Land use/land cover classification for the iron mining site of Kishushe, Kenya: A feasibility study of traditional and machine learning algorithms

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Siljander , M , Adero , N J , Gitau , F & Nyambu , E 2020 , ' Land use/land cover classification for the iron mining site of Kishushe, Kenya: A feasibility study of traditional and machine learning algorithms ' , African Journal of Mining, Entrepreneurship and Natural Resource Management (AJMENRM) , vol. 1 , no. 2 . < http://www.ajmenrm.ttu.ac.ke/admin/img/paper/Land%20use-land%20cover%20classification%20for%20the%20iron%20mining%20site%20of%20Kishushe%20Kenya_A%20feasibility%20study%20of%20traditional%20and%20machine%20learning%20algorithms.pdf >

Title: Land use/land cover classification for the iron mining site of Kishushe, Kenya: A feasibility study of traditional and machine learning algorithms
Author: Siljander, Mika; Adero, Nashon Juma; Gitau, Francis; Nyambu, Emmanuel
Contributor: University of Helsinki, Department of Geosciences and Geography
Date: 2020
Belongs to series: African Journal of Mining, Entrepreneurship and Natural Resource Management (AJMENRM)
ISSN: 2706-6002
URI: http://hdl.handle.net/10138/326921
Subject: 1171 Geosciences
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