Landslide susceptibility mapping using physics-guided machine learning: a case study of a debris flow event in Colorado Front Range
Author:
Funder
Google AI Impacts Challenge Grant
National Science Foundation
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11440-024-02384-y.pdf
Reference108 articles.
1. Anderson RS, Riihimaki CA, Safran EB, MacGregor KR (2006) Facing reality: late Cenozoic evolution of smooth peaks, glacially ornamented valleys, and deep river gorges of Colorado’s Front Range. In: Tectonics, climate, and landscape evolution. Geological Society of America, pp 397–418. https://doi.org/10.1130/2006.2398(25)
2. Anderson SW, Anderson SP, Anderson RS (2015) Exhumation by debris flows in the 2013 Colorado Front Range storm. Geology 43:391–394. https://doi.org/10.1130/g36507.1
3. Agarap AF (2018) Deep learning using rectified linear units (relu). arXiv preprint arXiv:1803.08375. https://doi.org/10.48550/arXiv.1803.08375
4. Bowles JE (1979) Physical and geotechnical properties of soils. McGraw-Hill, Incorporated, New York, NY
5. Birkeland PW, Shroba RR, Burns SF, Price AB, Tonkin PJ (2003) Integrating soils and geomorphology in mountains—an example from the Front Range of Colorado. Geomorphology 55:329–344. https://doi.org/10.1016/s0169-555x(03)00148-x
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