A global dataset of crowdsourced land cover and land use reference data

Global land cover is an essential climate variable and a key biophysical driver for earth system models. While remote sensing technology, particularly satellites, have played a key role in providing land cover datasets, large discrepancies have been noted among the available products. Global land us...

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Autores principales: Fritz, Steffen, See, Linda, Perger, Christoph, McCallum, Ian, Schill, Christian, Schepaschenko, Dmitry, Duerauer, Martina, Karner, Mathias, Dresel, Christopher, Laso-Bayas, Juan-Carlos, Lesiv, Myroslava, Moorthy, Inian, Salk, Carl F., Danylo, Ohla, Sturn, Tobias, Albrecht, Franziska, You, Liangzhi, Kraxner, Florian, Obersteiner, Michael
Formato: Journal Article
Lenguaje:Inglés
Publicado: Springer 2017
Materias:
Acceso en línea:https://hdl.handle.net/10568/146184
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author Fritz, Steffen
See, Linda
Perger, Christoph
McCallum, Ian
Schill, Christian
Schepaschenko, Dmitry
Duerauer, Martina
Karner, Mathias
Dresel, Christopher
Laso-Bayas, Juan-Carlos
Lesiv, Myroslava
Moorthy, Inian
Salk, Carl F.
Danylo, Ohla
Sturn, Tobias
Albrecht, Franziska
You, Liangzhi
Kraxner, Florian
Obersteiner, Michael
author_browse Albrecht, Franziska
Danylo, Ohla
Dresel, Christopher
Duerauer, Martina
Fritz, Steffen
Karner, Mathias
Kraxner, Florian
Laso-Bayas, Juan-Carlos
Lesiv, Myroslava
McCallum, Ian
Moorthy, Inian
Obersteiner, Michael
Perger, Christoph
Salk, Carl F.
Schepaschenko, Dmitry
Schill, Christian
See, Linda
Sturn, Tobias
You, Liangzhi
author_facet Fritz, Steffen
See, Linda
Perger, Christoph
McCallum, Ian
Schill, Christian
Schepaschenko, Dmitry
Duerauer, Martina
Karner, Mathias
Dresel, Christopher
Laso-Bayas, Juan-Carlos
Lesiv, Myroslava
Moorthy, Inian
Salk, Carl F.
Danylo, Ohla
Sturn, Tobias
Albrecht, Franziska
You, Liangzhi
Kraxner, Florian
Obersteiner, Michael
author_sort Fritz, Steffen
collection Repository of Agricultural Research Outputs (CGSpace)
description Global land cover is an essential climate variable and a key biophysical driver for earth system models. While remote sensing technology, particularly satellites, have played a key role in providing land cover datasets, large discrepancies have been noted among the available products. Global land use is typically more difficult to map and in many cases cannot be remotely sensed. In-situ or ground-based data and high resolution imagery are thus an important requirement for producing accurate land cover and land use datasets and this is precisely what is lacking. Here we describe the global land cover and land use reference data derived from the Geo-Wiki crowdsourcing platform via four campaigns. These global datasets provide information on human impact, land cover disagreement, wilderness and land cover and land use. Hence, they are relevant for the scientific community that requires reference data for global satellite-derived products, as well as those interested in monitoring global terrestrial ecosystems in general.
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publishDate 2017
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spelling CGSpace1461842025-12-08T10:29:22Z A global dataset of crowdsourced land cover and land use reference data Fritz, Steffen See, Linda Perger, Christoph McCallum, Ian Schill, Christian Schepaschenko, Dmitry Duerauer, Martina Karner, Mathias Dresel, Christopher Laso-Bayas, Juan-Carlos Lesiv, Myroslava Moorthy, Inian Salk, Carl F. Danylo, Ohla Sturn, Tobias Albrecht, Franziska You, Liangzhi Kraxner, Florian Obersteiner, Michael environmental impact land use geography land cover Global land cover is an essential climate variable and a key biophysical driver for earth system models. While remote sensing technology, particularly satellites, have played a key role in providing land cover datasets, large discrepancies have been noted among the available products. Global land use is typically more difficult to map and in many cases cannot be remotely sensed. In-situ or ground-based data and high resolution imagery are thus an important requirement for producing accurate land cover and land use datasets and this is precisely what is lacking. Here we describe the global land cover and land use reference data derived from the Geo-Wiki crowdsourcing platform via four campaigns. These global datasets provide information on human impact, land cover disagreement, wilderness and land cover and land use. Hence, they are relevant for the scientific community that requires reference data for global satellite-derived products, as well as those interested in monitoring global terrestrial ecosystems in general. 2017 2024-06-21T09:06:07Z 2024-06-21T09:06:07Z Journal Article https://hdl.handle.net/10568/146184 en Open Access Springer Fritz, Steffen; See, Linda; Perger, Christoph; McCallum, Ian; Schill, Christian; Schepaschenko, Dmitry; Duerauer, Martina; Karner, Mathias; Dresel, Christopher; Laso-Bayas, Juan-Carlos; Lesiv, Myroslava; Moorthy, Inian; Salk, Carl F.; Danylo, Ohla; Sturn, Tobais; Albrecht, Franziska; You, Liangzhi; Kraxner, Florian; and Obersteiner, Michael. A global dataset of crowdsourced land cover and land use reference data. Scientific Data 4 (170075): https://doi.org/10.1038/sdata.2017.75
spellingShingle environmental impact
land use
geography
land cover
Fritz, Steffen
See, Linda
Perger, Christoph
McCallum, Ian
Schill, Christian
Schepaschenko, Dmitry
Duerauer, Martina
Karner, Mathias
Dresel, Christopher
Laso-Bayas, Juan-Carlos
Lesiv, Myroslava
Moorthy, Inian
Salk, Carl F.
Danylo, Ohla
Sturn, Tobias
Albrecht, Franziska
You, Liangzhi
Kraxner, Florian
Obersteiner, Michael
A global dataset of crowdsourced land cover and land use reference data
title A global dataset of crowdsourced land cover and land use reference data
title_full A global dataset of crowdsourced land cover and land use reference data
title_fullStr A global dataset of crowdsourced land cover and land use reference data
title_full_unstemmed A global dataset of crowdsourced land cover and land use reference data
title_short A global dataset of crowdsourced land cover and land use reference data
title_sort global dataset of crowdsourced land cover and land use reference data
topic environmental impact
land use
geography
land cover
url https://hdl.handle.net/10568/146184
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