Estimating the global distribution of field size using crowdsourcing

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.

Keywords: crowdsourcing; environmental changes; field size; food security; visual interpretation.

Figure 1

Schematic showing the main steps in the methodology [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 2

Screenshot of the Geo‐Wiki interface showing: (a) the area measuring tool; (b) the actual field sizes delineated and measured using (a); (c) the cumulative work done by a participant; (d) the main classification area, gridded; (e) the button to switch between different background imagery, that is, Google or Bing; (f) buttons to select the field size categories: very large, large, medium, small, very small, or no fields; (g) possible reasons to skip the current location; (h) a button to display location in Google Earth; (k) examples of field size estimation for training; (l) a button to ask experts for help. Source of imagery: Google Maps [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 3

An example taken from the field map of the USA (Yan & Roy, 2016). Left image: blue indicates very large fields, green are large fields, and turquoise are medium‐sized fields. Right image: screenshot of a satellite image from Google Maps from 2010, where the blue lines correspond to tiny field boundaries that are not taken into account on the field map of Yan and Roy (2016). The location of the central point is 95.771°W, 42.975°N [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 4

The spatial distribution of dominant field size [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 5

The degree of agreement between the participants at all sample sites [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 6

Area percentages of different field sizes by continent and at the global level (confidence interval 95%). Oceania includes New Zealand, Melanesia, Micronesia, and Polynesia [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 7

Percentage of area by field size for selected countries (confidence interval 95%). ARG: Argentina; De: Germany; IND, Indonesia; KZ: Kazakhstan; N Zealand: New Zealand; Ro: Romania; S Africa: South Africa; UK: United Kingdom [Colour figure can be viewed at wileyonlinelibrary.com]