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Eyes in the sky, boots on the ground : assessing satellite- and ground-based approaches to crop yield measurement and analysis in Uganda

Author

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

Abstract

Crop yields in smallholder systems are traditionally assessed using farmer-reported information in surveys, occasionally by crop cuts for a sub-section of a farmer's plot, and rarely using full-plot harvests. Accuracy and cost vary dramatically across methods. In parallel, satellite data is improving in terms of spatial, temporal, and spectral resolution needed to discern performance on smallholder plots. This study uses data from a survey experiment in Uganda, and evaluates the accuracy of Sentinel-2 imagery-based, remotely-sensed plot-level maize yields with respect to ground-based measures relying on farmer self-reporting, sub-plot crop cutting (CC), and full-plot crop cutting (FP). Remotely-sensed yields include two versions calibrated to FP and CC yields (calibrated), and an alternative based on crop model simulations, using no ground data (uncalibrated). On the ground, self-reported yields explained less than 1 percent of FP (and CC) yield variability, and while the average difference between CC and FP yields was not significant, CC yields captured one-quarter of FP yield variability. With satellite data, both calibrated and uncalibrated yields captured FP yield variability on pure stand plots similarly well, and both captured half of FP yield variability on pure stand plots above 0.10 hectare. The uncalibrated yields were consistently 1 ton per hectare higher than FP or CC yields, and the satellite-based yields were less well correlated with the ground-based measures on intercropped plots compared with pure stand ones. Importantly, regressions using CC, FP and remotely-sensed yields as dependent variables all produced very similar coefficients for yield response to production factors.

Suggested Citation

  • Lobell,David B. & Azzari,George & Marshall,Burke & Gourlay,Sydney & Jin,Zhenong & Kilic,Talip & Murray,Siobhan, 2018. "Eyes in the sky, boots on the ground : assessing satellite- and ground-based approaches to crop yield measurement and analysis in Uganda," Policy Research Working Paper Series 8374, The World Bank.
  • Handle: RePEc:wbk:wbrwps:8374
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    Citations

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    Cited by:

    1. Rigo, Roberta & Santos, Paulo & Frontuto, Vito, 2022. "Landscape heterogeneity, basis risk and the feasibility of index insurance: An analysis of rice in upland regions of Southeast Asia," Food Policy, Elsevier, vol. 108(C).
    2. Gourlay, Sydney & Kilic, Talip & Lobell, David B., 2019. "A new spin on an old debate: Errors in farmer-reported production and their implications for inverse scale - Productivity relationship in Uganda," Journal of Development Economics, Elsevier, vol. 141(C).
    3. Elinor Benami & Michael R. Carter, 2021. "Can digital technologies reshape rural microfinance? Implications for savings, credit, & insurance," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(4), pages 1196-1220, December.
    4. Jonas Ardö, 2021. "A Sentinel-2 Dataset for Uganda," Data, MDPI, vol. 6(4), pages 1-16, March.
    5. Alistair Munro, 2020. "Using experimental manipulation of questionnaire design and a Kenyan panel to test for the reliability of reported perceptions of climate change and adaptation," Climatic Change, Springer, vol. 162(3), pages 1081-1105, October.
    6. Anthony Harris & Anthony D'Agostino & Sara Litke-Farzaneh & Beryl Seiler & Matt Sloan, "undated". "Morocco Land Productivity Project: Evaluation Design Report," Mathematica Policy Research Reports f3fc788501b64608b17e1cb23, Mathematica Policy Research.
    7. Maue, Casey C. & Burke, Marshall & Emerick, Kyle, 2020. "Productivity dispersion and persistence among the world's most numerous firms," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304287, Agricultural and Applied Economics Association.

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