Unmanned Aerial Systems in Precision Agriculture
Technological Progresses and Applications
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Beschreibung
This book, consisting of 8 chapters, describes the state-of-the-art technological progress and applications of unmanned aerial vehicles (UAVs) in precision agriculture. It focuses on the UAV application in agriculture, such as crop disease detection, mid-season yield estimation, crop nutrient status, and high-throughput phenotyping. Different from individual papers focusing on a specific application, this book provides a holistic view for readers with a wide range of subjects. In addition to researchers in the areas of plant science, plant pathology, breeding, engineering, it is also intended for undergraduates and graduates who are interested in imaging processing, artificial intelligence in agriculture, precision agriculture, agricultural automation, and robotics.
This book, consisting of 8 chapters, describes the state-of-the-art technological progress and applications of unmanned aerial vehicles (UAVs) in precision agriculture. It focuses on the UAV application in agriculture, such as crop disease detection, mid-season yield estimation, crop nutrient status, and high-throughput phenotyping. Different from individual papers focusing on a specific application, this book provides a holistic view for readers with a wide range of subjects. In addition to researchers in the areas of plant science, plant pathology, breeding, engineering, it is also intended for undergraduates and graduates who are interested in imaging processing, artificial intelligence in agriculture, precision agriculture, agricultural automation, and robotics.
Presents the technological progress of UAV applications in precision agriculture, coupled with deep learning Provides multiple UAV application cases in precision agriculture in Europe and USA Introduces general information for undergraduates and graduates
Autor*in
Zhao Zhang
Themen in »Unmanned Aerial Systems in Precision Agriculture«
Precision agriculture Plant health conditions Crop disease monitoring Machine learning Deep learning Unmanned system Unmanned Aerial System (UAS) Unmanned aerials vehicles Drone images Wheat disease Specialty crop management Nitrogen conditioning Crop disease detection Mid-season yield estimation Crop nutrient status