{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T19:04:25Z","timestamp":1773947065447,"version":"3.50.1"},"reference-count":64,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,22]],"date-time":"2022-12-22T00:00:00Z","timestamp":1671667200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002347","name":"the Federal Ministry for Education and Research","doi-asserted-by":"publisher","award":["01LZ1807D"],"award-info":[{"award-number":["01LZ1807D"]}],"id":[{"id":"10.13039\/501100002347","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Olive orchard intensification has transformed an originally drought-resilient tree crop into a competing water user in semi-arid regions. In our study, we used remote sensing to evaluate whether intensive olive plantations have increased between 2010 and 2020, contributing to the current risk of aquifer depletion in the Sa\u00efss plain in Morocco. We developed an unsupervised approach based on the principles of hierarchical clustering and used for each year of analysis two images (5 m pixel size) from the PlanetLabs archive. We first calculated area-based accuracy metrics for 2020 with reference data, reaching a user\u2019s accuracy of 0.95 and a producer\u2019s accuracy of 0.89. For 2010, we verified results among different plot size ranges using available 2010 Google Earth Imagery, reaching high accuracy among the 50 largest plots (correct classification rate, CCR, of 0.94 in 2010 and 0.92 in 2020) and lower accuracies among smaller plot sizes. This study allowed us to map super-intensive olive plantations, thereby addressing an important factor in the groundwater economy of many semi-arid regions. Besides the expected increase in plantation size and the emergence of new plantations, our study revealed that some plantations were also given up, despite the political framework encouraging the opposite.<\/jats:p>","DOI":"10.3390\/rs15010050","type":"journal-article","created":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T03:02:15Z","timestamp":1671764535000},"page":"50","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Spatio-Temporal Assessment of Olive Orchard Intensification in the Sa\u00efss Plain (Morocco) Using k-Means and High-Resolution Satellite Data"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1633-0410","authenticated-orcid":false,"given":"Rebecca","family":"Navarro","sequence":"first","affiliation":[{"name":"Bonn International Centre for Conflict Studies, 53121 Bonn, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9795-3187","authenticated-orcid":false,"given":"Lars","family":"Wirkus","sequence":"additional","affiliation":[{"name":"Bonn International Centre for Conflict Studies, 53121 Bonn, Germany"}]},{"given":"Olena","family":"Dubovyk","sequence":"additional","affiliation":[{"name":"Department of Geography, University of Bergen, 5020 Bergen, Norway"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"293","DOI":"10.5194\/hess-12-293-2008","article-title":"The olive tree: A paradigm for drought tolerance in Mediterranean climates","volume":"12","author":"Sofo","year":"2008","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_2","unstructured":"FAOSTAT (2021, September 10). FAOSTAT, 2021. Available online: http:\/\/www.fao.org\/faostat\/en\/#data."},{"key":"ref_3","first-page":"11","article-title":"Evolution and sustainability of the olive production systems","volume":"106","author":"Trapero","year":"2013","journal-title":"Options Mediterr."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Brito, C., Dinis, L.-T., Moutinho-Pereira, J., and Correia, C.M. (2019). Drought Stress Effects and Olive Tree Acclimation under a Changing Climate. Plants, 8.","DOI":"10.3390\/plants8070232"},{"key":"ref_5","unstructured":"Zribi, M., Brocca, L., Tramblay, Y., and Molle, F. (2020). Chapter 2\u2014Evapotranspiration in the Mediterranean region. Water Resources in the Mediterranean Region, Elsevier."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Rodr\u00edguez Sousa, A.A., Barandica, J.M., and Rescia, A. (2019). Ecological and Economic Sustainability in Olive Groves with Different Irrigation Management and Levels of Erosion: A Case Study. Sustainability, 11.","DOI":"10.3390\/su11174681"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez-Valderrama, J., Guirado, E., and Maestre, F. (2020). Unraveling Misunderstandings about Desertification: The Paradoxical Case of the Tabernas-Sorbas Basin in Southeast Spain. Land, 9.","DOI":"10.3390\/land9080269"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Molle, F., Sanchis-Ibor, C., and Avell\u00e0-Reus, L. (2019). Morocco. Irrigation in the Mediterranean, Springer International Publishing.","DOI":"10.1007\/978-3-030-03698-0"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"e1395","DOI":"10.1002\/wat2.1395","article-title":"Why is state-centered groundwater governance largely ineffective? A review","volume":"7","author":"Molle","year":"2020","journal-title":"WIREs Water"},{"key":"ref_10","unstructured":"ADA (2021, November 25). Foundations, Available online: https:\/\/www.ada.gov.ma\/en\/foundations."},{"key":"ref_11","unstructured":"ADA (2021, November 25). Approches de Mise en \u0152uvre des Deux Piliers du PMV, Available online: https:\/\/www.ada.gov.ma\/fr\/approches-de-mise-en-oeuvre-des-deux-piliers-du-pmv."},{"key":"ref_12","unstructured":"ADA (2021, November 25). Main Achievements of the Green Morocco Plan, Available online: https:\/\/www.ada.gov.ma\/en\/main-achievements-green-morocco-plan."},{"key":"ref_13","unstructured":"(2021, November 25). Fellah Trade. Les Chiffres Cl\u00e9s de la Fili\u00e8re Ol\u00e9iculture\u2014Fellah Trade, 2021. Available online: https:\/\/www.fellah-trade.com\/fr\/filiere-vegetale\/chiffres-cles-oleiculture?filiere=filiere_vegetale."},{"key":"ref_14","unstructured":"European Bank for Reconstruction, and Development EBRD (2022, October 21). Saiss and Garet Water Conservation Project, 2020. Available online: https:\/\/www.ebrd.com\/what-we-do\/project-information\/board-documents\/1395289064192\/Saiss_and_Garet_Water_Conservation_Project_(SSBR).pdf?blobnocache=true."},{"key":"ref_15","unstructured":"Agence du Bassin Hydraulique du Sebou ABHS (2021, December 04). Syst\u00e8me Aquif\u00e8re du Saiss, 2016. ABHS. Available online: http:\/\/www.abhsebou.ma\/presentation-du-bassin\/eaux-souterraines\/systeme-aquifere-du-saiss\/."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Lin, C., Jin, Z., Mulla, D., Ghosh, R., Guan, K., Kumar, V., and Cai, Y. (2021). Toward Large-Scale Mapping of Tree Crops with High-Resolution Satellite Imagery and Deep Learning Algorithms: A Case Study of Olive Orchards in Morocco. Remote Sens., 13.","DOI":"10.3390\/rs13091740"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Brinkhoff, J., Vardanega, J., and Robson, A.J. (2019). Land Cover Classification of Nine Perennial Crops Using Sentinel-1 and -2 Data. Remote Sens., 12.","DOI":"10.3390\/rs12010096"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"77816","DOI":"10.1109\/ACCESS.2018.2884199","article-title":"Remote Sensing: An Automated Methodology for Olive Tree Detection and Counting in Satellite Images","volume":"6","author":"Khan","year":"2018","journal-title":"IEEE Access"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Waleed, M., Um, T.-W., Khan, A., and Khan, U. (2020). Automatic Detection System of Olive Trees Using Improved K-Means Algorithm. Remote Sens., 12.","DOI":"10.3390\/rs12050760"},{"key":"ref_20","unstructured":"(2021, December 22). Apollo Mapping Price List. Available online: https:\/\/apollomapping.com\/image_downloads\/Apollo_Mapping_Imagery_Price_List.pdf."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"4213","DOI":"10.3390\/rs70404213","article-title":"High-Resolution Airborne UAV Imagery to Assess Olive Tree Crown Parameters Using 3D Photo Reconstruction: Application in Breeding Trials","volume":"7","year":"2015","journal-title":"Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1426","DOI":"10.1080\/10106049.2020.1768593","article-title":"A comparative analysis of different phenological information retrieved from Sentinel-2 time series images to improve crop classification: A machine learning approach","volume":"37","author":"Htitiou","year":"2020","journal-title":"Geocarto Int."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.quaint.2013.07.043","article-title":"Object-based identification of vegetation cover decline in irrigated agro-ecosystems in Uzbekistan","volume":"311","author":"Dubovyk","year":"2013","journal-title":"Quat. Int."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1126\/science.192.4237.376","article-title":"Leaf Pubescence: Effects on Absorptance and Photosynthesis in a Desert Shrub","volume":"192","author":"Ehleringer","year":"1976","journal-title":"Science"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Cavender-Bares, J., Gamon, J.A., and Townsend, P.A. (2020). How the Optical Properties of Leaves Modify the Absorption and Scattering of Energy and Enhance Leaf Functionality. Remote Sensing of Plant Biodiversity, Springer International Publishing.","DOI":"10.1007\/978-3-030-33157-3"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11676-020-01155-1","article-title":"A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing","volume":"32","author":"Huang","year":"2021","journal-title":"J. For. Res."},{"key":"ref_27","first-page":"309","article-title":"Monitoring vegetation systems in the Great Plains with ERTS","volume":"351","author":"Rouse","year":"1974","journal-title":"NASA Spec. Publ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/0034-4257(85)90099-9","article-title":"Influence of rock-soil spectral variation on the assessment of green biomass","volume":"17","author":"Elvidge","year":"1985","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/S0034-4257(97)00104-1","article-title":"On the relation between NDVI, fractional vegetation cover, and leaf area index","volume":"62","author":"Carlson","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/S0034-4257(99)00057-7","article-title":"Relationships between Leaf Area Index and Landsat TM Spectral Vegetation Indices across Three Temperate Zone Sites","volume":"70","author":"Turner","year":"1999","journal-title":"Remote Sens. Environ."},{"key":"ref_31","first-page":"1","article-title":"Forest leaf area index in an Alpine valley from medium resolution satellite imagery and in situ data","volume":"6","author":"Stroppiana","year":"2012","journal-title":"J. Appl. Remote Sens."},{"key":"ref_32","unstructured":"Qi, J., Kerr, Y., and Chehbouni, A. (1994, January 17\u201324). External factor consideration in vegetation index development. Proceedings of the 6th International Symposium on Physical Measurements and Signatures in Remote Sensing, Val d\u2019Isere, France."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.rse.2015.10.029","article-title":"Assessing fruit-tree crop classification from Landsat-8 time series for the Maipo Valley, Chile","volume":"171","author":"Brenning","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.isprsjprs.2017.03.019","article-title":"Using spectrotemporal indices to improve the fruit-tree crop classification accuracy","volume":"128","author":"Liao","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Richards, J.A. (2013). Supervised Classification Techniques. Remote Sensing Digital Image Analysis, Springer.","DOI":"10.1007\/978-3-642-30062-2"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/j.rse.2018.12.026","article-title":"Crop type mapping without field-level labels: Random forest transfer and unsupervised clustering techniques","volume":"222","author":"Wang","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Richards, J.A. (2013). Clustering and Unsupervised Classification. Remote Sensing Digital Image Analysis, Springer.","DOI":"10.1007\/978-3-642-30062-2"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Mather, P., and Tso, B. (2016). Classification Methods for Remotely Sensed Data, CRC Press.","DOI":"10.1201\/9781420090741"},{"key":"ref_39","unstructured":"Witten, I.H. (2017). Data Mining: Practical Machine Learning Tools and Techniques, Elsevier."},{"key":"ref_40","first-page":"768","article-title":"Cluster analysis of multivariate data: Efficiency versus interpretability of classifications","volume":"21","author":"Forgy","year":"1965","journal-title":"Biometrics"},{"key":"ref_41","unstructured":"Macqueen, J. (1967). Some Methods for Classification and Analysis of Multivariate Observations. Multivariate Observations, John Wiley & Sons."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Gul\u00e1csi, A., and Kov\u00e1cs, F. (2020). Sentinel-1-Imagery-Based High-Resolution Water Cover Detection on Wetlands, Aided by Google Earth Engine. Remote Sens., 12.","DOI":"10.3390\/rs12101614"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"964","DOI":"10.3390\/rs6020964","article-title":"Comparison of Classification Algorithms and Training Sample Sizes in Urban Land Classification with Landsat Thematic Mapper Imagery","volume":"6","author":"Li","year":"2014","journal-title":"Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1016\/j.landusepol.2015.01.035","article-title":"Mapping land use competition in the rural\u2013urban fringe and future perspectives on land policies: A case study of Mekn\u00e8s (Morocco)","volume":"47","author":"Debolini","year":"2015","journal-title":"Land Use Policy"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"150066","DOI":"10.1038\/sdata.2015.66","article-title":"The climate hazards infrared precipitation with stations\u2014A new environmental record for monitoring extremes","volume":"2","author":"Funk","year":"2015","journal-title":"Sci. Data"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.jafrearsci.2016.04.001","article-title":"Structural pattern of the Sa\u00efss basin and Tabular Middle Atlas in northern Morocco: Hydrological implications","volume":"119","author":"Dauteuil","year":"2016","journal-title":"J. Afr. Earth Sci."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1684\/agr.2014.0699","article-title":"Subterranean waters, a source of dignity as well as a social resource: The case of farmers on the Sa\u00efss plain of Morocco","volume":"23","author":"Quarouch","year":"2014","journal-title":"Cah. Agric."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"37","DOI":"10.30682\/nm1803d","article-title":"The Difficult Escape from Dualism: The Green Morocco Plan at a Crossroads","volume":"XVII","year":"2018","journal-title":"New Medit."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/j.agwat.2017.06.014","article-title":"Prosper, survive or exit: Contrasted fortunes of farmers in the groundwater economy in the Saiss plain (Morocco)","volume":"191","author":"Ameur","year":"2017","journal-title":"Agric. Water Manag."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Behnassi, M., Shahid, S.A., and Mintz-Habib, N. (2014). Agroforestry Systems in Morocco: The Case of Olive Tree and Annual Crops Association in Sa\u00efs Region. Science, Policy and Politics of Modern Agricultural System, Springer.","DOI":"10.1007\/978-94-007-7957-0"},{"key":"ref_51","unstructured":"(2021, August 19). Fellah Trade. Les Chiffres Cl\u00e9s de la Fili\u00e8re Rosac\u00e9es Fruiti\u00e8res\u2014Fellah Trade, 2021. Available online: https:\/\/www.fellah-trade.com\/fr\/filiere-vegetale\/chiffres-cles-rosacees-fruitieres?filiere=filiere_vegetale."},{"key":"ref_52","unstructured":"OCHA (2021, December 03). Morocco\u2014Subnational Administrative Boundaries\u2014Humanitarian Data Exchange, 2021. Available online: https:\/\/data.humdata.org\/dataset\/morocco-administrative-boundaries-populated-places."},{"key":"ref_53","unstructured":"ArcGIS (2021, December 08). ArcGIS\u2014Ressources en Eau du Maroc, 2020. Available online: https:\/\/www.arcgis.com\/home\/webmap\/viewer.html?webmap=af42905a1f74421c9d45a9607d6a2815."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"RG2004","DOI":"10.1029\/2005RG000183","article-title":"The Shuttle Radar Topography Mission","volume":"45","author":"Farr","year":"2007","journal-title":"Rev. Geophys."},{"key":"ref_55","unstructured":"Geofabrik GmbH (2021, December 03). Geofabrik Download Server, 2021. Available online: https:\/\/download.geofabrik.de\/africa\/morocco.html."},{"key":"ref_56","unstructured":"Planet Labs Inc (2022, October 21). Planet Imagery. Product Specifications, 2018. Available online: https:\/\/assets.planet.com\/docs\/Planet_Combined_Imagery_Product_Specs_letter_screen.pdf."},{"key":"ref_57","unstructured":"Planet Labs Inc (2021, November 26). Education and Research Program, 2021. Available online: https:\/\/www.planet.com\/markets\/education-and-research\/."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Qian, Y., Zhou, W., Yu, W., Han, L., Li, W., and Zhao, W. (2020). Integrating Backdating and Transfer Learning in an Object-Based Framework for High Resolution Image Classification and Change Analysis. Remote Sens., 12.","DOI":"10.3390\/rs12244094"},{"key":"ref_59","first-page":"e00971","article-title":"Land use\/cover classification in an arid desert-oasis mosaic landscape of China using remote sensed imagery: Performance assessment of four machine learning algorithms","volume":"22","author":"Ge","year":"2020","journal-title":"Glob. Ecol. Conserv."},{"key":"ref_60","unstructured":"(2021, December 06). Google Developers. Landsat8 Harmonic Modeling\u2014Earth Engine Code Editor, 2021, Available online: https:\/\/code.earthengine.google.com\/07fe82cb6d4ef2f13f85a1b278b98897."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Xiong, J., Thenkabail, P., Tilton, J., Gumma, M., Teluguntla, P., Oliphant, A., Congalton, R., Yadav, K., and Gorelick, N. (2017). Nominal 30-m Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine. Remote Sens., 9.","DOI":"10.3390\/rs9101065"},{"key":"ref_62","unstructured":"(2022, July 08). Sieve. Available online: https:\/\/docs.qgis.org\/2.8\/en\/docs\/user_manual\/processing_algs\/gdalogr\/gdal_analysis\/sieve.html."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.aej.2011.06.001","article-title":"Evaluation of change detection techniques for monitoring land-cover changes: A case study in new Burg El-Arab area","volume":"50","author":"Afify","year":"2011","journal-title":"Alex. Eng. J."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"27442","DOI":"10.1109\/ACCESS.2018.2807380","article-title":"Adaptive Change Detection with Significance Test","volume":"6","author":"Ke","year":"2018","journal-title":"IEEE Access"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/1\/50\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:48:15Z","timestamp":1760147295000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/1\/50"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,22]]},"references-count":64,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,1]]}},"alternative-id":["rs15010050"],"URL":"https:\/\/doi.org\/10.3390\/rs15010050","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,22]]}}}