# Subfield-level crop yield mapping without ground truth data: A scale transfer framework

*PRI Rank #18 · Topics and Trends in Most Cited Rice Cultivation and Yield Improvement Papers, Class of 2026*

*Canonical URL: https://pri.pepkio.com/top-papers/rice-cultivation-and-yield-improvement/2026/rank-18*

| Field | Value |
| --- | --- |
| Rank | #18 |
| 18m citations | 28 |
| Journal | Remote Sensing of Environment |
| Year | 2024 |
| DOI | 10.1016/j.rse.2024.114427 |
| Corresponding authors | Yuchi Ma, David B. Lobell |
| Institution | Stanford University, United States |

**Ranking page:** [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)

**Paper link:** [10.1016/j.rse.2024.114427](https://doi.org/10.1016/j.rse.2024.114427)

## 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

## Cite this ranking

```
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.

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
```