LCZ4r
An R Package for Local Climate Zones and Urban Heat Island Analysis.
https://github.com/bymaxanjos/lcz4r
Category: Climate Change
Sub Category: Earth and Climate Modeling
Last synced: about 13 hours ago
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Repository metadata
An R Package for Local Climate Zones and Urban Heat Island Analysis
- Host: GitHub
- URL: https://github.com/bymaxanjos/lcz4r
- Owner: ByMaxAnjos
- License: other
- Created: 2023-09-15T11:00:41.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2026-04-24T17:05:13.000Z (about 1 month ago)
- Last Synced: 2026-05-24T01:07:00.029Z (4 days ago)
- Language: R
- Homepage: https://bymaxanjos.github.io/LCZ4r/
- Size: 187 MB
- Stars: 21
- Watchers: 3
- Forks: 3
- Open Issues: 2
- Releases: 0
-
Metadata Files:
- Readme: README-en.md
- Changelog: NEWS.md
- License: LICENSE
README-en.md
Tools for Local Climate Zone and Urban Heat Island Analysis in R
The LCZ4r package provides a comprehensive suite of tools for analyzing and visualizing Local Climate Zones (LCZ) and Urban Heat Islands (UHI) in R. Designed for researchers, urban planners, and climate scientists, LCZ4r simplifies the process of downloading, processing, and interpreting LCZ data.
1. Installation
The LCZ4r package is available on GitHub and can be installed in two ways.
We recommend Option 1 for most users.
Option 1: Install from GitHub (Recommended)
This is the fastest way to get the latest version of the package.
::: callout-tip
Prerequisite: If you already have remotes or devtools installed, you can skip this step.
:::
if (!require("remotes")) { install.packages("remotes")}
# Install or update directly from GitHub
remotes::install_github("ByMaxAnjos/LCZ4r", upgrade = "never")
::: callout-warning
Updates: LCZ4r is under active development. To update, simply run the command above again.
R will automatically overwrite the previous version. After updating, it is recommended to restart your R session
(Session > Restart R).
:::
Option 2: Install from Local File (.zip)
This option is recommended for: unstable internet connections, restricted networks (e.g., institutional environments), and training sessions with multiple users.
Steps:
-
Download the package
👉 https://github.com/ByMaxAnjos/LCZ4r/archive/refs/heads/main.zip -
Extract the file
👉 After downloading, extract the .zip file to a local folder (e.g., Downloads or Desktop) -
Install locally
# IMPORTANT: Adjust the path to where you extracted the folder
remotes::install_local(
"C:/Path/to/your/folder/LCZ4r-main",
upgrade = "never"
)
::: callout-tip
Example: If you downloaded and extracted the file to your Downloads folder:
remotes::install_local(
"/Users/maxanjos/Downloads/LCZ4r-main",
upgrade = "never"
)
:::
Loading the package
After installation, load the package whenever you start a new R session:
library(LCZ4r)
Run LCZ4r in Posit Cloud, no RStudio installation required!
LCZ4r-QGIS Plugin: Multilingual Integration
The LCZ4r-QGIS plugin integrates the LCZ4r package with QGIS, enabling users to analyze Local Climate Zones and urban heat islands directly within the QGIS environment. The plugin supports multiple languages, making it accessible to a global audience.
Inspiration
The LCZ4r package is inspired by the following works:
-
Stewart, I., and T. Oke, 2012: Local Climate Zones for Urban Temperature Studies.
-
Ching, J., et al., 2018: WUDAPT: An Urban Weather, Climate, and Environmental Modeling Infrastructure for the Anthropocene.
-
Demuzere, M., et al., 2019: Mapping Europe into Local Climate Zones.
-
Demuzere, M., et al., 2020: Combining Expert and Crowd-Sourced Training Data to Map Urban Form and Functions for the Continental US.
-
Demuzere, M., et al., 2022: A Global Map of Local Climate Zones to Support Earth System Modelling and Urban-Scale Environmental Science.
Have Feedback or Suggestions?
We value your input! If you have ideas for improvement or spot any issues, please let us know by opening an issue on GitHub.
Owner metadata
- Name: ZoomCityCarbonModel
- Login: ByMaxAnjos
- Email:
- Kind: user
- Description:
- Website:
- Location: Berlin, Germany
- Twitter:
- Company: Technische Universität Berlin
- Icon url: https://avatars.githubusercontent.com/u/94705218?u=6e59b5f0677af789a813d23ca9f0a2262fe03992&v=4
- Repositories: 4
- Last ynced at: 2023-04-25T14:37:51.529Z
- Profile URL: https://github.com/ByMaxAnjos
GitHub Events
Total
- Fork event: 1
- Issues event: 3
- Watch event: 9
- Issue comment event: 2
- Push event: 267
Last Year
- Fork event: 1
- Watch event: 1
- Push event: 56
Committers metadata
Last synced: 4 days ago
Total Commits: 441
Total Committers: 2
Avg Commits per committer: 220.5
Development Distribution Score (DDS): 0.002
Commits in past year: 75
Committers in past year: 1
Avg Commits per committer in past year: 75.0
Development Distribution Score (DDS) in past year: 0.0
| Name | Commits | |
|---|---|---|
| Max Anjos | m****s@c****t | 440 |
| DayvidCMedeiros | 1****s | 1 |
Committer domains:
- campus.ul.pt: 1
Issue and Pull Request metadata
Last synced: 9 months ago
Total issues: 2
Total pull requests: 1
Average time to close issues: 43 minutes
Average time to close pull requests: 3 minutes
Total issue authors: 2
Total pull request authors: 1
Average comments per issue: 1.0
Average comments per pull request: 1.0
Merged pull request: 1
Bot issues: 0
Bot pull requests: 0
Past year issues: 2
Past year pull requests: 0
Past year average time to close issues: 43 minutes
Past year average time to close pull requests: N/A
Past year issue authors: 2
Past year pull request authors: 0
Past year average comments per issue: 1.0
Past year average comments per pull request: 0
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- ByMaxAnjos (1)
- Rapsodia86 (1)
Top Pull Request Authors
- DayvidCMedeiros (1)
Top Issue Labels
Top Pull Request Labels
Dependencies
Score: 3.828641396489095