The Copernicus component is governed by Regulation (EU) No 2021/696 of the European Parliament and of the Council of 28 April 2021 establishing the Union Space Programme and the European Union Agency for the Space Programme and repealing Regulations (EU) No 912/2010, (EU) No 1285/2013 and (EU) No 377/2014 and Decision No 541/2014/EU. Within the Copernicus component, a portfolio of land monitoring activities has been delegated by the European Union to the European Environment Agency (EEA) and the DG Joint Research Centre of the European Commission.

The Copernicus land monitoring products and services are made available on a principle of full, open and free access, as established by the Commission Delegated Regulation (EU) No 1159/2013 of 12 July 2013.

Free, full and open access to the products and services of the Copernicus Land Monitoring Service is made on the conditions that:

1. When distributing or communicating Copernicus Land Monitoring Service products and services (data, software scripts, web services, user and methodological documentation and similar) to the public, users shall inform the public of the source of these products and services.

2. Where the Copernicus Land Monitoring Service products and services have been adapted or modified by the user, the user shall clearly state this.

3. Users shall make sure not to convey the impression to the public that the user's activities are officially endorsed by the European Union.

The Tree Cover Change Mask (TCCM) 2015-2018 is a change product based on the binary Tree Cover Masks (TCMs) of the primary status layers Dominant Leaf Type 2015 at 20m spatial resolution and Dominant Leaf Type 2018 at 10m spatial resolution. First, the 2018 product has been aggregated to 20m to enable a map-to-map comparison. The therof derived pixel-based change map is categorised into loss and gain strata and subsequently reclassified using the Reference Database for Change Calibration to improve the TCM 2018 and to detect omission and commission errors in the TCM 2015. Subsequently, a 1 pixel boundary filter has been applied in order to mitigate geometric imprecisions between the input layers 2015 and 2018, caused by the different satellite input data characteristics. Remaining change areas are filtered according to the specified Minimum Mapping Unit (MMU) of 1 ha. Finally, a manual enhancement has been performed within identified regional clusters of remaining issues, considering both: loss and gain of tree cover. The product covers the whole EEA39 area and is provided in European projection. National products might show a broken MMU due to reprojection.

Quality assurance follows the ISO 9001:2015 standards for Quality Management and comprises of dedicated procedures of quality checks (QA breakpoints) during implementation of the production chain, in order to keep persistent control over the various stages of production, assure fitness-for-purpose of the end-products and that all quality requirements are fulfilled. Priority has been given to the target thematic accuracy to be achieved by each product, as well as to the issues of product consistency (spatial, thematic, temporal) and homogeneity. Quality Assessment: The quality assessment has been performed according to INSPIRE Data Specifications. The data quality elements considered are: (i) Completeness, (ii) Logical Consistency, (iii) positional accuracy, (iv) Thematic Accuracy, (v) Temporal quality and (vi) Usability.

Geometric accuracy (positioning scale): Less than one pixel (10m) according to ortho-rectified satellite image base (Sentinel-2 Level-2A) delivered by ESA.

Thematic target accuracy: 90% producer and user accuracy.

Final validation results TCCM 1518 at pan-European level: 97.99% overall accuracy with a 95% confidence level applied (unchanged areas with no tree cover: 98.45% producer accuracy and 98.47% user accuracy; new tree cover: 58.74% producer accuracy and 86.73% user accuracy; loss of tree cover: 65.08% producer accuracy and 87.28% user accuracy; unchanged areas with tree cover: 98.02% producer accuracy and 97.93% user accuracy).

Thematic accuracy has been assessed using a stratified random sampling approach with 9,695 points (area weighted), visually interpreted using VHR_IMAGE_2018, VHR_IMAGE_2015 and Sentinel-2 time series data, complemented by additional data sources like virtual globes (e.g. Google Earth Pro).