Balance anual de agua en cultivos utilizando datos de serie de tiempo armonizados de Landsat-8 y Sentinel- 2.
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Date
2019
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Publisher
Universidad de Concepción.
Abstract
La gestión eficiente del agua en la agricultura requiere una estimación precisa de la evapotranspiración (ET). Aunque se pueden utilizar mediciones locales para estimar los componentes del balance de energía en la superficie, estos valores no pueden extrapolarse a grandes áreas debido a la heterogeneidad y complejidad de las condiciones en las que se desarrolla la agricultura. Un análisis espacialmente distribuido utilizando imágenes de satélite representa una alternativa eficiente y económica para proporcionar estimaciones de ET en grandes áreas, a través de la información proporcionada tanto en el rango óptico como térmico del espectro electromagnético; sin embargo, la mayoría de los sensores actuales no proporcionan esta información, pero si incluyen un conjunto de bandas espectrales que permiten determinar el comportamiento radiométrico de la vegetación y que se relacionan estrechamente con la ET. Bajo este contexto, nuestra hipótesis de trabajo afirma que es posible elaborar un balance anual de agua en cultivos utilizando datos de serie de tiempo armonizados de Landsat-8 (L8) y Sentinel-2 (S2). A través de la integración y armonización de los mapas de NDVI calculados para ambos sensores, obteniendo como resultado una serie temporal multi-modal de NDVI utilizada para la estimación de ET durante la temporada agrícola (diciembre 2017 a marzo 2018). Los resultados obtenidos permiten evidenciar adecuadamente la respuesta que tienen los cultivos a los problemas de déficit y exceso de riego asociados al manejo del agua, caracterizado a través de la demanda de agua estimada obtenida desde la implementación de la metodología y de los requerimientos potenciales de los cultivos existentes en el sitio de estudio.
Efficient water management in agriculture requires a precise estimate of evapotranspiration (ET). Although local measurements can be used to estimate surface energy balance components, these values cannot be extrapolated to large areas due to the heterogeneity and complexity of the conditions in which agriculture develops. A spatially analysis distributed using satellite images represents an efficient and economical alternative to provide estimates of ET in large areas, through the information provided in both the optical and thermal range of the electromagnetic spectrum; however, most current sensors do not provide this information, but they do include a set of spectral bands that allow the radiometric behavior of the vegetation to be determined and which are closely related to the ET. In this context, our working hypothesis states that it is possible to perform an annual water balance in crops using harmonized time serie data from Landsat-8 (L8) and Sentinel-2 (S2). Through the integration and harmonization of the NDVI maps calculated for both S2 sensors, obtaining as a result a multi-modal time serie of NDVI used for ET estimation during the agricultural season (December 2017 to March 2018). The results obtained allow to adequately demonstrate the response of crops to the problems of deficit and excess irrigation associated with water management, characterized by the estimated water demand obtained from the implementation of the methodology and the potential requirements of the existing crops in the study site.
Efficient water management in agriculture requires a precise estimate of evapotranspiration (ET). Although local measurements can be used to estimate surface energy balance components, these values cannot be extrapolated to large areas due to the heterogeneity and complexity of the conditions in which agriculture develops. A spatially analysis distributed using satellite images represents an efficient and economical alternative to provide estimates of ET in large areas, through the information provided in both the optical and thermal range of the electromagnetic spectrum; however, most current sensors do not provide this information, but they do include a set of spectral bands that allow the radiometric behavior of the vegetation to be determined and which are closely related to the ET. In this context, our working hypothesis states that it is possible to perform an annual water balance in crops using harmonized time serie data from Landsat-8 (L8) and Sentinel-2 (S2). Through the integration and harmonization of the NDVI maps calculated for both S2 sensors, obtaining as a result a multi-modal time serie of NDVI used for ET estimation during the agricultural season (December 2017 to March 2018). The results obtained allow to adequately demonstrate the response of crops to the problems of deficit and excess irrigation associated with water management, characterized by the estimated water demand obtained from the implementation of the methodology and the potential requirements of the existing crops in the study site.
Description
Tesis presentada para optar al grado de Magíster en Ingeniería Agrícola con mención en Recursos Hídricos
Keywords
Hambre Cero