Beyond the Light Bulb - How sustainable finance can look to space, and how space must know its place in sustainable finance

Introduction

Sustainable finance as a concept and construct, holds great opportunity in how companies grow and transform into responsible businesses.  Varying levels of sustainable finance growth over the past decade have been touted – an expansion of somewhere between approximately 2x and 10x since 2015.  In the UK at least, we’ve seen a touch of dampening through late 2024 and 2025 because of the Sustainability Disclosure Requirement (UKSDR) as the Financial Conduct Authority (FCA) raises the bar.  The FCA’s aim is to limit green-washing opportunity and assure credible projects are delivered and real transformation is achieved.  Despite this additional rigour and strong intent, much of the practical deployment of sustainable finance focuses on short-term, easy-to-measure projects. These are often chosen because their impact stories are both simple to tell, and in practice, they are quick to both complete and report against.

Replacing industrial light bulbs with energy-efficient alternatives for instance, is often held up as a success story. Whilst sounding peculiar as an activity or project that might attract a sustainable finance, such projects deliver an immediate carbon saving and an easy to measure return on investment. This type of intervention however risks missing the point.  This can be viewed as a premature replacement of functioning assets as a short-term environmental harm alongside making a small, positive, long-term environmental choice.

The more fundamental, so perhaps better opportunity may be through tackling larger, systemic challenges.  These tend to lie in the areas where environmental and social transformation take time, that depend on place and scale, and that require new kinds of evidence. These are more likely interventions in areas with more complicated investment theses.  They may also include aspects that are tougher to evidence through independent means for quantified environmental, social and financial impact.  It is across these areas where space and geospatial technologies can today, and certainly will in future, help to play a powerful role.

The role of space is often misunderstood in non-space markets. Although it is more convincingly argued that there is an issue with how space companies communicate to non-space markets. Others however might say that space is undervalued.  Either way, satellites now provide a constant, objective record of the Earth's surface, yet crucially, the connection between satellite data capture and its utilisation in financial decision-making remains weakly linked.

Despite its flimsy thread today, this piece explores the intersection of space data, geospatial insight as evidence for ESG-related impact and sustainable finance, and how this end-to-end links might be strengthened in time. It asks how a sector managing over £3 trillion in UK pension assets could drive long-term sustainability if it better linked the financial system with environmental and social intelligence from space. 

The burden of compliance and the short horizon of impact

Once a fund, whether a pension or private equity fund, starts investing directly in projects that use sustainable finance mechanisms, the fund managers are understood to encounter a heavy compliance burden. Frameworks such as the Taskforce on Nature-related Financial Disclosures (TNFD) demand extensive reporting on biodiversity, dependencies and impacts. This is valuable for accountability and authenticity but absorbs much of the energy that might otherwise go into developing innovative ways to invest for impact and removes professionals from the conversations that help to spawn similar cases.  Where multiple independent analyses point in the same direction, then this absolutely creates an issue with scale.

The regulatory architecture of the EU’s sustainable‐finance regime may inadvertently reinforce short-termism dynamics. Villiers (2025) argues that, despite its ambitions, the framework risks becoming a ‘pact with the devil’ in which the burdens of compliance, measurement and financial‐flow logics dominate, and meaningful environmental outcomes, planetary boundaries and social justice become relegated to the background. Fichtner et al. (2025) highlight how private and regulatory standard-setting within the EU’s sustainable-finance architecture can entrench market-driven conventions that limit transformative environmental outcomes. The assertions illustrate how the regulatory design of sustainable-finance frameworks, intended to direct capital toward decarbonisation and other nature related benefit, can instead reinforce the dominance of financial logic and weaken incentives for genuine ecological transition.

Many portfolio managers therefore focus on projects with clear metrics and short payback periods. The light bulb analogy, financed as a sustainable loan, produces an immediate carbon reduction and a quantifiable return. The company undertaking the transition can claim an environmental success story in their next annual report. With capital cycling, the financier can demonstrably show win after win.  But it also produces waste and reinforces the idea that sustainable finance must always create a visible, countable impact on a short timeline. This appears to be more an operational mindset that sits inside the tenure window of a PLC leadership team, perhaps not so much a fully transformational mindset that spans a decadal implementation period and multi-decadal benefit window.

By contrast, investments that involve land restoration, ecosystem recovery or biodiversity gain deliver benefits over decades. Their impacts are gradual, spatially complex and dependent on local context. Measuring these requires consistent monitoring, historical comparison and dynamic baseline adjustment for normalisation against prevailing climatic conditions. This is where space and geospatial technologies can provide unique insight, but monitoring is rarely designed into projects from the start.

Grey infrastructure and the missed opportunity for nature

In the United Kingdom, most large-scale infrastructure remains dominated by traditional engineering methods that lead with concrete, steel and asphalt. Nature-based solutions as a function of these medium- and large-scale projects are often treated as decorative or compensatory, added only once the main design is complete.  Civil engineers who champion resilience increasingly argue that we should start from the opposite end: look first to what nature can provide, then blend grey and green infrastructure, and finally add engineered components where necessary.

Yet even when projects aim to integrate nature, the data that informs those decisions is usually fragmented. Ecologists collect field samples and combine them with various public datasets. These can describe what species are present but rarely how ecosystems are changing or how interventions might perform in the future.  At a site level, such assessments are manageable. But when scaled across transport corridors, urban areas or catchments, the economics of manually collected data wanes. This is one reason why space and geospatial data which can cover large areas with consistency, could be central to sustainable infrastructure planning. As it stands, most spatial data use in civil engineering is generic.  There are typically satellite basemaps, elevation models or land-cover data that help inform design but are seldom used to set baselines, verify outcomes, or underpin financing terms.

A limited but powerful role for space

As in many other sectors that use Earth observation, most sustainable finance decisions do not require high-resolution data. Instead, they depend on consistent, repeatable monitoring across space and time. The real value lies in a limited number of use cases where scale, comparability, and temporal depth are critical, and where the cost of maintaining the status quo is increasingly untenable.

Carbon and regenerative landscapes

Satellite-based Earth observation can be used to monitor land cover, vegetation health and biomass, supporting the identification of environmental change over time. In applied settings, these EO-derived indicators are routinely integrated into vegetation and soil carbon models to estimate biomass-based proxies relevant to carbon-related performance and to track temporal trends. In practice, as demonstrated in commercial land-use analytics platforms such as FLINTpro, satellite-derived inputs are combined with proprietary vegetation and soil models to operationalise these proxies for carbon accounting and land-use decision-making. Rapach et al. (2024) argue that a structured taxonomy of Earth observation data is essential for linking such insights to established ESG and sustainable finance disclosure frameworks, thereby improving transparency and enabling investors to better assess environmental performance.

Biodiversity credits and ecosystem services

Measuring biodiversity uplift is more complex than measuring carbon. It requires understanding habitat type, quality, function and connectedness. The combination of optical, radar and hyperspectral data, alongside emerging tools such as environmental DNA, can provide detailed insight into landscape recovery. Aragoneses et al. (2025) demonstrate how multi-sensor remote sensing methods combining spaceborne LiDAR, multispectral and radar data can produce spatially explicit, uncertainty-qualified maps of forest canopy structure at continental scale. While developed for wildfire risk assessment, such approaches illustrate how integrated Earth observation data can support robust measurement of biophysical ecosystem attributes. These hold direct relevance to wider ecosystem service and nature finance applications and so offer a potential starting position for evidencing credible biodiversity credit schemes.

However, the availability of increasingly sophisticated measurement techniques does not, on their own, determine how biodiversity is represented within policy and financial reporting frameworks. The challenge, as Zenglein (2025) observes, is that biodiversity measurement has become deeply politicised in the EU as part of the European Green Deal. The standardisation of biodiversity metrics for corporate sustainability reporting is more than a technical exercise. It is shaped by contested values, priorities, and competing interests. In this context, decisions over which aspects of nature are rendered visible, comparable, and governable, and who participates in those decisions, become inherently political. This politicisation shapes which measurement approaches are standardised and operationalised within reporting frameworks. For the space and geospatial data community, this has direct downstream implications for which types of Earth observation insights are demanded, how data products must be structured, and where institutional uptake and investment ultimately concentrate.

Grover et al. (2025) provide a practical illustration of these challenges through their study of natural capital accounting adoption in Tasmania’s forest management system. Their analysis shows that even in relatively well-resourced contexts with strong ecological data, translating ecosystem condition into financial and accounting frameworks requires navigating institutional barriers and ongoing debate around valuation approaches. The Tasmanian case demonstrates that the gap between ecological science and financial reporting is deeply institutional in nature.

In parallel to these institutional and political dynamics, and as a pragmatic response to the slow pace and contested nature of formal standard-setting processes, applied frameworks such as the NARIA methodology developed by the UK-based company CreditNature seek to enable action in the near term. NARIA is designed to work around wider politicisation by establishing ecologically acceptable condition categories, site-specific baselines, and dynamic reference points that allow biodiversity performance, additionality, and impact to be assessed across geographically distinct sites with differing ecological starting conditions and management objectives. While not yet universally adopted, such approaches aim to support consistent, repeatable measurement and monitoring in live projects, generating ecosystem service credits and evidence of uplift now, while remaining open to future alignment with more formalised standards as they evolve.

Temporal insight and baselining

One of the more overlooked advantages of Earth observation data is its long temporal record. Open access to historical Earth observation archives allows researchers to move beyond static assessments and understand how environmental systems have changed over time. Hinsby et al. (2024) highlight how sustained access to harmonised geoscience and Earth observation data supports sustainability applications by enabling the identification of long-term degradation trends, recovery dynamics, and delayed system responses. This temporal depth is particularly important for establishing credible environmental baselines that reflect a site’s historical condition rather than a single present-day snapshot, supporting more robust decision-making in sustainability policy and finance.

In applied contexts, this temporal perspective is increasingly operationalised through modelling frameworks that combine long-term Earth observation data with ecological and biophysical models. First-hand experience at FLINTpro illustrates how time-series satellite data can underpin dynamic baseline construction for forest and soil carbon assessment, enabling performance tracking that accounts for both management interventions and broader climatic variability.

A further and sometimes overlooked dimension of dynamic baselining is the need to establish credible counterfactuals. Rather than assessing temporal change at an intervention site in isolation, space-enabled time-series data allows comparison with neighbouring or representative reference sites that have not been subject to the same management intervention. These sites need not be immediately adjacent but must share sufficiently similar ecological characteristics and exposure to broader climatic drivers to be considered representative. By observing how these comparator sites evolve over the same period, it becomes possible to distinguish intervention-driven outcomes from background environmental change, strengthening claims of additionality and impact, or conversely demonstrating where broader climatic factors account for most of the observed change.

Product-grade data and assurance

For space-derived information to influence capital allocation, it must be translated into data products that meet the expectations of financial decision-making and assurance processes. This requires outputs that are reproducible, transparent, and capable of integration with existing reporting and analytical systems. Caldecott et al. (2022) highlight that while spatial finance is conceptually rich and offers significant potential, its practical application within mainstream financial analysis remains uneven and underdeveloped. Although geospatial data possess intrinsic qualities of traceability and verifiability, the absence of widely adopted protocols for translating observed environmental change into finance-grade evidence continues to limit their use as independent sources of assurance within sustainability and impact frameworks.

A persistent gap therefore remains between the potential of satellite-derived environmental data as a source of evidence and the expectations of the financial sector. Central to this gap is alignment with the professional norms that shape audit and assurance practice. These norms prioritise legal defensibility, procedural standardisation, and methodological precedent, and have yet to adapt to probabilistic, modelled, and spatially heterogeneous forms of evidence.

Filippi and Aiello (2025) illustrate this challenge through their analysis of Earth observation uptake within European local authorities. They show that even where satellite data are recognised as valuable for environmental monitoring and policy support, adoption is constrained by organisational routines, skills gaps, procurement practices, and institutional expectations around what constitutes usable and legitimate evidence. As a result, data products must align cleanly with existing workflows and accountability structures, and even analytically rigorous spatial data can be limited by the pace at which institutional processes evolve.

For sustainable finance and assurance this highlights a structural barrier. Evolution of audit conventions, assurance guidance, and institutional capability will in turn unlock wider utilisation of space-derived environmental data.

Schütze and Sandbaek (2025) make a related case, arguing that the EU Taxonomy represents a valuable framework, although its implementation is constrained by non-trivial practical challenges. Central among these is regulatory uncertainty over what constitutes sufficient and acceptable evidence for demonstrating taxonomy eligibility and alignment.  The EU taxonomy is understood to be driven by fragmented guidance, evolving requirements, and strict reliance on counterparty-provided data. The authors note that institutions often adopt conservative approaches to avoid reputational and greenwashing risks, prioritising legally defensible and standardised data even where this may understate alignment.

In this context, the integration of spatial and Earth observation data would require both technical validation for scientific robustness, and crucially, formal institutional recognition to adapt and shape disclosure, assurance, and audit practices. This points to the need for closer coordination between remote sensing experts, environmental auditors, and financial regulators to ensure that emerging data sources can be credibly incorporated within taxonomy-aligned reporting frameworks.  It additionally explains why technically mature Earth observation capabilities struggle today to be translated into finance-grade evidence.

Rebuilding trust and credibility

The credibility crisis in voluntary carbon markets has damaged investor confidence. Many REDD+ projects, designed to avoid emissions through forest conservation, have been criticised for overstating benefits. The issue is not only about intent but about evidence. Applied correctly, space and geospatial data can help rebuild that trust by providing continuous, independently verifiable monitoring.

Distinguishing between avoided emissions and genuine sequestration or biodiversity uplift, these data can support new kinds of nature-positive finance. They help underpin regenerative agriculture projects, catchment-scale rewilding or habitat. The results may be slower to appear than a light-bulb upgrade but managed well they could represent real and enduring change. In cases where there are heavily degraded landscapes and the interventions are well informed with soil types and drainage are well understood, and there is strong planning for climate change tolerant species, we should anticipate additionality to underpin credit issuance. But the converse is also true, i.e. where there is weaker design maybe because one of those key factors was poorly understood or deliberately ignored, then satellite derived geoinformation will reveal that too.

As of now, the market for such projects is small. There is limited demand for the kind of high-rigour products that would justify significant space-sector investment. Some argue a classic "chicken and egg" problem whereby investors want validated data products with a market ready-made before they commit, but product developers need committed finance and crucially committed buyers to build validation capacity on top of already high bar compliance requirements at project inception.

Connecting finance, data and purpose

To move beyond this impasse, both communities of finance and space may need to rethink how they communicate value. For the finance sector, this means recognising that not all sustainability benefits are immediate or easily monetised or are risk free. For the space sector, it means designing data products with end-user integration in mind.

Crona et al. (2025) offer a valuable framework for understanding how such transformation might occur. Adopting a systems perspective, they conceptualise sustainable finance as a complex adaptive system shaped by interactions between multiple actors, influence mechanisms, and reinforcing feedback loops. In their analysis, sustainable finance does not operate as a linear progression from capital allocation to environmental impact. Instead, feedback loops between investors, regulators, data providers, and project developers can either entrench existing practices or catalyse change.

Crucially, the authors argue that breaking entrenched dynamics requires deliberate interventions capable of initiating reinforcing, virtuous cycles. Rather than waiting for wholesale system transformation, targeted early actions and credible success cases can help reduce first-mover disadvantage, demonstrate viability, and trigger imitation across the system.

George et al. (2025) take this further by advancing the concept of “macro stewardship”, a transformative approach that reframes the role of institutional investors from passive capital allocators to active stewards of market systems. Macro stewardship positions large asset owners and managers as having responsibility for addressing systemic market failures and shaping the infrastructure within which markets operate.

This reframing implies that stewardship can extend beyond engagement with individual companies to include deliberate investment in, and advocacy for, the development of shared market infrastructure such as data standards, validation approaches, and measurement systems. In this view, stewardship is not ancillary to sustainability outcomes but constitutes a sustainability intervention aimed at correcting structural conditions that currently inhibit credible impact and long-term value creation.

Fichtner et al. (2025) provide empirical grounding for these theoretical positions by mapping the "channels of influence" through which private actors shape sustainable finance. Their framework reveals that financial institutions exercise power not only through capital allocation decisions but also through the development and application of standards, their use of ratings as an independent source of evidence, and other diligence practices that together shape how sustainability is incrementally delivered within the existing derisking regime. For space-derived data to gain traction as a routine channel of influence, it requires strategic positioning and integration into the taxonomies, indices, and reporting frameworks that structure investment decisions.

Lelechenko (2020) highlights that geoinformation technologies underpin many aspects of sustainable development yet are rarely treated as core components of economic and investment decision-making systems. Her analysis shows that while location-based data are widely used in territorial management and public administration, geospatial capabilities often remain institutionally separated from budgeting, investment planning, and resource allocation processes.

A similar disconnect exists where sustainability and ESG reporting increasingly rely on spatially explicit indicators, while the professionals responsible for managing geodata remain organisationally and culturally distant from those managing capital. Universities and applied research centres are increasingly repositioning themselves around more multidisciplinary models that combine Earth observation and geospatial analytics with finance, policy, and governance expertise. As a result, academia with a strong applied science focus has the potential to create the conditions for more effective deployment of sustainable finance.

Implications for policy and education

If the United Kingdom wishes to unlock the behavioural potential of its approximately £3 trillion pension system, sustainable finance must be more closely connected to credible and decision-useful evidence of environmental impact. By late 2024, estimates suggested that between 15 per cent and 25 per cent of pension assets claimed some degree of ESG alignment, a context that underpinned the introduction of the UK Sustainability Disclosure Requirements. Even a redirection of one per cent of pension capital, around £30 billion, towards verifiable nature-positive investment would represent funding at a scale comparable to roughly 30 per cent of annual net debt interest payments, calculated at 8.4 per cent of £1.155 trillion of public debt (Institute for Fiscal Studies, 2024). The principal constraint is probably less about capital availability, but the limited pipeline of investment-ready projects supported by credible and auditable measurement frameworks.

Whilst ecological and nature-based investments are often perceived as riskier than conventional infrastructure, the evidence suggests that the issue lies less in underlying risk and more in the difficulty of standardising, monitoring, and verifying environmental outcomes within existing financial architectures. Rodrigues Loiola et al. (2025) similarly argue that a significant component of perceived risk in sustainable finance instruments arises from weaknesses in outcome measurement and assurance, rather than from project fundamentals. As measurement and verification infrastructures mature, risk perceptions should adjust accordingly.

Addressing this gap responsibly requires new combinations of skill and institutional capability. Data literacy, environmental science, and financial modelling must increasingly intersect rather than operate in parallel. Graduates entering finance are likely to need the ability to interpret satellite-derived indicators of land-use change, ecosystem condition, or climate exposure with the same confidence as traditional financial ratios. Universities and applied research centres are therefore well placed to play a market-shaping role, developing curricula, research partnerships, and translational frameworks that embed spatial intelligence within financial decision-making without adding unnecessary complexity.

Conclusion

The intersection of sustainable finance and space technology is not a story of instant transformation. It is about shifting the mindset from quick wins to long-term, place-based change.

The financial system is already large enough to make this shift. The technology to measure and monitor outcomes already exists. The next step is creating a shared language and understanding connecting data with capital, and evidence with investment.

Sustainable finance may need to move beyond the light bulb and begin to embrace the complex, patient work of nature regeneration and ecosystem restoration. Space and geospatial data are certainly not the whole answer, but they are part of the toolkit that can make that transformation visible, measurable, assurable, and bankable.

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Graphic by Victoria Beall