Integrating UAVs, satellite remote sensing, and machine learning in precision agriculture: pathways to sustainable food production, resource efficiency, and scalable innovation
Abstract
Precision agriculture has emerged as a pivotal approach to achieving sustainable food production by integrating advanced technologies such as Unmanned Aerial Vehicles (UAVs), satellite remote sensing, and machine learning. This review examines the synergistic application of these technologies in enhancing agricultural efficiency, resource optimization, and environmental sustainability. UAVs enable high-resolution, real-time monitoring of crop health, soil conditions, and pest infestations, while satellite remote sensing provides scalable, large-scale agricultural data for comprehensive landscape analysis. Machine learning algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs)…
Citation impact
- FWCI
- 66.19
- Percentile
- 100%
- References
- 99
Authors
3- YXYingyig Xing
Yan'an University
- XLXuning Liu
Yan'an University
- XWXiukang WangCorresponding
Yan'an University
Topics & keywords
- Precision agriculture
- Sustainable agriculture
- Scalability
- Resource (disambiguation)
- Convolutional neural network
- Cloud computing
- Agricultural productivity
- Downy mildew
- Zero hunger