Classification of RASAT Satellite Images Using Machine Learning Algorithms

Basit Öğe Kaydı
dc.authoridK. M. Abujayyab, Sohaib/0000-0002-6692-3567
dc.contributor.authorAbujayyab, Sohaib K. M.
dc.contributor.authorYucer, Emre
dc.contributor.authorKaras, I. R.
dc.contributor.authorGultekin, I. H.
dc.contributor.authorAbali, O.
dc.contributor.authorBektas, A. G.
dc.date.accessioned2024-09-29T15:50:52Z
dc.date.available2024-09-29T15:50:52Z
dc.date.issued2022
dc.departmentKarabük Üniversitesien_US
dc.description6th International Conference on Smart City Applications -- OCT 27-29, 2021 -- Safranbolu, TURKEYen_US
dc.description.abstractThe development in the remote sensing and geographic information systems facilitated the monitoring processes of changes in land cover and use. This article aimed to evaluate the classification accuracy of five supervised classification methods: Neural Network, Naive Bayes, K-nearest neighbors, discriminant analysis and Decision Tree using the Turkish RASAT satellite images. The Bursa area in Turkey was taken as a study area to examine the RASAT satellite images. MATLAB and Python programming languages were employed to develop the training dataset and generated the five classifiers. According to the performance analysis using confusion matrix metric, the best overall accuracy was achieved by K-nearest neighbors. the K-nearest neighbors method produced 100% performance accuracy using RASAT satellite image. This comparative analysis showed that the K-nearest neighbors can be used as a trusted method for satellite image classification.en_US
dc.identifier.doi10.1007/978-3-030-94191-8_70
dc.identifier.endpage882en_US
dc.identifier.isbn978-3-030-94191-8
dc.identifier.isbn978-3-030-94190-1
dc.identifier.issn2367-3370
dc.identifier.issn2367-3389
dc.identifier.scopus2-s2.0-85126339796en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage871en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-030-94191-8_70
dc.identifier.urihttps://hdl.handle.net/20.500.14619/3769
dc.identifier.volume393en_US
dc.identifier.wosWOS:000928840400070en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer International Publishing Agen_US
dc.relation.ispartof6th International Conference On Smart City Applicationsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectRASATen_US
dc.subjectClassificationen_US
dc.subjectSatellite imagesen_US
dc.subjectMachine learningen_US
dc.subjectK-nearest neighborsen_US
dc.subjectTurkeyen_US
dc.titleClassification of RASAT Satellite Images Using Machine Learning Algorithmsen_US
dc.typeConference Objecten_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu