The notebooks in this repo highlight some of the analytics and visualization capabilities of the Fire Alarm: Science Data Platform for Wildfire and Air Quality system with the following example use cases:
- SARP Tutorial (directory containing all materials for the SARP tutorial):
- 2025 Eaton and Palisades Fires Impacting Southern California
- 2023 Canadian Wildfires Impacting New York Air Quality
- 2021 Dixie Wildfire
- 2023 Alberta Wildfires
- 2018 Carr Wildfire
- Los Angeles ports backlog Fall 2021
- Fireworks during 4th of July 2022 in Los Angeles county
- Predicting What We Breathe Los Angeles PM2.5 predictions
- OCO-3 Snapshot Area Map data:
- Impact of the COVID-19 pandemic response to CO2 emissions
- Bełchatów Power Station, Poland: Do observed emissions match reported emissions?
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conda >= 22.9.0
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OS: Mac (more OS options to come)
To run the notebooks, run the following commands that create a conda environment called firealarm_notebook using the
environment.yml file to include all required dependencies, and install the environment as a kernelspec:
conda env create -f environment.yml
conda activate firealarm_notebook
pip install notebook
pip install ipykernel
python -m ipykernel install --user --name=firealarm_notebook
jupyter notebook
From the localhost page that opens, you can run the notebooks. Make sure you change the kernel by selecting the option at the top Kernel -> Change kernel -> ideas_notebook (see here for more information).
To add a new notebook, duplicate the stub_notebook.ipynb file, name it with the following convention:
<notebook number>. <title>.ipynb. With the notebook implemented in this new file, add a link to it in the list at the
top of this file.