Articles | Volume 15, issue 23
https://doi.org/10.5194/gmd-15-8765-2022
https://doi.org/10.5194/gmd-15-8765-2022
Methods for assessment of models
 | 
06 Dec 2022
Methods for assessment of models |  | 06 Dec 2022

Transfer learning for landslide susceptibility modeling using domain adaptation and case-based reasoning

Zhihao Wang, Jason Goetz, and Alexander Brenning

Related authors

Deciphering seasonal effects of triggering and preparatory precipitation for improved shallow landslide prediction using generalized additive mixed models
Stefan Steger, Mateo Moreno, Alice Crespi, Peter James Zellner, Stefano Luigi Gariano, Maria Teresa Brunetti, Massimo Melillo, Silvia Peruccacci, Francesco Marra, Robin Kohrs, Jason Goetz, Volkmar Mair, and Massimiliano Pittore
Nat. Hazards Earth Syst. Sci., 23, 1483–1506, https://doi.org/10.5194/nhess-23-1483-2023,https://doi.org/10.5194/nhess-23-1483-2023, 2023
Short summary
Assessing uncertainties in landslide susceptibility predictions in a changing environment (Styrian Basin, Austria)
Raphael Knevels, Helene Petschko, Herwig Proske, Philip Leopold, Aditya N. Mishra, Douglas Maraun, and Alexander Brenning
Nat. Hazards Earth Syst. Sci., 23, 205–229, https://doi.org/10.5194/nhess-23-205-2023,https://doi.org/10.5194/nhess-23-205-2023, 2023
Short summary
Exploring the relationship between temperature forecast errors and Earth system variables
Melissa Ruiz-Vásquez, Sungmin O, Alexander Brenning, Randal D. Koster, Gianpaolo Balsamo, Ulrich Weber, Gabriele Arduini, Ana Bastos, Markus Reichstein, and René Orth
Earth Syst. Dynam., 13, 1451–1471, https://doi.org/10.5194/esd-13-1451-2022,https://doi.org/10.5194/esd-13-1451-2022, 2022
Short summary
Optimizing and validating the Gravitational Process Path model for regional debris-flow runout modelling
Jason Goetz, Robin Kohrs, Eric Parra Hormazábal, Manuel Bustos Morales, María Belén Araneda Riquelme, Cristián Henríquez, and Alexander Brenning
Nat. Hazards Earth Syst. Sci., 21, 2543–2562, https://doi.org/10.5194/nhess-21-2543-2021,https://doi.org/10.5194/nhess-21-2543-2021, 2021
Short summary
Vegetation modulates the impact of climate extremes on gross primary production
Milan Flach, Alexander Brenning, Fabian Gans, Markus Reichstein, Sebastian Sippel, and Miguel D. Mahecha
Biogeosciences, 18, 39–53, https://doi.org/10.5194/bg-18-39-2021,https://doi.org/10.5194/bg-18-39-2021, 2021
Short summary

Related subject area

Numerical methods
CHONK 1.0: landscape evolution framework: cellular automata meets graph theory
Boris Gailleton, Luca C. Malatesta, Guillaume Cordonnier, and Jean Braun
Geosci. Model Dev., 17, 71–90, https://doi.org/10.5194/gmd-17-71-2024,https://doi.org/10.5194/gmd-17-71-2024, 2024
Short summary
Perspectives of physics-based machine learning strategies for geoscientific applications governed by partial differential equations
Denise Degen, Daniel Caviedes Voullième, Susanne Buiter, Harrie-Jan Hendricks Franssen, Harry Vereecken, Ana González-Nicolás, and Florian Wellmann
Geosci. Model Dev., 16, 7375–7409, https://doi.org/10.5194/gmd-16-7375-2023,https://doi.org/10.5194/gmd-16-7375-2023, 2023
Short summary
Calibration of absorbing boundary layers for geoacoustic wave modeling in pseudo-spectral time-domain methods
Carlos Spa, Otilio Rojas, and Josep de la Puente
Geosci. Model Dev., 16, 7237–7252, https://doi.org/10.5194/gmd-16-7237-2023,https://doi.org/10.5194/gmd-16-7237-2023, 2023
Short summary
GeoINR 1.0: an implicit neural network approach to three-dimensional geological modelling
Michael Hillier, Florian Wellmann, Eric A. de Kemp, Boyan Brodaric, Ernst Schetselaar, and Karine Bédard
Geosci. Model Dev., 16, 6987–7012, https://doi.org/10.5194/gmd-16-6987-2023,https://doi.org/10.5194/gmd-16-6987-2023, 2023
Short summary
An automatic mesh generator for coupled 1D/2D hydrodynamic models
Younghun Kang and Ethan J. Kubatko
EGUsphere, https://doi.org/10.5194/egusphere-2023-1434,https://doi.org/10.5194/egusphere-2023-1434, 2023
Short summary

Cited articles

Ai, X., Sun, B., and Chen, X.: Construction of small sample seismic landslide susceptibility evaluation model based on transfer learning: a case study of Jiuzhaigou earthquake, B. Eng. Geol. Environ., 81, 116, https://doi.org/10.1007/s10064-022-02601-6, 2022. 
Baktashmotlagh, M., Harandi, M. T., Lovell, B. C., and Salzmann, M.: Unsupervised domain adaptation by domain invariant projection, IEEE I. Conf. Comp. Vis., 1–8 December, 769–776, https://doi.org/10.1109/ICCV.2013.100, 2013. 
Bannour, W., Maalel, A., and Ben Ghezala, H. H.: Emergency management case-based reasoning systems: a survey of recent developments, J. Exp. Theor. Artif. In., 1–24, https://doi.org/10.1080/0952813x.2021.1952654, 2021. 
Ben-David, S., Blitzer, J., Crammer, K., Kulesza, A., Pereira, F., and Vaughan, J. W.: A theory of learning from different domains, Mach. Learn., 79, 151–175, https://doi.org/10.1007/s10994-009-5152-4, 2010. 
Bordoni, M., Galanti, Y., Bartelletti, C., Persichillo, M. G., Barsanti, M., Giannecchini, R., Avanzi, G. D., Cevasco, A., Brandolini, P., Galve, J. P., and Meisina, C.: The influence of the inventory on the determination of the rainfall-induced shallow landslides susceptibility using generalized additive models, Catena, 193, 104630, https://doi.org/10.1016/j.catena.2020.104630, 2020. 
Download
Short summary
A lack of inventory data can be a limiting factor in developing landslide predictive models, which are crucial for supporting hazard policy and decision-making. We show how case-based reasoning and domain adaptation (transfer-learning techniques) can effectively retrieve similar landslide modeling situations for prediction in new data-scarce areas. Using cases in Italy, Austria, and Ecuador, our findings support the application of transfer learning for areas that require rapid model development.