{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T02:09:20Z","timestamp":1773972560442,"version":"3.50.1"},"reference-count":71,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,10,30]],"date-time":"2021-10-30T00:00:00Z","timestamp":1635552000000},"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>Many challenges prevail in cropland mapping over large areas, including dealing with massive volumes of datasets and computing capabilities. Accordingly, new opportunities have been opened at a breakneck pace with the launch of new satellites, the continuous improvements in data retrieval technology, and the upsurge of cloud computing solutions such as Google Earth Engine (GEE). Therefore, the present work is an attempt to automate the extraction of multi-year (2016\u20132020) cropland phenological metrics on GEE and use them as inputs with environmental covariates in a trained machine-learning model to generate high-resolution cropland and crop field-probabilities maps in Morocco. The comparison of our phenological retrievals against the MODIS phenology product shows very close agreement, implying that the suggested approach accurately captures crop phenology dynamics, which allows better cropland classification. The entire country is mapped using a large volume of reference samples collected and labelled with a visual interpretation of high-resolution imagery on Collect-Earth-Online, an online platform for systematically collecting geospatial data. The cropland classification product for the nominal year 2019\u20132020 showed an overall accuracy of 97.86% with a Kappa of 0.95. When compared to Morocco\u2019s utilized agricultural land (SAU) areas, the cropland probabilities maps demonstrated the ability to accurately estimate sub-national SAU areas with an R-value of 0.9. Furthermore, analyzing cropland dynamics reveals a dramatic decrease in the 2019\u20132020 season by 2% since the 2018\u20132019 season and by 5% between 2016 and 2020, which is partly driven by climate conditions, but even more so by the novel coronavirus disease 2019 (COVID-19) that impacted the planting and managing of crops due to government measures taken at the national level, like complete lockdown. Such a result proves how much these methods and associated maps are critical for scientific studies and decision-making related to food security and agriculture.<\/jats:p>","DOI":"10.3390\/rs13214378","type":"journal-article","created":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T22:24:22Z","timestamp":1635805462000},"page":"4378","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":41,"title":["National-Scale Cropland Mapping Based on Phenological Metrics, Environmental Covariates, and Machine Learning on Google Earth Engine"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5210-9732","authenticated-orcid":false,"given":"Abdelaziz","family":"Htitiou","sequence":"first","affiliation":[{"name":"Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Beni Mellal 23023, Morocco"},{"name":"Department of Environment and Natural Resources, National Institute of Agronomic Research, Rabat 10090, Morocco"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4033-9717","authenticated-orcid":false,"given":"Abdelghani","family":"Boudhar","sequence":"additional","affiliation":[{"name":"Department of Environment and Natural Resources, National Institute of Agronomic Research, Rabat 10090, Morocco"},{"name":"Center for Remote Sensing Applications, Mohammed VI Polytechnic University, Ben Guerir 43150, Morocco"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0270-1690","authenticated-orcid":false,"given":"Abdelghani","family":"Chehbouni","sequence":"additional","affiliation":[{"name":"Center for Remote Sensing Applications, Mohammed VI Polytechnic University, Ben Guerir 43150, Morocco"},{"name":"Centre d\u2019Etudes Spatiales de la Biosph\u00e8re (CESBIO), Institut de Recherche pour le D\u00e9veloppement (IRD), UMR CNES-CNRS-INRAE-UPS, Universit\u00e9 de Toulouse, CEDEX 9, 31401 Toulouse, France"}]},{"given":"Tarik","family":"Benabdelouahab","sequence":"additional","affiliation":[{"name":"Department of Environment and Natural Resources, National Institute of Agronomic Research, Rabat 10090, Morocco"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/B978-0-12-800131-8.00003-0","article-title":"Agronomic and Physiological Responses to High Temperature, Drought, and Elevated CO2 Interactions in Cereals","volume":"127","author":"Kadam","year":"2014","journal-title":"Adv. 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