TY - CHAP
T1 - Monitoring agricultural ecosystems
AU - Johansen, Kasper
AU - Maltese, Antonino
AU - McCabe, Matthew
N1 - KAUST Repository Item: Exported on 2023-05-29
PY - 2023/2/17
Y1 - 2023/2/17
N2 - Unmanned aerial system (UAS)-based sensing technologies are considered an invaluable component of digital agriculture through delivery of timely and accurate information that can contribute to food and water security and sustainable food production. Precision agriculture, which focuses on optimization procedures to increase food production with fewer inputs, is already benefiting from regular UAS-derived information on crop function, performance, and condition. UAS can also benefit yield prediction-related studies, further facilitating effective management and planning aspects of the production chain. While red–green–blue and multispectral sensors provide a means for many operational crop mapping and monitoring solutions, detection of plant disease and assessment of evapotranspiration of crops generally require more exploratory analysis of hyperspectral and thermal infrared data, respectively. This chapter provides an overview of UAS-based crop monitoring applications suitable for precision agriculture and demonstrates, through two separate case studies focusing on macadamia and orange trees, the UAS data processing chain and workflows required for individual tree crown delineation, crown area and tree height measurements, tree condition assessment and identification of evaporative fractions, canopy temperature, and associated water stress. This chapter concludes with a discussion of best practices for UAS-based data collection and processing, as well as an exploration of challenges and prospects for delivering valuable agricultural insights to meet the future demands for increasing food production.
AB - Unmanned aerial system (UAS)-based sensing technologies are considered an invaluable component of digital agriculture through delivery of timely and accurate information that can contribute to food and water security and sustainable food production. Precision agriculture, which focuses on optimization procedures to increase food production with fewer inputs, is already benefiting from regular UAS-derived information on crop function, performance, and condition. UAS can also benefit yield prediction-related studies, further facilitating effective management and planning aspects of the production chain. While red–green–blue and multispectral sensors provide a means for many operational crop mapping and monitoring solutions, detection of plant disease and assessment of evapotranspiration of crops generally require more exploratory analysis of hyperspectral and thermal infrared data, respectively. This chapter provides an overview of UAS-based crop monitoring applications suitable for precision agriculture and demonstrates, through two separate case studies focusing on macadamia and orange trees, the UAS data processing chain and workflows required for individual tree crown delineation, crown area and tree height measurements, tree condition assessment and identification of evaporative fractions, canopy temperature, and associated water stress. This chapter concludes with a discussion of best practices for UAS-based data collection and processing, as well as an exploration of challenges and prospects for delivering valuable agricultural insights to meet the future demands for increasing food production.
UR - http://hdl.handle.net/10754/692102
UR - https://linkinghub.elsevier.com/retrieve/pii/B9780323852838000138
UR - http://www.scopus.com/inward/record.url?scp=85159489088&partnerID=8YFLogxK
U2 - 10.1016/B978-0-323-85283-8.00013-8
DO - 10.1016/B978-0-323-85283-8.00013-8
M3 - Chapter
SN - 9780323852838
SP - 125
EP - 151
BT - Unmanned Aerial Systems for Monitoring Soil, Vegetation, and Riverine Environments
PB - Elsevier
ER -