prof.dr. C.J. van Westen (Cees)

Hoogleraar
ITC-AES
Langezijds 1432
c.j.vanwesten@utwente.nl
+31534874263
Visitekaartje

Expertises

  • Earth and Planetary Sciences

    • Landslide
    • Model
    • Hazard
    • Inventory
    • Datum
    • Earthquake
    • India
    • Investigation

Organisaties

Nevenwerkzaakheden

  • UN-APCICTRegular training courses
  • European Research CouncilReview Panel for European Research Council

Publicaties

2024
Event-based rainfall-induced landslide inventories and rainfall thresholds for Malawi, 1403-1424. Niyokwiringirwa, P., Lombardo, L., Dewitte, O., Deijns, A. A. J., Wang, N., Van Westen, C. J. & Tanyas, H.https://doi.org/10.1007/s10346-023-02203-7Space-time modeling of landslide size by combining static, dynamic, and unobserved spatiotemporal factors, Article 107989. Fang, Z., Wang, Y., van Westen, C. & Lombardo, L.https://doi.org/10.1016/j.catena.2024.107989Application of beta regression for the prediction of landslide areal density in South Tyrol, Italy . Moreno, M., Opitz, T., Steger, S., Westen, C. v. & Lombardo, L.https://doi.org/10.5194/egusphere-egu24-17785Space–time landslide hazard modeling via Ensemble Neural Networks, 823-845. Dahal, A., Tanyaș, H., Westen, C. v., Meijde, M. v. d., Mai, P. M., Huser, R. & Lombardo, L.https://doi.org/10.5194/nhess-24-823-2024From spatio-temporal landslide susceptibility to landslide risk forecast, Article 101765. Wang, T., Dahal, A., Fang, Z., van Westen, C., Yin, K. & Lombardo, L.https://doi.org/10.1016/j.gsf.2023.101765Space-time data-driven modeling of precipitation-induced shallow landslides in South Tyrol, Italy, Article 169166, 1-17. Moreno, M., Lombardo, L., Crespi, A., Zellner, P. J., Mair, V., Pittore, M., van Westen, C. J. & Steger, S.https://doi.org/10.1016/j.scitotenv.2023.169166Unveiling spatial inequalities: Exploring county-level disaster damages and social vulnerability on public disaster assistance in contiguous US, Article 119690, 1-12. Han, Y., Jia, H., Xu, C., Bočkarjova, M., van Westen, C. J. & Lombardo, L.https://doi.org/10.1016/j.jenvman.2023.119690Landslide hazard spatiotemporal prediction based on data-driven models: Estimating where, when and how large landslide may be, Article 103631. Fang, Z., Wang, Y., van Westen, C. & Lombardo, L.https://doi.org/10.1016/j.jag.2023.103631Standing on the shoulder of a giant landslide: A six-year long InSAR look at a slow-moving hillslope in the western Karakoram, Article 108959, 1-17. Ahmad, S. M., Sadhasivam, N., Lisa, M., Lombardo, L., Emil, M. K., Zaki, A., Van Westen, C. J., Fadel, I. & Tanyas, H.https://doi.org/10.1016/j.geomorph.2023.108959
2023
Mapping landslides through a temporal lens: an insight toward multi-temporal landslide mapping using the u-net deep learning model, Article 2182057. Bhuyan, K., Meena, S. R., Nava, L., van Westen, C., Floris, M. & Catani, F.https://doi.org/10.1080/15481603.2023.2182057From ground motion simulations to landslide occurrence prediction, Article 108898. Dahal, A., Castro-Cruz, D. A., Tanyaş, H., Fadel, I., Mai, P. M., van der Meijde, M., van Westen, C., Huser, R. & Lombardo, L.https://doi.org/10.1016/j.geomorph.2023.108898Mapping and characterising buildings for flood exposure analysis using open-source data and artificial intelligence, 805-835. Bhuyan, K., van Westen, C., Wang, J. & Meena, S. R.https://doi.org/10.1007/s11069-022-05612-4Impact-based probabilistic modeling of hydro-morphological processes in China (1985–2015), Article 118463. Wang, N., Cheng, W., Zhang, H., van Westen, C., Xiong, J., Liu, C. & Lombardo, L.https://doi.org/10.1016/j.jenvman.2023.118463Space–Time Landslide Susceptibility Modeling Based on Data-Driven Methods (E-pub ahead of print/First online). Fang, Z., Wang, Y., van Westen, C. & Lombardo, L.https://doi.org/10.1007/s11004-023-10105-6A breakthrough in fast flood simulation, Article 105787. van den Bout, B., Jetten, V. G., van Westen, C. J. & Lombardo, L.https://doi.org/10.1016/j.envsoft.2023.105787Space-time data-driven modeling of precipitation-induced shallow landslides in South Tyrol, Italy. Earth ArXiv. Moreno, M., Lombardo, L., Crespi, A., Zellner, P., Mair, V., Pittore, M., van Westen, C. & Steger, S.https://doi.org/10.31223/X59M3JFrom space-time landslide susceptibility to landslide risk forecast. Earth ArXiv. Wang, T., Dahal, A., Fang, Z., van Westen, C., Yin, K. & Lombardo, L.https://doi.org/10.31223/X5XT1FFunctional regression for space-time prediction of precipitation-induced shallow landslides in South Tyrol, Italy . Moreno, M., Steger, S., Lombardo, L., Opitz, T., Crespi, A., Marra, F., Vugt, L. d., Zieher, T., Rutzinger, M., Mair, V., Pittore, M. & van Westen, C.https://doi.org/10.5194/egusphere-egu23-9538Space-time landslide size modelling in Taiwan. Lombardo, L., Fang, Z., Wang, Y. & van Westen, C.https://doi.org/10.5194/egusphere-egu23-6999Space-time modelling of co-seismic and post-seismic landslide hazard via Ensemble Neural Networks.. Dahal, A., Tanyas, H., van Westen, C., van der Meijde, M., Mai, P. M., Huser, R. & Lombardo, L.https://doi.org/10.5194/egusphere-egu23-3496Fastflood.org, an open-source super-fast flood model in the browser. van den Bout, B., Jetten, V., van Westen, C. & Lombardo, L.https://doi.org/10.5194/egusphere-egu23-3611From ground motion simulations to landslide occurrence prediction. Earth ArXiv. Dahal, A., Cruz, D. A. C., Tanyas, H., Fadel, I., Mai, P. M., Meijde, M. v. d., Westen, C. v., Huser, R. & Lombardo, L.https://doi.org/10.31223/X5WM0PSpatio-temporal evolution of glacial lakes in the Tibetan Plateau over the past 30 years, Article 416. Dou, X., Fan, X., Wang, X., Yunus, A. P., Xiong, J., Tang, R., Lovati, M., van Westen, C. & Xu, Q.https://doi.org/10.3390/rs15020416Generating multi-temporal landslide inventories through a general deep transfer learning strategy using HR EO data, Article 162. Bhuyan, K., Tanyaş, H., Nava, L., Puliero, S., Meena, S. R., Floris, M., van Westen, C. & Catani, F.https://doi.org/10.1038/s41598-022-27352-yRealities of bridge resilience in Small Island Developing States, Article 1. Trigg, M. A., Dehghani, M. S., Kesete, Y. Y., Carr, A. B., Trigg, S. G., Zekkos, D., Lopez, D., Pertierra, M., van Westen, C., Jetten, V. & Ogden, F. L.https://doi.org/10.1007/s11027-022-10035-4

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Vakken collegejaar 2023/2024

Vakken in het huidig collegejaar worden toegevoegd op het moment dat zij definitief zijn in het Osiris systeem. Daarom kan het zijn dat de lijst nog niet compleet is voor het gehele collegejaar.

Vakken collegejaar 2022/2023

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