{
  "abstract": "To address the growing complexity between the built environment and urban life, modern urban planning has increasingly relied on digital technologies for decision-making, including City Information Modeling (CIM). While CIM has matured from standards and data integration to real-time analytics and digital twins, most initiatives optimize physical systems while struggling to incorporate “intangible” citizen-generated data. This paper addresses this gap by presenting a replicable methodology to embed a customized Environment, Social, and Governance (ESG) framework with a CIM workflow by joining both tangible and intangible city layers to inform planning. The general methodology includes: (1) identifying a French priority neighborhood (QPV) and prioritizing local ESG indicators with a focus group, (2) conceptualizing and designing a data model that integrates urban geometry with subjective human perceptions, and (3) prototyping and developing the CIM model. This approach allows for a multi-scale assessment of socio-environmental sustainability, accounting for uncertainty in human perception. The novelty of this research lies in creating a replicable CIM method that converts non-geocoded citizen perceptions into spatially weighted and probabilistic indicators. Future work will complete the CIM workflow, detailing the integration of the ESG indicators in a practical CIM tool designed to inform decisions through reporting and recommendations.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "name": "Majd Al Jurdi"
    },
    {
      "name": "Vedrana Ikalovic"
    },
    {
      "name": "Rania Wehbe"
    },
    {
      "name": "Hussein Mroueh"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/3qwnwsy319p98.bib",
  "cited_by": 0,
  "doi": "10.1016/j.scs.2026.107982",
  "fulltext_url": null,
  "id": "3qwnwsy319p98",
  "issns": [
    "2210-6707"
  ],
  "landing_url": "https://hal.science/hal-05794936v1",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "hal",
      "0.sde"
    ],
    [
      "hal",
      "1.sde.ie"
    ],
    [
      "openalex",
      "3305|Geographic Information Systems Studies"
    ]
  ],
  "openalex": "W7220470303",
  "pdf_url": "https://www.sciencedirect.com/science/article/pii/S2210670726008668/pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-12",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/3qwnwsy319p98.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:54Z",
      "native_id": "hal-05794936",
      "source": "hal",
      "url": "https://hal.science/hal-05794936v1"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "hal:0.sde",
      "subfield": "environmental-science"
    }
  ],
  "title": "Methodology for a human-centric CIM: Translating non-geocoded citizen perceptions into spatial indicators",
  "title_text": "Methodology for a human-centric CIM: Translating non-geocoded citizen perceptions into spatial indicators",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:54Z",
  "url": "https://research.draconitic.com/paper/3qwnwsy319p98",
  "venue": "Sustainable Cities and Society",
  "versions": []
}