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Remote Sens. 2016, 8(8), 638; doi:10.3390/rs8080638

Estimation of Energy Balance Components over a Drip-Irrigated Olive Orchard Using Thermal and Multispectral Cameras Placed on a Helicopter-Based Unmanned Aerial Vehicle (UAV)

Centro de Investigación y Transferencia en Riego y Agroclimatología (CITRA) and Research program on Adaptation of Agriculture to Climate Change (A2C2), Universidad de Talca, Casilla 747, Talca 3460000, Chile
School of Natural Resources and Civil Engineering, University of Nebraska-Lincoln, 311 Hardin Hall, 3310 Holdrege Street, Lincoln, NE 68588, USA
Biological and Agricultural Engineering and Civil Engineering, Research and Ext. Center, University of Idaho, Kimberly, Moscow, ID 83844, USA
Escuela de Agronomía, Pontificia Universidad Católica de Valparaíso, Quillota 2260000, Chile
Author to whom correspondence should be addressed.
Academic Editors: Mutlu Ozdogan, Jose Moreno, Clement Atzberger and Prasad S. Thenkabail
Received: 23 February 2016 / Revised: 28 July 2016 / Accepted: 1 August 2016 / Published: 8 August 2016
(This article belongs to the Special Issue Remote Sensing in Precision Agriculture)
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A field experiment was carried out to implement a remote sensing energy balance (RSEB) algorithm for estimating the incoming solar radiation (Rsi), net radiation (Rn), sensible heat flux (H), soil heat flux (G) and latent heat flux (LE) over a drip-irrigated olive (cv. Arbequina) orchard located in the Pencahue Valley, Maule Region, Chile (35°25′S; 71°44′W; 90 m above sea level). For this study, a helicopter-based unmanned aerial vehicle (UAV) was equipped with multispectral and infrared thermal cameras to obtain simultaneously the normalized difference vegetation index (NDVI) and surface temperature (Tsurface) at very high resolution (6 cm × 6 cm). Meteorological variables and surface energy balance components were measured at the time of the UAV overpass (near solar noon). The performance of the RSEB algorithm was evaluated using measurements of H and LE obtained from an eddy correlation system. In addition, estimated values of Rsi and Rn were compared with ground-truth measurements from a four-way net radiometer while those of G were compared with soil heat flux based on flux plates. Results indicated that RSEB algorithm estimated LE and H with errors of 7% and 5%, respectively. Values of the root mean squared error (RMSE) and mean absolute error (MAE) for LE were 50 and 43 W m−2 while those for H were 56 and 46 W m−2, respectively. Finally, the RSEB algorithm computed Rsi, Rn and G with error less than 5% and with values of RMSE and MAE less than 38 W m−2. Results demonstrated that multispectral and thermal cameras placed on an UAV could provide an excellent tool to evaluate the intra-orchard spatial variability of Rn, G, H, LE, NDVI and Tsurface over the tree canopy and soil surface between rows. View Full-Text
Keywords: evapotranspiration; irrigation; remote sensing; energy balance; olive orchard; UAV evapotranspiration; irrigation; remote sensing; energy balance; olive orchard; UAV

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Ortega-Farías, S.; Ortega-Salazar, S.; Poblete, T.; Kilic, A.; Allen, R.; Poblete-Echeverría, C.; Ahumada-Orellana, L.; Zuñiga, M.; Sepúlveda, D. Estimation of Energy Balance Components over a Drip-Irrigated Olive Orchard Using Thermal and Multispectral Cameras Placed on a Helicopter-Based Unmanned Aerial Vehicle (UAV). Remote Sens. 2016, 8, 638.

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