Unmanned Aerial Systems in Precision Agriculture (eBook)
Technological Progresses and Applications
eBook Download:
PDF
2022
|
1. Auflage
V, 136 Seiten
Springer Nature Singapore (Verlag)
978-981-19-2027-1 (ISBN)
V, 136 Seiten
Springer Nature Singapore (Verlag)
978-981-19-2027-1 (ISBN)
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.
Dr. Zhao Zhang earned his Ph.D. from the Department of Agricultural and Biological Engineering, The Pennsylvania State University. After conducting research as a PostDoc in USDA-ARS, he joined the Department of Agricultural and Biosystems Engineering, North Dakota State University, as Research Assistant Professor. He is now a professor with College of Information and Electrical Engineering, China Agricultural University, working in the area of smart agriculture'.
Dr. Hu Liu earned his Ph.D. from Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, and then joined the same institute as a researcher. Dr. Liu's research topic is using remote sensing technology in agriculture.
Dr. Ce Yang earned her Ph.D. from University of Florida, and then joined the
University of Minnesota at Twin Cities as a faculty member. Dr. Yang has conducted numerous research in using unmanned aerials vehicles in agriculture, which includes, but it not limited to, using drone images to monitor wheat disease and maize nitrogen status.
Dr. Yiannis Ampatzidis is a renowned professor with the Department of Agricultural and Biological Engineering, University of Florida. Dr. Ampatzidis is also a key member of the Southwest Florida Research & Education Center, located in Immokalee, FL. Dr. Ampatzidis focuses on using innovative technology on orchard management.
Dr. Jianfeng Zhou earned his Ph.D. from Washington State University, and he is now an assistant professor with University of Missouri. Dr. Zhou has conducted a number of studies on using drone technology for both row and specialty crop management, such as apples, wheat, and cotton.
Dr. Yu Jiang earned his Ph.D. in Agricultural and Biological Engineering from University of Georgia, after which he joined the Cornell University as a faculty member. His research interests include multimodal sensing, agricultural robotics, and artificial intelligence in agriculture. He has conducted multiple projects to develop plant phenomics tools for crops such as cotton, blueberries, grapes, and apples.
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.
| Erscheint lt. Verlag | 17.5.2022 |
|---|---|
| Reihe/Serie | Smart Agriculture |
| Zusatzinfo | V, 136 p. 68 illus., 60 illus. in color. |
| Sprache | englisch |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Naturwissenschaften ► Biologie | |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Fahrzeugbau / Schiffbau | |
| Technik ► Luft- / Raumfahrttechnik | |
| Technik ► Maschinenbau | |
| Weitere Fachgebiete ► Land- / Forstwirtschaft / Fischerei | |
| Schlagworte | Crop disease detection • Crop disease monitoring • Crop nutrient status • Deep learning • drone images • High-throughput phenotyping • machine learning • Mid-season yield estimation • Nitrogen conditioning • Plant health conditions • Precision Agriculture • Specialty crop management • Unmanned aerials vehicles • Unmanned Aerial System (UAS) • Unmanned system • wheat disease |
| ISBN-10 | 981-19-2027-3 / 9811920273 |
| ISBN-13 | 978-981-19-2027-1 / 9789811920271 |
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