{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T09:35:28Z","timestamp":1766050528137,"version":"build-2065373602"},"reference-count":61,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2024,1,26]],"date-time":"2024-01-26T00:00:00Z","timestamp":1706227200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"ERANETMED CHAAMS project","award":["ERANET3-062"],"award-info":[{"award-number":["ERANET3-062"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This article aims to estimate the water footprint (WF) of cereals\u2014specifically, wheat and barley\u2014in the Kairouan plain, located in central Tunisia. To achieve this objective, two components must be determined: actual evapotranspiration (ETa) and crop yield. The study covers three growing seasons from 2010 to 2013. The ETa estimation employed the S-SEBI (simplified surface energy balance index) model, utilizing Landsat 7 and 8 optical and thermal infrared spectral bands. For yield estimation, an empirical model based on the normalized difference vegetation index (NDVI) was applied. Results indicate the effectiveness of the S-SEBI model in estimating ETa, demonstrating an R2 of 0.82 and an RMSE of 0.45 mm\/day. Concurrently, yields mapped over the area range between 6 and 77 qx\/ha. Globally, cereals\u2019 average WF varied from 1.08 m3\/kg to 1.22 m3\/kg over the three study years, with the majority below 1 m3\/kg. Notably in dry years, the importance of the blue WF is emphasized compared to years with average rainfall (WFb-2013 = 1.04 m3\/kg, WFb-2012 = 0.61 m3\/kg, WFb-2011 = 0.41 m3\/kg). Moreover, based on an in-depth agronomic analysis combining yields and WF, four classes were defined, ranging from the most water efficient to the least, revealing that over 30% of cultivated areas during the study years (approximately 40% in 2011 and 2012 and 29% in 2013) exhibited low water efficiency, characterized by low yields and high WF. A unique index, the WFI, is proposed to assess the spatial variability of green and blue water. Spatial analysis using the WFI highlighted that in 2012, 40% of cereal plots with low yields but high water consumption were irrigated (81% blue water compared to 6% in 2011).<\/jats:p>","DOI":"10.3390\/rs16030491","type":"journal-article","created":{"date-parts":[[2024,1,29]],"date-time":"2024-01-29T12:25:01Z","timestamp":1706531101000},"page":"491","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Water Footprint of Cereals by Remote Sensing in Kairouan Plain (Tunisia)"],"prefix":"10.3390","volume":"16","author":[{"given":"Vetiya","family":"Dellaly","sequence":"first","affiliation":[{"name":"LR99ES19 Laboratory of Modelling in Hydraulics and Environment (LMHE), National Engineering School of Tunis (ENIT), University of Tunis El Manar, BP 37, Tunis 1002, Tunisia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5032-7325","authenticated-orcid":false,"given":"Aicha","family":"Chahbi Bellakanji","sequence":"additional","affiliation":[{"name":"LR17AGR01 InteGRatEd Management of Natural Resources: Remote Sensing, Spatial Analysis and Modeling (GREEN-TEAM), National Agronomic Institute of Tunisia, Carthage University, 43 Avenue Charles Nicolle, Tunis 1082, Tunisia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2245-5252","authenticated-orcid":false,"given":"Hedia","family":"Chakroun","sequence":"additional","affiliation":[{"name":"LR99ES19 Laboratory of Modelling in Hydraulics and Environment (LMHE), National Engineering School of Tunis (ENIT), University of Tunis El Manar, BP 37, Tunis 1002, Tunisia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0103-2816","authenticated-orcid":false,"given":"Sameh","family":"Saadi","sequence":"additional","affiliation":[{"name":"Dynafor UMR 1201, Engineering School of Purpan, University of Toulouse, 75 voie du TOEC, BP57611, 31076 Toulouse, Cedex 3, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3905-7560","authenticated-orcid":false,"given":"Gilles","family":"Boulet","sequence":"additional","affiliation":[{"name":"CNES\/CNRS\/INRAE\/IRD\/UT3-Paul Sabatier, CESBIO, University of Toulouse, 18 Avenue Edouard Belin, 31401 Toulouse, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6141-8222","authenticated-orcid":false,"given":"Mehrez","family":"Zribi","sequence":"additional","affiliation":[{"name":"CNES\/CNRS\/INRAE\/IRD\/UT3-Paul Sabatier, CESBIO, University of Toulouse, 18 Avenue Edouard Belin, 31401 Toulouse, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0578-1630","authenticated-orcid":false,"given":"Zohra","family":"Lili Chabaane","sequence":"additional","affiliation":[{"name":"LR17AGR01 InteGRatEd Management of Natural Resources: Remote Sensing, Spatial Analysis and Modeling (GREEN-TEAM), National Agronomic Institute of Tunisia, Carthage University, 43 Avenue Charles Nicolle, Tunis 1082, Tunisia"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s11269-006-9037-z","article-title":"Shift in Thinking to Address the 21st Century Hunger Gap","volume":"21","author":"Falkenmark","year":"2007","journal-title":"Water Resour. Manag."},{"key":"ref_2","first-page":"763","article-title":"The Green, Blue and Grey Water Footprint of Crops and Derived Crop Products","volume":"8","author":"Mekonnen","year":"2011","journal-title":"Hydrol. Earth Syst. Sci. Discuss."},{"key":"ref_3","unstructured":"Hoekstra, A.Y., Chapagain, A.K., and Van Oel, P.R. (2019). Progress in Water Footprint Assessment, MDPI AG."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"4581","DOI":"10.5194\/hess-19-4581-2015","article-title":"Review and Classification of Indicators of Green Water","volume":"19","author":"Schyns","year":"2015","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_5","unstructured":"Hoekstra, A.Y. (2003). Proceedings of the International Expert Meeting on Virtual Water Trade, Delft, The Netherlands, 12\u201313 December 2002, UNESCO-IHE. Value of Water Research Report Series No. 12."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Besbes, M., Chahed, J., and Hamdane, A. (2019). National Water Security: Case Study of an Arid Country: Tunisia, Springer.","DOI":"10.1007\/978-3-319-75499-4"},{"key":"ref_7","unstructured":"Besbes, M., Chahed, J., and Hamdane, A. (2014). S\u00e9curit\u00e9 Hydrique de la Tunisie, L\u2019Harmattan."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/j.scitotenv.2017.09.032","article-title":"Virtual Water Trade Patterns in Relation to Environmental and Socioeconomic Factors: A Case Study for Tunisia","volume":"613\u2013614","author":"Chouchane","year":"2018","journal-title":"Sci. Total Environ."},{"key":"ref_9","unstructured":"Chapagain, A.K., and Hoekstra, A.Y. (2004). Water Footprints of Nations, UNESCOIHE. Value of Water Research Report Series No. 16."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Aldaya, M.M., Chapagain, A.K., Hoekstra, A.Y., and Mekonnen, M.M. (2011). The Water Footprint Assessment Manual, Routledge. Setting the Global Standard.","DOI":"10.4324\/9781849775526"},{"key":"ref_11","unstructured":"FAO (2018). \u00c9valuation de L\u2019approvisionnement Alimentaire dans un Contexte de P\u00e9nurie d\u2019eau dans le R\u00e9gion NENA, FAO."},{"key":"ref_12","unstructured":"Lasram, A., M\u2019Nassri, S., Nciri, R., Gharbi, W., Masmoudi, M.M., and Mechlia, N.B. (2023, November 28). Combining Remote Sensing Data and AquaCrop for Assessement of Yield and Water Productivity of Durum Wheat in Semi-Arid Conditions in Tunisia. Available online: https:\/\/swdcc2022.com\/wp-content\/uploads\/2022\/08\/Session-FAO."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1628","DOI":"10.1016\/j.agwat.2010.05.017","article-title":"WATPRO: A Remote Sensing Based Model for Mapping Water Productivity of Wheat","volume":"97","author":"Zwart","year":"2010","journal-title":"Agric. Water Manag."},{"key":"ref_14","unstructured":"Allen, R.G., Pereira, L.S., Raes, D., and Smith, M. (1998). Crop Evapotranspiration-Guidelines for Computing Crop Water Requirements-FAO Irrigation and Drainage Paper 56, Fao. D05109."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Allen, R.G., Pereira, L.S., Smith, M., Raes, D., and Wright, J.L. (2005). FAO-56 Dual Crop Coefficient Method for Estimating Evaporation from Soil and Application Extensions, Fao.","DOI":"10.1061\/(ASCE)0733-9437(2005)131:1(2)"},{"key":"ref_16","first-page":"205","article-title":"Evaporation and environment","volume":"19","author":"Monteith","year":"1965","journal-title":"Symp. Soc. Exp. Biol."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Calera, A., Campos, I., Osann, A., D\u2019urso, G., and Menenti, M. (2017). Remote Sensing for Crop Water Management: From ET Modelling to Services for the End Users. Sensors, 17.","DOI":"10.3390\/s17051104"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/S1464-1909(99)00128-8","article-title":"S-SEBI: A simple remote sensing algorithm to estimate the surface energy balance","volume":"25","author":"Roerink","year":"2000","journal-title":"Phys. Chem. Earth Part B Hydrol. Oceans Atmos."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3801","DOI":"10.3390\/s90503801","article-title":"A review of current methodologies for regional evapotranspiration estimation from remotely sensed data","volume":"9","author":"Li","year":"2009","journal-title":"Sensors"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1326","DOI":"10.1016\/j.rse.2011.01.013","article-title":"Comparison of two temperature differencing methods to estimate daily evapotranspiration over a Mediterranean vineyard watershed from ASTER data","volume":"115","author":"Galleguillos","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Acharya, B., and Sharma, V. (2021). Comparison of satellite driven surface energy balance models in estimating crop evapotranspiration in semi-arid to arid inter-mountain region. Remote Sens., 13.","DOI":"10.3390\/rs13091822"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.agsy.2007.07.009","article-title":"Integrated assessment of agricultural systems\u2014A component-based framework for the European Union (SEAMLESS)","volume":"96","author":"Ewert","year":"2008","journal-title":"Agric. Syst."},{"key":"ref_23","first-page":"438","article-title":"Empirical Regression Models Using NDVI, Rainfall and Temperature Data for the Early Prediction of Wheat Grain Yields in Morocco","volume":"10","author":"Balaghi","year":"2008","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1312","DOI":"10.1016\/j.rse.2010.01.010","article-title":"A generalized regression-based model for forecasting winter wheat yields in Kansas and Ukraine using MODIS Data","volume":"114","author":"Vermote","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.rse.2015.02.014","article-title":"Improving the Timeliness of Winter Wheat Production Forecast in the United States of America, Ukraine and China Using MODIS Data and NCAR Growing Degree Day Information","volume":"161","author":"Franch","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1004","DOI":"10.1080\/01431161.2013.875629","article-title":"Estimation of the dynamics and yields of cereals in a semi-arid area using remote sensing and the SAFY growth model","volume":"35","author":"Chahbi","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_27","unstructured":"Nougaret, G., Jenhaoui, Z., and Leduc, C. (2023, November 28). Ressources en Eau Dans Le Kairouanais: \u00c9volutions des Disponibilit\u00e9s et des Usages DEPUIS 2000 Ans. Available online: http:\/\/www5.funceme.br\/arid\/wp-content\/uploads\/2020\/05\/guide_terrain_Merguellil_04-10-2019-GN-CL.pdf."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"345","DOI":"10.5194\/hess-15-345-2011","article-title":"Soil Surface Moisture Estimation over a Semi-Arid Region Using ENVISAT ASAR Radar Data for Soil Evaporation Evaluation","volume":"15","author":"Zribi","year":"2011","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_29","unstructured":"Luca, C., Michele, M., and Silvia, M. (2013). Investigating the Relationship between Land Cover and Vulnerability T0 Climate Change in dar es Salaam, Sapienza University. Working Paper April 2013."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1016\/0034-4257(88)90019-3","article-title":"An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data","volume":"24","author":"Chavez","year":"1988","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/978-3-540-74831-1_5","article-title":"The Geospatial Data Abstraction Library","volume":"2","author":"Warmerdam","year":"2008","journal-title":"Open Source Approaches Spat. Data Handl."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1016\/j.rse.2003.11.005","article-title":"Estimation of land surface temperature\u2014Vegetation abundance relationship for urban heat island studies","volume":"89","author":"Weng","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"13005","DOI":"10.3390\/rs71013005","article-title":"Monitoring Irrigation Consumption Using High Resolution NDVI Image Time Series: Calibration and Validation in the Kairouan Plain (Tunisia)","volume":"7","author":"Saadi","year":"2015","journal-title":"Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1080\/01431169408954055","article-title":"SMAC: A simplified method for the atmospheric correction of satellite measurements in the solar spectrum","volume":"15","author":"Rahman","year":"1994","journal-title":"Int. J. Remote. Sens."},{"key":"ref_35","unstructured":"Guyot, G., and Phulpin, T. (1997). Physical Measurements and Signatures in Remote Sensing, Courchevel."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"6762","DOI":"10.1364\/AO.45.006762","article-title":"Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data. Part I: Path radiance","volume":"45","author":"Kotchenova","year":"2006","journal-title":"Appl. Opt."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1080\/01431169008955048","article-title":"Description of a computer code to simulate the satellite signal in the solar spectrum: The 5S code","volume":"11","author":"Deroo","year":"1990","journal-title":"Int. J. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Caloz, R., and Collet, C. (2001). Pr\u00e9cis de T\u00e9l\u00e9d\u00e9tection, Volume 3 Traitements Num\u00e9riques D\u2019images de T\u00e9l\u00e9d\u00e9tection, Presses de l\u2019Universit\u00e9 du Qu\u00e9bec\/AUPELF.","DOI":"10.2307\/j.ctv5j018b"},{"key":"ref_39","first-page":"294","article-title":"Ein Energiehaushalts- und Verdunstungsmodell for Wasser und Stoffhaushaltsuntersuchungen landwirtschaftlich genutzer Einzugsgebiete","volume":"42","author":"Braden","year":"1985","journal-title":"M. Dtsch. Bodenkd. Geselschaft"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/0034-4257(94)90020-5","article-title":"Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index","volume":"49","author":"Moran","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(79)90013-0","article-title":"Red and Photographic Infrared Linear Combinations for Monitoring Vegetation","volume":"150","author":"Tucker","year":"1979","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1016\/0168-1923(95)02265-Y","article-title":"Source Approach for Estimating Soil and Vegetation Energy Fluxes in Observations of Directional Radiometric Surface Temperature","volume":"77","author":"Norman","year":"1995","journal-title":"Agric. For. Meteorol."},{"key":"ref_43","unstructured":"Chemin, Y. (2003). Evapotranspiration of Crops by Remote Sensing Using the Energy Balance Based Algorithms, International Water Management Institute."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0034-4257(94)90090-6","article-title":"Relations between evaporation coefficients and vegetation indices studied by model simulations","volume":"50","author":"Choudhury","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/0034-4257(96)00039-9","article-title":"Mapping land surface emissivity from NDVI: Application to European, African, and South American areas","volume":"57","author":"Valor","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_46","first-page":"161","article-title":"Analyse comparative d\u2019IKONOS, Donn\u00e9es SPOT et ETM+ pour l\u2019estimation de l\u2019indice de surface foliaire des conif\u00e8res et des feuillus temp\u00e9r\u00e9s peuplements forestiers","volume":"102","author":"Soudani","year":"2006","journal-title":"T\u00e9l\u00e9d\u00e9tection L\u2019environnement"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Chakroun, H., Zemni, N., Benhmid, A., Dellaly, V., Slama, F., Bouksila, F., and Berndtsson, R. (2023). Evapotranspiration in Semi-Arid Climate: Remote Sensing vs. Soil Water Simulation. Sensors, 23.","DOI":"10.3390\/s23052823"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/0168-1923(90)90033-3","article-title":"Estimation of the soil heat flux\/net radiation ratio from spectral data","volume":"49","author":"Kustas","year":"1990","journal-title":"Agric. For. Meteorol."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/S0168-1923(00)00214-8","article-title":"A long-term study of soil heat flux under a forest canopy","volume":"106","author":"Lamaud","year":"2001","journal-title":"Agric. For. Meteorol."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/0034-4257(87)90059-9","article-title":"Relationships between vegetation indices, radiation absorption, and net photosynthesis evaluated by a 638 sensitivity analysis","volume":"22","author":"Choudhury","year":"1987","journal-title":"Remote Sens. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1175\/1520-0450(2003)042<0851:DCISHF>2.0.CO;2","article-title":"Diurnal covariation in soil heat flux and net radiation","volume":"42","author":"Santanello","year":"2003","journal-title":"J. Appl. Meteorol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.rse.2007.02.017","article-title":"Application of a Simple Algorithm to Estimate Daily Evapotranspiration from NOAA-AVHRR Images for the Iberian Peninsula","volume":"110","author":"Sobrino","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_53","unstructured":"Abdallah, A. (2015). Eau Virtuelle et S\u00e9curit\u00e9 Alimentaire en Tunisie: Du Constat \u00e0 l\u2019Appui au D\u00e9vellopement (EVSAT-CAD), Projet de Recherche Developpement."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1080\/02508060802543105","article-title":"A comprehensive water balance of Tunisia: Blue water, green water and virtual water","volume":"33","author":"Chahed","year":"2008","journal-title":"Water Int."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Ghorbanpour, A.K., Kisekka, I., Afshar, A., Hessels, T., Taraghi, M., Hessari, B., Touri-an, M.J., and Duan, Z. (2022). Crop Water Productivity Mapping and Benchmarking Using Re-mote Sensing and Google Earth Engine Cloud Computing. Remote Sens., 14.","DOI":"10.3390\/rs14194934"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1016\/j.scitotenv.2016.09.032","article-title":"The Water Productivity Score (WPS) at Global and Regional Level: Methodology and First Results from Remote Sensing Measurements of Wheat, Rice and Maize","volume":"575","author":"Bastiaanssen","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Blatchford, M.L., Karimi, P., Bastiaanssen, W., and Nouri, H. (2018). From Global Goals to Local Gains\u2014A Framework for Crop Water Productivity. ISPRS Int. J. Geo-Inf., 7.","DOI":"10.3390\/ijgi7110414"},{"key":"ref_58","unstructured":"Chahed, Y., and Hassan, F.A. (2012). 2012 Grain and Feed Update Tunisia, Global Agricultural Information Network, TS1204."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Khlif, M., Escorihuela, M.J., Bellakanji, A.C., Paolini, G., Kassouk, Z., and Chabaane, Z.L. (2023). Multi-Year Cereal Crop Classification Model Using Sentinel 2 and 3 Landsat 7\u20138 Data. Agriculture, 13.","DOI":"10.3390\/agriculture13081633"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Bousbih, S., Zribi, M., Lili-Chabaane, Z., Baghdadi, N., El Hajj, M., Gao, Q., and Mougenot, B. (2017). Potential of Sentinel-1 Radar Data for the Assessment of Soil and Cereal Cover Parameters. Sensors, 17.","DOI":"10.3390\/s17112617"},{"key":"ref_61","unstructured":"Chouchane, H. (2019). Economic Allocation of Water to Crops in International Context: A National and Global Perspective. [Ph.D. Thesis, University of Twente]."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/3\/491\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T13:50:12Z","timestamp":1760104212000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/3\/491"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,26]]},"references-count":61,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2024,2]]}},"alternative-id":["rs16030491"],"URL":"https:\/\/doi.org\/10.3390\/rs16030491","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2024,1,26]]}}}