Supra-National Thematic Land Use Cover Datasets

Author:

García-Álvarez David,Jurado Pérez Francisco José,Lara Hinojosa Javier

Abstract

AbstractSupra-national thematic Land Use Cover (LUC) datasets are not very common. While there are several general datasets mapping all the land uses or covers in different supra-national areas across the world, LUC datasets with a similar extent that focus on the mapping of specific land covers in greater thematic detail are scarce. In this chapter, we review six different supra-national thematic LUC datasets. Three others were also found in the literature, but are not fully available for download, namely the TREES Vegetation Map of Tropical South America, the Central Africa—Vegetation map and FACET. The Circumpolar Arctic Region Vegetation dataset was also excluded from this review because of its specificity and coarse scale (1:7,500,000). Europe is the continent with the most relevant, most updated and most detailed LUC thematic datasets at supra-national scales. This is due to the work being done by the European Commission through its Joint Research Centre (JRC) and the Copernicus Land Monitoring Programme. The High-Resolution Layers (HRL) provide very detailed information, both thematically and spatially (from 10 m), for five different themes: imperviousness, tree cover, grasslands, water and wet covers, and small woody features. The European Settlement Map also provides information on built-up areas at very detailed scales (from 2.5 m). HRL and ESM are recently launched datasets which, therefore, do not provide a long series of historical data. In addition, ESM is an experimental dataset produced within the framework of a research project funded by the European Commission and no updates are expected. The datasets reviewed in this chapter for other parts of the world focus on vegetation covers of tropical forests and other relevant areas in terms of biodiversity and environmental studies. These datasets were produced within projects funded by the European Commission and the United States Agency for International Development. Unlike the previous datasets for Europe, they are already outdated and are usually produced at coarser spatial resolutions: Insular Southeast Asia—Forest Cover Map (1 km, 1998/00); Continental Southeast Asia—Forest Cover Map (1 km, 1998/02). For its part, the Congo Basin Monitoring dataset, although outdated, provides information at a higher resolution (57 m) for two different dates: 1990, 2000. The Joint Research Centre of the European Commission also produced an African cropland mask as a source of information for policy-makers. Of all the datasets reviewed in this chapter, it is the only one to focus on agricultural covers. It was obtained from data fusion at 250 m. Consequently, it does not show the cropland areas of Africa for a specific date across the whole continent.

Funder

Universidad de Granada

Publisher

Springer International Publishing

Reference39 articles.

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2. Copernicus Land Monitoring Service (2020a) Copernicus land monitoring service high resolution land cover characteristics. Lot1: imperviousness 2018, imperviousness change 2015–2018 and built-up 2018. https://land.copernicus.eu/user-corner/technical-library/hrl-imperviousness-2018-user-manual. Accessed 30 Sept 2020

3. Copernicus Land Monitoring Service (2020b) Copernicus land monitoring service high resolution land cover characteristics. Tree-cover/forest and change 2015–2018. https://land.copernicus.eu/user-corner/technical-library/forest-2018-user-manual-v1-0.pdf. Accessed 30 Sept 2020

4. Copernicus Land Monitoring Service (2020c) Copernicus land monitoring service high resolution land cover characteristics. Grassland 2018 and grassland change 2015–2018. https://land.copernicus.eu/user-corner/technical-library/hrl-grassland-2018-user-manual. Accessed 30 Sept 2020

5. Copernicus Land Monitoring Service (2020d) Copernicus land monitoring service high resolution land cover characteristics. Lot4: water & wetness 2018. https://land.copernicus.eu/user-corner/technical-library/hrl-water-and-wetness-2018-user-manual. Accessed 30 Sept 2020

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