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Article

Mapping Very-High-Resolution Evapotranspiration from Unmanned Aerial Vehicle (UAV) Imagery

1
Hort-Eye Pty Ltd., Melbourne, VIC 3000, Australia
2
Department of Infrastructure Engineering, The University of Melbourne, Parkville, VIC 3010, Australia
3
Digital Agriculture, Food and Wine Group, School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC 3010, Australia
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Department of Mechanical and Aerospace Engineering, Monash University, Clayton, VIC 3800, Australia
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Department of Jobs, Precincts and Regions, Tatura, VIC 3616, Australia
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Centre for Agricultural Innovation, The University of Melbourne, Parkville, VIC 3010, Australia
7
Center for Data Science, Seoul Institute of Technology, Seoul 03909, Korea
*
Author to whom correspondence should be addressed.
Academic Editors: Filiberto Chiabrando and Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2021, 10(4), 211; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10040211
Received: 15 February 2021 / Revised: 16 March 2021 / Accepted: 22 March 2021 / Published: 1 April 2021
There is a growing concern about water scarcity and the associated decline in Australia’s agricultural production. Efficient water use as a natural resource requires more precise and adequate monitoring of crop water use and irrigation scheduling. Therefore, accurate estimations of evapotranspiration (ET) at proper spatial–temporal scales are critical to understand the crop water demand and uptake and to enable optimal irrigation scheduling. Remote sensing (RS)-based ET estimation has been adopted as a method for large-scale applications when the detailed spatial representation of ET is required. This research aimed to estimate instantaneous ET using very-high-resolution (VHR) multispectral and thermal imagery (GSD < 8 cm) collected using a single flight of a UAV over a high-density peach orchard with a discontinuous canopy. The energy balance component estimation was based on the high-resolution mapping of evapotranspiration (HRMET) model. A tree-by-tree ET map was produced using the canopy surface temperature and the leaf area index (LAI) resampled at the corresponding scale via a systematic feature segmentation method based on pure canopy extraction. Results showed a strong linear relationship between the estimated ET and the leaf transpiration (n = 42) measured using a gas exchange sensor, with a coefficient of determination (R2) of 0.89. Daily ET (5.5 mm d−1) derived from the instantaneous ET map was comparable with daily crop ET (6.4 mm d−1) determined by the meteorological approach over the study site. The proposed approach has important implications for mapping tree-by-tree ET over horticultural fields using VHR imagery. View Full-Text
Keywords: water use; thermal infrared (TIR) imagery; multispectral (MS) imagery; surface energy balance model (SEBM); high-resolution mapping of evapotranspiration (HRMET) water use; thermal infrared (TIR) imagery; multispectral (MS) imagery; surface energy balance model (SEBM); high-resolution mapping of evapotranspiration (HRMET)
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MDPI and ACS Style

Park, S.; Ryu, D.; Fuentes, S.; Chung, H.; O’Connell, M.; Kim, J. Mapping Very-High-Resolution Evapotranspiration from Unmanned Aerial Vehicle (UAV) Imagery. ISPRS Int. J. Geo-Inf. 2021, 10, 211. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10040211

AMA Style

Park S, Ryu D, Fuentes S, Chung H, O’Connell M, Kim J. Mapping Very-High-Resolution Evapotranspiration from Unmanned Aerial Vehicle (UAV) Imagery. ISPRS International Journal of Geo-Information. 2021; 10(4):211. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10040211

Chicago/Turabian Style

Park, Suyoung, Dongryeol Ryu, Sigfredo Fuentes, Hoam Chung, Mark O’Connell, and Junchul Kim. 2021. "Mapping Very-High-Resolution Evapotranspiration from Unmanned Aerial Vehicle (UAV) Imagery" ISPRS International Journal of Geo-Information 10, no. 4: 211. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10040211

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