Dataset
Copernicus Land Monitoring Service Land Cover 2020, version 1
Abstract
Provides at the global level information on different types (classes) of physical coverage of the Earth's surface, e.g. tree cover, grasslands, croplands, permanent water bodies, wetlands at 10 m spatial resolution for the 2020 base year. The data are updated annually and will be available for the 2020-2026 years. This dataset builds upon initiatives like the 100 m Copernicus Global Land Cover layers (2015-2019) and offers enhanced spatial detail that facilitates more effective monitoring of global land cover changes, including deforestation, urbanization, and other environmental transformations. Please note: this version is still in beta status, as final validation is ongoing.
DOI for these data: https://doi.org/10.2909/602507b2-96c7-47bb-b79d-7ba25e97d0a9
Details
| Previous Info: |
No news update for this record
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| Previously used record identifiers: |
No related previous identifiers.
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| Access rules: |
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence(s): http://creativecommons.org/licenses/by/4.0/ When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record. |
| Data lineage: |
Data were produced by the project team and downloaded from the Copernicus Land Monitoring Service to be archived at the Centre for Environmental Data Analysis (CEDA). |
| Data Quality: |
Data downloaded directly from the Copernicus Land Monitoring Service for archival
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| File Format: |
These data are in Cloud Optimised GeoTiff (COG) format with a corresponding quicklook image.
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Related Documents
| Data information page |
| DOI |
| Full Land Cover metadata |
| User Manual |
| Data Policy |
Process overview
Instrument/Platform pairings
| Sentinel 1 Synthetic Aperture Radar (SAR) | Deployed on: Sentinel 1A |
Instrument/Platform pairings
| Sentinel 2 Multispectral Instrument (MSI) | Deployed on: Sentinel 2A |
Instrument/Platform pairings
| Sentinel 1 Synthetic Aperture Radar (SAR) | Deployed on: Sentinel 1B |
Instrument/Platform pairings
| Sentinel 2 Multispectral Instrument (MSI) | Deployed on: Sentinel 2B |
Computation Element: 1
| Title | Computation for the Copernicus Land Cover product |
| Abstract | Pre-processing: Deep-learning (DL) based clouds detection: Land Occlusion Score (LOS) product LOS weighted compositing and timeseries interpolation LSF-ANNUAL-S2 and LSF-ANNUAL-S1 extraction Ancillary data preparation: AgERA5 climatic regions embeddings processing Modelling: The backbone to produce the LCM-10 layers is EvoNet, a novel algorithm that integrates the strengths of convolutional neural networks (CNNs) and pixel-based classifiers into a unified framework. EvoNet avoids the inefficiencies of conventional approaches that either rely on multiple regional models, requiring complex post-processing, or exclusively use CNNs or pixel classifiers, each of which has limitations. CNNs excel in generalization but struggle with fine spatial details, while pixel classifiers offer high spatial resolution but are prone to noise and overfitting. The core innovation of EvoNet lies in unifying these strengths with its dual architecture: a CNN-based spatial feature extractor and a multi-layer perceptron (MLP) pixel classifier. Post-processing: expert rules polishing and tiling of the final product. |
| Input Description | None |
| Output Description | None |
| Software Reference | None |
| Output Description | None |
| Output Description | None |
| Output Description | None |
| Output Description | None |
No variables found.
Temporal Range
2020-01-01T00:00:00
2020-12-31T23:59:59
Geographic Extent
90.0000° |
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-180.0000° |
180.0000° |
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-90.0000° |