{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:10:51Z","timestamp":1790813451571,"version":"4.1.0"},"reference-count":66,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,4,11]],"date-time":"2023-04-11T00:00:00Z","timestamp":1681171200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002347","name":"German Federal Ministry of Education and Research (BMBF)","doi-asserted-by":"publisher","award":["02WPL1449D"],"award-info":[{"award-number":["02WPL1449D"]}],"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>Plastics are part of our everyday life, as they are versatile materials and can be produced inexpensively. Approximately 10 Gt of plastics have been produced to date, of which the majority have been accumulated in landfills or have been spread into the terrestrial and aquatic environment in an uncontrolled way. Once in the environment, plastic litter\u2014in its large form or degraded into microplastics\u2014causes several harms to a variety of species. Thus, the detection of plastic waste is a pressing research question in remote sensing. The majority of studies have used Sentinel-2 or WorldView-3 data and empirically explore the usefulness of the given spectral channels for the detection of plastic litter in the environment. On the other hand, laboratory infrared spectroscopy is an established technique for the differentiation of plastic types based on their type-specific absorption bands; the potential of hyperspectral remote sensing for mapping plastics in the environment has not yet been fully explored. In this study, reflectance spectra of the five most commonly used plastic types were used for spectral sensor simulations of ten selected multispectral and hyperspectral sensors. Their signals were classified in order to differentiate between the plastic types as would be measured in nature and to investigate sensor-specific spectral configurations neglecting spatial resolution limitations. Here, we show that most multispectral sensors are not able to differentiate between plastic types, while hyperspectral sensors are. To resolve absorption bands of plastics with multispectral sensors, the number, position, and width of the SWIR channels are decisive for a good classification of plastics. As ASTER and WorldView-3 had\/have narrow SWIR channels that match with diagnostic absorption bands of plastics, they yielded outstanding results. Central wavelengths at 1141, 1217, 1697, and 1716 nm, in combination with narrow bandwidths of 10\u201320 nm, have the highest capability for plastic differentiation.<\/jats:p>","DOI":"10.3390\/rs15082020","type":"journal-article","created":{"date-parts":[[2023,4,12]],"date-time":"2023-04-12T01:35:08Z","timestamp":1681263308000},"page":"2020","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Potential of Optical Spaceborne Sensors for the Differentiation of Plastics in the Environment"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2134-7527","authenticated-orcid":false,"given":"Toni","family":"Schmidt","sequence":"first","affiliation":[{"name":"Department Remote Sensing, Helmholtz-Centre for Environmental Research\u2014UFZ, 04318 Leipzig, Germany"},{"name":"Remote Sensing Centre for Earth System Research\u2014RSC4Earth, Leipzig University, 04103 Leipzig, Germany"},{"name":"Remote Sensing and Geoinformatics Section, Helmholtz Centre Potsdam\u2014GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0596-5621","authenticated-orcid":false,"given":"Theres","family":"Kuester","sequence":"additional","affiliation":[{"name":"Remote Sensing and Geoinformatics Section, Helmholtz Centre Potsdam\u2014GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6763-7204","authenticated-orcid":false,"given":"Taylor","family":"Smith","sequence":"additional","affiliation":[{"name":"Institute of Geosciences, University of Potsdam, 14476 Potsdam, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2380-4429","authenticated-orcid":false,"given":"Mathias","family":"Bochow","sequence":"additional","affiliation":[{"name":"Remote Sensing and Geoinformatics Section, Helmholtz Centre Potsdam\u2014GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e1700782","DOI":"10.1126\/sciadv.1700782","article-title":"Production, use, and fate of all plastics ever made","volume":"3","author":"Geyer","year":"2017","journal-title":"Sci. Adv."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2115","DOI":"10.1098\/rstb.2008.0311","article-title":"Plastics recycling: Challenges and opportunities","volume":"364","author":"Hopewell","year":"2009","journal-title":"Philos. Trans. R. Soc. B Biol. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.marenvres.2016.05.012","article-title":"Plastics and microplastics in the oceans: From emerging pollutants to emerged threat","volume":"128","author":"Avio","year":"2017","journal-title":"Mar. Environ. Res."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"6453","DOI":"10.1021\/es302011r","article-title":"Microplastic in Terrestrial Ecosystems and the Soil?","volume":"46","author":"Rillig","year":"2012","journal-title":"Environ. Sci. Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"842","DOI":"10.1016\/S0025-326X(02)00220-5","article-title":"The pollution of the marine environment by plastic debris: A review","volume":"44","author":"Derraik","year":"2002","journal-title":"Mar. Pollut. Bull."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1985","DOI":"10.1098\/rstb.2008.0205","article-title":"Accumulation and fragmentation of plastic debris in global environments","volume":"364","author":"Barnes","year":"2009","journal-title":"Philos. Trans. R. Soc. B Biol. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Kukulka, T., Proskurowski, G., Mor\u00e9t-Ferguson, S., Meyer, D.W., and Law, K.L. (2012). The effect of wind mixing on the vertical distribution of buoyant plastic debris. Geophys. Res. Lett., 39.","DOI":"10.1029\/2012GL051116"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"111023","DOI":"10.1016\/j.marpolbul.2020.111023","article-title":"Behaviour of plastic litter in nearshore waters: First insights from wind and wave laboratory experiments","volume":"153","author":"Forsberg","year":"2020","journal-title":"Mar. Pollut. Bull."},{"key":"ref_9","unstructured":"Andrady, A.L. (2015). Marine Anthropogenic Litter, Springer."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"100352","DOI":"10.1016\/j.eti.2019.100352","article-title":"Plastics and microplastics: A threat to environment","volume":"14","author":"Laskar","year":"2019","journal-title":"Environ. Technol. Innov."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"6634","DOI":"10.1021\/acs.est.7b00423","article-title":"Plastic and Human Health: A Micro Issue?","volume":"51","author":"Wright","year":"2017","journal-title":"Environ. Sci. Technol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.coesh.2017.10.003","article-title":"Micro(nano)plastics: A threat to human health?","volume":"1","author":"Revel","year":"2018","journal-title":"Curr. Opin. Environ. Sci. Health"},{"key":"ref_13","unstructured":"Swain, S.K., and Mohammad, J. (2019). Nanostructured Polymer Composites for Biomedical Applications, Elsevier."},{"key":"ref_14","unstructured":"Workman, J., and Workman, J. (2001). Handbook of Organic Compounds: Methods and Interpretations, Academic Press."},{"key":"ref_15","unstructured":"Eisenreich, N., and Rohe, T. (2006). Encyclopedia of Analytical Chemistry: Applications, Theory and Instrumentation, Wiley."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Osswald, T.A. (2006). International Plastics Handbook: The Resource for Plastics Engineers, Hanser. [1st ed.].","DOI":"10.3139\/9783446407923.fm"},{"key":"ref_17","first-page":"8","article-title":"Short Cuts to the Analysis of Plastics by Infrared Spectroscopy","volume":"5","author":"Hausdorff","year":"1950","journal-title":"Appl. Spectrosc."},{"key":"ref_18","unstructured":"Kraft, E. (1968). Analysis of Plastics by ATR Spectroscopy, McGraw-Hill. Modern Plastics."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1039\/an9851000643","article-title":"Rapid analysis of packaging laminates by near-infrared spectroscopy","volume":"110","author":"Davies","year":"1985","journal-title":"Analyst"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1126\/science.245.4914.165","article-title":"Spectral Reflectance Properties of Hydrocarbons: Remote-Sensing Implications","volume":"245","author":"Cloutis","year":"1989","journal-title":"Science"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2467","DOI":"10.1080\/01431160310001642287","article-title":"Hydrocarbon Index\u2014An algorithm for hyperspectral detection of hydrocarbons","volume":"25","author":"Oppermann","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"4548","DOI":"10.1109\/JSTARS.2014.2327226","article-title":"A Decision-Tree Classifier for Extracting Transparent Plastic-Mulched Landcover from Landsat-5 TM Images","volume":"7","author":"Lu","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Maximenko, N., Chao, Y., and Moller, D. (2016). Developing a Remote Sensing System to Track Marine Debris. Eos, 97.","DOI":"10.1029\/2016EO061605"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.compag.2017.07.003","article-title":"Agricultural plastic waste spatial estimation by Landsat 8 satellite images","volume":"141","author":"Lanorte","year":"2017","journal-title":"Comput. Electron. Agric."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.isprsjprs.2017.03.002","article-title":"Mapping plastic greenhouse with medium spatial resolution satellite data: Development of a new spectral index","volume":"128","author":"Yang","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/j.marpolbul.2017.11.011","article-title":"Concept for a hyperspectral remote sensing algorithm for floating marine macro plastics","volume":"126","author":"Peters","year":"2018","journal-title":"Mar. Pollut. Bull."},{"key":"ref_27","unstructured":"Biermann, L., Vincente, V.M., Sailley, S., Mata, A., and Steele, C. (2019, January 7\u201312). Towards a method for detecting macroplastics by satellite: Examining Sentinel-2 earth observation data for floating debris in the coastal zone. Proceedings of the 21st EGU General Assembly, EGU2019, Vienna, Austria."},{"key":"ref_28","unstructured":"Fouzia, H.B. (2018). Monitoring of Marine Pollution, IntechOpen. Chapter 2."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez-Vicente, V., Clark, J.R., Corradi, P., Aliani, S., Arias, M., Bochow, M., Bonnery, G., Cole, M., C\u00f3zar, A., and Donnelly, R. (2019). Measuring Marine Plastic Debris from Space: Initial Assessment of Observation Requirements. Remote Sens., 11.","DOI":"10.3390\/rs11202443"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Kuester, T., and Bochow, M. (2019, January 24\u201326). Spectral Modeling of Plastic Litter in Terrestrial Environments-Use of 3D Hyperspectral Ray Tracing Models to Analyze the Spectral Influence of Different Natural Ground Surfaces on Remote Sensing Based Plastic Mapping. Proceedings of the 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), Amsterdam, The Netherlands.","DOI":"10.1109\/WHISPERS.2019.8920847"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"5364","DOI":"10.1038\/s41598-020-62298-z","article-title":"Finding Plastic Patches in Coastal Waters using Optical Satellite Data","volume":"10","author":"Biermann","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"112598","DOI":"10.1016\/j.rse.2021.112598","article-title":"A knowledge-based, validated classifier for the identification of aliphatic and aromatic plastics by WorldView-3 satellite data","volume":"264","author":"Zhou","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"113263","DOI":"10.1016\/j.rse.2022.113263","article-title":"Identifying distinct plastics in hyperspectral experimental lab-, aircraft-, and satellite data using machine\/deep learning methods trained with synthetically mixed spectral data","volume":"281","author":"Zhou","year":"2022","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Berk, A., Conforti, P., Kennett, R., Perkins, T., Hawes, F., and van den Bosch, J. (2014). MODTRAN6: A Major Upgrade of the MODTRAN Radiative Transfer Code, SPIE.","DOI":"10.1117\/12.2050433"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"7396","DOI":"10.1364\/AO.54.007396","article-title":"Multi-spectral infrared spectroscopy for robust plastic identification","volume":"54","author":"Money","year":"2015","journal-title":"Appl. Opt."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"ASD Inc. (2010). FieldSpec 3 User Manual, ASD Inc.. Technical Report ASD Document 600540 Rev. I.","DOI":"10.4016\/11826.01"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1828","DOI":"10.1109\/TGRS.2014.2349737","article-title":"Independent Laboratory Characterization of NEO HySpex Imaging Spectrometers VNIR-1600 and SWIR-320m-e","volume":"53","author":"Lenhard","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Rogass, C., Koerting, F.M., Mielke, C., Brell, M., Boesche, N.K., Bade, M., and Hohmann, C. (2017). Translational imaging spectroscopy for proximal sensing. Sensors, 17.","DOI":"10.3390\/s17081857"},{"key":"ref_39","unstructured":"Siegert, F., Atwood, E.C., Piehl, S., Bochow, M., Laforsch, C., and Franke, J. (2018). Belastung Aquatischer \u00d6kosysteme Mit Kunststoffm\u00fcll: Globales und Lokales Monitoring Mittels Satellitengest\u00fctzter Methoden: Schlussbericht, Universit\u00e4t Bayreuth. Berichtszeitraum: 1 July 2013\u201331 July 2017; Technical Report."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.ecoinf.2016.10.002","article-title":"Mapping multiple plant species abundance patterns\u2014A multiobjective optimization procedure for combining reflectance spectroscopy and species ordination","volume":"36","author":"Neumann","year":"2016","journal-title":"Ecol. Inform."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1525","DOI":"10.1109\/36.934082","article-title":"Automated differentiation of urban surfaces based on airborne hyperspectral imagery","volume":"39","author":"Roessner","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"11125","DOI":"10.3390\/rs70911125","article-title":"Organic Matter Modeling at the Landscape Scale Based on Multitemporal Soil Pattern Analysis Using RapidEye Data","volume":"7","author":"Blasch","year":"2015","journal-title":"Remote Sens."},{"key":"ref_43","unstructured":"Spengler, D. (2013). Anwendung Vierdimensionaler Bestandsmodelle f\u00fcr die Charakterisierung von Getreidearten aus Hyperspektralen Fernerkundungsdaten. [Ph.D. Thesis, Technische Universit\u00e4t Berlin]."},{"key":"ref_44","unstructured":"Bochow, M. (2010). Automatisierungspotenzial von Stadtbiotopkartierungen durch Methoden der Fernerkundung, Logos-Verlag."},{"key":"ref_45","unstructured":"K\u00fcster, T. (2011). Modellierung von Getreidebestandsspektren zur Korrektur BRDF-Bedingter Einfl\u00fcsse auf Vegetationsindizes im Rahmen der EnMAP-Mission. [Ph.D. Thesis, Humboldt-Universit\u00e4t Zu Berlin]."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1364\/AO.51.000439","article-title":"End-to-end sensor simulation for spectral band selection and optimization with application to the Sentinel-2 mission","volume":"51","author":"Segl","year":"2012","journal-title":"Appl. Opt."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"13485","DOI":"10.3390\/rs71013485","article-title":"Comparison of the Continuity of Vegetation Indices Derived from Landsat 8 OLI and Landsat 7 ETM+ Data among Different Vegetation Types","volume":"7","author":"She","year":"2015","journal-title":"Remote Sens."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1080\/2150704X.2015.1007246","article-title":"New geometric hull continuum removal algorithm for automatic absorption band detection from spectroscopic data","volume":"6","author":"Mielke","year":"2015","journal-title":"Remote Sens. Lett."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"10635","DOI":"10.1029\/JB088iB12p10635","article-title":"Spectral properties of mixtures of montmorillonite and dark carbon grains: Implications for remote sensing minerals containing chemically and physically adsorbed water","volume":"88","author":"Clark","year":"1983","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2784","DOI":"10.1080\/01431161.2018.1433343","article-title":"Implementation of machine-learning classification in remote sensing: An applied review","volume":"39","author":"Maxwell","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Shalev-Shwartz, S., and Ben-David, S. (2014). Understanding Machine Learning, Cambridge University Press.","DOI":"10.1017\/CBO9781107298019"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_53","unstructured":"Valera, D., Belmonte, L., Molina-Aiz, F., and L\u00f3pez, A. (2016). Greenhouse Agriculture in Almeria. A Comprehensive Techno-Economic Analysis, Cajamar Caja Rural."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Karaca, A.C., Ert\u00fcrk, A., G\u00fcll\u00fc, M.K., Elmas, M., and Ert\u00fcrk, S. (2013, January 24\u201326). Plastic Waste Sorting Using Infrared Hyperspectral Imaging System. Proceedings of the 2013 21st Signal Processing and Communications Applications Conference (SIU), Haspolat, Turkey.","DOI":"10.1109\/SIU.2013.6531170"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1016\/j.rse.2017.11.023","article-title":"An airborne remote sensing case study of synthetic hydrocarbon detection using short wave infrared absorption features identified from marine-harvested macro- and microplastics","volume":"205","author":"Garaba","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"2205","DOI":"10.3390\/s150102205","article-title":"PET and PVC Separation with Hyperspectral Imagery","volume":"15","author":"Moroni","year":"2015","journal-title":"Sensors"},{"key":"ref_57","first-page":"30","article-title":"Plasticulture magazine: Amilestone for a history of progress in plasticulture","volume":"1","author":"Garnaud","year":"2000","journal-title":"Plasticulture"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"155939","DOI":"10.1016\/j.scitotenv.2022.155939","article-title":"UAV remote sensing applications in marine monitoring: Knowledge visualization and review","volume":"838","author":"Yang","year":"2022","journal-title":"Sci. Total Environ."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"118551","DOI":"10.1016\/j.watres.2022.118551","article-title":"Can we quantify the aquatic environmental plastic load from aquaculture?","volume":"219","author":"Tian","year":"2022","journal-title":"Water Res."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1080\/00031305.1994.10476030","article-title":"The Three Sigma Rule","volume":"48","author":"Pukelsheim","year":"1994","journal-title":"Am. Stat."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/0034-4257(82)90057-8","article-title":"Spectral reflectance of partly transmitting leaves: Laboratory measurements and mathematical modeling","volume":"12","author":"Lillesaeter","year":"1982","journal-title":"Remote Sens. Environ."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"3273","DOI":"10.1080\/01431169208904118","article-title":"Reflection of layered bean leaves over different soil backgrounds: Measured and simulated spectra","volume":"13","author":"Miller","year":"1992","journal-title":"Int. J. Remote Sens."},{"key":"ref_63","unstructured":"Jacquemoud, S., and Ustin, S.L. (2001). Leaf Optical Properties: A State of the Art, Cambridge University Press."},{"key":"ref_64","unstructured":"Chen, C., and Breiman, L. (2004). Using Random Forest to Learn Imbalanced Data, University of California."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"020023","DOI":"10.1063\/1.4954536","article-title":"Handling imbalanced dataset using SVM and k-NN approach","volume":"1750","author":"Wah","year":"2016","journal-title":"AIP Conf. Proc."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Ramezan, C.A., Warner, T.A., and Maxwell, A.E. (2019). Evaluation of Sampling and Cross-Validation Tuning Strategies for Regional-Scale Machine Learning Classification. Remote Sens., 11.","DOI":"10.3390\/rs11020185"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/8\/2020\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:13:57Z","timestamp":1760123637000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/8\/2020"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4,11]]},"references-count":66,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["rs15082020"],"URL":"https:\/\/doi.org\/10.3390\/rs15082020","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,11]]}}}