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A global reference database of crowdsourced cropland data collected using the Geo-Wiki platform.

Juan Carlos Laso BayasMyroslava LesivFrançois WaldnerAnne SchucknechtMartina DuerauerLinda SeeSteffen FritzDilek FraislInian MoorthyIan McCallumChristoph PergerOlha DanyloPierre DefournyJavier GallegoSven GilliamsIbrar Ul Hassan AkhtarSwarup Jyoti BaishyaMrinal BaruahKhangsembou BungnameiAlfredo CamposTrishna ChangkakatiAnna CiprianiKrishna DasKeemee DasInamani DasKyle Frankel DavisPurabi HazarikaBrian Alan JohnsonZiga MalekMonia Elisa MolinariKripal PangingChandra Kant PaweAna Pérez-HoyosParag Kumar SahariahDhrubajyoti SahariahAnup SaikiaMeghna SaikiaPeter SchlesingerElena SeidacaruKuleswar SinghaJohn W Wilson
Published in: Scientific data (2017)
A global reference data set on cropland was collected through a crowdsourcing campaign using the Geo-Wiki crowdsourcing tool. The campaign lasted three weeks, with over 80 participants from around the world reviewing almost 36,000 sample units, focussing on cropland identification. For quality assessment purposes, two additional data sets are provided. The first is a control set of 1,793 sample locations validated by students trained in satellite image interpretation. This data set was used to assess the quality of the crowd as the campaign progressed. The second data set contains 60 expert validations for additional evaluation of the quality of the contributions. All data sets are split into two parts: the first part shows all areas classified as cropland and the second part shows cropland average per location and user. After further processing, the data presented here might be suitable to validate and compare medium and high resolution cropland maps generated using remote sensing. These could also be used to train classification algorithms for developing new maps of land cover and cropland extent.
Keyphrases
  • electronic health record
  • big data
  • high resolution
  • machine learning
  • deep learning
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