Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=tres20 International Journal of Remote Sensing ISSN: 0143-1161 (Print) 1366-5901 (Online) Journal homepage: https://www.tandfonline.com/loi/tres20 A comparison of machine and deep-learning algorithms applied to multisource data for a subtropical forest area classification C. Sothe, C. M. De Almeida, M. B. Schimalski, V. Liesenberg, L. E. C. La Rosa, J. D. B. Castro & R. Q. Feitosa To cite this article: C. Sothe, C. M. De Almeida, M. B. Schimalski, V. Liesenberg, L. E. C. La Rosa, J. D. B. Castro & R. Q. Feitosa (2019): A comparison of machine and deep-learning algorithms applied to multisource data for a subtropical forest area classification, International Journal of Remote Sensing, DOI: 10.1080/01431161.2019.1681600 To link to this article: https://doi.org/10.1080/01431161.2019.1681600 Published online: 28 Oct 2019. Submit your article to this journal Article views: 47 View related articles View Crossmark data