{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T12:44:01Z","timestamp":1775738641496,"version":"3.50.1"},"reference-count":205,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2021,10,17]],"date-time":"2021-10-17T00:00:00Z","timestamp":1634428800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Currently, the world is facing high competition and market risks in improving yield, crop illness, and crop water stress. This could potentially be addressed by technological advancements in the form of precision systems, improvements in production, and through ensuring the sustainability of development. In this context, remote-sensing systems are fully equipped to address the complex and technical assessment of crop production, security, and crop water stress in an easy and efficient way. They provide simple and timely solutions for a diverse set of ecological zones. This critical review highlights novel methods for evaluating crop water stress and its correlation with certain measurable parameters, investigated using remote-sensing systems. Through an examination of previous literature, technologies, and data, we review the application of remote-sensing systems in the analysis of crop water stress. Initially, the study presents the relationship of relative water content (RWC) with equivalent water thickness (EWT) and soil moisture crop water stress. Evapotranspiration and sun-induced chlorophyll fluorescence are then analyzed in relation to crop water stress using remote sensing. Finally, the study presents various remote-sensing technologies used to detect crop water stress, including optical sensing systems, thermometric sensing systems, land-surface temperature-sensing systems, multispectral (spaceborne and airborne) sensing systems, hyperspectral sensing systems, and the LiDAR sensing system. The study also presents the future prospects of remote-sensing systems in analyzing crop water stress and how they could be further improved.<\/jats:p>","DOI":"10.3390\/rs13204155","type":"journal-article","created":{"date-parts":[[2021,10,17]],"date-time":"2021-10-17T23:25:15Z","timestamp":1634513115000},"page":"4155","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":132,"title":["A Review of Crop Water Stress Assessment Using Remote Sensing"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7384-9449","authenticated-orcid":false,"given":"Uzair","family":"Ahmad","sequence":"first","affiliation":[{"name":"Department of Agricultural, Environmental and Food Sciences (DAEFS), University of Molise, 86100 Campobasso, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2003-1643","authenticated-orcid":false,"given":"Arturo","family":"Alvino","sequence":"additional","affiliation":[{"name":"Department of Agricultural, Environmental and Food Sciences (DAEFS), University of Molise, 86100 Campobasso, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9062-3142","authenticated-orcid":false,"given":"Stefano","family":"Marino","sequence":"additional","affiliation":[{"name":"Department of Agricultural, Environmental and Food Sciences (DAEFS), University of Molise, 86100 Campobasso, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,17]]},"reference":[{"key":"ref_1","unstructured":"FAO (2017). 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