A new review discusses prospects, challenges, and regulatory frameworks for integration of geospatial data and workflow into sustainability compliance reporting
Environmental and sustainability compliance reporting is getting increasingly dependent on geospatial data and workflows. However, understanding of the connection between new European Union (EU) regulations and existing Earth Observation (EO) and Geographic Information System (GIS) technologies is limited. A new review study highlights how close alignment of law, data, and corporate practices can ensure that the geospatial workflows are fit for purpose in environmental and sustainability compliance reporting.
Sustainability reporting has evolved over the last ten years from being mostly optional to being mandatory. In the EU, major frameworks such as the Corporate Sustainability Reporting Directive (CSRD), the European Sustainability Reporting Standards (ESRS), the EU Taxonomy, the Sustainable Finance Disclosure Regulation (SFDR), and the EU Deforestation Regulation (EUDR) now require companies to disclose detailed, verifiable information about their environmental impacts, risks, and supply chains.
However, there is a growing disconnect between new, stricter sustainability regulations and how companies currently report environmental performance. Most corporate disclosures still rely on aggregated metrics, self-reported data, or methods that are difficult to audit. At the same time, although satellite and geospatial data are widely used in environmental research, their role in legally robust compliance reporting has not been clearly defined.
To address this, a structured scoping review was conducted by a group of scientists, led by Professor Thomas Blaschke from the University of Salzburg. Based on the review, they proposed a framework for distinguishing three families of geospatial workflows—risk screening, attribution, and verification. Their novel findings were made available online in the journal Big Earth Data on January 24, 2026.
Prof. Blaschke, the corresponding author of the study, highlights the importance of their work. “Our work focused on understanding how companies can comply with the rapidly evolving sustainability laws. Environmental impacts are often definite, yet reporting from the private sector has often remained nonconcrete. By bringing together regulatory requirements and advances in satellite and geospatial science, our study shows how Earth observation can help turn sustainability reporting into something more transparent, comparable, and independently verifiable.”
The study proposes three families of geospatial workflows that recur across multiple frameworks. Risk screening can be done, using global land cover products, forest loss maps, and near‑real‑time alerts, to flag geographies, suppliers, or assets that may be exposed to deforestation, biodiversity loss, or other environmental risks. Attribution of impacts to specific assets or value-chain segments is also important, which can be done by linking detected impacts, such as forest loss or pollution, to specific farms, facilities, or value-chain segments. This often requires higher‑resolution data and more complex analysis. Lastly, verification involves independent assessment of the company self‑reports, for example, by confirming that a “deforestation‑free” coffee supply does not overlap with forest loss after the EUDR’s 31 December 2020 cut‑off date.
Instead of being used as ornamental maps in sustainability reports, the study strongly emphasizes the need for geospatial layers to be handled as regulated reporting inputs with documented provenance, uncertainty, and versioning. The authors highlight the significance of methodically reporting lineage, completeness, positional, temporal, and thematic accuracy, ideally using ISO 19115-style metadata, based on geospatial data quality research. This allows auditors and regulators to determine whether a dataset is “fit for purpose” in a particular compliance context.
The paper also highlights the opportunity and risk in the rapid rise of GeoAI, the fusion of artificial intelligence (AI) and EO in operational services. While AI models promise more detailed, consistent mapping of forest structure, agroforestry systems, and land‑use dynamics that are critical for regulations, understanding about their training data, benchmarking, or uncertainty is limited, which hinders their suitability for regulated reporting. As the study suggests, open, peer-reviewed geospatial workflows and reference implementations can help to close this gap.
“For researchers, our review offers workflows of where methodological work is most urgently needed. For policymakers, it clarifies what kind of geospatial guidance and infrastructure would make regulations more implementable. And, for companies, it suggests a strategy that uses modular workflows, open EO data, and explicit reporting to navigate an increasingly GeoAI‑enabled compliance landscape,” remarks Prof. Blaschke while talking about the impact of this study.
As sustainability reporting becomes increasingly regulated, geospatial data is emerging as a critical bridge between policy and practice. The study emphasizes how standardized reference datasets, benchmarking protocols, and interoperable platforms involving regulators, data providers, and corporate users can make GIS and satellites essential tools for transparent and trustworthy environmental accountability.
