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

Steffen FritzLinda SeeChristoph PergerIan McCallumChristian SchillDmitry G SchepaschenkoMartina DuerauerMathias KarnerChristopher DreselJuan-Carlos Laso-BayasMyroslava LesivInian MoorthyCarl F SalkOlha DanyloTobias SturnFranziska AlbrechtLiangzhi YouFlorian KraxnerMichael Obersteiner
Published in: Scientific data (2017)
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.
Keyphrases
  • climate change
  • high resolution
  • big data
  • water quality
  • healthcare
  • endothelial cells
  • machine learning
  • high throughput
  • mass spectrometry
  • artificial intelligence
  • high speed
  • induced pluripotent stem cells