ForeFire

An open-source code for wildland fire spread models.
https://github.com/forefireAPI/forefire

Keywords

cpp python

Keywords from Contributors

optimize archiving measur transforms generic compose observation conversion projection animals

Last synced: 2 days ago
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Repository metadata

ForeFire is an open-source code for wildland fire spread models

Host: GitHub
URL: https://github.com/forefireAPI/forefire
Owner: forefireAPI
License: gpl-3.0
Created: 2014-02-27T13:34:40.000Z (almost 12 years ago)
Default Branch: master
Last Pushed: 2025-12-12T16:35:07.000Z (about 1 month ago)
Last Synced: 2026-01-14T20:12:37.012Z (11 days ago)
Topics: cpp, python
Language: C++
Homepage:
Size: 12.4 MB
Stars: 74
Watchers: 6
Forks: 33
Open Issues: 0
Releases: 5
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff

ForeFire is an open-source wildfire simulation engine written in C++. Developed by CNRS at the Université de Corse Pascal Paoli, it is used for research and operational forecasting. The engine implements various fire behavior models and enables high-fidelity coupled fire-atmosphere simulations, aiming to improve wildfire prediction and understanding for complex environments.

Key Links:

📚 Full Documentation: forefire.readthedocs.io
🚀 Live Demo: forefire.univ-corse.fr/sim
🌍 Website: forefire.univ-corse.fr

Features

Advanced Simulation Engine: Core C++ logic for fire propagation using various Rate of Spread (ROS) models and handling complex geospatial data (NetCDF).
Fire-Atmosphere Coupling: Designed for two-way coupling by linking the core library with atmospheric models like MesoNH (developed by CNRS & Météo-France).
High Performance: Optimized C++ core with MPI support for parallel computing.
Flexible Interfaces: Built upon a core C++ Simulation Engine (Library):
- forefire Interpreter: The primary way to run simulations using script files (.ff), interactive console commands, or the web interface (via listenHTTP[]).
- C++ Library (libforefireL): Allows direct integration into other software.
- Python Bindings: Enable scripting and control from Python (see ./bindings/python/README.md).
Flexible Output: Can generate outputs in various formats, including KML for visualization in Google Earth, Geojson, NetCDF, and custom binary/text formats.
Extensible: Add custom ROS models in C++; customize web interfaces.
Applications: Research, case reanalysis, ensemble forecasting.

Quick Start with Docker

The easiest way to get started is often using Docker and the interactive console with instruction noted below via the forefire command-line interpreter see in video :

Clone the repository

# Clone the repository
git clone https://github.com/forefireAPI/forefire.git
cd forefire

Build the Docker image
```
docker build . -t forefire:latest
```

Run the container interactively

docker run -it --rm -p 8000:8000 --name ff_interactive forefire

Inside the container navigate to test directory and launch the forefire console:
```
cd tests/runff

# start the forefire console with the command
forefire
```

67 ```bash
listenHTTP[]
````
the output should be :

```bash
>> ForeFire HTTP command server listening at http://localhost:8000
```

This server provides a graphical user interface that you can access on your browser at http://localhost:8000/

Run your first simulation

In ForeFire (web or on console are equivalent), running a simulation and viewing the result are separate commands. The UI guides you through this process.
- Step 1: Run the simulation script. In HTTP Interface click the include button or type include[real_case.ff] in command input box, and click the Send button.
  ou can also run the same command directly in the interactive console if you prefer py typing include[real_case.ff] and press enter.
  The scripts executes a simulation by loading data, starting fires, applying wind triggers, and running the simulation for a specified duration.
- Step 2: View the result. After the command finishes, click the Refresh Map button to display the simulation results onto the web map.
- Step 3 (optional): iterate more. you can continue the simulation, command include[real_case.ff] the Refresh Map button to display the simulation results onto the web map.
You should see a simulation running in the Aullène region of Corsica. This confirms your Docker setup is working! Check the full documentation for more details on this example

Sample data and Git LFS

The demo datasets bundled under tests/runff/ are stored with Git LFS because they include several megabytes of raster data that we only use in the quick-start examples and regression tests. Make sure Git LFS is installed before cloning; otherwise Git will pull pointer files only. If that happens, download the dataset directly from the GitHub web interface and drop it back into the expected folder before running the examples. This data is only provided for the bundled test scenarios.

Build from source

See the Full Documentation for more details on building from source with the install-forefire.sh file

Python Bindings

ForeFire provides Python bindings for easier scripting and integration. See the Python Bindings ./bindings/python/README.md for details.

Contributing

We welcome contributions to ForeFire! We especially appreciate help with:

Improving documentation and tutorials.
Python bindings
Enhancing packaging (Docker, Pip, etc.) and cross-platform compatibility.

Please read our Contributing Guidelines to learn how you can help, including how to report bugs, suggest features, and submit code changes.

All contributors are expected to adhere to our Code of Conduct.

License

ForeFire is licensed under the GNU General Public License v3.0. See LICENSE for full details.

Citation

If you use ForeFire in your work, please cite:

BibTex

@article{article,
author = {Filippi, Jean-Baptiste and Bosseur, Frédéric and Grandi, Damien},
year = {2014},
month = {11},
pages = {},
title = {ForeFire: open-source code for wildland fire spread models},
isbn = {9789892608846},
doi = {10.14195/978-989-26-0884-6_29}
}

Plain Text

Filippi, Jean-Baptiste & Bosseur, Frédéric & Grandi, Damien. (2014). ForeFire: open-source code for wildland fire spread models. 10.14195/978-989-26-0884-6_29.

Citation (CITATION.cff)

cff-version: "1.2.0"
authors:
- family-names: Filippi
  given-names: Jean-Baptiste
  orcid: "https://orcid.org/0000-0002-6244-0648"
- family-names: Baggio
  given-names: Roberta
  orcid: "https://orcid.org/0000-0003-1531-0530"
- family-names: Paugam
  given-names: Ronan
  orcid: "https://orcid.org/0000-0001-6429-6910"
- family-names: Bosseur
  given-names: Frédéric
  orcid: "https://orcid.org/0000-0002-8108-0887"
- family-names: Leblanc
  given-names: Antonio
  orcid: "https://orcid.org/0009-0001-9043-2039"
- family-names: Alonso-Pinar
  given-names: Alberto
  orcid: "https://orcid.org/0009-0009-2051-9700"
contact:
- family-names: Filippi
  given-names: Jean-Baptiste
  orcid: "https://orcid.org/0000-0002-6244-0648"
doi: 10.5281/zenodo.17742375
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - family-names: Filippi
    given-names: Jean-Baptiste
    orcid: "https://orcid.org/0000-0002-6244-0648"
  - family-names: Baggio
    given-names: Roberta
    orcid: "https://orcid.org/0000-0003-1531-0530"
  - family-names: Paugam
    given-names: Ronan
    orcid: "https://orcid.org/0000-0001-6429-6910"
  - family-names: Bosseur
    given-names: Frédéric
    orcid: "https://orcid.org/0000-0002-8108-0887"
  - family-names: Leblanc
    given-names: Antonio
    orcid: "https://orcid.org/0009-0001-9043-2039"
  - family-names: Alonso-Pinar
    given-names: Alberto
    orcid: "https://orcid.org/0009-0009-2051-9700"
  date-published: 2025-12-05
  doi: 10.21105/joss.08680
  issn: 2475-9066
  issue: 116
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 8680
  title: "ForeFire: A Modular, Scriptable C++ Simulation Engine and
    Library for Wildland-Fire Spread"
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.08680"
  volume: 10
title: "ForeFire: A Modular, Scriptable C++ Simulation Engine and
  Library for Wildland-Fire Spread"

Owner metadata

Name: forefireAPI
Login: forefireAPI
Email:
Kind: organization
Description:
Website:
Location:
Twitter:
Company:
Icon url: https://avatars.githubusercontent.com/u/6805132?v=4
Repositories: 1
Last ynced at: 2023-08-16T07:20:30.677Z
Profile URL: https://github.com/forefireAPI

GitHub Events

Total

Create event: 12
Release event: 1
Issues event: 34
Watch event: 12
Delete event: 17
Member event: 3
Issue comment event: 75
Push event: 196
Gollum event: 1
Pull request review event: 11
Pull request event: 50
Fork event: 2

Last Year

Create event: 12
Release event: 1
Issues event: 34
Watch event: 12
Delete event: 17
Member event: 3
Issue comment event: 75
Push event: 196
Gollum event: 1
Pull request review event: 11
Pull request event: 50
Fork event: 2

Committers metadata

Last synced: 10 days ago

Total Commits: 753
Total Committers: 23
Avg Commits per committer: 32.739
Development Distribution Score (DDS): 0.584

Commits in past year: 463
Committers in past year: 10
Avg Commits per committer in past year: 46.3
Development Distribution Score (DDS) in past year: 0.49

Name	Email	Commits
antonio-leblanc	a**c@p**r	313
FILIPPI Jean-Baptiste	f**i@u**r	179
CI BOT	c**t@e**m	98
Jean-Baptiste Filippi	b**i@g**m	69
ludobegins	l**n@g**m	34
filippi_j	f**j@U**l	12
ronan	r**m@g**m	11
Frederic Allaire	f**e@i**r	6
Thoreau Romain	r**u@c**r	6
th96r4ss	a**a@u**r	6
jdurand	j**d@u**r	3
baggiocolpir	1****r	3
Dominik Laux	d**x@o**m	2
Damien Grandi	d**i@g**m	2
serbal193	j**s@g**m	1
BAGGIO_R	b**r@o**l	1
Jean-Baptiste FILIPPI	f**j@B**)	1
damien	d**n@d**)	1
rbaggio	r**i@g**m	1
dependabot[bot]	4****]	1
Philip Cardiff	p**f@g**m	1
Johanna Strebl	j**l@g**m	1
Fernando Veiga Lopez	f**a@u**l	1

Committer domains:

Issue and Pull Request metadata

Last synced: about 2 months ago

Total issues: 35
Total pull requests: 63
Average time to close issues: about 1 month
Average time to close pull requests: 5 days
Total issue authors: 12
Total pull request authors: 11
Average comments per issue: 3.43
Average comments per pull request: 0.22
Merged pull request: 48
Bot issues: 0
Bot pull requests: 4

Past year issues: 23
Past year pull requests: 49
Past year average time to close issues: 11 days
Past year average time to close pull requests: 1 day
Past year issue authors: 7
Past year pull request authors: 7
Past year average comments per issue: 4.09
Past year average comments per pull request: 0.24
Past year merged pull request: 37
Past year bot issues: 0
Past year bot pull requests: 4

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py3_tools/requirements.txt pypi

pyproj ==3.4.0

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