Map, Area and Parameters

Max Anjos

March 25, 2026

The LCZ4r general functions are designed to facilitate the retrieval, analysis, and visualization of LCZs, when data is not readily available. These functions enable users to quickly download LCZ maps, compute LCZ classes, and extract specific urban canopy parameters (UCPs) of interest, such as Sky View Factor, impervious surface fraction, and roughness element height and so on.

Getting Started

The general functions, each serving a unique purpose:

Function	Description	Data Required	Internet Access Required
lcz_get_map()	Download your LCZ map from Global dataset	Not needed	Yes
lcz_get_map_euro()	Download your LCZ map from European dataset	Not needed	Yes
lcz_get_map_usa()	Download your LCZ map from Continental United States dataset	Not needed	Yes
lcz_get_map_generator()	Download your LCZ map from LCZ Generator Platform	Not needed	Yes
lcz_get_map2()	Clip the LCZ map for your city or ROI	Both	Both
lcz_plot_map()	Visualize the LCZ map	Not needed	Not needed
lcz_cal_area()	Calculate LCZ areas	Not needed	Not needed
lcz_get_parameters()	Retrieve LCZ parameters	Not needed	Not needed
lcz_plot_parameters()	Visualize LCZ parameters map	Not needed	Not needed

Tip: Utilize the help(lcz_*) function to access comprehensive documentation for each LCZ function. For instance, you can explore details about the lcz_get_map function by typing help("lcz_get_map").

Download and visualize the LCZ map

The lcz_get_map() function facilitates obtaining the LCZ map for your chosen city or a specific Region of Interest (ROI). Here are examples for cities around the world:

• São Paulo
• Paris
• London
• Sydney
• Beijing
• New York
• Nairobi

library(LCZ4r)

# Get the LCZ map for your city
lcz_map <- lcz_get_map(city = "São Paulo")

# Visualize the obtained LCZ map
lcz_plot_map(lcz_map)

LCZ map for São Paulo

euro_map <- lcz_get_map_euro(city = "Paris")
lcz_plot_map(euro_map)

LCZ map for Paris

euro_map <- lcz_get_map_euro(city = "London")
lcz_plot_map(euro_map)

LCZ map for London

lcz_map <- lcz_get_map(city = "Sydney")
lcz_plot_map(lcz_map)

LCZ map for Sydney

lcz_map <- lcz_get_map(city = "Beijing")
lcz_plot_map(lcz_map)

LCZ map for Beijing

usa_map <- lcz_get_map_usa(city = "New York")
lcz_plot_map(usa_map)

LCZ map for New York

my_map <- lcz_get_map(city = "Nairobi")
lcz_plot_map(my_map)

LCZ map for Nairobi

Download LCZ map from LCZ Generator Platform

To seamlessly integrate LCZ maps into the LCZ4r package, follow these steps to obtain the ID code for your desired city:

1. Access the LCZ Generator: Visit the LCZ Generator page.
2. Locate your city: Navigate to the Submissions section and search for your city using the search bar.
3. Obtain the ID from Factsheet: Click Show Factsheet next to your city’s submission and copy the ID from Submission Information section (e.g., 3110e623fbe4e73b1cde55f0e9832c4f5640ac21)
4. Example for Reference: View this sample LCZ Factsheet to understand the format and details.

lcz_map <- lcz_get_map_generator(ID = "3110e623fbe4e73b1cde55f0e9832c4f5640ac21")
lcz_plot_map(lcz_map)

LCZ map from Generator Platform

💡 Tip 1: LCZ map for Region Of Interest (ROI)

This example demonstrates how to use the roi argument in lcz_get_map* functions to clip the LCZ map for your ROI. You must import shapefile into R.

# Load package
library(sf)

# Import Shapefile into R
my_shp <- sf::st_read("path/shp_name.shp") # You can also use shapefile in .gpkg format

# Get LCZ map for your ROI
lcz_map <- lcz_get_map(roi = my_shp)

# Visualize LCZ map
lcz_plot_map(lcz_map)

💡 Tip 2: Clip LCZ map generator for your city or Region Of Interest (ROI) using lcz_get_map2()

This example demonstrates how to use the lcz_get_map2() function to clip the LCZ map for your specific city or ROI. For cities, the clipped map is derived from the OpenStreetMap database, while for ROIs, it uses your imported shapefile.

# Get LCZ map generator (e.g., Rio de Janeiro)
lcz_map_generator <- lcz_get_map_generator(ID = "3110e623fbe4e73b1cde55f0e9832c4f5640ac21")

# Clip LCZ map generator to your city 
lcz_map <- lcz_get_map2(lcz_map_generator, city = "Rio de Janeiro")

# Visualize LCZ map
lcz_plot_map(lcz_map)

# Clip LCZ map generator to ROI
library(sf)
my_shp <- sf::st_read("path/shp_name.shp") # You can also use shapefile in .gpkg format
lcz_map <- lcz_get_map2(lcz_map_generator, roi = my_shp)

# Visualize LCZ map
lcz_plot_map(lcz_map)

Clipped LCZ map for Rio de Janeiro

Calculate LCZ areas

The lcz_cal_area() function calculates the area for each LCZ class:

lcz_map <- lcz_get_map(city = "Rio de Janeiro")
lcz_cal_area(lcz_map)

LCZ areas calculation for Rio de Janeiro

Tip: This function provides a table.csv of the calculated LCZ areas. To save as CSV, use: lcz_cal_area(lcz_map, iplot = FALSE)

Retrieve and visualize LCZ parameters

The lcz_get_parameters() function gives you access to diverse LCZ parameters, encompassing minimum, maximum, and mean values, drawn from Stewart and Oke (2012). These parameters are convertible into either shapefiles or a raster stack, where multiple rasters are aggregated into a single file.

Here’s a glimpse of the available LCZ parameters:

Code	Parameter	Description	Unit
SVFmin	Sky View Factor	Minimum Sky View Factor	[0-1]
SVFmax	Sky View Factor	Maximum Sky View Factor	[0-1]
SVFmean	Sky View Factor	Mean Sky View Factor	[0-1]
ARmin	Aspect ratio	Minimum Aspect Ratio	[0-3]
ARmax	Aspect ratio	Maximum Aspect Ratio	[0-3]
ARmean	Aspect ratio	Mean Aspect Ratio	[0-3]
BSFmin	Building Surface Fraction	Minimum Building Surface Fraction	[%]
BSFmax	Building Surface Fraction	Maximum Building Surface Fraction	[%]
BSFmean	Building Surface Fraction	Mean Building Surface Fraction	[%]
ISFmin	Impervious Surface Fraction	Minimum Impervious Surface Fraction	[%]
ISFmax	Impervious Surface Fraction	Maximum Impervious Surface Fraction	[%]
ISFmean	Impervious Surface Fraction	Mean Impervious Surface Fraction	[%]
PSFmin	Vegetation Surface Fraction	Minimum Vegetation Surface Fraction	[%]
PSFmax	Vegetation Surface Fraction	Maximum Vegetation Surface Fraction	[%]
PSFmean	Vegetation Surface Fraction	Mean Vegetation Surface Fraction	[%]
TSFmin	Tree Surface Fraction	Minimum Tree Surface Fraction	[%]
TSFmax	Tree Surface Fraction	Maximum Tree Surface Fraction	[%]
TSFmean	Tree Surface Fraction	Mean Tree Surface Fraction	[%]
HREmin	Height Roughness Elements	Minimum Height Roughness Elements	[meters]
HREmax	Height Roughness Elements	Maximum Height Roughness Elements	[meters]
HREmean	Height Roughness Elements	Mean Height Roughness Elements	[meters]
TRCmin	Terrain Roughness class	Minimum Terrain Roughness class	[meters]
TRCmax	Terrain Roughness class	Maximum Terrain Roughness class	[meters]
TRCmean	Terrain Roughness class	Mean Terrain Roughness class	[meters]
SADmin	Surface Admittance	Minimum Surface Admittance	[J m⁻² s¹⁄² K⁻¹]
SADmax	Surface Admittance	Maximum Surface Admittance	[J m⁻² s¹⁄² K⁻¹]
SADmean	Surface Admittance	Mean Surface Admittance	[J m⁻² s¹⁄² K⁻¹]
SALmin	Surface Albedo	Minimum Surface Albedo	[0-0.5]
SALmax	Surface Albedo	Maximum Surface Albedo	[0-0.5]
SALmean	Surface Albedo	Mean Surface Albedo	[0-0.5]
AHmin	Anthropogenic Heat Output	Minimum Anthropogenic Heat Output	[W m⁻²]
AHmax	Anthropogenic Heat Output	Maximum Anthropogenic Heat Output	[W m⁻²]
AHmean	Anthropogenic Heat Output	Mean Anthropogenic Heat Output	[W m⁻²]
z0	Roughness Length	Roughness Length class	[meters]

Rio de Janeiro LCZ parameters

# Extract the LCZ parameters for raster stack format
lcz_map <- lcz_get_map(city = "Rio de Janeiro")
LCZpar <- lcz_get_parameters(lcz_map, istack = TRUE)
LCZpar

LCZ parameters raster stack for Rio de Janeiro

Maps

• Sky View Factor
• Building Surface Fraction
• Roughness Length

lcz_plot_parameters(LCZpar, iselect = "SVFmean")

Sky View Factor map for Rio de Janeiro

lcz_plot_parameters(LCZpar, iselect = "BSFmax")

Building Surface Fraction map for Rio de Janeiro

lcz_plot_parameters(LCZpar, iselect = "z0")

Roughness Length map for Rio de Janeiro

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