Overview
- 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
Part of the book series: Smart Agriculture (SA, volume 2)
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Keywords
- 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
- High-throughput phenotyping
Table of contents (8 chapters)
Editors and Affiliations
About the editors
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.
Bibliographic Information
Book Title: Unmanned Aerial Systems in Precision Agriculture
Book Subtitle: Technological Progresses and Applications
Editors: Zhao Zhang, Hu Liu, Ce Yang, Yiannis Ampatzidis, Jianfeng Zhou, Yu Jiang
Series Title: Smart Agriculture
DOI: https://doi.org/10.1007/978-981-19-2027-1
Publisher: Springer Singapore
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022
Hardcover ISBN: 978-981-19-2026-4Published: 18 May 2022
Softcover ISBN: 978-981-19-2029-5Published: 19 May 2023
eBook ISBN: 978-981-19-2027-1Published: 17 May 2022
Series ISSN: 2731-3476
Series E-ISSN: 2731-3484
Edition Number: 1
Number of Pages: V, 136
Number of Illustrations: 8 b/w illustrations, 60 illustrations in colour
Topics: Agriculture, Signal, Image and Speech Processing, Machine Learning, Robotics and Automation, Plant Sciences