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Cell2Fire: A Cell Based Forest Fire Growth Model  C++/Python\n## Cristobal Pais, Jaime Carrasco, David Martell, David L. Woodruff, Andres Weintraub\n\n# Disclaimer\n\nThis software is for research use only. There is no warranty of any kind;\nthere is not even the implied warranty of fitness for use.\n\n![](https://github.com/cell2fire/Cell2Fire/workflows/TestExamples/badge.svg)\n\n# Introduction\n\nA more actively maintained fork of this repository is [C2FK](https://github.com/fire2a/C2FK).\n\nCell2Fire is a new cell-based forest and wildland landscape fire spread simulator.\nThe fire environment is characterized by partitioning the landscape into a large number of homogeneous cells and specifying the fuel, weather, fuel moisture and topography attributes of each cell.\nFire spread within each cell is assumed to be elliptical and governed by spread rates predicted by any independent fire spread model (e.g. the Canadian Forest Fire Behavior Prediction System).\nCell2Fire exploits parallel computation methods which allows users to run large-scale simulations in short periods of time.\nIt includes powerful statistical, graphical output, and spatial analysis features to facilitate the display and analysis of projected fire growth.\n\nWork in progress documentation is available at\n[readthedocs](https://cell2fire.readthedocs.io/) and there is an\noriginal draft of a paper on\n[arXiv](https://arxiv.org/abs/1905.09317v1).\n\n# Citation\n\n@ARTICLE{Cell2Fire,\nAUTHOR={Pais, Cristobal and Carrasco, Jaime and Martell, David L. and Weintraub, Andres and Woodruff, David L.},\nTITLE={Cell2Fire: A Cell-Based Forest Fire Growth Model to Support Strategic Landscape Management Planning},  \nJOURNAL={Frontiers in Forests and Global Change},\nVOLUME={4},\nYEAR={2021},\nURL={https://www.frontiersin.org/articles/10.3389/ffgc.2021.692706},\nDOI={10.3389/ffgc.2021.692706},\nISSN={2624-893X}\n}\n   \n# Requirements\n- g++\n- Boost (C++)\n- Eigen (C++)\n- Python \u003e3.6; you might need 3.12\n- numpy\n- pandas\n- matplotlib\n- seaborn\n- tqdm\n- opencv\n- imageio (replaced imread, April 2026)\n- networkx (for stats module)\n\n# Installation\n\nInstallation may require some familiarity with C++, make, and Python. \n- cd Cell2Fire/cell2fire/Cell2FireC\n- (edit Makefile to have the correct path to Eigen)\n- make\n- cd ../..\n- pip install -r requirements.txt  # might not do anything\n- pip install -e .\n\n# Usage\nIn order to run the simulator (after installation and cd to  Cell2Fire/cell2fire), the following command can be used:\n```\n$ python main.py --input-instance-folder ../data/Sub40x40/ --output-folder ../results/Sub40x40 --ignitions --sim-years 1 --nsims 5 --finalGrid --weather rows --nweathers 1 --Fire-Period-Length 1.0 --output-messages --ROS-CV 0.0 --seed 123 --stats --allPlots --IgnitionRad 5 --grids --combine\n```\nFor the full list of arguments and their explanation use:\n```\n$ python main.py -h\n```\n\nIn addition, both the C++ core and Python scripts can be used separately:\n## C ++\nOnly simulation and generate evolution grids (no stats or plots).\nParallel-ready version will be uploaded soon.\n```\n$ ./Cell2Fire --input-instance-folder ../data/Sub40x40/ --output-folder ../results/Sub40x40 --ignitions --sim-years 1 --nsims 1 --grids --final-grid --Fire-Period-Length 1.0 --weather rows --nweathers 1 --output-messages --ROS-CV 0.0 --seed 123 --IgnitionRad 0 --HFactor 1.0 --FFactor 1.0 --BFactor 1.0 --EFactor 1.0\n```\n\n\n## Python \nOnly processing option (reads a previously simulated instance and computes stats/plots).\nImportant: provide the number of sims --nsims to be processed\n```\n$ python main.py --input-instance-folder ../data/Sub40x40/ --output-folder ../results/Sub40x40_Previous_simulation --nsims 10 --stats --allPlots --onlyProcessing\n```\n\n# Output examples\n## Dogrib forest (Canadian instance)\n![Dogrib Instance](outputs/Example4.png)\n\n## Visualize shortest paths propagation (10 scens)\n![Dogrib Fire Propagation and ROS map](outputs/Example1.png)\n\n## Shortest paths propagation and ROS intensity (10 scens)\n![Dogrib Fire Propagation map](outputs/Example2.png)\n\n## Burn-Probability maps (10 scens)\n![Dogrib BP map](outputs/Example3.png)\n","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":[],"project_url":"https://ost.ecosyste.ms/api/v1/projects/175595","html_url":"https://ost.ecosyste.ms/projects/175595"}