{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T12:24:47Z","timestamp":1783513487465,"version":"3.55.0"},"reference-count":70,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T00:00:00Z","timestamp":1783382400000},"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>Satellite Synthetic Aperture Radar (SAR) is an established technology for studying and monitoring archaeological landscapes, providing insights into surface morphology and the presence of near subsurface features. However, its application in large-scale archaeological prospection is limited by the lack of robust, automated methods for SAR data analysis. This study introduces a novel Deep Learning pipeline to automatically detect and segment archaeological settlement mounds, known as tells, in central Iraq on satellite SAR data. The pipeline leverages a state-of-the-art supervised method for instance segmentation, YOLOv8-Seg, and medium-resolution satellite SAR products, specifically the Copernicus Sentinel-1 Interferometric Wide Swath Mode Ground Range Detected and Copernicus Global 30-m Digital Elevation Model products. The model identifies tell sites with an Average Precision of 0.495\u00b10.010 and a pixel-wise Intersection over Union of 0.361\u00b10.048 over the test areas. Archaeological interpretation of the model\u2019s inferences confirms its reliability in locating and segmenting archaeological sites, leading also to the identification of previously unmapped potential sites. After a main test in central Iraq, the proposed workflow demonstrates promising transferability to a nearby test area in Iran, although with a need for regional fine-tuning to account for inherent variations in feature morphology and environmental context. This research establishes a baseline for future Deep Learning applications in Synthetic Aperture Radar-based archaeological prospection.<\/jats:p>","DOI":"10.3390\/rs18132255","type":"journal-article","created":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T13:19:31Z","timestamp":1783430371000},"page":"2255","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Learning Enables the Automatic Mapping of Tell Sites on Satellite Synthetic Aperture Radar Products"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-0283-7794","authenticated-orcid":false,"given":"Elena","family":"Chiricallo","sequence":"first","affiliation":[{"name":"Center for Cultural Heritage Technology, Istituto Italiano di Tecnologia, 31056 Treviso, Italy"},{"name":"Department of Environmental Sciences, Informatics and Statistics, Universit\u00e0 Ca\u2019 Foscari, 30171 Venezia, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7741-0150","authenticated-orcid":false,"given":"Giulio","family":"Poggi","sequence":"additional","affiliation":[{"name":"Center for Cultural Heritage Technology, Istituto Italiano di Tecnologia, 31056 Treviso, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9937-7112","authenticated-orcid":false,"given":"Sara","family":"Ferro","sequence":"additional","affiliation":[{"name":"Center for Cultural Heritage Technology, Istituto Italiano di Tecnologia, 31056 Treviso, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7855-1641","authenticated-orcid":false,"given":"Sebastiano","family":"Vascon","sequence":"additional","affiliation":[{"name":"Department of Environmental Sciences, Informatics and Statistics, Universit\u00e0 Ca\u2019 Foscari, 30171 Venezia, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4508-1540","authenticated-orcid":false,"given":"Arianna","family":"Traviglia","sequence":"additional","affiliation":[{"name":"Center for Cultural Heritage Technology, Istituto Italiano di Tecnologia, 31056 Treviso, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Comer, D.C., and Harrower, M.J. (2013). Mapping Archaeological Landscapes from Space, Springer.","DOI":"10.1007\/978-1-4614-6074-9"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1002\/arp.1451","article-title":"Amplitude change detection with ENVISAT ASAR to image the cultural landscape of the Nasca region, Peru","volume":"20","author":"Cigna","year":"2013","journal-title":"Archaeol. Prospect."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1002\/arp.1444","article-title":"Possibilities of archaeological prospection by high-resolution X-band satellite radar\u2014A case study from Syria","volume":"20","author":"Linck","year":"2013","journal-title":"Archaeol. Prospect."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1002\/arp.1446","article-title":"New research in polarimetric SAR technique for archaeological purposes using ALOS PALSAR data","volume":"20","author":"Dore","year":"2013","journal-title":"Archaeol. Prospect."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"24","DOI":"10.3390\/rs70100024","article-title":"A space view of radar archaeological marks: First applications of COSMO-SkyMed X-band data","volume":"7","author":"Chen","year":"2014","journal-title":"Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Tapete, D., and Cigna, F. (2017). SAR for landscape archaeology. Sensing the Past: From Artifact to Historical Site, Springer.","DOI":"10.1007\/978-3-319-50518-3_5"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Paillou, P. (2017). Mapping palaeohydrography in deserts: Contribution from space-borne imaging radar. Water, 9.","DOI":"10.3390\/w9030194"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.culher.2015.05.003","article-title":"An overview of satellite synthetic aperture radar remote sensing in archaeology: From site detection to monitoring","volume":"23","author":"Chen","year":"2017","journal-title":"J. Cult. Herit."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Tapete, D., and Cigna, F. (2019). COSMO-SkyMed SAR for detection and monitoring of archaeological and cultural heritage sites. Remote Sens., 11.","DOI":"10.3390\/rs11111326"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Tapete, D., Traviglia, A., Delpozzo, E., and Cigna, F. (2021). Regional-scale systematic mapping of archaeological mounds and detection of looting using COSMO-SkyMed high resolution DEM and satellite imagery. Remote Sens., 13.","DOI":"10.3390\/rs13163106"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Tapete, D., and Cigna, F. (2022). Detection, morphometric analysis and digital surveying of archaeological mounds in southern Iraq with CartoSat-1 and COSMO-SkyMed DEMs. Land, 11.","DOI":"10.3390\/land11091406"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"526","DOI":"10.1080\/10095020.2023.2223603","article-title":"Exploiting satellite SAR for archaeological prospection and heritage site protection","volume":"27","author":"Cigna","year":"2024","journal-title":"Geo-Spat. Inf. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Cigna, F., and Tapete, D. (2024). Archaeological Prospection and Site Monitoring with Medium to Very High Resolution SAR Imagery: Case Studies in Rome (Italy). Proceedings of the IGARSS 2024-2024 IEEE International Geoscience and Remote Sensing Symposium, IEEE.","DOI":"10.1109\/IGARSS53475.2024.10642085"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"12593","DOI":"10.3390\/rs61212593","article-title":"Persistent scatterer interferometry processing of COSMO-SkyMed StripMap HIMAGE time series to depict deformation of the historic centre of Rome, Italy","volume":"6","author":"Cigna","year":"2014","journal-title":"Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.rse.2016.02.055","article-title":"\u2018Looting marks\u2019 in space-borne SAR imagery: Measuring rates of archaeological looting in Apamea (Syria) with TerraSAR-X Staring Spotlight","volume":"178","author":"Tapete","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"e1601284","DOI":"10.1126\/sciadv.1601284","article-title":"Radar interferometry offers new insights into threats to the Angkor site","volume":"3","author":"Chen","year":"2017","journal-title":"Sci. Adv."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Zaina, F., and Tapete, D. (2022). Satellite-based methodology for purposes of rescue archaeology of cultural heritage threatened by dam construction. Remote Sens., 14.","DOI":"10.3390\/rs14041009"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Richards, J.A. (2009). Remote Sensing with Imaging Radar, Springer.","DOI":"10.1007\/978-3-642-02020-9"},{"key":"ref_19","unstructured":"Long, D., and Ulaby, F. (2015). Microwave Radar and Radiometric Remote Sensing, University of Michigan Press."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Woodhouse, I.H. (2017). Introduction to Microwave Remote Sensing, CRC Press.","DOI":"10.1201\/9781315272573"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Shimada, M. (2018). Imaging from Spaceborne and Airborne SARs, Calibration, and Applications, CRC Press.","DOI":"10.1201\/b21909"},{"key":"ref_22","unstructured":"Flores-Anderson, A.I., Herndon, K.E., Thapa, R.B., and Cherrington, E. (2019). The SAR Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation."},{"key":"ref_23","unstructured":"National Aeronautics and Space Administration, and Indian Space Research Organisation (2025). NASA-ISRO SAR (NISAR) Mission Science Users\u2019 Handbook."},{"key":"ref_24","unstructured":"Ferretti, A., Monti-Guarnieri, A., Prati, C., Rocca, F., and Massonet, D. (2007). InSAR Principles-Guidelines for SAR Interferometry Processing and Interpretation, ESA Publications."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"18240","DOI":"10.1073\/pnas.2005583117","article-title":"Automated detection of archaeological mounds using machine-learning classification of multisensor and multitemporal satellite data","volume":"117","author":"Orengo","year":"2020","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1109\/MGRS.2020.3046356","article-title":"Deep learning meets SAR: Concepts, models, pitfalls, and perspectives","volume":"9","author":"Zhu","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Schmitt, M., and H\u00e4nsch, R. (2025). Deep Learning for Synthetic Aperture Radar Remote Sensing, Elsevier.","DOI":"10.1016\/B978-0-44-336344-3.00006-4"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/MGRS.2023.3237465","article-title":"Explainable, physics-aware, trustworthy artificial intelligence: A paradigm shift for synthetic aperture radar","volume":"11","author":"Datcu","year":"2023","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_29","first-page":"31","article-title":"Learning to look at LiDAR: The use of R-CNN in the automated detection of archaeological objects in LiDAR data from the Netherlands","volume":"2","author":"Lambers","year":"2019","journal-title":"J. Comput. Appl. Archaeol."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Fiorucci, M., Verschoof-Van Der Vaart, W.B., Soleni, P., Le Saux, B., and Traviglia, A. (2022). Deep learning for archaeological object detection on LiDAR: New evaluation measures and insights. Remote Sens., 14.","DOI":"10.3390\/rs14071694"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"558","DOI":"10.1038\/s41597-023-02455-x","article-title":"Machine learning-ready remote sensing data for Maya archaeology","volume":"10","author":"Kokalj","year":"2023","journal-title":"Sci. Data"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Casini, L., Orr\u00f9, V., Roccetti, M., and Marchetti, N. (2022). When machines find sites for the archaeologists: A preliminary study with semantic segmentation applied on satellite imagery of the Mesopotamian floodplain. Proceedings of the 2022 ACM Conference on Information Technology for Social Good, ACM.","DOI":"10.1145\/3524458.3547121"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"8699","DOI":"10.1038\/s41598-023-36015-5","article-title":"A human\u2013AI collaboration workflow for archaeological sites detection","volume":"13","author":"Casini","year":"2023","journal-title":"Sci. Rep."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Pistola, A., Orr\u00f9, V., Marchetti, N., and Roccetti, M. (2025). AI-ming backwards: Vanishing archaeological landscapes in Mesopotamia and automatic detection of sites on CORONA imagery. PLoS ONE, 20.","DOI":"10.1371\/journal.pone.0330419"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Smith, C. (2014). Tells in Archaeology. Encyclopedia of Global Archaeology, Springer. [2nd ed.].","DOI":"10.1007\/978-1-4419-0465-2"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Wilkinson, T.J. (2003). Archaeological Landscapes of the Near East, University of Arizona Press.","DOI":"10.2307\/j.ctv1jf2ddx"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1007\/s10814-024-09197-3","article-title":"Long-term urban and population trends in the Southern Mesopotamian floodplains","volume":"33","author":"Marchetti","year":"2025","journal-title":"J. Archaeol. Res."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1080\/13505033.2019.1662653","article-title":"A risk assessment for cultural heritage in southern Iraq: Framing drivers, threats and actions affecting archaeological sites","volume":"21","author":"Zaina","year":"2019","journal-title":"Conserv. Manag. Archaeol. Sites"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Cigna, F., Rayne, L., Makovics, J.L., Irvine, H.K., Jotheri, J., Algabri, A., and Tapete, D. (2025). Environmental Challenges and Vanishing Archaeological Landscapes: Remotely Sensed Insights into the Climate\u2013Water\u2013Agriculture\u2013Heritage Nexus in Southern Iraq. Land, 14.","DOI":"10.3390\/land14051013"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2112772","DOI":"10.1080\/17445647.2022.2112772","article-title":"Geomorphology of the lower Mesopotamian plain at Tell Zurghul archaeological site","volume":"19","author":"Iacobucci","year":"2023","journal-title":"J. Maps"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1007\/978-3-030-66238-7_2","article-title":"Cities in the Water: Waterscape and Evolution of Urban Civilisation in Southern Mesopotamia as Seen from Tell Zurghul, Iraq","volume":"Volume 36","author":"Jawad","year":"2021","journal-title":"Southern Iraq\u2019s Marshes"},{"key":"ref_42","unstructured":"The World Bank Group (2026, March 16). World Bank Climate Change Knowledge Portal: Iraq. Available online: https:\/\/climateknowledgeportal.worldbank.org\/country\/iraq."},{"key":"ref_43","unstructured":"Zanaga, D., Van De Kerchove, R., Daems, D., De Keersmaecker, W., Brockmann, C., Kirches, G., Wevers, J., Cartus, O., Santoro, M., and Fritz, S. (2026, March 16). ESA WorldCover 10 m 2021 v200, 2022. Data Set. Available online: https:\/\/zenodo.org\/records\/7254221."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"69","DOI":"10.3406\/paleo.2004.4773","article-title":"Human-environment interactions on the Upper Khuzestan Plains, southwest Iran. Recent investigations","volume":"30","author":"Alizadeh","year":"2004","journal-title":"Pal\u00e9orient"},{"key":"ref_45","first-page":"9","article-title":"The Dez-Karun-Confluence in Lower Susiana SW Iran) in the Last Millennia; a Case Study for the Human-Environment-Interaction","volume":"11","author":"Rashidian","year":"2021","journal-title":"Iran. J. Archaeol. Stud."},{"key":"ref_46","unstructured":"Copernicus Data Space Ecosystem (2026, March 16). Copernicus DEM\u2014Global and European Digital Elevation Model | Copernicus Data Space Ecosystem. Available online: https:\/\/dataspace.copernicus.eu\/explore-data\/data-collections\/copernicus-contributing-missions\/collections-description\/COP-DEM."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"4503922","DOI":"10.1109\/TGRS.2024.3368015","article-title":"Novel approach for ranking DEMs: Copernicus DEM improves one arc second open global topography","volume":"62","author":"Bielski","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_48","unstructured":"(ArcGIS Pro, 2022). ArcGIS Pro, Version 3.0.3."},{"key":"ref_49","first-page":"385","article-title":"Ancient Near East on Google Earth: Problems, Preliminary Results, and Prospects","volume":"Volume 3","year":"2012","journal-title":"Proceedings of the 7th International Congress on the Archaeology of the Ancient Near East"},{"key":"ref_50","unstructured":"Peders\u00e9n, O. (2026, March 16). ANE Site Placemarks for Google Earth (Versione 10), 2007. Data Set. Available online: https:\/\/zenodo.org\/records\/6384045."},{"key":"ref_51","first-page":"921","article-title":"FloodPlains. Developing a public archaeological WebGIS for the Southern Mesopotamian alluvium","volume":"Volume 1","author":"Marchetti","year":"2023","journal-title":"Proceedings of the 12th International Congress on the Archaeology of the Ancient Near East"},{"key":"ref_52","unstructured":"Jocher, G., Chaurasia, A., and Qiu, J. (Ultralytics Yolo, 2023). Ultralytics Yolo, Version 8.0.0."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Bolya, D., Zhou, C., Xiao, F., and Lee, Y.J. (2019). Yolact: Real-time instance segmentation. Proceedings of the 2019 IEEE\/CVF International Conference on Computer Vision (ICCV), IEEE.","DOI":"10.1109\/ICCV.2019.00925"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Doll\u00e1r, P., and Zitnick, C.L. (2014). Microsoft coco: Common objects in context. Proceedings of the European Conference on Computer Vision, Springer.","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1109\/MGRS.2020.3043504","article-title":"Toward a collective agenda on AI for earth science data analysis","volume":"9","author":"Tuia","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1109\/MGRS.2024.3425961","article-title":"Artificial Intelligence to Advance Earth Observation: A review of models, recent trends, and pathways forward","volume":"13","author":"Tuia","year":"2024","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1109\/MGRS.2024.3467001","article-title":"Opening the Black Box: A systematic review on explainable artificial intelligence in remote sensing","volume":"12","author":"Obadic","year":"2024","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_59","unstructured":"Chollet, F. (2018). Deep Learning with Python, Manning Publications Co."},{"key":"ref_60","unstructured":"Molnar, C. (2026, March 16). Interpretable Machine Learning. Available online: https:\/\/christophm.github.io\/interpretable-ml-book\/."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Muhammad, M.B., and Yeasin, M. (2020). Eigen-cam: Class activation map using principal components. Proceedings of the 2020 International Joint Conference on Neural Networks (IJCNN), IEEE.","DOI":"10.1109\/IJCNN48605.2020.9206626"},{"key":"ref_62","unstructured":"Rigved, S. (2026, March 16). YOLO-V12-CAM. Available online: https:\/\/github.com\/rigvedrs\/YOLO-V12-CAM."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"e453","DOI":"10.7717\/peerj.453","article-title":"scikit-image: Image processing in Python","volume":"2","author":"Boulogne","year":"2014","journal-title":"PeerJ"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1038\/s41597-022-01189-6","article-title":"Global seasonal Sentinel-1 interferometric coherence and backscatter data set","volume":"9","author":"Kellndorfer","year":"2022","journal-title":"Sci. Data"},{"key":"ref_65","first-page":"42691","article-title":"Position: Mission critical\u2014Satellite data is a distinct modality in machine learning","volume":"Volume 235","author":"Rolf","year":"2024","journal-title":"Proceedings of the Forty-First International Conference on Machine Learning"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1038\/s43247-025-03127-x","article-title":"On the foundations of Earth foundation models","volume":"7","author":"Zhu","year":"2026","journal-title":"Commun. Earth Environ."},{"key":"ref_67","unstructured":"Leberl, F. (1989). Radargrammetric Image Processing, Artech House."},{"key":"ref_68","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_69","doi-asserted-by":"crossref","first-page":"E778","DOI":"10.1073\/pnas.1115472109","article-title":"Mapping patterns of long-term settlement in Northern Mesopotamia at a large scale","volume":"109","author":"Menze","year":"2012","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_70","unstructured":"Food and Agriculture Organization (2026, March 16). GIEWS\u2014Global Information and Early Warning System Country Brief: Iraq. Available online: https:\/\/www.fao.org\/giews\/countrybrief\/country.jsp?lang=en&code=IRQ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/18\/13\/2255\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T12:06:58Z","timestamp":1783512418000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/18\/13\/2255"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,7]]},"references-count":70,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2026,7]]}},"alternative-id":["rs18132255"],"URL":"https:\/\/doi.org\/10.3390\/rs18132255","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,7]]}}}