Exploring the potential role of multi-source remote sensing data during different growth stages in crop yield prediction
, and SIF, whereas leaf chlorophyll concentration exhibited comparatively weaker associations with these indicators. These findings provide valuable insights for improving crop yield forecasts using remote sensing, thereby contributing to enhanced agricultural management and food security strategies under climate change.
Authors
- Xingli Gu
- Enxiang Xu
- Yonggang Chi
- Qin’ou Liang
- Lei Zhou
Institutions
- Zhejiang Normal University (CN)
Publication Details
- Journal
- PeerJ
- Published
- 2026-04-01
- DOI
- https://doi.org/10.7717/peerj.21031
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China