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Eyes in the Sky, Boots on the Ground: Assessing Satellite‐ and Ground‐Based Approaches to Crop Yield Measurement and Analysis

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  • David B Lobell
  • George Azzari
  • Marshall Burke
  • Sydney Gourlay
  • Zhenong Jin
  • Talip Kilic
  • Siobhan Murray

Abstract

Understanding the determinants of agricultural productivity requires accurate measurement of crop output and yield. In smallholder production systems across low‐ and middle‐income countries, crop yields have traditionally been assessed based on farmer‐reported production and land areas in household/farm surveys, occasionally by objective crop cuts for a sub‐section of a farmer's plot, and rarely using full‐plot harvests. In parallel, satellite data continue to improve in terms of spatial, temporal, and spectral resolution needed to discern performance on smallholder plots. This study evaluates ground‐ and satellite‐based approaches to estimating crop yields and yield responsiveness to inputs, using data on maize from Eastern Uganda. Using unique, simultaneous ground data on yields based on farmer reporting, sub‐plot crop cutting, and full‐plot harvests across hundreds of smallholder plots, we document large discrepancies among the ground‐based measures, particularly among yields based on farmer‐reporting versus sub‐plot or full‐plot crop cutting. Compared to yield measures based on either farmer‐reporting or sub‐plot crop cutting, satellite‐based yield measures explain as much or more variation in yields based on (gold‐standard) full‐plot crop cuts. Further, estimates of the association between maize yield and various production factors (e.g., fertilizer, soil quality) are similar across crop cut‐ and satellite‐based yield measures, with the use of the latter at times leading to more significant results due to larger sample sizes. Overall, the results suggest a substantial role for satellite‐based yield estimation in measuring and understanding agricultural productivity in the developing world.

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  • David B Lobell & George Azzari & Marshall Burke & Sydney Gourlay & Zhenong Jin & Talip Kilic & Siobhan Murray, 2020. "Eyes in the Sky, Boots on the Ground: Assessing Satellite‐ and Ground‐Based Approaches to Crop Yield Measurement and Analysis," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(1), pages 202-219, January.
  • Handle: RePEc:wly:ajagec:v:102:y:2020:i:1:p:202-219
    DOI: 10.1093/ajae/aaz051
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    Cited by:

    1. Newhouse David, 2020. "Discussion of “Small area estimation: its evolution in five decades”, by Malay Ghosh," Statistics in Transition New Series, Polish Statistical Association, vol. 21(4), pages 45-50, August.
    2. Chaoran Chen & Diego Restuccia & Raül Santaeulàlia-Llopis, 2023. "Land Misallocation and Productivity," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(2), pages 441-465, April.
    3. Jules Gazeaud & Victor Stephane, 2023. "Productive Workfare? Evidence from Ethiopia's Productive Safety Net Program," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(1), pages 265-290, January.
    4. Jeffrey D. Michler & Anna Josephson & Talip Kilic & Siobhan Murray, 2020. "Estimating the Impact of Weather on Agriculture," Papers 2012.11768, arXiv.org, revised Oct 2021.
    5. Kosmowski, Frederic & Chamberlin, Jordan & Ayalew, Hailemariam & Sida, Tesfaye & Abay, Kibrom & Craufurd, Peter, 2021. "How accurate are yield estimates from crop cuts? Evidence from smallholder maize farms in Ethiopia," Food Policy, Elsevier, vol. 102(C).
    6. Merfeld, Joshua D. & Newhouse, David & Weber, Michael & Lahiri, Partha, 2022. "Combining Survey and Geospatial Data Can Significantly Improve Gender-Disaggregated Estimates of Labor Market Outcomes," IZA Discussion Papers 15390, Institute of Labor Economics (IZA).
    7. Maryia Bakhtsiyarava & Tim G. Williams & Andrew Verdin & Seth D. Guikema, 2021. "A nonparametric analysis of household-level food insecurity and its determinant factors: exploratory study in Ethiopia and Nigeria," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(1), pages 55-70, February.
    8. Thomas Daum & Filippo Capezzone & Regina Birner, 2021. "Using smartphone app collected data to explore the link between mechanization and intra-household allocation of time in Zambia," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 38(2), pages 411-429, June.
    9. He, Xi, 2023. "Dams, cropland productivity, and economic development in China," China Economic Review, Elsevier, vol. 81(C).
    10. Hailemariam Ayalew & Jordan Chamberlin & Carol Newman & Kibrom A. Abay & Frederic Kosmowski & Tesfaye Sida, 2024. "Revisiting the size–productivity relationship with imperfect measures of production and plot size," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(2), pages 595-619, March.
    11. Helfand, Steven M. & Taylor, Matthew P.H., 2021. "The inverse relationship between farm size and productivity: Refocusing the debate," Food Policy, Elsevier, vol. 99(C).
    12. Sydney Gourlay & Talip Kilic, 2023. "Is dirt cheap? The economic costs of failing to meet soil health requirements on smallholder farms," Agricultural Economics, International Association of Agricultural Economists, vol. 54(6), pages 793-818, November.
    13. Deininger, Klaus & Ali, Daniel Ayalew & Kussul, Nataliia & Shelestov, Andrii & Lemoine, Guido & Yailimova, Hanna, 2023. "Quantifying war-induced crop losses in Ukraine in near real time to strengthen local and global food security," Food Policy, Elsevier, vol. 115(C).
    14. Christopher B. Barrett, 2021. "Overcoming Global Food Security Challenges through Science and Solidarity," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(2), pages 422-447, March.
    15. Matthieu Stigler & Apratim Dey & Andrew Hobbs & David Lobell, 2022. "With big data come big problems: pitfalls in measuring basis risk for crop index insurance," Papers 2209.14611, arXiv.org.

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