Deforestation (including drivers)
Quantifies the extent and temporal dynamics of forest cover loss within a defined area, enabling the monitoring and assessment of ecosystem degradation and land-use change.
availability
On Demand
Now
indicator tier
Silver
unit
Hectares; Percent
spatial resolution
30m
measurement frequency
Annual
measurement level
Plot
historic data availability
2005 - 2025
Forescast data availability
N/A
applicable crop types
All
applicable land type
Grassland
Forestry
Perennial Cropland
Annual Cropland
compliance frameworks
CSRD (ESRS E4), EUDR, Nature Positive Initiative (NPI), SBTN, SBTi, TNFD
description
This indicator tracks the loss of forest cover. Monitoring deforestation is critical for assessing environmental impact, as it is a primary driver of biodiversity loss and greenhouse gas emissions. For businesses, this data is essential for ensuring supply chain transparency, complying with international regulations like the EUDR, and mitigating reputational risks associated with forest-risk commodities.
methodology
Our deforestation model provides information on forest loss from 2005 to 2025 and consists of two components. The first component, the basic section, reports deforestation based on the Hansen Global Forest Change dataset v1.13 (Hansen et al., 2013), which covers tree cover loss up to 2020. The second component, the advanced section, focuses exclusively on natural forest loss using data provided by Google, supplemented with additional information from RADD (Radar for Detecting Deforestation) alerts.
In addition, we provide location-based drivers of deforestation derived from the Global Drivers of Forest Loss dataset, developed by the World Resources Institute (WRI) and Google DeepMind (Sims et al., 2025).
validation
TBD
model limitations
Outputs are limited to the years covered by the configured forest‑loss datasets. Area estimates can be affected by classification and resampling uncertainty, and the benchmark labels are threshold-based categories rather than direct measures of ecological impact.
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