A Global Dataset of Crowdsourced Land Cover and Land Use Reference Data

A Global Dataset of Crowdsourced Land Cover and Land Use Reference Data. Fritz, S., See, L., Perger, C., McCallum, I., Schill, C., Schepaschenko, D., Duerauer, M., Karner, M., Dresel, C., Laso-Bayas, J., Lesiv, M., Moorthy, I., Salk, C. F., Danylo, O., Sturn, T., Albrecht, F., You, L., Kraxner, F., & Obersteiner, M. Scientific Data, 4:170075+, June, 2017.
doi abstract bibtex

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.

@article{fritzGlobalDatasetCrowdsourced2017,
  title = {A Global Dataset of Crowdsourced Land Cover and Land Use Reference Data},
  author = {Fritz, Steffen and See, Linda and Perger, Christoph and McCallum, Ian and Schill, Christian and Schepaschenko, Dmitry and Duerauer, Martina and Karner, Mathias and Dresel, Christopher and {Laso-Bayas}, Juan-Carlos and Lesiv, Myroslava and Moorthy, Inian and Salk, Carl F. and Danylo, Olha and Sturn, Tobias and Albrecht, Franziska and You, Liangzhi and Kraxner, Florian and Obersteiner, Michael},
  year = {2017},
  month = jun,
  volume = {4},
  pages = {170075+},
  issn = {2052-4463},
  doi = {10.1038/sdata.2017.75},
  abstract = {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.},
  journal = {Scientific Data},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14639723,crowd-sourcing,field-measurements,global-scale,land-cover,land-use,open-data,visual-assessment,visual-interpretation},
  lccn = {INRMM-MiD:c-14639723}
}

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