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Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users

The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters...

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Detalles Bibliográficos
Autores principales: Calera, Alfonso, Campos, Isidro, Osann, Anna, D’Urso, Guido, Menenti, Massimo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5470494/
https://www.ncbi.nlm.nih.gov/pubmed/28492515
http://dx.doi.org/10.3390/s17051104
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author Calera, Alfonso
Campos, Isidro
Osann, Anna
D’Urso, Guido
Menenti, Massimo
author_facet Calera, Alfonso
Campos, Isidro
Osann, Anna
D’Urso, Guido
Menenti, Massimo
author_sort Calera, Alfonso
collection PubMed
description The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e., professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies (Geographic Information Systems based on web technologies). This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools, which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools.
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spelling pubmed-54704942017-06-16 Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users Calera, Alfonso Campos, Isidro Osann, Anna D’Urso, Guido Menenti, Massimo Sensors (Basel) Review The experiences gathered during the past 30 years support the operational use of irrigation scheduling based on frequent multi-spectral image data. Currently, the operational use of dense time series of multispectral imagery at high spatial resolution makes monitoring of crop biophysical parameters feasible, capturing crop water use across the growing season, with suitable temporal and spatial resolutions. These achievements, and the availability of accurate forecasting of meteorological data, allow for precise predictions of crop water requirements with unprecedented spatial resolution. This information is greatly appreciated by the end users, i.e., professional farmers or decision-makers, and can be provided in an easy-to-use manner and in near-real-time by using the improvements achieved in web-GIS methodologies (Geographic Information Systems based on web technologies). This paper reviews the most operational and explored methods based on optical remote sensing for the assessment of crop water requirements, identifying strengths and weaknesses and proposing alternatives to advance towards full operational application of this methodology. In addition, we provide a general overview of the tools, which facilitates co-creation and collaboration with stakeholders, paying special attention to these approaches based on web-GIS tools. MDPI 2017-05-11 /pmc/articles/PMC5470494/ /pubmed/28492515 http://dx.doi.org/10.3390/s17051104 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Calera, Alfonso
Campos, Isidro
Osann, Anna
D’Urso, Guido
Menenti, Massimo
Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users
title Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users
title_full Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users
title_fullStr Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users
title_full_unstemmed Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users
title_short Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users
title_sort remote sensing for crop water management: from et modelling to services for the end users
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5470494/
https://www.ncbi.nlm.nih.gov/pubmed/28492515
http://dx.doi.org/10.3390/s17051104
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