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Traditional methodologies for estimating irrigation amounts face limitations in terms of overall precision and operational scalability. This study proposes to estimate irrigation amounts from soil moisture (SM) data by adapting the PrISM (Precipitation Inferred from Soil Moisture) methodology. The PrISM assimilates SM into a simple Antecedent Precipitation Index (API) model using a particle filter approach, which allows the creation and estimation of irrigation events. The methodology is applied in a semi-arid region in the Ebro basin, located in the north-east of Spain (Catalonia), from 2016 to 2023. Multi-year drought, which started in 2020, particularly affected the region starting from the spring of 2023, which led to significant reductions in irrigation district water allocations in some of the areas of the region. This study demonstrates that the PrISM approach can correctly identify areas where water restrictions were adopted in 2023, and monitor the water usage with good performances and reliable results. When compared with in situ data for 8 consecutive years, PrISM showed a significant person\u2019s correlation between 0.58 and 0.76 and a cumulative weekly root mean squared error (rmse) between 7 and 11 mm. Additionally, PrISM was applied to three irrigation districts with different levels of modernization, due to the different predominant irrigation systems: flood, sprinkler, and drip. This analysis underlined the strengths and limitations of PrISM depending on the irrigation techniques monitored. PrISM has good performances in areas irrigated by sprinkler and flood systems, while difficulties are present over drip irrigated areas, where the very localized and limited irrigation amounts could not be detected from SM observations.<\/jats:p>","DOI":"10.3390\/rs16071116","type":"journal-article","created":{"date-parts":[[2024,3,22]],"date-time":"2024-03-22T10:03:59Z","timestamp":1711101839000},"page":"1116","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["PrISM at Operational Scale: Monitoring Irrigation District Water Use during Droughts"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4309-281X","authenticated-orcid":false,"given":"Giovanni","family":"Paolini","sequence":"first","affiliation":[{"name":"isardSAT, Carrer del Dr. Trueta, 113, Sant Mart\u00ed, 08005 Barcelona, Catalunya, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7780-7334","authenticated-orcid":false,"given":"Maria Jose","family":"Escorihuela","sequence":"additional","affiliation":[{"name":"isardSAT, Carrer del Dr. Trueta, 113, Sant Mart\u00ed, 08005 Barcelona, Catalunya, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9234-7110","authenticated-orcid":false,"given":"Joaquim","family":"Bellvert","sequence":"additional","affiliation":[{"name":"Efficient Use of Water in Agriculture Program, Institut de Recerca i Tecnologia Agroaliment\u00e0ries (IRTA), Fruitcentre, Parc Cientific i Tecnol\u00f2gic Agroalimentari (PCiTAL), 25003 Lleida, Catalunya, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1985-6039","authenticated-orcid":false,"given":"Olivier","family":"Merlin","sequence":"additional","affiliation":[{"name":"CESBIO (Centre d\u2019\u00c9tudes Spatiales de la BIOsph\u00e8re), University of Toulouse, CNES\/CNRS\/INRAE\/IRD\/UPS, 31401 Toulouse, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4157-1446","authenticated-orcid":false,"given":"Thierry","family":"Pellarin","sequence":"additional","affiliation":[{"name":"Institut des G\u00e9osciences de l\u2019Environnement (IGE), CNRS, IRD, University Grenoble Alpes, Saint-Martin-d\u2019H\u00e8res, 38400 Grenoble, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1023\/A:1022103315424","article-title":"US agriculture and climate change: New results","volume":"57","author":"Reilly","year":"2003","journal-title":"Clim. Chang."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.gloenvcha.2003.10.008","article-title":"Effects of climate change on global food production under SRES emissions and socio-economic scenarios","volume":"14","author":"Parry","year":"2004","journal-title":"Glob. Environ. Chang."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"19691","DOI":"10.1073\/pnas.0701890104","article-title":"Adapting agriculture to climate change","volume":"104","author":"Howden","year":"2007","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"014010","DOI":"10.1088\/1748-9326\/5\/1\/014010","article-title":"Robust negative impacts of climate change on African agriculture","volume":"5","author":"Schlenker","year":"2010","journal-title":"Environ. Res. Lett."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"7799","DOI":"10.1002\/2017GL073606","article-title":"Probabilistic estimates of drought impacts on agricultural production","volume":"44","author":"Madadgar","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_6","unstructured":"Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S.L., P\u00e9an, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., and Gomis, M.I. (2021). Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press."},{"key":"ref_7","unstructured":"Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S.L., P\u00e9an, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., and Gomis, M.I. (2021). Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press."},{"key":"ref_8","unstructured":"Toreti, A., Bavera, D., Acosta, N.J., Arias-Mu\u00f1oz, C., Barbosa, P., De, J.A., Di, C.C., Fioravanti, G., Grimaldi, S., and Hrast, E.A. (2023). Drought in the western Mediterranean\u2014May 2023, Publications Office of the European Union. EUR 31555 EN."},{"key":"ref_9","unstructured":"Vanneuville, W., Werner, B., Kjeldsen, T., Miller, J., Kossida, M., Tekidou, A., Kakava, A., and Crouzet, P. (2012). Water Resources in Europe in the Context of Vulnerability: EEA 2012 State of Water Assessment, European Environment Agency."},{"key":"ref_10","unstructured":"Baruth, B., Bassu, S., Ben, A.W., Biavetti, I., Bratu, M., Cerrani, I., Chemin, Y., Claverie, M., De, P.P., and Fumagalli, D. (2023). JRC MARS Bulletin\u2014Crop Monitoring in Europe\u2014May 2023, Publications Office of the European Union."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1038\/s41612-024-00569-6","article-title":"Record-shattering 2023 Spring heatwave in western Mediterranean amplified by long-term drought","volume":"7","author":"Trigo","year":"2024","journal-title":"NPJ Clim. Atmos. Sci."},{"key":"ref_12","unstructured":"(2023, January 21). NFORME DE LA SEQU\u00cdA DE 2023 presentado en la Junta de Gobierno de 21\/12\/2023 para recibir aportaciones [Report on the drought of 2023]. Memoria 7. Proceedings of the Confederaci\u00f3n Hidrogr\u00e1fica del Ebro (CHE), Zaragoza, Spain."},{"key":"ref_13","unstructured":"FAO (2023). AQUASTAT\u2014FAO\u2019s Global Information System on Water and Agriculture, FAO."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1038\/nature10452","article-title":"Solutions for a cultivated planet","volume":"478","author":"Foley","year":"2011","journal-title":"Nature"},{"key":"ref_15","unstructured":"Gleick, P.H., Allen, L., Christian-Smith, J., Cohen, M.J., Cooley, H., Heberger, M., Morrison, J., Palaniappan, M., and Schulte, P. (2012). The World\u2019s Water Volume 7: The Biennial Report on Freshwater Resources, Island Press."},{"key":"ref_16","unstructured":"United Nations Environment Programme\/Mediterranean Action Plan, and Plan Bleau (2020). State of the Environment and Development in the Mediterranean, Food & Agriculture Org."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Massari, C., Modanesi, S., Dari, J., Gruber, A., De Lannoy, G.J.M., Girotto, M., Quintana-Segu\u00ed, P., Le Page, M., Jarlan, L., and Zribi, M. (2021). A Review of Irrigation Information Retrievals from Space and Their Utility for Users. Remote Sens., 13.","DOI":"10.3390\/rs13204112"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3679","DOI":"10.1080\/01431160802698919","article-title":"Global irrigated area map (GIAM), derived from remote sensing, for the end of the last millennium","volume":"30","author":"Thenkabail","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Portmann, F.T., Siebert, S., and D\u00f6ll, P. (2010). MIRCA2000\u2014Global monthly irrigated and rainfed crop areas around the year 2000: A new high-resolution data set for agricultural and hydrological modeling. Glob. Biogeochem. Cycles, 24.","DOI":"10.1029\/2008GB003435"},{"key":"ref_20","first-page":"321","article-title":"Global rain-fed, irrigated, and paddy croplands: A new high resolution map derived from remote sensing, crop inventories and climate data","volume":"38","author":"Salmon","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_21","first-page":"1177","article-title":"Irrigated crop area estimation using Landsat TM imagery in La Mancha, Spain","volume":"67","author":"Beltran","year":"2001","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1016\/j.rse.2004.12.018","article-title":"Ganges and Indus river basin land use\/land cover (LULC) and irrigated area mapping using continuous streams of MODIS data","volume":"95","author":"Thenkabail","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3520","DOI":"10.1016\/j.rse.2008.04.010","article-title":"A new methodology to map irrigated areas using multi-temporal MODIS and ancillary data: An application example in the continental US","volume":"112","author":"Ozdogan","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"357","DOI":"10.5194\/isprs-archives-XLII-3-W6-357-2019","article-title":"Surface Moisture And Irrigation Mapping At Agricultural Field Scale Using The Synergy Sentinel-1\/Sentinel-2 Data","volume":"XLII-3-W6","author":"Zribi","year":"2019","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"441","DOI":"10.5194\/hess-28-441-2024","article-title":"An Inter-Comparison of Approaches and Frameworks to Quantify Irrigation from Satellite Data","volume":"28","author":"Kragh","year":"2024","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_26","first-page":"752","article-title":"How much water is used for irrigation? A new approach exploiting coarse resolution satellite soil moisture products","volume":"73","author":"Brocca","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Dari, J., Brocca, L., Quintana-Segu\u00ed, P., Escorihuela, M.J., Stefan, V., and Morbidelli, R. (2020). Exploiting High-Resolution Remote Sensing Soil Moisture to Estimate Irrigation Water Amounts over a Mediterranean Region. Remote Sens., 12.","DOI":"10.3390\/rs12162593"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"107537","DOI":"10.1016\/j.agwat.2022.107537","article-title":"Irrigation estimates from space: Implementation of different approaches to model the evapotranspiration contribution within a soil-moisture-based inversion algorithm","volume":"265","author":"Dari","year":"2022","journal-title":"Agric. Water Manag."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1555","DOI":"10.5194\/essd-15-1555-2023","article-title":"Regional data sets of high-resolution (1 and 6&thinsp;km) irrigation estimates from space","volume":"15","author":"Dari","year":"2023","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"106236","DOI":"10.1016\/j.agwat.2020.106236","article-title":"Remote Sensing\u2013Based Soil Water Balance for Irrigation Water Accounting at Plot and Water User Association Management Scale","volume":"238","author":"Campos","year":"2020","journal-title":"Agric. Water Manag."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"108119","DOI":"10.1016\/j.agwat.2022.108119","article-title":"Modeling actual water use under different irrigation regimes at district scale: Application to the FAO-56 dual crop coefficient method","volume":"278","author":"Laluet","year":"2023","journal-title":"Agric. Water Manag."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"108704","DOI":"10.1016\/j.agwat.2024.108704","article-title":"Retrieving the Irrigation Actually Applied at District Scale: Assimilating High-Resolution Sentinel-1-derived Soil Moisture Data into a FAO-56-based Model","volume":"293","author":"Laluet","year":"2024","journal-title":"Agric. Water Manag."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Wei, S., Xu, T., Niu, G.Y., and Zeng, R. (2022). Estimating Irrigation Water Consumption Using Machine Learning and Remote Sensing Data in Kansas High Plains. Remote Sens., 14.","DOI":"10.3390\/rs14133004"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"897","DOI":"10.5194\/hess-23-897-2019","article-title":"Estimating irrigation water use over the contiguous United States by combining satellite and reanalysis soil moisture data","volume":"23","author":"Zaussinger","year":"2019","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1016\/j.scitotenv.2019.04.365","article-title":"Detecting global irrigated areas by using satellite and reanalysis products","volume":"677","author":"Zohaib","year":"2019","journal-title":"Sci. Total. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1351","DOI":"10.1016\/j.agwat.2010.03.017","article-title":"Estimating actual irrigation application by remotely sensed evapotranspiration observations","volume":"97","author":"Droogers","year":"2010","journal-title":"Agric. Water Manag."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"107602","DOI":"10.1016\/j.agwat.2022.107602","article-title":"A novel evapotranspiration based irrigation quantification method using the hydrological similar pixels algorithm","volume":"267","author":"Brombacher","year":"2022","journal-title":"Agric. Water Manag."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"e2021WR031382","DOI":"10.1029\/2021WR031382","article-title":"Estimating Spatially Explicit Irrigation Water Use Based on Remotely Sensed Evapotranspiration and Modeled Root Zone Soil Moisture","volume":"57","author":"Zhang","year":"2021","journal-title":"Water Resour. Res."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"4685","DOI":"10.5194\/hess-26-4685-2022","article-title":"Challenges and benefits of quantifying irrigation through the assimilation of Sentinel-1 backscatter observations into Noah-MP","volume":"26","author":"Modanesi","year":"2022","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"3670","DOI":"10.1029\/2019MS001797","article-title":"Soil Moisture Data Assimilation to Estimate Irrigation Water Use","volume":"11","author":"Livneh","year":"2019","journal-title":"J. Adv. Model. Earth Syst."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"e2022WR033342","DOI":"10.1029\/2022WR033342","article-title":"Is It Possible to Quantify Irrigation Water-Use by Assimilating a High-Resolution Satellite Soil Moisture Product?","volume":"59","author":"Jalilvand","year":"2023","journal-title":"Water Resour. Res."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Pan, F., Peters-Lidard, C.D., and Sale, M.J. (2003). An analytical method for predicting surface soil moisture from rainfall observations. Water Resour. Res., 39.","DOI":"10.1029\/2003WR002142"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.rse.2016.02.046","article-title":"Comparison of remote sensing and simulated soil moisture datasets in Mediterranean landscapes","volume":"180","author":"Escorihuela","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_44","first-page":"102979","article-title":"How accurately can we retrieve irrigation timing and water amounts from (satellite) soil moisture?","volume":"113","author":"Zappa","year":"2022","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"108594","DOI":"10.1016\/j.agwat.2023.108594","article-title":"Estimating multi-scale irrigation amounts using multi-resolution soil moisture data: A data-driven approach using PrISM","volume":"290","author":"Paolini","year":"2023","journal-title":"Agric. Water Manag."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.rse.2012.11.008","article-title":"Self-calibrated evaporation-based disaggregation of SMOS soil moisture: An evaluation study at 3km and 100m resolution in Catalunya, Spain","volume":"130","author":"Merlin","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Oiha, N., Merlin, O., Molero, B., Sucre, C., Olivera, L., Rivalland, V., and Er-Raki, S. (2018, January 22\u201327). Sequential Downscaling of the SMOS Soil Moisture at 100 M Resolution Via a Variable Intermediate Spatial Resolution. Proceedings of the IGARSS 2018\u20142018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8518599"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1556","DOI":"10.1109\/TGRS.2011.2175000","article-title":"Disaggregation of SMOS Soil Moisture in Southeastern Australia","volume":"50","author":"Merlin","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Ojha, N., Merlin, O., Suere, C., and Escorihuela, M.J. (2021). Extending the Spatio-Temporal Applicability of DISPATCH Soil Moisture Downscaling Algorithm: A Study Case Using SMAP, MODIS and Sentinel-3 Data. Front. Environ. Sci., 9.","DOI":"10.3389\/fenvs.2021.555216"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/j.rse.2016.02.045","article-title":"SMOS disaggregated soil moisture product at 1 km resolution: Processor overview and first validation results","volume":"180","author":"Molero","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"3783","DOI":"10.3390\/rs70403783","article-title":"Performance Metrics for Soil Moisture Downscaling Methods: Application to DISPATCH Data in Central Morocco","volume":"7","author":"Merlin","year":"2015","journal-title":"Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1536","DOI":"10.1016\/j.scitotenv.2016.08.213","article-title":"Evaluation of eight high spatial resolution gridded precipitation products in Adige Basin (Italy) at multiple temporal and spatial scales","volume":"573","author":"Duan","year":"2016","journal-title":"Sci. Total. Environ."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"111697","DOI":"10.1016\/j.rse.2020.111697","article-title":"Have satellite precipitation products improved over last two decades? A comprehensive comparison of GPM IMERG with nine satellite and reanalysis datasets","volume":"240","author":"Tang","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_54","unstructured":"Maneewongvatana, S., and Mount, D.M. (1999). Analysis of approximate nearest neighbor searching with clustered point sets. arXiv."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Pellarin, T., Ali, A., Chopin, F., Jobard, I., and Berg\u00e8s, J.C. (2008). Using spaceborne surface soil moisture to constrain satellite precipitation estimates over West Africa. Geophys. Res. Lett., 35.","DOI":"10.1029\/2007GL032243"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1016\/j.rse.2017.08.022","article-title":"Correcting satellite-based precipitation products through SMOS soil moisture data assimilation in two land-surface models of different complexity: API and SURFEX","volume":"200","author":"Pellarin","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.rse.2013.04.011","article-title":"A simple and effective method for correcting soil moisture and precipitation estimates using AMSR-E measurements","volume":"136","author":"Pellarin","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Pellarin, T., Rom\u00e1n-Casc\u00f3n, C., Baron, C., Bindlish, R., Brocca, L., Camberlin, P., Fern\u00e1ndez-Prieto, D., Kerr, Y.H., Massari, C., and Panthou, G. (2020). The Precipitation Inferred from Soil Moisture (PrISM) Near Real-Time Rainfall Product: Evaluation and Comparison. Remote Sens., 12.","DOI":"10.3390\/rs12030481"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"10055","DOI":"10.1109\/JSTARS.2022.3222884","article-title":"Classification of Different Irrigation Systems at Field Scale Using Time-Series of Remote Sensing Data","volume":"15","author":"Paolini","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/7\/1116\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:17:59Z","timestamp":1760105879000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/7\/1116"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,22]]},"references-count":59,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2024,4]]}},"alternative-id":["rs16071116"],"URL":"https:\/\/doi.org\/10.3390\/rs16071116","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,22]]}}}