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

Shovkat Khodjaev, Ihtiyor Bobojonov, Lena Kuhn and Thomas Glauben

EconStor Open Access Articles and Book Chapters, 2026, vol. 28, issue 3, 6799-6830

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.

Keywords: yield estimation; sentinel; cotton; vegetation indices; panel data regression; crop phenology (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/338231/1/K ... yield_estimation.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zbw:espost:338231

DOI: 10.1007/s10668-024-05220-1

Access Statistics for this article

More articles in EconStor Open Access Articles and Book Chapters from ZBW - Leibniz Information Centre for Economics Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().