Articles | Volume 21, issue 5
https://doi.org/10.5194/nhess-21-1467-2021
https://doi.org/10.5194/nhess-21-1467-2021
Invited perspectives
 | Highlight paper
 | 
11 May 2021
Invited perspectives | Highlight paper |  | 11 May 2021

Invited perspectives: Landslide populations – can they be predicted?

Fausto Guzzetti

Related authors

The ITAlian rainfall-induced LandslIdes CAtalogue, an extensive and accurate spatio-temporal catalogue of rainfall-induced landslides in Italy
Silvia Peruccacci, Stefano Luigi Gariano, Massimo Melillo, Monica Solimano, Fausto Guzzetti, and Maria Teresa Brunetti
Earth Syst. Sci. Data, 15, 2863–2877, https://doi.org/10.5194/essd-15-2863-2023,https://doi.org/10.5194/essd-15-2863-2023, 2023
Short summary
Dynamic path-dependent landslide susceptibility modelling
Jalal Samia, Arnaud Temme, Arnold Bregt, Jakob Wallinga, Fausto Guzzetti, and Francesca Ardizzone
Nat. Hazards Earth Syst. Sci., 20, 271–285, https://doi.org/10.5194/nhess-20-271-2020,https://doi.org/10.5194/nhess-20-271-2020, 2020
Short summary
Brief communication: Remotely piloted aircraft systems for rapid emergency response: road exposure to rockfall in Villanova di Accumoli (central Italy)
Michele Santangelo, Massimiliano Alvioli, Marco Baldo, Mauro Cardinali, Daniele Giordan, Fausto Guzzetti, Ivan Marchesini, and Paola Reichenbach
Nat. Hazards Earth Syst. Sci., 19, 325–335, https://doi.org/10.5194/nhess-19-325-2019,https://doi.org/10.5194/nhess-19-325-2019, 2019
Short summary
Rainfall events with shallow landslides in the Entella catchment, Liguria, northern Italy
Anna Roccati, Francesco Faccini, Fabio Luino, Laura Turconi, and Fausto Guzzetti
Nat. Hazards Earth Syst. Sci., 18, 2367–2386, https://doi.org/10.5194/nhess-18-2367-2018,https://doi.org/10.5194/nhess-18-2367-2018, 2018
Short summary
Criteria for the optimal selection of remote sensing optical images to map event landslides
Federica Fiorucci, Daniele Giordan, Michele Santangelo, Furio Dutto, Mauro Rossi, and Fausto Guzzetti
Nat. Hazards Earth Syst. Sci., 18, 405–417, https://doi.org/10.5194/nhess-18-405-2018,https://doi.org/10.5194/nhess-18-405-2018, 2018
Short summary

Related subject area

Landslides and Debris Flows Hazards
Comparison of conditioning factor classification criteria in large-scale statistically based landslide susceptibility models
Marko Sinčić, Sanja Bernat Gazibara, Mauro Rossi, and Snježana Mihalić Arbanas
Nat. Hazards Earth Syst. Sci., 25, 183–206, https://doi.org/10.5194/nhess-25-183-2025,https://doi.org/10.5194/nhess-25-183-2025, 2025
Short summary
Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems
Benjamin B. Mirus, Thom Bogaard, Roberto Greco, and Manfred Stähli
Nat. Hazards Earth Syst. Sci., 25, 169–182, https://doi.org/10.5194/nhess-25-169-2025,https://doi.org/10.5194/nhess-25-169-2025, 2025
Short summary
Predicting deep-seated landslide displacement on Taiwan's Lushan through the integration of convolutional neural networks and the Age of Exploration-Inspired Optimizer
Jui-Sheng Chou, Hoang-Minh Nguyen, Huy-Phuong Phan, and Kuo-Lung Wang
Nat. Hazards Earth Syst. Sci., 25, 119–146, https://doi.org/10.5194/nhess-25-119-2025,https://doi.org/10.5194/nhess-25-119-2025, 2025
Short summary
Limit analysis of earthquake-induced landslides considering two strength envelopes
Di Wu, Yuke Wang, and Xin Chen
Nat. Hazards Earth Syst. Sci., 24, 4617–4630, https://doi.org/10.5194/nhess-24-4617-2024,https://doi.org/10.5194/nhess-24-4617-2024, 2024
Short summary
The vulnerability of buildings to a large-scale debris flow and outburst flood hazard cascade that occurred on 30 August 2020 in Ganluo, southwest China
Li Wei, Kaiheng Hu, Shuang Liu, Lan Ning, Xiaopeng Zhang, Qiyuan Zhang, and Md. Abdur Rahim
Nat. Hazards Earth Syst. Sci., 24, 4179–4197, https://doi.org/10.5194/nhess-24-4179-2024,https://doi.org/10.5194/nhess-24-4179-2024, 2024
Short summary

Cited articles

Alexander, E. D.: Vulnerability to landslides, in: Landslide risk assessment, edited by: Glade, T., Anderson, M. G., and Crozier, M. J., John Wiley, Chichester, UK, 175–198, https://doi.org/10.1002/9780470012659.ch5, 2005. 
Alvioli, M. and Baum, R. L.: Parallelization of the TRIGRS model for rainfall-induced landslides using the message passing interface, Environ. Model. Softw,. 81, 122–135, https://doi.org/10.1016/j.envsoft.2016.04.002, 2016.  
Alvioli, M., Melillo, M., Guzzetti, F., Rossi, M., Palazzi, E., von Hardenberg, J., Brunetti, M. T., and Peruccacci, S.: Implications of climate change on landslide hazard in Central Italy, Sci. Total Environ., 630, 1528–1543, https://doi.org/10.1016/j.scitotenv.2018.02.315, 2018. 
Aschbacher, J.: ESA's Earth Observation Strategy and Copernicus, in: Satellite Earth Observations and Their Impact on Society and Policy, chap. 5, edited by: Onoda, M. and Young, O. R., Springer, Singapore, Singapore, 81–86, https://doi.org/10.1007/978-981-10-3713-9_5, 2017. 
Bellugi, D., Dietrich, W. E., Stock, J. D., McKean, J. A., Kazian, B., and Hargrove, P.: Spatially Explicit Shallow Landslide Susceptibility Mapping Over Large Areas, Ital. J. Eng. Geol. Environ., 399–407, https://doi.org/10.4408/IJEGE.2011-03.B-045, 2011. 
Short summary
This is a perspective based on personal experience on whether a large number of landslides caused by a single trigger (e.g. an earthquake, an intense rainfall, a rapid snowmelt event) or by multiple triggers in a period can be predicted, in space and time, considering the consequences of slope failures.
Altmetrics
Final-revised paper
Preprint