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dc.contributor.author | Quille-Mamani, Javier A. | es_ES |
dc.contributor.author | Ramos-Fernández, Lia | es_ES |
dc.contributor.author | Ontiveros-Capurata, Ronald E. | es_ES |
dc.coverage.spatial | east=-75.015152; north=-9.189967; name=Perú | es_ES |
dc.date.accessioned | 2021-07-26T06:39:01Z | |
dc.date.available | 2021-07-26T06:39:01Z | |
dc.date.issued | 2021-07-21 | |
dc.identifier.issn | 1133-0953 | |
dc.identifier.uri | http://hdl.handle.net/10251/170135 | |
dc.description.abstract | [EN] Modern remote measurement techniques using cameras mounted on an unmanned aerial vehicle (UAV) have made possible to acquire high-resolution images and estimating evapotranspiration at more detailed spatial and temporal scales. The objective of the present research was to estimate crop evapotranspiration (ETc) of rice crop using the “mapping evapotranspiration with internalized calibration model (METRIC)” using high spatial resolution multispectral and thermal images obtained from a UAV. A total of 18 flights with UAV were performed to get the images; likewise, data were collected from the weather station and thermocouple information installed in the crop canopy under soil water potential conditions of –10 kPa (T1), –15 kPa (T2), –20 kPa (T3) and a control of 0 kPa (T0), from November 13, 2017, to April 30, 2018. The results indicate that the METRIC model compared to ETc measurements recorded by a field drainage lysimeter presents a Pearson correlation coefficient (r) of 0.97, root mean square error (RMSE) of 0.51 mm d–1, Nash-Sutcliffe coefficient (EF) of 0.87 and underestimation of 7 %. Evapotranspiration reached values of 7.48 mm d–1, with differences between treatments of 0.2 %, 6 % and 8 % concerning to T0 and yield reduction of 9 %, 34 % and 35 % for T1, T2 and T3 soil water potential. The high[1]resolution images allowed obtaining detailed information on the spatial variability of ETc that could be used in the more efficient application of plot irrigation. | es_ES |
dc.description.abstract | [ES] Las modernas técnicas de mediciones remotas con el uso de cámaras (multiespectral y térmica) acopladas a un vehículo aéreo no tripulado (VANT) han permitido adquirir imágenes de alta resolución, haciendo posible estimar la evapotranspiración a una mayor escala espacial y temporal. El objetivo de la presente investigación fue estimar la evapotranspiración del cultivo (ETc) de arroz mediante el modelo METRIC (Mapping evapotranspiration at high resolution with internalized calibration) a partir de imágenes multiespectrales y térmicas de alta resolución espacial obtenidas desde un VANT. Se realizaron 18 vuelos con VANT para obtener las imágenes, así mismo, se recolectaron datos de una estación meteorológica e información de termopares instalados en el dosel del cultivo en condiciones de potencial hídrico del suelo de –10 kPa (T1), –15 kPa (T2), –20 kPa (T3) y un control de 0 kPa (T0), desde el 13 de noviembre del 2017 al 30 de abril del 2018. Los resultados indican que el modelo METRIC, comparado con las medidas de ETc registradas por un lisímetro de drenaje en campo, presenta un coeficiente de correlación de Pearson (r) de 0,97, un error cuadrático medio (RMSE) de 0,51 mm d–1, un coeficiente de Nash-Sutcliffe (EF) de 0,87 y subestimación del 7 %. La evapotranspiración alcanzó valores de 7,48 mm d–1, con diferencias entre tratamientos de 0,2%, 6% y 8% con respecto al T0 y una reducción del rendimiento del 9 %, 34 % y 35 % para T1, T2 y T3 del potencial hídrico del suelo. Las imágenes de alta resolución permitieron obtener información detallada de la variabilidad espacial de ETc que podría ser utilizada en la aplicación más eficiente del riego parcelario. | es_ES |
dc.description.sponsorship | Al Proyecto “Uso de sensores remotos para determinar índice de estrés hídrico en el mejoramiento del manejo de riego de arroz (Oryza sativa) en zonas áridas, para enfrentar al cambio climático”. Convenio N° 008-2016-INIA-PNIA/UPMSI/IE. | es_ES |
dc.language | Español | es_ES |
dc.publisher | Universitat Politècnica de València | es_ES |
dc.relation.ispartof | Revista de Teledetección | es_ES |
dc.rights | Reconocimiento - No comercial - Compartir igual (by-nc-sa) | es_ES |
dc.subject | Remote sensing | es_ES |
dc.subject | UAV | es_ES |
dc.subject | Energy balance | es_ES |
dc.subject | Multispectral imaging | es_ES |
dc.subject | Thermal imaging | es_ES |
dc.subject | Oryza sativa | es_ES |
dc.subject | Teledetección | es_ES |
dc.subject | Dron | es_ES |
dc.subject | Balance de energía | es_ES |
dc.subject | Imágenes multiespectrales | es_ES |
dc.subject | Imágenes térmicas | es_ES |
dc.title | Estimación de la evapotranspiración del cultivo de arroz en Perú mediante el algoritmo METRIC e imágenes VANT | es_ES |
dc.title.alternative | Estimation of rice crop evapotranspiration in Perú based on the METRIC algorithm and UAV images | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.4995/raet.2021.13699 | |
dc.relation.projectID | info:eu-repo/grantAgreement/INIA//008-2016-INIA-PNIA%2FUPMSI%2FIE/PE/Uso de sensores remotos para determinar índice de estrés hídrico en el mejoramiento del manejo de riego de arroz (Oryza sativa) en zonas áridas, para enfrentar al cambio climático/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.description.bibliographicCitation | Quille-Mamani, JA.; Ramos-Fernández, L.; Ontiveros-Capurata, RE. (2021). Estimación de la evapotranspiración del cultivo de arroz en Perú mediante el algoritmo METRIC e imágenes VANT. Revista de Teledetección. 0(58):23-38. https://doi.org/10.4995/raet.2021.13699 | es_ES |
dc.description.accrualMethod | OJS | es_ES |
dc.relation.publisherversion | https://doi.org/10.4995/raet.2021.13699 | es_ES |
dc.description.upvformatpinicio | 23 | es_ES |
dc.description.upvformatpfin | 38 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 0 | es_ES |
dc.description.issue | 58 | es_ES |
dc.identifier.eissn | 1988-8740 | |
dc.relation.pasarela | OJS\13699 | es_ES |
dc.contributor.funder | Instituto Nacional de Innovación Agraria, Perú | es_ES |
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