Subfield-level crop yield mapping without ground truth data: A scale transfer framework
Most Cited Paper
in Rice Cultivation and Yield Improvement
18 Months Post-Publication
Class of 2026
“Subfield-level crop yield mapping without ground truth data: A scale transfer framework”
A research intelligence initiative by Pepkio
pri.pepkio.com
Topics
subfield-level crop yield mapping · scale transfer framework · ground truth data · remote sensing · spatial resolution · Crop yield prediction · transfer learning · satellite imagery · precision agriculture · spatial disaggregation · Crop yield prediction · cross-scale inference · agricultural monitoring · field-scale mapping · within-field variability
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Pepkio Research Index (PRI). Topics and Trends in Most Cited Rice Cultivation and Yield Improvement Papers, Class of 2026. https://pri.pepkio.com/top-papers/rice-cultivation-and-yield-improvement/2026. Accessed 2026-07-24. Methodology Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459