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Unmanned Aerial Systems in Precision Agriculture

Technological Progresses and Applications

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  • © 2022

Overview

Editors:
  1. Zhao Zhang

    1. Key Lab of Smart Agriculture Systems, Ministry of Education, China Agricultural University, Beijing, China

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  2. Hu Liu

    1. Chinese Academy of Sciences, Northwest Institute of Eco-Environment and Resources, Lanzhou, China

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  3. Ce Yang

    1. Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, USA

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  4. Yiannis Ampatzidis

    1. UF/IFAS Southwest Florida Research and Education Center, University of Florida, Immokalee, USA

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  5. Jianfeng Zhou

    1. University of Missouri, Columbia, USA

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  6. Yu Jiang

    1. School of Integrative Plant Science, Cornell University, Geneva, USA

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  • 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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Table of contents (8 chapters)

  1. Front Matter

    Pages i-v
    Download chapter PDF

  2. Applications of UAVs and Machine Learning in Agriculture

    • Sri Charan Kakarla, Lucas Costa, Yiannis Ampatzidis, Zhao Zhang
    Pages 1-19

  3. Robot Operating System Powered Data Acquisition for Unmanned Aircraft Systems in Digital Agriculture

    • Yu Jiang
    Pages 21-38

  4. Unmanned Aerial Vehicle (UAV) Applications in Cotton Production

    • Aijing Feng, Chin Nee Vong, Jianfeng Zhou
    Pages 39-57

  5. Time Effect After Initial Wheat Lodging on Plot Lodging Ratio Detection Using UAV Imagery and Deep Learning

    • Zhao Zhang, Cannayen Igathinathane, Paulo Flores, Yiannis Ampatzidis, Hu Liu, Jithin Mathew et al.
    Pages 59-72

  6. UAV Mission Height Effects on Wheat Lodging Ratio Detection

    • Zhao Zhang, Cannayen Igathinathane, Paulo Flores, Jithin Mathew, Joel Ransom, Yiannis Ampatzidis et al.
    Pages 73-85

  7. Wheat-Net: An Automatic Dense Wheat Spike Segmentation Method Based on an Optimized Hybrid Task Cascade Model

    • JiaJing Zhang, An Min, Brian J. Steffenson, Wenhao Su, Cory D. Hirsch, James Anderson et al.
    Pages 87-106

  8. UAV Multispectral Remote Sensing for Yellow Rust Mapping: Opportunities and Challenges

    • Jinya Su, Cunjia Liu, Wen-Hua Chen
    Pages 107-122

  9. Corn Goss’s Wilt Disease Assessment Based on UAV Imagery

    • Anup Kumar Das, Jithin Mathew, Zhao Zhang, Andrew Friskop, Yuxiang Huang, Paulo Flores et al.
    Pages 123-136
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Keywords

About this book

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.

Editors and Affiliations

  • Key Lab of Smart Agriculture Systems, Ministry of Education, China Agricultural University, Beijing, China

    Zhao Zhang

  • Chinese Academy of Sciences, Northwest Institute of Eco-Environment and Resources, Lanzhou, China

    Hu Liu

  • Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, USA

    Ce Yang

  • UF/IFAS Southwest Florida Research and Education Center, University of Florida, Immokalee, USA

    Yiannis Ampatzidis

  • University of Missouri, Columbia, USA

    Jianfeng Zhou

  • School of Integrative Plant Science, Cornell University, Geneva, USA

    Yu Jiang

About the editors

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. 


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

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