Abstract
Decision tree classification algorithms have significant potential for remote sensing data classification. This paper advances to adopt decision tree technologies to classify remote sensing images. First, this paper discussed the algorithms structure and the algorithms theory of decision tree. Second, C4.5 basic theory and boosting technology are explained. The decision tree technologies have several advantages for remote sensing application by virtue of their relatively simple, explicit and intuitive classification structure.
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© 2011 IFIP International Federation for Information Processing
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Jiang, L., Wang, W., Yang, X., Xie, N., Cheng, Y. (2011). Classification Methods of Remote Sensing Image Based on Decision Tree Technologies. In: Li, D., Liu, Y., Chen, Y. (eds) Computer and Computing Technologies in Agriculture IV. CCTA 2010. IFIP Advances in Information and Communication Technology, vol 344. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18333-1_41
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DOI: https://doi.org/10.1007/978-3-642-18333-1_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-18332-4
Online ISBN: 978-3-642-18333-1
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