A review of the application of UAV multispectral remote sensing technology in precision agriculture
Shuang Zhang, Xiaorui Wang, Hong Lin, Yueyu Dong, Zhenping Qiang
Abstract
With the growing demand for precision agriculture, which requires high spatial and temporal resolution crop information, unmanned aerial vehicles (UAVs) equipped with multispectral sensors have become increasingly vital tools for agricultural management due to their real-time monitoring capabilities, flexibility, and cost-effectiveness. This paper provides a scoping review of advances in UAV-based multispectral remote sensing applications in precision agriculture, focusing on four key domains: crop growth monitoring, pest and disease identification, nutrient status assessment, and yield prediction. We offer a comprehensive analysis of the relevant literature, evaluating the principal challenges and opportunities associated with deploying this technology in the field. Our review indicates that traditional vegetation indices (e.g., NDVI, GNDVI, SAVI) have achieved mature application across diverse crops. In contrast, integrating emerging indices (e.g., TCARI, RDVI, OSAVI) with intelligent algorithms can significantly enhance monitoring accuracy and operational efficiency. In addition, we recommend that future research prioritize improvements in algorithmic precision, optimizing the data-processing workflows, and interdisciplinary collaboration to promote deeper integration of UAV-based multispectral sensing and artificial intelligence methods. Finally, we outline several practical research directions to inform and guide subsequent investigations.