{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T23:00:53Z","timestamp":1784934053214,"version":"3.55.0"},"reference-count":152,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2017,5,11]],"date-time":"2017-05-11T00:00:00Z","timestamp":1494460800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/s17051104","type":"journal-article","created":{"date-parts":[[2017,5,11]],"date-time":"2017-05-11T11:06:46Z","timestamp":1494500806000},"page":"1104","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":215,"title":["Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4271-2439","authenticated-orcid":false,"given":"Alfonso","family":"Calera","sequence":"first","affiliation":[{"name":"GIS and Remote Sensing Group, Institute for Regional Development, University of Castilla-La Mancha, Campus Universitario SN, 02071 Albacete, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7542-7779","authenticated-orcid":false,"given":"Isidro","family":"Campos","sequence":"additional","affiliation":[{"name":"GIS and Remote Sensing Group, Institute for Regional Development, University of Castilla-La Mancha, Campus Universitario SN, 02071 Albacete, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna","family":"Osann","sequence":"additional","affiliation":[{"name":"GIS and Remote Sensing Group, Institute for Regional Development, University of Castilla-La Mancha, Campus Universitario SN, 02071 Albacete, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0251-4668","authenticated-orcid":false,"given":"Guido","family":"D\u2019Urso","sequence":"additional","affiliation":[{"name":"Department of Agricultural Sciences, University of Naples Federico II, Via Universit\u00e0 100, 80055 Portici (NA), Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Massimo","family":"Menenti","sequence":"additional","affiliation":[{"name":"Department of Geoscience and Remote Sensing, Delft University of Technology, Stevinweg 1, 2628 CN Delft, The Netherlands"},{"name":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Science, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,5,11]]},"reference":[{"key":"ref_1","unstructured":"Animal Production and Health Division (2014). 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