Biodiversity credit markets are growing, driven by policy pressure, corporate nature commitments, and the EU Nature Restoration Regulation. Establishing credible credits requires evidence that biodiversity improved — and traditional monitoring approaches create several barriers:
- Field surveys are expensive and slow: Comprehensive habitat and species surveys cost tens to hundreds of euros per hectare and cannot be repeated frequently across large sites. For many projects, monitoring costs exceed what credit revenues can support.
- Baselines are hard to reconstruct: Proving biodiversity improved requires knowing what the site looked like before the intervention. Without historical spatial data, establishing this baseline after the fact is difficult and open to dispute.
- Greenwashing risk undermines buyer confidence: Without independent, objective monitoring, buyers cannot verify that the biodiversity outcomes a project claims actually occurred — or that those gains are being maintained over time.
- Methodologies are fragmented: Different credit standards (Verra, Gold Standard, IUCN, national schemes) use different biodiversity metrics and monitoring approaches. This makes comparison across markets difficult and limits investor confidence.
- Large and remote sites are not covered: The biodiversity-rich landscapes most in need of protection are often too large or too remote for comprehensive field survey programmes.
How EO can help
Satellite data provides spatially consistent, repeatable, and independently produced monitoring information that complements or replaces field surveys in biodiversity credit schemes:
- Habitat mapping and extent accounts: Satellite imagery classified against EUNIS or IUCN Global Ecosystem Typologies maps habitat types at 0.5 ha resolution. These maps provide the spatial baseline that credit issuance requires and can be updated annually to track change.
- Vegetation condition tracking: Multi-temporal Copernicus Sentinel-2 imagery detects shifts in vegetation cover, greenness, and land use over time — giving verifiers objective evidence that an intervention is working or that a credited habitat is being maintained.
- Above-ground biomass estimation: SAR-based biomass mapping using Sentinel-1 and ALOS-2 PALSAR-2 data quantifies vegetation structure — a measurable proxy for habitat quality in forest and woodland credit schemes.
- Independent verification layer: Satellite products are produced independently of any project developer or verifier, making them a credible reference that auditors and buyers can use to check credit claims against observed outcomes.
- Scalable coverage: A single satellite acquisition covers millions of hectares at consistent cost. This makes monitoring financially viable for large and remote sites where field survey programmes are not.
Key examples
1- LEON — Pilot 4: EO for biodiversity credit markets
LEON (Leveraging Earth Observation for Nature Finance) is an ESA-funded project developing EO-based data tools for nature finance. Pilot 4, led by the University of Oxford’s Nature Positive Hub and involving TNFD stakeholders, assesses emerging biodiversity credit markets to identify monitoring gaps and develop EO-based approaches for tracking biodiversity improvements at credit project sites. The pilot examines existing and planned credit systems, identifies where EO data can substitute or supplement field monitoring, and works to prevent greenwashing through satellite-verified reporting.
Figure: Global map of biodiversity credit initiatives: operational state and market function (n=37) (from Wunder et al., 2025)
2- EO4Biodiversity — EO for Biodiversity Net Gain compliance
EO4Biodiversity, funded by ESA’s InCubed programme and developed by HR Wallingford, automates habitat mapping and Biodiversity Net Gain (BNG) assessment using satellite data. Under UK law, all new developments must deliver at least a 10% net gain in biodiversity, measured in Standardised Biodiversity Units (SBUs). Calculating SBUs manually across large schemes is expensive — Water Resources South East estimated manual costs at around 1.6 million euros per planning cycle. EO4Biodiversity replaces this with an automated, satellite-driven workflow that identifies habitat types, calculates biodiversity values, and produces repeatable BNG assessments at landscape scale.
Source: HR Wallingford
3- Planet Project Centinela — satellite data for biodiversity conservation sites
Planet Project Centinela is a digital public good programme that grants conservation organisations at selected biodiversity sites three years of access to Planet’s full data stack: near-daily PlanetScope imagery, monthly mosaics, and Planetary Variables covering forest structure and carbon, soil water content, and land surface temperatures. The programme currently covers 18 sites, spanning 271 protected and conserved areas, 132 key biodiversity areas, and habitat for 845 threatened and endangered species.
Source: Planet.com
4- Verra Nature Framework — standardised biodiversity credit methodology
Verra has launched the Nature Framework under its SD VISta programme, establishing a methodology for biodiversity credit issuance measured in quality hectares (Qha) of net biodiversity outcomes. The framework sets out requirements for baseline setting, additionality, social safeguards, and credit issuance. The programme has active pilot projects across Europe, Africa, Asia, and the Americas, and is intended to contribute to the biodiversity finance targets of the Kunming-Montreal Global Biodiversity Framework.
5- APEx SEF Ecosystems and Biodiversity Explorer — habitat mapping demonstration
The ESA SEF team has integrated habitat mapping products into the Ecosystems and Biodiversity Geospatial Explorer. The Terrestrial Monitoring section includes EUNIS-classified habitat maps for Greece and Slovakia produced by the ESA PEOPLE-EA project, and Natura 2000 land cover and topsoil carbon data within protected site boundaries. These datasets illustrate the kind of habitat condition data that biodiversity credit schemes use to set baselines and track change.
Figure: Habitat map for Greece showing ecosystem types at EUNIS Level 1 2020, with NUTS regional statistics. Data source: ESA PEOPLE-EA via APEx SEF Ecosystems and Biodiversity Explorer.
