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Mapping ESRS Disclosure Datapoints to Relevant Datasets

Steven Owens

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Abstract

The integration of geospatial data into sustainability reporting frameworks addresses challenges related to inconsistent and outdated Environmental, Social, and Governance (ESG) information. This third white paper from the Financial Regulation Innovation Laboratory (FRIL) explores the application of geospatial data in enhancing the European Sustainability Reporting Standards (ESRS). By aligning geospatial datasets with specific ESRS disclosure requirements, the study provides a foundation for corporations conducting double materiality assessments, auditors validating disclosures, and third parties—such as financial institutions and environmental organisations—performing due diligence.

Geospatial data can be applied at the asset level (e.g., factories) or aggregated using a bottom-up approach linked to financial ownership, improving transparency and comparability across companies, sectors, and regions. However, the study finds that only 7% of ESRS datapoints can be externally validated due to the dependence on proprietary company information. Despite this limitation, different stakeholders benefit from distinct datapoints: investors may prioritise datapoints linked to external risks such as flooding or greenhouse gas emissions, while water-focused non-governmental organisations may emphasise hydrological indicators.
The EU Omnibus package (February 2025) introduces significant changes to ESRS and corporate sustainability reporting. These include a reduction in in-scope companies (80% fewer under the Corporate Sustainability Reporting Directive), limited value chain coverage, and fewer required datapoints, which may lead to a data gap and reduced transparency. However, the shift towards quantitative over qualitative datapoints presents a critical opportunity for geospatial data to bridge this gap, offering independent, real-time, and scalable insights for ESG reporting.

Furthermore, the revision of assurance requirements under the Omnibus package raises concerns about data verification and reporting accuracy. Given these regulatory shifts, integrating satellite-derived data into sustainability reporting frameworks could enhance objectivity, comparability, and reliability. Future regulations should embed geospatial data as a core element to strengthen the integrity and effectiveness of sustainability disclosures in the EU and beyond.
Original languageEnglish
Place of PublicationGlasgow
PublisherUniversity of Strathclyde
Number of pages33
DOIs
Publication statusPublished - 14 Mar 2025

Publication series

NameFinancial Regulation Innovation Lab White Paper Series
PublisherUniversity of Strathclyde
ISSN (Electronic)3033-4136

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  3. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  4. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  5. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • sustainable finance
  • Earth observation
  • satellite data
  • financial services
  • EU
  • CSDDD
  • CSRD
  • SFDR
  • ISSB
  • GRI
  • artificial inteligence
  • generative AI (GenAI)
  • biodiversity
  • nature
  • sustainability standards
  • disclosures
  • assurance
  • ESG
  • environmental
  • geospatial

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