Executive summary

The Leveraging Earth Observation for Nature Finance (LEON) project, supported by the European Space Agency (ESA), aims to transform the use of Earth Observation (EO) data in scaling nature-positive finance. Nature finance encompasses activities shifting financial flows away from nature-negative impacts and towards the conservation and restoration of natural ecosystems. A substantial financing gap persists, with the European Union alone requiring an estimated €200 billion per year to meet its biodiversity and restoration targets. Conversely, more than $7 trillion annually supports activities that degrade ecosystems. Key findings indicate that while demand for nature-related information is increasing due to disclosure frameworks like the Corporate Sustainability Reporting Directive (CSRD) and the Taskforce on Nature-related Financial Disclosures (TNFD), institutional integration remains limited by granular data gaps and fragmented platforms.

Introduction

The goal of LEON is to mobilise nature finance by embedding EO data into financial decision-making. The report establishes the conceptual foundation for the project and its six thematic pilots. It reviews the legal and regulatory drivers across Europe, standardises definitions, and presents user requirements based on multi-stakeholder engagement. Analyses underscore the urgent need for restoration, as 81% of protected habitats and 63% of protected species in the EU are currently in poor or bad conservation status.

Policy and environmental context for Europe

The European Commission has made major commitments to protect nature, including the 2024 Nature Restoration Law and the EU Biodiversity Strategy for 2030. These mandate Member States to restore 30% of degraded habitats by 2030. To meet these objectives, an additional €200 billion is needed annually. The EU is exploring market-based mechanisms such as biodiversity credits and aligning wider public finance flows, including the Common Agricultural Policy (CAP), with biodiversity goals. The LIFE Programme remains a primary funding instrument with a budget of €5.45 billion for the 2021–2027 period.

Nature finance: definitions, concepts and actors

LEON defines nature finance as incorporating both ‘greening finance’ (integrating nature-related risks into mainstream decisions) and ‘financing green’ (mobilising investment for conservation). The World Bank defines nature finance as finance contributing to the goal of halting and reversing nature loss. Four of the EU Taxonomy’s six environmental objectives have a strong nature component, including the protection of water resources and the transition to a circular economy.

Framing nature finance: status and trends

In 2022, annual financial flows to nature-based solutions were US$200 billion, of which 82% came from the public sector. Private finance flows remain modest at approximately $35 billion per year. The largest damaging sectors, representing over $200 billion annually in negative impacts, include construction and engineering ($570 billion), electric utilities ($445 billion), and real estate ($424 billion). Metals and mining account for $224 billion in negative impacts annually.

Instruments

Firms can raise capital for nature-positive practices through corporate bonds or sustainability-linked finance. Use of proceeds bonds allocate funds to specific projects, such as sustainable forest management. Sustainability-linked bonds (SLBs) include interest rate reductions if the issuer meets predefined sustainability targets. Examples include Ørsted’s €100 million blue bond for ocean biodiversity and Chilean manufacturer CMPC’s bonds for forest management.

Actors

The nature finance ecosystem involves real economy firms, financial institutions, and enablers such as regulators. Data providers and specialists play an essential role in providing information to mid-sized institutions. Central banks maintain strong capability on macroeconomic modelling but often rely on partners for environmental and EO expertise. LEON focuses on engaging this wider ecosystem to ensure knowledge and tools are embedded in decision chains.

PESTLE analysis

The political dimension shows high impact through the EU Green Deal and Global Biodiversity Framework. Economically, funding gaps limit scaling, though green jobs in the restoration economy present opportunities. Sociocultural awareness is growing, but institutional capacity remains limited. Technological growth in AI and remote sensing is enabling but hindered by data gaps. Legally, mandatory disclosures like the CSRD drive corporate behaviour, while environmental pressures like rapid biodiversity loss provide a foundational rationale for finance.

User requirements

Survey results indicate a strong demand for spatial environmental data, yet institutional integration is at an early stage. Respondents identified barriers including the lack of standardised metrics and insufficient asset-level geolocation data. Users strongly prefer processed, decision-ready datasets over raw satellite imagery. Medium spatial resolution (10–30 metres) is generally considered sufficient, and 78% of respondents emphasised the importance of ground-truth validation to build confidence.

Thematic findings

Six pilots test EO applications in real contexts. The mining pilot monitors water quality near Brazilian lithium sites, identifying pollution hotspots at a watershed scale. The agrifood pilot focuses on oil palm supply chains in Indonesia and Malaysia, using EO to track deforestation and fire incidence. Soil degradation is the focus of the financial risks pilot, noting that in England and Wales alone, soil degradation generates annual economic losses between £0.9–£1.4 billion. The biodiversity credits pilot examines measurement in the Netherlands and Mozambique. The natural capital accounting pilot applies the Biodiversity Intactness Index (BII) to Denmark. Finally, the sovereign finance pilot explores EO-verified KPIs for bonds and debt-for-nature swaps, following Uruguay’s issuance of the first sovereign SLB incorporating EO data.

EO best practices

A best-practice EO workflow should follow six components: compile high-quality documented satellite data; describe algorithms in transparent documentation; build modular, version-controlled software; generate experimental datasets in open formats; perform quantifiable validation against in-situ data; and publish data and code according to FAIR principles. A review of 22 datasets found that 18 were quantifiably validated, but only 14 were published according to FAIR principles and only 15 provided open access to source code.

Defining Earth Observation best practices for nature finance

Pragmatic data selection must reconcile trade-offs between spatial resolution, spectral resolution, and frequency of observation. High-quality EO data from programs like Copernicus meet international standards such as QA4EO. When using new or commercial datasets, users should document characteristics, disclose limitations, and cross-reference outputs with validated data to ensure robustness in financial decision-making.

Alignment to market needs and best practice – example of TNFD LEAP

The TNFD provides guidance on decision-useful data for the LEAP assessment framework. Challenges identified include variance in measurement approaches and relevance to market decision-making. TNFD recommends measuring both living components (structure, composition, function) and non-living components (water quality, soil structure). EO approaches are critical for identifying sensitive locations and determining ecosystem condition through changes in extent and quality.