{
  "abstract": "The dataset is a spatially and temporally organized curated subset of National Infrared Operations Program real-time high-resolution fire perimeter acquisitions for the Western United States from 2020 to 2024. The U.S. Forest Service’s National Infrared Operations is an ordered resource that flies only when requested and prioritized, and which tracks and documents wildfire progression over time. Through a structured data retrieval, consolidation, and metadata curation process, the dataset organizes fire perimeters and associated attributes to facilitate the temporal and spatial reconstruction of fire progression. The resulting shapefile integrates multiple data sources, ensuring spatial standardization to improve interoperability. This resource may be applied in various fields, including fire behavior modeling, fire risk analysis, ecological impact assessment, and resource management. It offers a transparent, replicable workflow and encourages reuse by providing supporting code, enabling researchers, land managers, and policymakers to incorporate these fire perimeters into broader analyses and decision-making processes.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Forest and Rangeland Stewardship, Colorado State University, Fort Collins, Colorado USA",
    "USDA Forest Service Rocky Mountain Research Station, 800 E. Beckwith Ave., Missoula, Montana USA",
    "Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee USA",
    "Department of Anthropology & Geography, Colorado State University, Fort Collins, Colorado USA",
    "Department of Political Science, Colorado State University, Fort Collins, Colorado USA"
  ],
  "article_type": "data paper",
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Shayne Magstadt"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Rahul Wadhwani"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Matthew A. Whitley"
    },
    {
      "affs": [
        3
      ],
      "name": "Timothy J. Martin"
    },
    {
      "affs": [
        4
      ],
      "name": "Eleanor Sitter"
    },
    {
      "affs": [
        0
      ],
      "name": "Yu Wei"
    },
    {
      "affs": [
        1
      ],
      "name": "Christopher D. O’Connor"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6dv4ps8cjk6sn.bib",
  "cited_by": 1,
  "doi": "10.1038/s41597-026-07695-1",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13739917/",
  "id": "6dv4ps8cjk6sn",
  "issns": [
    "2052-4463"
  ],
  "landing_url": "https://doi.org/10.1038/s41597-026-07695-1",
  "language": "en",
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Data Descriptor"
    ],
    [
      "openalex",
      "2306|Fire effects on ecosystems"
    ]
  ],
  "openalex": "W7168165595",
  "pdf_url": "https://www.nature.com/articles/s41597-026-07695-1_reference.pdf",
  "pmcid": "PMC13739917",
  "pmid": "42443226",
  "published": "2026-07-13",
  "publisher": "Nature Publishing Group",
  "ris": "https://research.draconitic.com/paper/6dv4ps8cjk6sn.ris",
  "sources": [
    {
      "first_seen": "2026-11-10T12:21:16Z",
      "native_id": "PMC13739917",
      "source": "pmc",
      "url": "https://doi.org/10.1038/s41597-026-07695-1"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "openalex:2306|Fire effects on ecosystems",
      "subfield": "climate"
    }
  ],
  "title": "A high spatial resolution daily fire perimeter progression dataset for wildfires in the Western United States: 2020–2024",
  "title_text": "A high spatial resolution daily fire perimeter progression dataset for wildfires in the Western United States: 2020–2024",
  "type": "peer-reviewed",
  "updated_at": "2026-11-10T12:21:16Z",
  "url": "https://research.draconitic.com/paper/6dv4ps8cjk6sn",
  "venue": "Scientific Data",
  "versions": []
}