UAV multi-source data fusion with super-resolution for accurate soybean leaf area index estimation
The results demonstrate that the fusion of SR-reconstructed imagery with multi-sensor data can effectively mitigate the negative impact of higher flight altitudes on LAI estimation accuracy. This approach provides a robust and efficient framework for UAV-based crop monitoring, enhancing data-driven decision-making in precision agriculture.
Authors
- Hong Yao (ORCID: https://orcid.org/0000-0002-3333-0925)
- Depeng Zeng
- Xihai Zhang (ORCID: https://orcid.org/0000-0001-6370-6279)
- Zhenqing Zhao
- Zhenfeng Jiang
Institutions
- Harbin Engineering University (CN)
- Northeast Agricultural University (CN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-11-20
- DOI
- https://doi.org/10.3389/fpls.2025.1700660
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Heilongjiang Province