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European Environment Agency
Kongens Nytorv 6 Copenhagen - 1050 Denmark

High Resolution Layer: Forest Type 2018 (raster 100m), Oct. 2020

Type: datasetLicense: not specifiedCategory: imagery, base maps, earth coverResolution: 100 metersLast update: 2 years ago
Land cover

The High Resolution Layer (HRL) Forest Type (FTY) 2018 at 100 m spatial resolution is an aggregated version of the FTY layer at 10 m spatial reoslution, fully aligned with the EEA reference grid, and provides a forest classification with 3 thematic classes (all non-forest areas / broadleaved forest / coniferous forest). The dataset is provided as a full mosaic covering EEA38 countries and the United Kingdom. The production of the High Resolution forest layers was coordinated by the European Environment Agency (EEA) in the frame of the EU Copernicus programme.

The high resolution forest product consists of three types of (status) products and additional change products. The status products are available for the 2012, 2015 and 2018 reference years: 1. Tree cover density providing level of tree cover density in a range from 0-100%; 2. Dominant leaf type providing information on the dominant leaf type: broadleaved or coniferous; 3. A Forest type product. The forest type product allows…

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Data origin:

The Forest Type 2018 status layer at 10m spatial resolution is mainly based on the primary status layer Dominant Leaf Type 2018, which was produced by a hierarchical spatio-temporal classification of time features derived from Sentinel-2A+B time series (Level-2A data) using a Random Forest (RF) classifier with 500 trees. The default time window ranges from 01-03-2018 to 31-10-2018 and was adapted to regional conditions where needed. In total, 147 statistical time features have been calculated using more than 500,000 samples, automatically collected from the LUCAS 2018 database and various CLMS products plus additional manual sampling. First, a binary Tree Cover Mask (TCM) with 2 classes (all non-tree covered areas / tree cover) has been generated. Various post-processing steps have been applied in order to improve the quality of the mask (e.g. correction of omission errors caused by the topographic overcorrection within the native Sentinel-2 Level-2A input data). Subsequently, the…

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Purpose: not specified

Data life cycle, according to producer:
Creation date: October 20, 2020
Update frequency: continual



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