| Literature DB >> 30549201 |
Myroslava Lesiv1, Juan Carlos Laso Bayas1, Linda See1, Martina Duerauer1, Domian Dahlia1, Neal Durando2, Rubul Hazarika3, Parag Kumar Sahariah3, Mar'yana Vakolyuk4, Volodymyr Blyshchyk5, Andrii Bilous4, Ana Perez-Hoyos6, Sarah Gengler7, Reinhard Prestele8, Svitlana Bilous5, Ibrar Ul Hassan Akhtar9,10, Kuleswar Singha11, Sochin Boro Choudhury11, Tilok Chetri12, Žiga Malek13, Khangsembou Bungnamei11, Anup Saikia11, Dhrubajyoti Sahariah11, William Narzary12, Olha Danylo1, Tobias Sturn1, Mathias Karner1, Ian McCallum1, Dmitry Schepaschenko1,14, Elena Moltchanova15, Dilek Fraisl1, Inian Moorthy1, Steffen Fritz1.
Abstract
There is an 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. However, both have limitations, for example, automatic field size delineation using remote sensing has not yet been implemented at a global scale while the spatial resolution is very coarse when using census data. This paper demonstrates a unique approach to quantifying and mapping agricultural 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 130 K unique locations around the globe. Using this sample, we have produced the most accurate global field size map to date 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 up to 40% of agricultural areas globally, which means that, potentially, there are many more smallholder farms in comparison with the two different current global estimates of 12% and 24%. The global field size map and the crowdsourced data set are openly available and can be used for integrated assessment modeling, comparative studies of agricultural dynamics across different contexts, for training and validation of remote sensing field size delineation, and potential contributions to the Sustainable Development Goal of Ending hunger, achieve food security and improved nutrition and promote sustainable agriculture.Entities:
Keywords: crowdsourcing; environmental changes; field size; food security; visual interpretation
Mesh:
Year: 2018 PMID: 30549201 DOI: 10.1111/gcb.14492
Source DB: PubMed Journal: Glob Chang Biol ISSN: 1354-1013 Impact factor: 10.863