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An accuracy assessment of satellite-based cotton yield estimation using panel data regression: A case study of Uzbekistan

Author

Listed:
  • Khodjaev, Shovkat
  • Bobojonov, Ihtiyor
  • Kuhn, Lena
  • Glauben, Thomas

Abstract

Satellite-based yield estimation is crucial for spotting potential deficits in crop yields at an early stage, supports farm-level decision-making and early-warning systems, and is a prerequisite for index insurance markets. Precise satellite-based yield estimations are already established for important food crops like maize and wheat. However, for many cash crops like cotton, the accuracy of satellite-based yield estimation has not been scientifically tested, mainly due to their low biomass-yield correlation. This paper contributes to exploring the suitability of multiple vegetation indices based on Sentinel-2 imagery to estimate farm-level yields for one of these cash crops, cotton. We estimated various vegetation indices conjugated with the cotton crop phenology for the selected study area and compared them with farm-level panel data (n = 232) for the years 2016–2018 obtained from a statistical agency in Uzbekistan. Overall, we tested the suitability of the Normalized Difference Vegetation Index, the Modified Soil Adjusted Vegetation Index 2, the Red-Edge Chlorophyll Index and the Normalized Difference Red-Edge Index (NDRE). Among these indices, the NDRE index shows the highest fit with the actual cotton yield data (R² up to 0.96, adj R² = 0.95 and RMSE = 0.21). These results indicate that the NDRE index is a powerful indicator for determining cotton yields. Based on this approach, farmers can monitor crop growth, which in turn avoids crop loss and thereby increases productivity. This research highlights that a satellite-based estimate of crop production can provide a unique perspective which should improve the possibility of identifying management priorities to improve agriculture productivity and mitigate climate impacts.

Suggested Citation

  • Khodjaev, Shovkat & Bobojonov, Ihtiyor & Kuhn, Lena & Glauben, Thomas, 2026. "An accuracy assessment of satellite-based cotton yield estimation using panel data regression: A case study of Uzbekistan," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 28(3), pages 6799-6830.
  • Handle: RePEc:zbw:espost:338231
    DOI: 10.1007/s10668-024-05220-1
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    1. Bikash Ranjan Parida & Amit Kushwaha & Avinash Kumar Ranjan, 2022. "Synergy of Sentinel-2A and Near-proximal sensor data for deriving biochemical parameters of paddy at different growth stages," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(1), pages 1048-1068, January.
    2. David J Mitchell & Antoine M Dujon & Christa Beckmann & Peter A Biro & Niels Dingemanse, 2020. "Temporal autocorrelation: a neglected factor in the study of behavioral repeatability and plasticity," Behavioral Ecology, International Society for Behavioral Ecology, vol. 31(1), pages 222-231.
    3. William R. Sutton & Jitendra P. Srivastava & James E. Neumann & Kenneth M. Strz?pek & Peter Droogers, 2013. "Reducing the Vulnerability of Albania's Agricultural Systems to Climate Change : Impact Assessment and Adaptation Options," World Bank Publications - Books, The World Bank Group, number 16198, April.
    4. William R. Sutton & Jitendra P. Srivastava & James E. Neumann & Kenneth M. Strz?pek & Brent B. Boehlert, 2013. "Reducing the Vulnerability of the Former Yugoslav Republic of Macedonia's Agricultural Systems to Climate Change : Impact Assessment and Adaptation Options," World Bank Publications - Books, The World Bank Group, number 16201, April.
    5. William R. Sutton & Jitendra P. Srivastava & James E. Neumann & Ana Iglesias & Brent B. Boehlert, 2013. "Reducing the Vulnerability of Moldova's Agricultural Systems to Climate Change : Impact Assessment and Adaptation Options," World Bank Publications - Books, The World Bank Group, number 16199, April.
    6. Beck, Nathaniel & Katz, Jonathan N., 1995. "What To Do (and Not to Do) with Time-Series Cross-Section Data," American Political Science Review, Cambridge University Press, vol. 89(3), pages 634-647, September.
    7. Ahmed Mushfiq Mobarak & Mark R. Rosenzweig, 2013. "Informal Risk Sharing, Index Insurance, and Risk Taking in Developing Countries," American Economic Review, American Economic Association, vol. 103(3), pages 375-380, May.
    8. Michael Carter & Alain de Janvry & Elisabeth Sadoulet & Alexandros Sarris, 2017. "Index Insurance for Developing Country Agriculture: A Reassessment," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 421-438, October.
    9. Chakir, Raja & Le Gallo, Julie, 2013. "Predicting land use allocation in France: A spatial panel data analysis," Ecological Economics, Elsevier, vol. 92(C), pages 114-125.
    10. Dean Karlan & Robert Osei & Isaac Osei-Akoto & Christopher Udry, 2014. "Agricultural Decisions after Relaxing Credit and Risk Constraints," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(2), pages 597-652.
    11. Krol, Robert, 1996. "International capital mobility: evidence from panel data," Journal of International Money and Finance, Elsevier, vol. 15(3), pages 467-474, June.
    12. Ajay, Kumar Singh & Kumar, Sanjeev & Ashraf, Shah Nawaz & Jyoti, Bhim, . "Implications of Farmer’s Adaptation Strategies to Climate Change in Agricultural Sector of Gujarat: Experience from Farm Level Data," Research on World Agricultural Economy, Nan Yang Academy of Sciences Pte Ltd (NASS), vol. 3(01).
    13. Thomas, Ashok & Spataro, Luca & Mathew, Nanditha, 2014. "Pension funds and stock market volatility: An empirical analysis of OECD countries," Journal of Financial Stability, Elsevier, vol. 11(C), pages 92-103.
    14. Mario J. Miranda & Katie Farrin, 2012. "Index Insurance for Developing Countries," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 34(3), pages 391-427.
    15. William R. Sutton & Jitendra P. Srivastava & James E. Neumann & Peter Droogers & Brent B. Boehlert, 2013. "Reducing the Vulnerability of Uzbekistan's Agricultural Systems to Climate Change : Impact Assessment and Adaptation Options," World Bank Publications - Books, The World Bank Group, number 16200, April.
    16. Christopher Bennett & Rodney A. Stewart & Junwei Lu, 2014. "Autoregressive with Exogenous Variables and Neural Network Short-Term Load Forecast Models for Residential Low Voltage Distribution Networks," Energies, MDPI, vol. 7(5), pages 1-23, April.
    17. Kentaro Kawasaki & Shinsuke Uchida, 2016. "Quality Matters More Than Quantity: Asymmetric Temperature Effects on Crop Yield and Quality Grade," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(4), pages 1195-1209.
    18. Sohail Abbas & Shazia Kousar, 2021. "Spatial analysis of drought severity and magnitude using the standardized precipitation index and streamflow drought index over the Upper Indus Basin, Pakistan," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(10), pages 15314-15340, October.
    19. Babakholov Sherzod & Kyung-Ryang Kim & Sang Hyeon Lee, 2018. "Agricultural Transition and Technical Efficiency: An Empirical Analysis of Wheat-Cultivating Farms in Samarkand Region, Uzbekistan," Sustainability, MDPI, vol. 10(9), pages 1-11, September.
    20. 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.
    21. Michael Carter & Alain de Janvry & Elisabeth Sadoulet & Alexandros Sarris, 2017. "Index Insurance for Developing Country Agriculture: A Reassessment," Annual Review of Resource Economics, Annual Reviews, vol. 9(1), pages 421-438, October.
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