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            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>Agricultura sostenible</text>
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            <name>Description</name>
            <description>An account of the resource</description>
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                <text>Dominio científico: Agricultura sostenible</text>
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          <name>Title</name>
          <description>A name given to the resource</description>
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              <text>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)</text>
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          <name>Creator</name>
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              <text>Samuel Ortega-Farías, Samuel Ortega-Salazar, Tomas Poblete, Ayse Kilic, Richard Allen, Carlos Poblete-Echeverría, Luis Ahumada-Orellana, Mauricio Zuñiga, Daniel Sepúlveda</text>
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              <text>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.</text>
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          <name>Date</name>
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              <text>2016</text>
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          <name>Subject</name>
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              <text>UAV, energy balance, evapotranspiration, irrigation, olive orchard, remote sensing</text>
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          <name>Identifier</name>
          <description>An unambiguous reference to the resource within a given context</description>
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            <elementText elementTextId="160617">
              <text>10.3390/rs8080638</text>
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          <name>Source</name>
          <description>A related resource from which the described resource is derived</description>
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              <text>Remote Sensing</text>
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          <name>Publisher</name>
          <description>An entity responsible for making the resource available</description>
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              <text>MDPI AG</text>
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          <name>Coverage</name>
          <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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              <text>Science</text>
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          <description>A related resource</description>
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              <text>&lt;a href="http://www.mdpi.com/2072-4292/8/8/638" target="_blank" rel="noreferrer noopener"&gt;http://www.mdpi.com/2072-4292/8/8/638&lt;/a&gt;</text>
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