Ecosystem Integrity Index (EII)
Assesses the overall health of an ecosystem with focus on structure, composition and function.
availability
On Demand
Now
indicator tier
Gold
unit
Index values ranging from 0 (degraded) to 1 (intact)
spatial resolution
300m
measurement frequency
Annual
measurement level
Plot
historic data availability
2025
Forescast data availability
N/A
applicable crop types
All
applicable land type
Grassland
Conservation
Forestry
Annual Cropland
Perennial Cropland
compliance frameworks
Nature Positive Initiative (NPI), TNFD, SBTN, CSRD (ESRS E4)
description
The Ecosystem Integrity Index (EII) is a composite measure designed to assess the integrity of terrestrial ecosystems, defined as the combination of three key components: structural, compositional, and functional integrity. The EII provides a quantitative score, ranging from 0 (highly degraded) to 1 (fully intact), allowing for the measurement, monitoring, and reporting of ecosystem health.
methodology
This implementation of the EII follows a framework published by UNEP WCMC (Hill et al., 2022). It quantifies the subcomponents of compositional intactness (Biodiversity Intactness Index, Gassert et al. 2022)), structural intactness (derived from Global Human Modification footprint (Theobald et al., 2025) and functional integrity (based on remotely-sensed net primary productivity from Sentinel 3). The operational spatial resolution is 300m. Data will be updated annually.
validation
The sub-components of the EII are validated during model development against hold-out data and plausibility. The BII has been evaluated using hold-out sets by Gassert et al. (2022), the human modification layer has been peer-reviewed and validated by Theobald et al. (2025). Productivity data itself has been validated by the Copernicus Land monitoring center. Further modelling of potential net primary productivity potential has been validated using spatial hold-out techniques.
model limitations
The index combines components built from different source datasets and reference years, so they may not perfectly align in rapidly changing landscapes. The “natural potential” productivity reference is a contemporary benchmark and can require extrapolation in regions with little remaining pristine area; the functional component also penalises unusually high productivity (which can occur under intensive management). Structural and compositional components are influenced by human‑pressure data and do not capture all aspects of connectivity, and confidence is higher in well‑surveyed regions than in data‑sparse areas.
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