Adaptive estimation of crop water stress in nectarine and peach orchards using high-resolution imagery from an unmanned aerial vehicle (UAV)

S Park; D Ryu; S Fuentes; H Chung; E Hernández-Montes; M O'Connell

Journal article

Adaptive estimation of crop water stress in nectarine and peach orchards using high-resolution imagery from an unmanned aerial vehicle (UAV)

S Park, D Ryu, S Fuentes, H Chung, E Hernández-Montes, M O'Connell

Remote Sensing | Published : 2017

DOI: 10.3390/rs9080828

Abstract

The capability to monitor water status from crops on a regular basis can enhance productivity and water use efficiency. In this paper, high-resolution thermal imagery acquired by an unmanned aerial vehicle (UAV) was used to map plant water stress and its spatial variability, including sectors under full irrigation and deficit irrigation over nectarine and peach orchards at 6.12 cm ground sample distance. The study site was classified into sub-regions based on crop properties, such as cultivars and tree training systems. In order to enhance the accuracy of the mapping, edge extraction and filtering were conducted prior to the probability modelling employed to obtain crop-property-specific ('a..

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University of Melbourne Researchers

Dongryeol Ryu Author

Sigfredo Fuentes Author

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INTEGRATED GREENHOUSE GAS MEASUREMENT SYSTEM (IGMS) FOR MONITORING AGRICULTURAL EMISSIONS AT FIELD TO REGIONAL SCALES

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Grants

Awarded by ARC LIEF Grant

Awarded by DEDJTR

Awarded by Australian Research Council

Funding Acknowledgements

This research was supported by the Innovation Seed Fund for Horticulture Development grant from the University of Melbourne and Department of Economic Development, Jobs, Transport, and Resources (DEDJTR), Victoria and ARC LIEF Grant (LE130100040). The use of the experimental stonefruit orchard as a resource for the study is acknowledged, with financial support from Horticulture Innovation Australia and DEDJTR (project SF12003: 'Increased stone fruit profitability by consistently meeting market expectations').