The UN Statistical Commission adopted SEEA-EA as the international standard for natural capital accounting in 2021. Around 80 countries are now compiling some form of ecosystem accounts. Translating the standard into practice requires data that most national systems cannot currently produce:
- Ecosystem extent data is patchy and outdated: National land cover maps exist in most countries but use inconsistent classification systems, are updated infrequently, and rarely cover the full range of ecosystem types SEEA-EA requires.
- Ecosystem condition data is almost entirely missing: SEEA-EA requires biophysical condition indicators for each ecosystem type — vegetation health, soil carbon, biomass, water quality. National field survey programmes cannot produce these at national scale or at the annual cadence the standard expects.
- Green national income requires updatable biodiversity metrics: Several countries are developing biodiversity indicators for adjusted macroeconomic measures (green NNI, natural capital balance sheets). Traditional national biodiversity surveys are conducted every 5 to 10 years — too infrequent for annual reporting.
- Cross-border comparability is limited: Without a common spatial data infrastructure, ecosystem accounts compiled by different countries use different baselines, ecosystem typologies, and condition thresholds — making EU-level or global aggregation difficult.
- Capacity is uneven: National statistics offices in many countries do not have remote sensing capacity in-house, and the tools for translating EO data into SEEA-EA-ready accounts are not yet widely accessible.
How EO can help
Satellite data provides the consistent, spatially explicit, and updatable measurements that ecosystem accounting requires at national scale:
- Ecosystem extent mapping: Copernicus Land Monitoring Service and WorldCover provide annual land cover maps at 10 m resolution usable as the foundation for ecosystem extent accounts under the SEEA-EA framework.
- Ecosystem condition indicators: Satellite-derived variables — NDVI trends, tree cover density, fractional canopy cover, land surface temperature — provide biophysical condition measures across the full extent of each ecosystem type, at annual or seasonal frequency.
- Forest carbon stocks: BIOMASAR-derived above-ground and below-ground biomass maps, produced using Sentinel-1 and ALOS-2 PALSAR-2 data, quantify carbon in forest ecosystems — a core component of forest ecosystem accounts and natural capital balance sheets.
- Biodiversity condition indicators: EO-derived habitat maps combined with species distribution models can produce spatially explicit biodiversity indicators — such as the Biodiversity Intactness Score — at the resolution and frequency needed for green national income calculations.
- Historical baselines: Satellite time series going back to 1984 (Landsat) and 2016 (Sentinel-2) provide the multi-decade coverage that ecosystem accounting needs to establish reference conditions and measure long-term trends.
Key examples
1- LEON — Pilot 5: EO for green national income
LEON (Leveraging Earth Observation for Nature Finance) includes a pilot focused on integrating biodiversity into natural capital accounting at national level. Building on Denmark’s work to include biodiversity in green net national income using Red List indicators, the pilot develops and tests EO-derived metrics — including the Biodiversity Intactness Score — to produce high-resolution, annually updatable biodiversity assessments for inclusion in national accounts. The goal is a method that national statistics offices can use without requiring specialist remote sensing capacity in-house.
2- PEOPLE-EA — EO for ecosystem accounting
PEOPLE-EA is an ESA-funded project developing earth observation methods aligned with the SEEA-EA framework. The project produces ecosystem extent and condition accounts using Copernicus data streams, including EUNIS-classified habitat maps for multiple European countries such as ARIES for PEOPLE-EA Explorer.
The ARIES for PEOPLE-EA Explorer is a web-based application built on the k.LAB Integrated Modelling Platform. The application has access to all information (data and models) available on the Integrated Modelling network, and provides a dedicated user interface to allow the Early Adopters to easily access and test the output (ecosystem accounts) of the PEOPLE-EA project, funded by the European Space Agency, and developed by the ARIES team (BC3) in collaboration with the VITO team. It enables the power of using Earth Observation for ecosystem accounting through the use of the OpenEO (Open Earth Observations) platform, and through demonstrating the technical feasibility to integrate the European INCA ecosystem service account models.
Source: ARIES for SEEA
3- APEx SEF Ecosystems and Biodiversity Explorer — forest and habitat accounting data
The ESA SEF Ecosystems and Biodiversity Explorer integrates several datasets directly relevant to ecosystem accounting: EUNIS-classified habitat maps from PEOPLE-EA (ecosystem extent accounts), above-ground and below-ground biomass maps from BIOMASAR using Sentinel-1 and ALOS-2 PALSAR-2 (forest condition and carbon accounts), and Natura 2000 land cover statistics (condition within protected area boundaries).
Figure: Forest monitoring layers in the APEx SEF Ecosystems and Biodiversity Explorer showing above-ground biomass at 20 m resolution across Europe. Data source: BIOMASAR (Sentinel-1 and ALOS-2 PALSAR-2).
Further resources
Relevant resources:
Copernicus Land Monitoring Service — European land cover and ecosystem condition data
