Xia Wang
Jiangsu Key Laboratory for Recognition and Remediation of Emerging Pollutants in Taihu Basin, School of Environmental Science and Engineering, Wuxi University, Wuxi, 214105, ChinaPublications
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Mini Review
Fusion of multi-source UAV and PhenoCam data for advancing forage crop monitoring and yield prediction
Author(s): Kang Xu*, Yihang Wu, Yifan Zhang and Xia Wang
Accurate monitoring and reliable prediction of forage crop productivity are essential for promoting sustainable agriculture and ensuring food security. Low-cost and non-invasive remote sensing platforms, particularly Unmanned Aerial Vehicles (UAVs) and PhenoCams, offer substantial potential for achieving these objectives. This study reviews the main types of sensors, including Red, Green, Blue (RGB) bands, multispectral, hyperspectral, thermal infrared, and Light Detection and Ranging (LiDAR), deployed on UAV platforms and ground- based PhenoCams, as well as their applications in forage crop monitoring and yield estimation. It further examines the algorithmic models and predictive frameworks developed from Vegetation Indices (VIs) and plant-level traits derived from these diverse data sources. Existing research indicates that integrating data from multiple platforms leverages their co.. Read More»
DOI: 10.5281/zenodo.18231119