{
  "abstract": "Identifying economic corridors at national scale is challenging where firm registries, transaction flows, and local economic-output statistics are incomplete or unavailable. This paper develops a reproducible multi-proxy screening framework for detecting economic-corridor candidates across Nigeria using a kilometre-scale analytical grid. The framework combines built-up land cover from ESA WorldCover, night-time light radiance from NASA VIIRS Black Marble, building-footprint density from Google Open Buildings, a static urban-intensity proxy derived from population, built-up share and night-time light level, and commercial point-of-interest density from Overture Places and OpenStreetMap. A dual proxy gate requiring both built-up evidence, defined as built-up fraction above 0.1, and night-time luminosity, defined as radiance above 1 nW cm-2 sr-1, identifies active corridor cells, which are then clustered into corridor objects and assigned interpretable typologies. The analytical frame contains 762,751 cells: national, state, and geopolitical-zone summaries use 749,191 canonical national-grid cells, while 13,560 configured metropolitan area-of-interest overlay cells are reserved for an eight-metro comparison. Applied to Nigeria, the framework identifies 11,243 active corridor cells on the national grid, representing 1.50% of cells, and 598 corridor objects spanning 10,682 retained cells and approximately 36.3 million people. Corridor activity concentrates around Lagos and other southern commercial geographies, while the method also surfaces emerging and constrained corridor candidates for review. All outputs are proxy-based screening signals for spatial planning, infrastructure prioritisation, and market-intelligence triage; they do not measure GDP, firm revenue, transaction volume, freight movement, infrastructure capacity, service adequacy, or official corridor designation.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.31675",
  "author_total": 1,
  "authors": [
    {
      "name": "Richard Oduntan"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/c9ptyb82y8dsy.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.31675",
  "fulltext_url": null,
  "id": "c9ptyb82y8dsy",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.31675",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.CY"
    ],
    [
      "arxiv",
      "physics.soc-ph"
    ],
    [
      "openalex",
      "2306|Impact of Light on Environment and Health"
    ]
  ],
  "openalex": "W7223709081",
  "pdf_url": "https://arxiv.org/pdf/2610.31675",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-01",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/c9ptyb82y8dsy.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:35:15Z",
      "native_id": "2610.31675",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.31675"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:physics.soc-ph",
      "subfield": "statistical-nonlinear"
    }
  ],
  "title": "Economic Corridor Detection from Multi-Source Earth Observation and Commercial Geospatial Data Across Nigeria's Kilometre-Scale Grid",
  "title_text": "Economic Corridor Detection from Multi-Source Earth Observation and Commercial Geospatial Data Across Nigeria's Kilometre-Scale Grid",
  "type": "preprint",
  "updated_at": "2026-10-30T12:35:15Z",
  "url": "https://research.draconitic.com/paper/c9ptyb82y8dsy",
  "venue": "arXiv",
  "versions": []
}