{"id":19557971,"url":"https://github.com/mbjoseph/wildfire-extremes","last_synced_at":"2025-02-26T08:16:39.729Z","repository":{"id":149590647,"uuid":"64492265","full_name":"mbjoseph/wildfire-extremes","owner":"mbjoseph","description":"Spatiotemporal modeling of wildfire 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Spatiotemporal modeling of wildfire extremes\n\n[![Docker Automated build](https://img.shields.io/docker/automated/mbjoseph/wildfire-extremes.svg)](https://hub.docker.com/r/mbjoseph/wildfire-extremes/)\n[![Docker Build Status](https://img.shields.io/docker/build/mbjoseph/wildfire-extremes.svg)](https://hub.docker.com/r/mbjoseph/wildfire-extremes/)\n[![DOI](https://zenodo.org/badge/64492265.svg)](https://zenodo.org/badge/latestdoi/64492265)\n\nThis repository contains code to build spatiotemporal models of wildfire extremes in the contiguous United States. \n\n## Hardware requirements\n\nWe recommend at least 4 physical CPUs and 30 GB of RAM. \n\n## Reproducing the analysis\n\n### Spinning up the computational environment\n\nWe have provided a Docker container that bundles up the software dependencies \nfor this project, and provides an RStudio server instance that can be used in a \nweb browser. \nTo launch the container, run the following:\n\n```bash\ndocker run -e PASSWORD=yourpassword -d -p 8787:8787 mbjoseph/wildfire-extremes\n```\n\nThen, navigate to port 8787 on a web browser (e.g., `localhost:8787`, or \n`\u003cInsert EC2 IP addres heres\u003e:8787` if running on AWS) and log in \nwith username `rstudio`, and the password you provided in your call to `docker run`. \n\n### Optional: creating an RStudio project\n\nIf you plan to interact much with the code, you may want to create an RStudio \nproject. \nTo do so, after connecting to your RStudio server, choose \nFile \u003e New Project..., then select \"Existing Directory\" \u003e Browse..., and \nchoose wildfire-extremes, and finally click Create Project. \nThis will create and then open a project associated with this repository.\n\n### Running the analysis\n\nTo run everything, you can type the following command from a terminal \n(e.g., the terminal pane in RStudio server): \n\n```\nmake\n```\n\nThis takes ~3-4 days on a machine with 4 cores, assuming that you're making\neverything from scratch. \nFitting the models takes the longest due to data volume and parameter \ndimensionality. \n\n## Overview of workflow\n\n### 1. Data processing \n\nWe define targets for the input data to the models in the Makefile as follows: \n\n- `data/processed/ecoregion_summaries.csv`: Summaries of climate data for every \nEPA level 3 ecoregion for each month from 1984-2015. \n\n- `data/processed/housing_density.csv`: Summary of housing density for each \necoregion, each month. \n\n- `data/processed/stan_d.rds`: A serialized rds object that bundles all input \ndata for the model fitting step.\n\nWe also generate some ancillary data to be used downstream in the analysis of \nmodel results, including `data/processed/mtbs.rds` and \n`data/processed/ecoregions.rds`.\n\n\n### 2. Model training and evaluation\n\nOnce the serialized model input data (`data/processed/stan_d.rds`) exist, then\nall of the models can be fit. \nThese include burn area models and wildfire count models, all of which have\nthe suffix `_fit.rds`, e.g., `nb_fit.rds`, `ba_gamma_fit.rds`.\nEach model fit object corresponds to a separate target in the Makefile. \n\nWith these model fits, a set of figures and tables (`figs` and `tables` in\nthe Makefile) are generated. \nThese are passed into the manuscript in the next step.\n\n### 3. Manuscript generation\n\nThe manuscript `main.pdf` is generated from the `main.Rmd` file, and all of the \ntables and figures. \nThe source code for the manuscript is an R Markdown document, which dynamically \ninserts the figures, tables, and summary statistics into the paper in an \nautomated way. \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmbjoseph%2Fwildfire-extremes","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmbjoseph%2Fwildfire-extremes","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmbjoseph%2Fwildfire-extremes/lists"}