Analysis code and derived data for: Artificial Intelligence Across the Wildfire Management Lifecycle — A PRISMA-Guided Survey of Techniques, Validation Practices, and the Global-South Gap

This deposit contains the complete analysis pipeline and the derived datasets behind the review article "Artificial Intelligence Across the Wildfire Management Lifecycle: A PRISMA-Guided Survey of Techniques, Validation Practices, and the Global-South Gap".

The review follows a reproducible PRISMA-2020 protocol. A single Scopus query, executed on 29 June 2026 and published verbatim in this deposit, returned 4,463 records, reduced to an eligible corpus of 2,086 journal articles (2015–2025). The article characterises that corpus bibliometrically, formalises how the surveyed methods work, and quantifies validation practice on the corpus itself: fewer than 1% of eligible abstracts mention spatially blocked validation, and only one of the 41 primary studies synthesised reports a spatially honest protocol.

Contents

• code/ — Python and R scripts that regenerate every reported count, table and figure: PRISMA flow, bibliometric profile, stratified selection pool, supplementary tables, and the keyword co-occurrence network of Figure 3.
• data/corpus/ — the corpus accession list identifying all 2,086 eligible records (DOI, Scopus EID, year, source, document type, open-access status, citation count, author keywords), plus the exact query string and retrieval date.
• data/derived/ — annual production, source counts, author-keyword frequencies, the top-50 co-occurrence matrix, Louvain community assignments, PRISMA exclusion logs and the abstract-level term scan results.
• data/supplementary_tables/ — supplementary tables S1–S3 as CSV.
• docs/ESM_1.pdf — the article's supplementary material (Online Resource 1), sections S1–S5.

On the raw Scopus export. The raw export is deliberately not included: it carries the Abstract and References fields, which are copyrighted content owned by the individual publishers and licensed to the authors through an institutional Scopus subscription. The accession list identifies the corpus record-for-record, so it can be reconstructed exactly by anyone with Scopus access. Every analysis in the article is reproducible from the files shipped here, with one exception: the abstract-level term scan searches abstract text and therefore requires the licensed export. Its results are included; re-running it requires supplying your own export. See README.md, Section 3.

Licences. Code is released under MIT; derived data and documentation under CC BY 4.0.