A review of UAV remote sensing technology applications in common gramineous crops

In recent years, UAV remote sensing technology (UAV-RS) has been widely used in agricultural monitoring, especially in managing gramineous crops. Gramineous crops like wheat, rice, maize, sorghum, and sugarcane are vital global food and energy sources. They are crucial for food security and agricultural economies. The integration of UAV-RS with computer vision (CV), machine learning (ML), and deep learning (DL) has enabled the precise monitoring of these crops across various growth stages. Notably, researchers have made significant progress in monitoring key agronomic parameters such as plant height, leaf area index, nitrogen nutritional status, aboveground biomass, and crop growth status indicators such as lodging, plant detection, yield prediction, and pest and disease monitoring. This study offers a systematic review of the recent advancements in the application of UAV-RS for agricultural information monitoring in growing wheat, rice, maize, sorghum, and sugarcane since 2020. The focus is on summarizing remote sensing methods for monitoring various agronomic parameters and crop growth status. Furthermore, it discusses the interrelationships among these monitoring parameters. This provides a theoretical foundation for developing comprehensive monitoring models. By considering the phenological characteristics of different crops, this study also identifies the optimal timing for monitoring key parameters. This offers scientific guidance for optimizing monitoring strategies. Finally, we address current research limitations and propose future research directions.