Expertises
Engineering & Materials Science
# Deep Learning
# Disasters
# Geographic Information Systems
# Landslides
# Population Distribution
# Satellite Imagery
Earth & Environmental Sciences
# Landslide
# Population Distribution
Faculty of Geo-Information Science and Earth Observation (ITC), Department of Applied Earth Sciences (AES)Onderzoek
Geo-AI Based Modelling of Earthquake Induced Landslides Using Ground Motion Simulation
Publicaties
Recent
Wang, N., Zhang, H.
, Dahal, A., Cheng, W., Zhao, M.
, & Lombardo, L. (2024).
On the use of explainable AI for susceptibility modeling: Examining the spatial pattern of SHAP values.
Geoscience Frontiers,
15(4), Article 101800.
https://doi.org/10.1016/j.gsf.2024.101800
Dahal, A.
, Tanyaș, H.
, & Lombardo, L. (2024).
Full seismic waveform analysis combined with transformer neural networks improves coseismic landslide prediction.
Communications Earth and Environment,
5(75), Article 75. Advance online publication.
https://doi.org/10.1038/s43247-024-01243-8
Cisneros, D., Richards, J.
, Dahal, A.
, Lombardo, L., & Huser, R. (2024).
Deep graphical regression for jointly moderate and extreme Australian wildfires.
Spatial statistics,
59, Article 100811.
https://doi.org/10.1016/j.spasta.2024.100811
Wang, T.
, Dahal, A.
, Fang, Z.
, van Westen, C., Yin, K.
, & Lombardo, L. (2024).
From spatio-temporal landslide susceptibility to landslide risk forecast.
Geoscience Frontiers,
15(2), Article 101765.
https://doi.org/10.1016/j.gsf.2023.101765
Ahmed, M.
, Tanyaș, H., Huser, R.
, Dahal, A., Titti, G., Borgatti, L., Francioni, M.
, & Lombardo, L. (2023).
Dynamic rainfall-induced landslide susceptibility: A step towards a unified forecasting system.
International Journal of Applied Earth Observation and Geoinformation,
125, Article 103593.
https://doi.org/10.1016/j.jag.2023.103593
Fang, Z.
, Tanyaș, H.
, Gorum, T.
, Dahal, A., Wang, Y.
, & Lombardo, L. (2023).
Speech-recognition in landslide predictive modelling: A case for a next generation early warning system.
Environmental Modelling and Software,
170, Article 105833.
https://doi.org/10.1016/j.envsoft.2023.105833
Dahal, A., Castro-Cruz, D. A.
, Tanyaş, H.
, Fadel, I., Mai, P. M.
, van der Meijde, M.
, van Westen, C., Huser, R.
, & Lombardo, L. (2023).
From ground motion simulations to landslide occurrence prediction.
Geomorphology,
441, Article 108898.
https://doi.org/10.1016/j.geomorph.2023.108898
He, K.
, Lombardo, L.
, Chang, L., Sadhasivam, N., Hu, X.
, Fang, Z.
, Dahal, A.
, Fadel, I., Luo, G.
, & Tanyas, H. (2023).
Investigating earthquake legacy effect on hillslope deformation using InSAR-derived time series.
Earth surface processes and landforms, 1-11.
https://doi.org/10.1002/esp.5746
Elia, L., Castellaro, S.
, Dahal, A.
, & Lombardo, L. (2023).
Assessing multi-hazard susceptibility to cryospheric hazards: Lesson learnt from an Alaskan example.
Science of the total environment,
898, Article 165289.
https://doi.org/10.1016/j.scitotenv.2023.165289
Cisneros, D., Richards, J.
, Dahal, A.
, Lombardo, L., & Huser, R. (2023).
Deep graphical regression for jointly moderate and extreme Australian wildfires. ArXiv.org.
https://doi.org/10.48550/arXiv.2308.14547
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Contactgegevens
Bezoekadres
Universiteit Twente
Faculty of Geo-Information Science and Earth Observation
Langezijds
(gebouwnr. 19), kamer 2419
Hallenweg 8
7522NH Enschede
Postadres
Universiteit Twente
Faculty of Geo-Information Science and Earth Observation
Langezijds
2419
Postbus 217
7500 AE Enschede