Pixel-based classification method for earthquake-induced landslide mapping using remotely sensed imagery, geospatial data and temporal change information
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DOI: 10.1007/s11069-023-06399-8
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- Yang Hong & Robert Adler & George Huffman, 2007. "Use of satellite remote sensing data in the mapping of global landslide susceptibility," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 43(2), pages 245-256, November.
- Kemal Hacıefendioğlu & Gökhan Demir & Hasan Basri Başağa, 2021. "Landslide detection using visualization techniques for deep convolutional neural network models," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 109(1), pages 329-350, October.
- Thomas Stanley & Dalia B. Kirschbaum, 2017. "A heuristic approach to global landslide susceptibility mapping," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(1), pages 145-164, May.
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Keywords
Machine learning; Pixel-based classification; Landslide mapping; 2016 Kumamoto earthquake; Feature ranking; Logistic regression;All these keywords.
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