3 March 2026
How sustainable finance can look to space and how space must know its place in sustainable finance
Sustainable finance has made rapid progress over the past decade, but it has also developed a structural blind spot. In seeking credibility, consistency, and regulatory compliance though traditional sector norms, it has gravitated toward short-term, easily measurable interventions. These are actions that deliver visible, auditable outcomes within reporting cycles, yet often fail to address the deeper, long-term environmental challenges that sustainability frameworks and responsible investing are intended to confront.
At the same time, a powerful but underutilised set of tools has matured largely outside the financial system: space-based and geospatial data. Earth observation (EO), satellite analytics, and spatial modelling now provide continuous, global, and historically rich insights into land use, ecosystems, carbon stocks, and environmental change. The challenge is no longer technological. It is institutional. The core question is how such data can become finance-grade: credible, decision-relevant, and trusted within investment, assurance, and regulatory processes.
This piece focuses on two related issues: where space data can genuinely add value to sustainable finance, and why the assurance gap remains the principal barrier to its adoption.
Where space data can add real value
Space data is often presented as a universal solution to sustainability measurement. This is a mistake. Its real strength lies not in replacing existing tools, but in augmenting financial decision-making precisely where traditional data struggles most: scale, time, and counterfactuals.
Long-horizon monitoring of natural capital and land systems
Many of the most important sustainability investments, including reforestation, peatland restoration, regenerative agriculture, biodiversity recovery, each operate on decadal timescales. Conventional project monitoring, based on periodic site visits or self-reported metrics, is poorly suited to capturing slow, spatially heterogeneous change.
Satellite data, by contrast, offers continuous observation over long periods, often spanning decades, consistent coverage across regions and jurisdictions; and coupled with robust science-grounded models, holds the ability to detect trends, not just point-in-time outcomes.
For sustainable finance, this matters because the value of many nature-based investments lies in persistence and resilience, not immediate impact. EO data enables investors, policymakers, and regulators to observe whether environmental gains are maintained, degraded, or reversed over time; something traditional reporting frameworks struggle to do.
Establishing baselines and credible counterfactuals
One of the most contentious issues in sustainable finance is additionality: would an environmental outcome have occurred anyway, without the investment? Weak baselines undermine credibility, particularly in voluntary carbon and biodiversity markets.
Space data provides a unique advantage here. Historical satellite archives allow analysts to construct dynamic baselines that reflect prior land use and environmental trajectories, compare treated and untreated areas in a spatially explicit way; and develop counterfactual scenarios grounded in observed patterns rather than assumptions.
This capability is critical for moving beyond static, narrative-based claims of impact toward evidence-based assessment. When properly integrated into financial evaluation, it strengthens the integrity of claims around carbon sequestration, land regeneration, and ecosystem recovery.
Scaling nature-based solutions and green infrastructure
Nature-based solutions are frequently constrained not by lack of capital, but by lack of investment-ready evidence. Investors need confidence that projects can be assessed, monitored, and compared across locations.
Geospatial data helps bridge this gap by enabling portfolio-level assessment of environmental exposure and impact, identification of regions where nature-based interventions are most likely to be effective; and ongoing monitoring at scale, reducing reliance on bespoke, site-specific reporting.
This is particularly relevant for institutional investors seeking exposure to sustainability themes without assuming unmanageable monitoring costs or verification risks.
Supporting transition and adaptation finance
Beyond mitigation, space data is increasingly relevant for physical climate risk and adaptation finance. Satellite-derived indicators of drought stress, flood exposure, land degradation, and temperature variability can inform both asset-level risk assessment and broader transition strategies. Here, the value proposition is not precision at the individual asset level, but consistency and comparability across portfolios and regions, allowing investors and regulators to understand relative exposure and vulnerability.
The assurance and “finance-grade data” gap
Despite these advantages, space data remains peripheral to mainstream sustainable finance. The principal reason is not scientific uncertainty, but a misalignment between how geospatial data is produced and how financial systems establish trust.
Science-grade versus finance-grade evidence
Earth observation data is probabilistic, model-based, and often indirect. Financial assurance systems, by contrast, are built around: deterministic metrics, clear audit trails, and legal defensibility.
This mismatch creates discomfort. Even when satellite-derived indicators are scientifically robust, they may be perceived as insufficiently “hard” for financial reporting or regulatory compliance. As a result, institutions default to simpler, more familiar metrics, even if these are less informative.
Auditability and accountability
A central challenge is who stands behind the data. In financial reporting, assurance depends on clear responsibility: auditors certify numbers produced under defined standards. With space data, responsibility is distributed across satellite operators, data processors, model developers, and end users.
Without agreed standards for validation, uncertainty disclosure, and governance, geospatial insights struggle to achieve the status of finance-grade evidence. This is not a technical problem alone; it is a governance problem.
Lessons from voluntary carbon markets
The credibility crisis in voluntary carbon markets illustrates the cost of weak assurance. Many failures were not due to malicious intent, but to poor baselines, inadequate monitoring, and over-reliance on self-reported or episodic data.
Ironically, these are precisely the weaknesses that continuous satellite monitoring could help address. However, without formal recognition within standards and assurance frameworks, EO data has often been used inconsistently or selectively, undermining trust rather than strengthening it.
Institutional conservatism and capability gaps
Financial institutions are understandably cautious. Integrating geospatial data requires new skills, new procurement practices, and new forms of collaboration between finance, science, and policy teams. In the absence of regulatory clarity, many institutions prefer to wait.
This creates a coordination problem: widespread adoption depends on standards and recognition, yet standards and recognition depend on adoption.
Implications for policy, finance, and research
Closing the assurance gap will require institutional innovation, not just better data. Key priorities include:
- Developing shared validation and assurance frameworks for space-derived sustainability metrics.
- Embedding geospatial evidence within regulatory and disclosure regimes in a way that recognises uncertainty without paralysing decision-making.
- Strengthening the role of universities and applied research centres as trusted intermediaries between science and finance.
Large asset owners and public institutions also have a role to play in supporting market infrastructure, rather than waiting for fully formed solutions to emerge.
Conclusion: space data can play a central role, if it is allowed to become finance-grade
Seeing space and geospatial data as mainstay in sustainable finance means recognising that many of the hardest sustainability challenges are long-term, spatially complex, and system-wide. Space data will not solve these challenges on its own, but without it, sustainable finance risks remaining focused on what is easiest to measure rather than what matters most.
The next phase of sustainable finance will be defined not by more data, but by better alignment between data, robust science, assurance, and institutional purpose. Space data can play a central role, if it is allowed to become finance-grade.
Andrew Iwanoczko
Founder and CEO of innovation consultancy Callala Ltd