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  • Format: ePub

This book features five peer-reviewed reviews on the use of unmanned aircraft systems in an array of agricultural settings.
The first chapter provides an overview of unmanned aerial system (UAS) platforms and sensors, flight planning and imagery acquisition, before moving on to consider stitching and ortho-rectification in UAS image processing.
The second chapter discusses approaches to unmanned aerial vehicle (UAV) remote sensing and data analysis for high-throughput field phenotyping and ecophysiological research. The chapter reviews the use of UAV remote sensing to measure key plant
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Produktbeschreibung
This book features five peer-reviewed reviews on the use of unmanned aircraft systems in an array of agricultural settings.

The first chapter provides an overview of unmanned aerial system (UAS) platforms and sensors, flight planning and imagery acquisition, before moving on to consider stitching and ortho-rectification in UAS image processing.

The second chapter discusses approaches to unmanned aerial vehicle (UAV) remote sensing and data analysis for high-throughput field phenotyping and ecophysiological research. The chapter reviews the use of UAV remote sensing to measure key plant traits, such as canopy cover and leaf area index.

The third chapter presents a useful overview of the advantages and limitations of UAV remote sensing platforms and their applications in precision agriculture.

The fourth chapter discusses the quantification of plant water status and the various methods used to assess plant water stress. A section on optical remote sensing of plant water status is also provided, followed by sections on thermal infrared remote sensing and microwave remote sensing of plant water status.

The final chapter reviews the application of small unmanned aircraft systems (sUAS) and remote sensing technology in turfgrass systems. The chapter also highlights the various sUAS platforms and sensors necessary to measure and monitor the target of interest.


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Autorenporträt
Chunhua Zhang, Algoma University, Canada; and John M. Kovacs and Dan Walters, Nipissing University, Canada; Helge Aasen, Institute of Agricultural Sciences, ETH Zurich and Remote Sensing Team, Division of Agroecology and Environment, Agroscope, Switzerland; and Lukas Roth, Institute of Agricultural Sciences, ETH Zurich, Switzerland; Tarin Paz-Kagan, Ben Gurion University of the Negev, Israel; Wenxuan Guo, Texas Tech University and Texas A&M AgriLife Research, USA; and Haibin Gu, Bishnu Ghimire and Oluwatola Adedeji, Texas Tech University, USA