{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T16:02:30Z","timestamp":1781107350151,"version":"3.54.1"},"reference-count":68,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2020,5,27]],"date-time":"2020-05-27T00:00:00Z","timestamp":1590537600000},"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>The increased development of computer vision technology combined with the increased availability of innovative platforms with ultra-high-resolution sensors, has generated new opportunities and fields for investigation in the engineering geology domain in general and landslide identification and characterization in particular. During the last decade, the so-called Unmanned Aerial Vehicles (UAVs) have been evaluated for diverse applications such as 3D terrain analysis, slope stability, mass movement hazard and risk management. Their advantages of detailed data acquisition at a low cost and effective performance identifies them as leading platforms for site-specific 3D modelling. In this study, the proposed methodology has been developed based on Object-Based Image Analysis (OBIA) and fusion of multivariate data resulted from UAV photogrammetry processing in order to take full advantage of the produced data. Two landslide case studies within the territory of Greece, with different geological and geomorphological characteristics, have been investigated in order to assess the developed landslide detection and characterization algorithm performance in distinct scenarios. The methodology outputs demonstrate the potential for an accurate characterization of individual landslide objects within this natural process based on ultra high-resolution data from close range photogrammetry and OBIA techniques for landslide conceptualization. This proposed study shows that UAV-based landslide modelling on the specific case sites provides a detailed characterization of local scale events in an automated sense with high adaptability on the specific case site.<\/jats:p>","DOI":"10.3390\/rs12111711","type":"journal-article","created":{"date-parts":[[2020,5,28]],"date-time":"2020-05-28T12:36:58Z","timestamp":1590669418000},"page":"1711","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":68,"title":["Object-Based Analysis Using Unmanned Aerial Vehicles (UAVs) for Site-Specific Landslide Assessment"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6514-7789","authenticated-orcid":false,"given":"Efstratios","family":"Karantanellis","sequence":"first","affiliation":[{"name":"Laboratory of Engineering Geology and Hydrogeology, Department of Geology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7575-7006","authenticated-orcid":false,"given":"Vassilis","family":"Marinos","sequence":"additional","affiliation":[{"name":"Laboratory of Engineering Geology and Hydrogeology, Department of Geology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1175-3628","authenticated-orcid":false,"given":"Emmanuel","family":"Vassilakis","sequence":"additional","affiliation":[{"name":"Remote Sensing Laboratory, Department of Geology and Geoenvironment, National and Kapodistrian University of Athens, 15784 Zografou, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Basile","family":"Christaras","sequence":"additional","affiliation":[{"name":"Laboratory of Engineering Geology and Hydrogeology, Department of Geology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,27]]},"reference":[{"key":"ref_1","first-page":"325","article-title":"Identification of landslide hazard and risk \u201chotspots\u201d in Europe","volume":"73","author":"Jaedicke","year":"2014","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_2","unstructured":"Vassilakis, E., Foumelis, M., Erkeki, A., Kotsi, E., Parcharidis, I., and Lekkas, E. (2019). Multitemporal Surface Deformation Analysis of Amyntaio Slide (Greece) Using Remotely Piloted Airborne System and Structure-from-Motion photogrammetry, National and Kapodistrian University of Athens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.enggeo.2018.08.010","article-title":"Mapping an earthquake-induced landslide based on UAV imagery; case study of the 2015 Okeanos landslide, Lefkada, Greece","volume":"245","author":"Valkaniotis","year":"2018","journal-title":"Eng. Geol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.earscirev.2012.02.001","article-title":"Landslide inventory maps: New tools for an old problem","volume":"112","author":"Guzzetti","year":"2012","journal-title":"Earth-Sci. Rev."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1079","DOI":"10.5194\/nhess-18-1079-2018","article-title":"Review article: The use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management","volume":"18","author":"Giordan","year":"2018","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_6","first-page":"209","article-title":"Recommendations for the quantitative analysis of landslide risk","volume":"73","author":"Corominas","year":"2014","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2715","DOI":"10.5194\/nhess-11-2715-2011","article-title":"Landslide mapping with multi-scale object-based image analysis\u2014A case study in the Baichi watershed, Taiwan","volume":"11","author":"Lahousse","year":"2011","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1007\/s10064-005-0023-0","article-title":"Landslide hazard and risk zonation\u2014Why is it still so difficult?","volume":"65","author":"Soeters","year":"2006","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/j.enggeo.2008.03.018","article-title":"A review of assessing landslide frequency for hazard zoning purposes","volume":"102","author":"Corominas","year":"2008","journal-title":"Eng. Geol."},{"key":"ref_10","first-page":"92","article-title":"Landslide mapping and monitoring by using radar and optical remote sensing: Examples from the EC-FP7 project SAFER","volume":"4","author":"Casagli","year":"2016","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"9600","DOI":"10.3390\/rs6109600","article-title":"Remote sensing for landslide investigations: An overview of recent achievements and perspectives","volume":"6","author":"Scaioni","year":"2014","journal-title":"Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Zhao, C., and Lu, Z. (2018). Remote sensing of landslides\u2014A review. Remote Sens., 10.","DOI":"10.3390\/rs10020279"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1843","DOI":"10.1080\/01431160600935638","article-title":"Comparison between automated and manual mapping of typhoon-triggered landslides from SPOT-5 imagery","volume":"28","author":"Borghuis","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Joyce, K., Samsonov, S., and Jolly, G. (2008, January 11\u201314). Satellite remote sensing of volcanic activity in New Zealand. Proceedings of the 2008 Second Workshop on Use of Remote Sensing Techniques for Monitoring Volcanoes and Seismogenic Areas, Napoli, Italy.","DOI":"10.1109\/USEREST.2008.4740346"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.isprsjprs.2013.09.014","article-title":"Geographic object-based image analysis\u2014Towards a new paradigm","volume":"87","author":"Blaschke","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.isprsjprs.2019.02.009","article-title":"Segmentation for Object-Based Image Analysis (OBIA): A review of algorithms and challenges from remote sensing perspective","volume":"150","author":"Hossain","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1016\/j.geomorph.2013.09.012","article-title":"Producing a landslide inventory map using pixel-based and object-oriented approaches optimized by Taguchi method","volume":"204","author":"Moosavi","year":"2014","journal-title":"Geomorphology"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1101","DOI":"10.1016\/j.asr.2008.11.008","article-title":"Hierarchical object oriented classification using very high resolution imagery and LIDAR data over urban areas","volume":"43","author":"Chen","year":"2009","journal-title":"Adv. Space Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1876","DOI":"10.1080\/01431161.2013.879350","article-title":"Improving detailed rule-based feature extraction of urban areas from WorldView-2 image and lidar data","volume":"35","author":"Hamedianfar","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Berhane, T., Lane, C., Wu, Q., Anenkhonov, O., Chepinoga, V., Autrey, B., and Liu, H. (2017). Comparing pixel- and object-based approaches in effectively classifying wetland-dominated landscapes. Remote Sens., 10.","DOI":"10.3390\/rs10010046"},{"key":"ref_21","first-page":"1","article-title":"A comparative analysis of pixel- and object-based detection of landslides from very high-resolution images","volume":"64","author":"Keyport","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2354","DOI":"10.1109\/TGRS.2003.815972","article-title":"A combined fuzzy pixel-based and object-based approach for classification of high-resolution multispectral data over urban areas","volume":"41","author":"Shackelford","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Ho, P.-G. (2011). Segmentation of remotely sensed imagery: Moving from sharp objects to fuzzy regions. Image Segmentation, InTechOpen.","DOI":"10.5772\/628"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.isprsjprs.2013.11.018","article-title":"Automated parameterisation for multi-scale image segmentation on multiple layers","volume":"88","author":"Csillik","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1007\/s12524-017-0685-7","article-title":"A tool assessing optimal multi-scale image segmentation","volume":"46","author":"Kamala","year":"2018","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"4318","DOI":"10.3390\/rs70404318","article-title":"Automatic case-based reasoning approach for landslide detection: Integration of object-oriented image analysis and a genetic algorithm","volume":"7","author":"Dou","year":"2015","journal-title":"Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"4928","DOI":"10.1109\/TGRS.2011.2151866","article-title":"Segment optimization and data-driven thresholding for knowledge-based landslide detection by object-based image analysis","volume":"49","author":"Martha","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2564","DOI":"10.1016\/j.rse.2011.05.013","article-title":"Object-oriented mapping of landslides using Random Forests","volume":"115","author":"Stumpf","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Chen, T., Trinder, J., and Niu, R. (2017). Object-oriented landslide mapping using ZY-3 satellite imagery, random forest and mathematical morphology, for the Three-Gorges Reservoir, China. Remote Sens., 9.","DOI":"10.3390\/rs9040333"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1080\/15481603.2018.1426091","article-title":"Comparing fully convolutional networks, random forest, support vector machine, and patch-based deep convolutional neural networks for object-based wetland mapping using images from small unmanned aircraft system","volume":"55","author":"Liu","year":"2018","journal-title":"GISci. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Mezaal, M.R., Pradhan, B., Sameen, M.I., Mohd Shafri, H.Z., and Yusoff, Z.M. (2017). Optimized neural architecture for automatic landslide detection from high-resolution airborne laser scanning data. Appl. Sci., 7.","DOI":"10.3390\/app7070730"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Karantanellis, E., Marinos, V., and Vassilakis, E. (2019). 3D hazard analysis and object-based characterization of landslide motion mechanism using UAV imagery. ISPRS-Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., 425\u2013430.","DOI":"10.5194\/isprs-archives-XLII-2-W13-425-2019"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.isprsjprs.2009.06.004","article-title":"Object based image analysis for remote sensing","volume":"65","author":"Blaschke","year":"2010","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"H\u00f6lbling, D., Eisank, C., Albrecht, F., Vecchiotti, F., Friedl, B., Weinke, E., and Kociu, A. (2017). Comparing manual and semi-automated landslide mapping based on optical satellite images from different sensors. Geosciences, 7.","DOI":"10.3390\/geosciences7020037"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1111\/phor.12215","article-title":"Object-based classification of terrestrial laser scanning point clouds for landslide monitoring","volume":"32","author":"Mayr","year":"2017","journal-title":"Photogramm. Rec."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Farmakis, I., Marinos, V., Papathanassiou, G., and Karantanellis, E. (2020). Automated 3D jointed rock mass structural analysis and characterization using LiDAR terrestrial laser scanner for rockfall susceptibility assessment: Perissa area case (Santorini). Geotech. Geol. Eng.","DOI":"10.1007\/s10706-020-01203-x"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12518-013-0120-x","article-title":"UAV for 3D mapping applications: A review","volume":"6","author":"Nex","year":"2014","journal-title":"Appl. Geomat."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2143","DOI":"10.5194\/nhess-17-2143-2017","article-title":"Brief communication: Landslide motion from cross correlation of UAV-derived morphological attributes","volume":"17","author":"Peppa","year":"2017","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_39","unstructured":"Eisenbei\u00df, H. (2009). UAV Photogrammetry, ETH, Inst. f\u00fcr Geod\u00e4sie und Photogrammetrie. Mitteilungen\/Institut f\u00fcr Geod\u00e4sie und Photogrammetrie an der Eidgen\u00f6ssischen Technischen Hochschule Z\u00fcrich."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.enggeo.2017.11.004","article-title":"Unmanned Aerial Vehicle (UAV) based mapping in engineering geological surveys: Considerations for optimum results","volume":"232","author":"Tziavou","year":"2018","journal-title":"Eng. Geol."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1177\/0309133313515293","article-title":"Mapping landslide displacements using Structure from Motion (SfM) and image correlation of multi-temporal UAV photography","volume":"38","author":"Lucieer","year":"2014","journal-title":"Prog. Phys. Geogr. Earth Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.isprsjprs.2014.02.013","article-title":"Unmanned aerial systems for photogrammetry and remote sensing: A review","volume":"92","author":"Colomina","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_43","unstructured":"Bendea, H., Boccardo, P., Dequal, S., Tonolo, F.G., Marenchino, D., and Piras, M. (2008, January 3\u201311). Low cost UAV for post-disaster assessment. Proceedings of the XXIst ISPRS Congress: International Society for Photogrammetry and Remote Sensing, Beijing, China."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"011001","DOI":"10.1088\/1742-6596\/755\/1\/011001","article-title":"International Conference on Recent Trends in Physics 2016 (ICRTP2016)","volume":"755","author":"Tahar","year":"2016","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1736","DOI":"10.3390\/rs70201736","article-title":"Time series analysis of landslide dynamics using an Unmanned Aerial Vehicle (UAV)","volume":"7","author":"Turner","year":"2015","journal-title":"Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.cageo.2014.04.012","article-title":"Semi-automatic mapping of geological Structures using UAV-based photogrammetric data: An image analysis approach","volume":"69","author":"Vasuki","year":"2014","journal-title":"Comput. Geosci."},{"key":"ref_47","first-page":"496","article-title":"Nav-based remote sensing of landslides","volume":"38","author":"Niethammer","year":"2010","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci.-ISPRS Arch."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"3390","DOI":"10.3390\/rs4113390","article-title":"Unmanned aerial vehicle (UAV) for monitoring soil erosion in Morocco","volume":"4","author":"Marzolff","year":"2012","journal-title":"Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"476","DOI":"10.1002\/rob.21586","article-title":"Use of a small unmanned aerial system for the SR-530 Mudslide Incident near Oso, Washington","volume":"33","author":"Murphy","year":"2016","journal-title":"J. Field Robot."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Rau, J.Y., Jhan, J.P., Lo, C.F., and Lin, Y.S. (2012). Landslide mapping using imagery acquired by a fixed-wing Uav. ISPRS-Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., 195\u2013200.","DOI":"10.5194\/isprsarchives-XXXVIII-1-C22-195-2011"},{"key":"ref_51","first-page":"277","article-title":"Application of 3D laser scanner for monitoring of landslide hazards","volume":"XXXVII","author":"Sui","year":"2008","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_52","unstructured":"Koma, Z., Sz\u00e9kely, B., Dorninger, P., Rasztovits, S., and Roncat, A. (May, January 27). Comparison of UAV and TLS DTMs for acquisition of geological, geomorphological information for Doren landslide. Proceedings of the European Geosciences Union General Assembly 2014, Vienna, Austria."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1111\/phor.12063","article-title":"State of the art in high density image matching","volume":"29","author":"Remondino","year":"2014","journal-title":"Photogramm. Rec."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1007\/BF00127003","article-title":"The great Minoan eruption of Thera volcano and the ensuing tsunami in the Greek Archipelago","volume":"5","author":"Antonopoulos","year":"1992","journal-title":"Nat. Hazards"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.geomorph.2009.12.015","article-title":"Rockfall susceptibility map for Athinios port, Santorini Island, Greece","volume":"118","author":"Antoniou","year":"2010","journal-title":"Geomorphology"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1007\/s12665-017-6823-2","article-title":"Beyond the boundaries of feasible engineering geological solutions: Stability considerations of the spectacular Red Beach cliffs on Santorini Island, Greece","volume":"76","author":"Marinos","year":"2017","journal-title":"Environ. Earth Sci."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s12518-015-0165-0","article-title":"UAV monitoring and documentation of a large landslide","volume":"8","author":"Lindner","year":"2016","journal-title":"Appl. Geomat."},{"key":"ref_58","unstructured":"Pix4D (2019). Pix4D www.pix4d.com, S.A., Pix4D."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1007\/s10346-013-0436-y","article-title":"The Varnes classification of landslide types, an update","volume":"11","author":"Hungr","year":"2014","journal-title":"Landslides"},{"key":"ref_60","unstructured":"Turner, A.K., and Schuster, R.L. (1996). Landslides: Investigation and Mitigation, National Academy Press. Special Report\/Transportation Research Board, National Research Council."},{"key":"ref_61","unstructured":"(2019). eCognition Developer, Trimble."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1016\/j.geomorph.2014.02.028","article-title":"Assessment of multiresolution segmentation for delimiting drumlins in digital elevation models","volume":"214","author":"Eisank","year":"2014","journal-title":"Geomorphology"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1007\/s12145-015-0217-3","article-title":"An object-based approach for semi-automated landslide change detection and attribution of changes to landslide classes in northern Taiwan","volume":"8","author":"Friedl","year":"2015","journal-title":"Earth Sci. Inform."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Comert, R., Avdan, U., and Gorum, T. (2018). Rapid mapping of forested landslide from ultra-high resolution unmanned aerial vehicle data. ISPRS-Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., 171\u2013176.","DOI":"10.5194\/isprs-archives-XLII-3-W4-171-2018"},{"key":"ref_65","first-page":"12","article-title":"Multi resolution Segmentation: An optimum approach for high quality multi scale image segmentation","volume":"XII","author":"Baatz","year":"2000","journal-title":"Proc. Angew. Geogr. Inf."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"259","DOI":"10.13031\/2013.27838","article-title":"Color indices for weed identification under various soil, residue, and lighting conditions","volume":"38","author":"Woebbecke","year":"1995","journal-title":"Trans. ASAE"},{"key":"ref_67","first-page":"135","article-title":"Geological lineament interpretation using the Object-based Image Analysis approach: Results of semi-automated analyses versus visual interpretation","volume":"57","author":"Middleton","year":"2015","journal-title":"Geol. Surv. Finl."},{"key":"ref_68","first-page":"397","article-title":"Accuracy assessment: A user\u2019s perspective","volume":"52","author":"Story","year":"1986","journal-title":"Am. Soc. Photogramm. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/11\/1711\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:32:56Z","timestamp":1760175176000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/11\/1711"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,27]]},"references-count":68,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2020,6]]}},"alternative-id":["rs12111711"],"URL":"https:\/\/doi.org\/10.3390\/rs12111711","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,27]]}}}