Sharif, HaidarUyaver, ŞahinSharif, Haris Uddinİnce, İbrahim FurkanZerdo, Zaid2021-01-082021-01-08201997898113150082194-5357https://doi.org/10.1007/978-981-13-1501-5_27https://hdl.handle.net/20.500.12846/339International Conference on Emerging Technologies in Data Mining and Information Security, IEMIS 2018, 23 February 2018 through 25 February 2018, , 217929It is a challenging task to classify heterogeneous geographical features from satellite imagery. This paper addresses 31 straightforward classification algorithms based on predominantly pixels to classify miscellaneous geographical features from satellite imagery. The addressed algorithms can extract and process the features of a large dataset with high-resolution images expeditiously. A total of 606 red-green-blue satellite images of the Bosnian city of Banja Luka are exercised to comprehend their performances for classifying cemeteries, fields, houses, industries, rivers, and trees. The recorded experimental results demonstrate that the best average performance can come into possession of 87%. © Springer Nature Singapore Pte Ltd. 2019.eninfo:eu-repo/semantics/closedAccessConference Object81410.1007/978-981-13-1501-5_27309321N/A2-s2.0-85053501295