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Estimación de la evapotranspiración del cultivo de arroz en Perú mediante el algoritmo METRIC e imágenes VANT

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Estimación de la evapotranspiración del cultivo de arroz en Perú mediante el algoritmo METRIC e imágenes VANT

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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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