Print Email Facebook Twitter Remote sensing for crop water management Title Remote sensing for crop water management: From ET modelling to services for the end users Author Calera, Alfonso (Universidad de Castilla-La Mancha) Campos, Isidro (Universidad de Castilla-La Mancha) Osann, Anna (Universidad de Castilla-La Mancha) D’Urso, Guido (Università degli Studi di Napoli Federico II) Menenti, M. (TU Delft Optical and Laser Remote Sensing; Chinese Academy of Sciences) Date 2017-05-11 Abstract 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. Subject Crop coefficientCrop water requirementsEarth observationEvapotranspirationIrrigation water requirementsWeb-GIS To reference this document use: http://resolver.tudelft.nl/uuid:56587660-c335-4cd6-b3fa-1a88970124c2 DOI https://doi.org/10.3390/s17051104 ISSN 1424-8220 Source Sensors, 17 (5) Part of collection Institutional Repository Document type review Rights © 2017 Alfonso Calera, Isidro Campos, Anna Osann, Guido D’Urso, M. Menenti Files PDF sensors_17_01104.pdf 1.52 MB Close viewer /islandora/object/uuid:56587660-c335-4cd6-b3fa-1a88970124c2/datastream/OBJ/view