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 3 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 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-02T20:27:02.000Z (28 days ago)
- Last Synced: 2025-04-18T05:41:09.106Z (13 days ago)
- Language: R
- Homepage: https://bymaxanjos.github.io/LCZ4r/
- Size: 255 MB
- Stars: 13
- Watchers: 3
- Forks: 1
- Open Issues: 1
- Releases: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
README.md
Tools for Local Climate Zone and Urban Heat Island Analysis in R
The LCZ4r package offers a suite of functions designed to analyze and visualize Local Climate Zones and Urban Heat Islands in R.
Package Overview
The LCZ4r is a comprehensive toolkit, including the following functions:
lcz_get_map()
Download your LCZ map from global datasetlcz_get_map_euro()
Download your LCZ map from European datasetlcz_get_map_usa()
Download your LCZ map from Continental United States datasetlcz_get_map_generator()
Download your LCZ map from LCZ Generator Platformlcz_plot_map()
Visualize the LCZ maplcz_cal_area()
Calculate LCZ areaslcz_get_parameters()
Retrieve LCZ parameterslcz_plot_parameters()
Visualize LCZ parameter maplcz_ts()
Analyze LCZ Time Serieslcz_anomaly()
Calculate LCZ Thermal Anomalieslcz_anomaly_map()
Map LCZ Thermal Anomalylcz_interp_map()
Map LCZ Interpolationlcz_plot_interp()
Visualize LCZ Interpolationlcz_interp_eval()
Evaluate LCZ Interpolationlcz_uhi_intensity()
Assess LCZ for Urban Heat Island Intensity
🗃️ Instalation
To Install to the LCZ4r use the development version on GitHub.
Function types and tutorials
These functions are categorized into two main types: general functions and local functions. We highly recommend that users explore the following tutorials to gain a deeper understanding of the capabilities and applications of the LCZ4r package:
LCZ4r-QGIS plugin: A Multilingual Integration
A LCZ4r-QGIS plugin repository that integrates the LCZ4r package with QGIS in multiple languages. It facilitates the integration of the General Functions and Local Functions from LCZ4r package into QGIS, allowing users to analyze Local Climate Zones (LCZ) and urban heat islands directly within the QGIS environment.
You can watch a detailed tutorial on installing LCZ4r in QGIS below:
People
The development of the package R LCZ4r has been led by Dr. Max Anjos and joined by:
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–> Dr.Fred Meier, Chair of Climatology, Institute of Ecology, Technische Universität Berlin.
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–> Dr. Francisco Castelhano, Center for Climate Crisis Studies, Department of Geography, Federal University of Rio Grande do Norte, Brazil.
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–> Dayvid Carlos de Medeiros, Center for Climate Crisis Studies, Department of Geography, Federal University of Rio Grande do Norte, Brazil.
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–> Antônio Campos Neto, Center for Climate Crisis Studies, Department of Geography, Federal University of Rio Grande do Norte, Brazil.
Funding
This project was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) – Finance Code 001, and by the Alexander von Humboldt Foundation.
Contact
Please feel free to contact us if you have any questions or suggestions by emailing maxanjos@campus.ul.pt. If you are interested in contributing to the development of this R package, we welcome you to join our team.
Inspiration
- Stewart, I., and T. Oke, 2012: Local climate zones for urban temperature studies. Bull. Amer. Meteor. Soc., 93, 1879–1900 DOI
- Ching, J., Mills, G., Bechtel, B., See, L., Feddema, J., Wang, X., … Theeuwes, N. (2018). WUDAPT: An Urban Weather, Climate, and Environmental Modeling Infrastructure for the Anthropocene. Bulletin of the American Meteorological Society, 99(9), 1907–1924 DOI
- Demuzere, M., Bechtel, B., Middel, A., & Mills, G. (2019). Mapping Europe into local climate zones. PLOS ONE, 14(4), e0214474 DOI
- Demuzere, M., Hankey, S., Mills, G., Zhang, W., Lu, T., & Bechtel, B. (2020). Combining expert and crowd-sourced training data to map urban form and functions for the continental US. Scientific Data, 7(1), 264 DOI
- Demuzere, M., Kittner, J., Martilli, A., Mills, G., Moede, C., Stewart, I. D., van Vliet, J., and Bechtel, B. (2022). A global map of Local Climate Zones to support earth system modelling and urban scale environmental science, Earth Syst. Sci. Data 14(8) 3835-3873. DOI
Have feedback or suggestions?
Do you have an idea for improvement or did you spot a mistake? We'd love to hear from you! Click the button below to create a new issue (Github) and share your feedback or suggestions directly with us.
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
- Issues event: 3
- Watch event: 8
- Issue comment event: 2
- Push event: 205
Last Year
- Issues event: 3
- Watch event: 8
- Issue comment event: 2
- Push event: 205
Committers metadata
Last synced: about 21 hours ago
Total Commits: 362
Total Committers: 2
Avg Commits per committer: 181.0
Development Distribution Score (DDS): 0.003
Commits in past year: 183
Committers in past year: 1
Avg Commits per committer in past year: 183.0
Development Distribution Score (DDS) in past year: 0.0
Name | Commits | |
---|---|---|
Max Anjos | m****s@c****t | 361 |
DayvidCMedeiros | 1****s | 1 |
Committer domains:
- campus.ul.pt: 1
Issue and Pull Request metadata
Last synced: 1 day 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: 3.332204510175204