Copernicus Global Land Cover Layers - Collection 2
By Marcel Buchhorn, Myroslava Lesiv, N. Tsendbazar, Martin Herold, L. Bertels, B. Smets. Remote Sensing, 2020
684 citations recorded by the source corpus.
In May 2019, Collection 2 of the Copernicus Global Land Cover layers was released. Next to a global discrete land cover map at 100 m resolution, a set of cover fraction layers is provided depicting the percentual cover of the main land cover types in a pixel. This additional continuous classification scheme represents areas of heterogeneous land cover better than the standard discrete classification scheme. Overall, 20 layers are provided which allow customization of land cover maps to specific user needs or applications (e.g., forest monitoring, crop monitoring, biodiversity and conservation, climate modeling, etc.). However, Collection 2 was not just a global up-scaling, but also includes major improvements in the map quality, reaching around 80% or more overall accuracy. The processing system went into operational status allowing annual updates on a global scale with an additional implemented training and validation data collection system. In this paper, we provide an overview of the major changes in the production of the land cover maps, that have led to this increased accuracy, including aligning with the Sentinel 2 satellite system in the grid and coordinate system, improving the metric extraction, adding better auxiliary data, improving the biome delineations, as well as enhancing the expert rules. An independent validation exercise confirmed the improved classification results. In addition to the methodological improvements, this paper also provides an overview of where the different resources can be found, including access channels to the product layer as well as the detailed peer-review product documentation.
Subfields: Ecology, Environmental Engineering, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/f4ba68a50922a52e7bcb85a424fa77330f6f491f
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Citations in the corpus
- Global land use / land cover with Sentinel 2 and deep learning (2021, background): “500m MODIS Land Cover Type product [2], 300m European Space Agency Climate Change Initiative (CCI) Land Cover product [3], 100m Copernicus Global Land Cover [4], or 30m USGS National Land Cover Database [5] and the Land Change Monitoring, Assessment, and Projection (LCMAP) [6].”
- Global 10 m Land Use Land Cover Datasets: A Comparison of Dynamic World, World Cover and Esri Land Cover (2022, background): “Even though this is a much simpler typology than other regional LULC datasets (e.g., CORINE land cover [31]), there remain significant challenges in distinguishing spectrally similar classes, such as bare ground, grass, shrub and scrub, a finding often echoed in the literature [16,32,33].”