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
Mishra, B., Bhandari, R., Bhandari, K. P., Bhandari, D. M., Luintel, N.
, Dahal, A., & Poudel, S. (2023).
High-resolution mapping of seasonal crop pattern using sentinel imagery in mountainous region of Nepal: A semi-automatic approach.
Geomatics,
3(2), 312-327.
https://doi.org/10.3390/geomatics3020017
Dahal, A.
, & Lombardo, L. (2023).
Explainable artificial intelligence in geoscience: A glimpse into the future of landslide susceptibility modeling.
Computers & geosciences,
176, [105364].
https://doi.org/10.1016/j.cageo.2023.105364
Wang, N., Zhang, H.
, Dahal, A., Cheng, W., Zhao, M.
, & Lombardo, L. (2023).
On the use of explainable AI for susceptibility modeling: examining the spatial pattern of SHAP values. Earth ArXiv.
https://doi.org/10.31223/X5P078
Tanyas, H., He, K., Sadhasivam, N.
, Lombardo, L.
, Chang, L., Fang, Z.
, Dahal, A.
, Fadel, I., Hu, X., & Luo, G. (2023).
Monitoring and prediction of InSAR-derived post-seismic hillslope deformation rates. Abstract from EGU General Assembly 2023, Vienna, Austria.
https://doi.org/10.5194/egusphere-egu23-14415
Dahal, A.
, Tanyas, H.
, van Westen, C.
, van der Meijde, M., Mai, P. M., Huser, R.
, & Lombardo, L. (2023).
Space-time modelling of co-seismic and post-seismic landslide hazard via Ensemble Neural Networks.. Abstract from EGU General Assembly 2023, Vienna, Austria.
https://doi.org/10.5194/egusphere-egu23-3496
Dahal, A., Cruz, D. A. C.
, Tanyas, H.
, Fadel, I., Mai, P. M.
, Meijde, M. V. D.
, Westen, C. V., Huser, R.
, & Lombardo, L. (2023).
From ground motion simulations to landslide occurrence prediction. Earth ArXiv.
https://doi.org/10.31223/X5WM0P
He, K.
, Lombardo, L.
, Chang, L., Sadhasivam, N., Hu, X.
, Fang, Z.
, Dahal, A.
, Fadel, I., Luo, G.
, & Tanyas, H. (2022).
Hillslope recovery after a major earthquake: InSAR-derived time series analyses to capture earthquake-legacy effect.
https://doi.org/10.31223/X5Q65W
van Westen, C., Hazarika, M. K.
, Dahal, A., Kshetri, T., Shakya, A., & Nashrrullah, S. (2022).
The RiskChanges tool for multi-hazard risk-informed planning at local government level. Abstract from EGU General Assembly 2022, Vienna, Austria.
https://doi.org/10.5194/egusphere-egu22-3026
Dahal, A.
, & Lombardo, L. (2022).
Explainable artificial intelligence in geoscience: a glimpse into the future of landslide susceptibility modeling. Earth and Space Science Open Archive.
https://doi.org/10.1002/essoar.10512130.1
Pure Link
Google Scholar Link
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