Estimating the Global Distribution of Field Size using Crowdsourcing

  • Myroslava Lesiv (Contributor)
  • Juan Carlos Laso Bayas (Contributor)
  • Linda See (Contributor)
  • Martina Duerauer (Contributor)
  • Dahlia Domian (Contributor)
  • Neal Durando (Contributor)
  • Rubul Hazarika (Contributor)
  • Parag Kumar Sahariah (Contributor)
  • Mar'yana Vakolyuk (Contributor)
  • Volodymyr Blyshchyk (Contributor)
  • A.M. Bilous (Contributor)
  • Ana Perez‐Hoyos (Contributor)
  • Sarah Gengler (Contributor)
  • Reinhard Prestele (Contributor)
  • S.Y. Bilous (Contributor)
  • Kuleswar Singha (Contributor)
  • Sochin Boro Choudhury (Contributor)
  • Tilok Chetri (Contributor)
  • Žiga Malek (Contributor)
  • Khangsembou Bungnamei (Contributor)
  • Anup Saikia (Contributor)
  • Dhrubajyoti Sahariah (Contributor)
  • William Narzary (Contributor)
  • Olha Danylo (Contributor)
  • Tobias Sturn (Contributor)
  • Mathias Karner (Contributor)
  • Ian Mccallum (Contributor)
  • Dmitry Schepaschenko (Contributor)
  • Elena Moltchanova (Contributor)
  • Dilek Fraisl (Contributor)
  • Inian Moorthy (Contributor)
  • Steffen Fritz (Contributor)

Dataset / Software

Description

There is increasing evidence that smallholder farms contribute substantially to food production globally yet spatially explicit data on agricultural field sizes are currently lacking. Automated field size delineation using remote sensing or the estimation of average farm size at subnational level using census data are two approaches that have been used but both have limitations, e.g. limited geographical coverage by remote sensing or coarse spatial resolution when using census data. This paper demonstrates another approach to quantifying and mapping field size globally using crowdsourcing. A campaign was run in June 2017 where participants were asked to visually interpret very high resolution satellite imagery from Google Maps and Bing using the Geo-Wiki application. During the campaign, participants collected field size data for 130K unique locations around the globe. Using this sample, we have produced an improved global field size map (over the previous version) and estimated the percentage of different field sizes, ranging from very small to very large, in agricultural areas at global, continental and national levels. The results show that smallholder farms occupy no more than 40% of agricultural areas, which means that, potentially, there are much more smallholder farms in comparison with the current global estimate of 12%. The global field size map and the crowdsourced data set are openly available and can be used for integrated assessment modelling, comparative studies of agricultural dynamics across different contexts and contribute to SDG 2, among many others. The dataset (global field sizes.zip) contains: - map of dominant field sizes (dominant_field_size_categories.tif) and description of legend items (legend_items.txt) - table with all submissions by the participant (those who completed more than 10 classifications) and table description - table with quality score of all the participants and table description - table with estimated dominant field sizes at each location and table description
Date made available2018
PublisherZenodo

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