{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,27]],"date-time":"2024-08-27T23:05:41Z","timestamp":1724799941361},"reference-count":83,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2021,10,13]],"date-time":"2021-10-13T00:00:00Z","timestamp":1634083200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100008736","name":"Fondo de Fomento al Desarrollo Cient\u00edfico y Tecnol\u00f3gico","doi-asserted-by":"publisher","award":["IT18I0022"],"id":[{"id":"10.13039\/501100008736","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"Evapotranspiration (ET) is key to assess crop water balance and optimize water-use efficiency. To attain sustainability in cropping systems, especially in semi-arid ecosystems, it is necessary to improve methodologies of ET estimation. A method to predict ET is by using land surface temperature (LST) from remote sensing data and applying the Operational Simplified Surface Energy Balance Model (SSEBop). However, to date, LST information from Landsat-8 Thermal Infrared Sensor (TIRS) has a coarser resolution (100 m) and longer revisit time than Sentinel-2, which does not have a thermal infrared sensor, which compromises its use in ET models as SSEBop. Therefore, in the present study we set out to use Sentinel-2 data at a higher spatial-temporal resolution (10 m) to predict ET. Three models were trained using TIRS\u2019 images as training data (100 m) and later used to predict LST at 10 m in the western section of the Copiap\u00f3 Valley (Chile). The models were built on cubist (Cub) and random forest (RF) algorithms, and a sinusoidal model (Sin). The predicted LSTs were compared with three meteorological stations located in olives, vineyards, and pomegranate orchards. RMSE values for the prediction of LST at 10 m were 7.09 K, 3.91 K, and 3.4 K in Cub, RF, and Sin, respectively. ET estimation from LST in spatial-temporal relation showed that RF was the best overall performance (R2 = 0.710) when contrasted with Landsat, followed by the Sin model (R2 = 0.707). Nonetheless, the Sin model had the lowest RMSE (0.45 mm d\u22121) and showed the best performance at predicting orchards\u2019 ET. In our discussion, we argue that a simplistic sinusoidal model built on NDVI presents advantages over RF and Cub, which are constrained to the spatial relation of predictors at different study areas. Our study shows how it is possible to downscale Landsat-8 TIRS\u2019 images from 100 m to 10 m to predict ET.<\/jats:p>","DOI":"10.3390\/rs13204105","type":"journal-article","created":{"date-parts":[[2021,10,14]],"date-time":"2021-10-14T01:48:39Z","timestamp":1634176119000},"page":"4105","source":"Crossref","is-referenced-by-count":8,"title":["Determining Actual Evapotranspiration Based on Machine Learning and Sinusoidal Approaches Applied to Thermal High-Resolution Remote Sensing Imagery in a Semi-Arid Ecosystem"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-2202-2297","authenticated-orcid":false,"given":"Luis A.","family":"Reyes Rojas","sequence":"first","affiliation":[{"name":"Laboratory of Territorial Analysis (LAT), University of Chile, Santiago 8820808, Chile"}]},{"ORCID":"http:\/\/orcid.org\/0000-0003-0609-9649","authenticated-orcid":false,"given":"Italo","family":"Moletto-Lobos","sequence":"additional","affiliation":[{"name":"Laboratory for the Analysis of the Biosphere (LAB), Santiago 8820808, Chile"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-9696-7643","authenticated-orcid":false,"given":"Fabio","family":"Corradini","sequence":"additional","affiliation":[{"name":"INIA La Platina, Instituto de Investigaciones Agropecuarias, Santiago 8831314, Chile"}]},{"given":"Cristian","family":"Mattar","sequence":"additional","affiliation":[{"name":"Laboratory for the Analysis of the Biosphere (LAB), Santiago 8820808, Chile"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-5804-3324","authenticated-orcid":false,"given":"Rodrigo","family":"Fuster","sequence":"additional","affiliation":[{"name":"Laboratory of Territorial Analysis (LAT), University of Chile, Santiago 8820808, Chile"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-6755-0013","authenticated-orcid":false,"given":"Cristi\u00e1n","family":"Escobar-Avaria","sequence":"additional","affiliation":[{"name":"Laboratory of Territorial Analysis (LAT), University of Chile, Santiago 8820808, Chile"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,13]]},"reference":[{"key":"ref_1","first-page":"1327","article-title":"Evapotranspiration monitoring","volume":"Volume 3","author":"Maurice","year":"2020","journal-title":"Encyclopedia of Water: Science, Technology, and Society"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2618","DOI":"10.1002\/2016WR020175","article-title":"The future of evapotranspiration: Global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources: The future of evapotranspiration","volume":"53","author":"Fisher","year":"2017","journal-title":"Water Resour. 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