geom_sf(aes(fill = as.factor(Class_2018)), color = NA) +
  scale_fill_manual(values = lcdb_colours_vector) +
  theme_void() +
  theme(legend.position = "none")

4.2 Leaflet

Here’s an example of how to use the LCDB symbology in leaflet.

library(leaflet)

lcdb5_chch <- lcdb5_chch |> 
  left_join(landcover_df, by = c("Class_2018" = "Class"))

# Create a leaflet map of Christchurch
leaflet(data = lcdb5_chch |> st_transform(4326)) %>%
  addTiles() %>%
  addPolygons(
    fillColor = ~Colour,
    weight = 0, # Border thickness
    fillOpacity = 1,
    popup = ~paste(Name)
  )

lcdb5_blenheim <- lcdb5_blenheim |> 
  left_join(landcover_df, by = c("Class_2018" = "Class"))

# Create a leaflet map of Blenheim
leaflet(data = lcdb5_blenheim |> st_transform(4326)) %>%
  addTiles() %>%
  addPolygons(
    fillColor = ~Colour,
    weight = 0, # Border thickness
    fillOpacity = 1,
    popup = ~paste(Name)
  )