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A respondent‐driven method for mapping small agricultural plots using tablets and high resolution imagery

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Agricultural statistics on small farms are critical for informing sustainable development policies, but often suffer from selection bias and are time consuming and costly to collect. Less burdensome and reliable methods are needed. We report on a scalable method using a respondent's knowledge about their land, high resolution imagery, and tablet devices to draw spatially explicit plot boundaries. We find the method may work best with respondents that own their plots are farmers, and for smaller plots (<1 hectare). We also find incongruence between survey questions and spatially-derived data, indicating the importance of incorporating spatial data to verify responses about plot characteristics.
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A RESPONDENT-DRIVEN METHOD FOR
MAPPING SMALL AGRICULTURAL PLOTS
USING TABLETS AND HIGH RESOLUTION
IMAGERY
YUTA J. MASUDA
1
*, JONATHAN R.B. FISHER
2
, WEI ZHANG
3
,
CAROLINA CASTILLA
4
, TIMOTHY M. BOUCHER
1
and GENOWEFA BLUNDO-CANTO
5
1
Global Science, The Nature ConservancyArlington, VA, USA
2
Conservation Science Program, Pew Charitable Trust, Washington, DC
3
Environment, Production and Technology Division, International Food Policy Research Institute,
Washington, DC, USA
4
Department of Economics, Colgate University, NY, USA
5
Département Environnements et sociétés, La recherche agronomique pour le développement,
Campus international de Baillarguet TA C-DIR/B 34398, Montpellier, France
Abstract: Agricultural statistics on small farms are critical for informing sustainable development
policies, but often suffer from selection bias and are time consuming and costly to collect. Less
burdensome and reliable methods are needed. We report on a scalable method using a respondents
knowledge about their land, high resolution imagery, and tablet devices to draw spatially explicit plot
boundaries. We nd the method may work best with respondents that own their plots are farmers, and
for smaller plots (<1 hectare). We also nd incongruence between survey questions and
spatially-derived data, indicating the importance of incorporating spatial data to verify responses
about plot characteristics. © 2020 John Wiley & Sons, Ltd.
Keywords: agriculture; spatial data; methodology; household surveys; smallholder
1 INTRODUCTION
With over 375 million households relying on small plots for food and livelihoods
(FAO, 2014), developing cost effective and reliable methods for collecting agricultural
statistics is critical for tackling sustainable development challenges. Plot boundary
*Correspondence to: Yuta J. Masuda.
E-mail: ymasuda@tnc.org
© 2020 John Wiley & Sons, Ltd.
Journal of International Development
J. Int. Dev. 32, 727748 (2020)
Published online 13 April 2020 in Wiley Online Library
(wileyonlinelibrary.com) DOI: 10.1002/jid.3475
... Our approach to estimating the effect of gender composition on decision-making relies on the random assignment of participants to single or mixed gender groups. The group games were part of a larger study examining individual and household decisionmaking and behaviors around agricultural management practices (for details see Masuda et al., 2020). The study area, the Upper Tana basin in Kenya, is approximately 80 km northwest of Nairobi, Kenya, and consists of households primarily engaged in smallholder agriculture. ...
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