Access to data is based on a principle of full, open and free access as established by the Copernicus data and information policy Regulation (EU) No 1159/2013 of 12 July 2013. This regulation establishes registration and licensing conditions for GMES/Copernicus users.

Free, full and open access to this data set is made on the conditions that:

1. When distributing or communicating Copernicus dedicated data and Copernicus service information to the public, users shall inform the public of the source of that data and information.

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

3. Where that data or information has been adapted or modified, the user shall clearly state this.

4. The data remain the sole property of the European Union. Any information and data produced in the framework of the action shall be the sole property of the European Union. Any communication and publication by the beneficiary shall acknowledge that the data were produced “with funding by the European Union”.

For Dominant Leaf Type (DLT), temporal convolutional neural networks have been trained for biogeographically strata (production units) on Sentinel-2 time-series for all reference years ± 3 months. The training data has been derived from LUCAS 2018, existing CLMS products and through interpretation of VHR imagery and Sentinel-2 time series. Post-classification processing steps include spatial and temporal filtering to assure a high consistencyof the time series while preserving acutal land cover changes. Thematic target accuracy: 90% producer and user accuracy.

This dataset is a continuation of the HRL Dominant Leaf Type timeseries, previously generated on a 3-year update cycle since 2012. The models and input data used to generate the product have evolved and therefore higher quality is to be expected as the timeseries progress.

Quality assurance follows the ISO9000 standards for Quality Management and comprises of dedicated procedures of ongoing 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 accuracies 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) Thematic Accuracy,

(iv) Temporal quality and

(v) Usability.

Each of them (excl. the Thematic Accuracy hereafter) forms a section in the QA/QC Procedures.