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

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

Research output: Contribution to journalArticlepeer-review

128 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)202-219
Number of pages18
JournalAmerican Journal of Agricultural Economics
Volume102
Issue number1
DOIs
StatePublished - Jan 1 2020

Bibliographical note

Publisher Copyright:
© The Author(s) 2019. Published by Oxford University Press on behalf of the Agricultural and Applied Economics Association. All rights reserved.

Keywords

  • Agricultural productivity
  • Uganda
  • crop cutting
  • crop yield estimation
  • maize
  • remote sensing

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