Gardoni, P., Der Kiureghian, A., Mosalam, K. M. – Probabilistic capacity models and fragility estimates for reinforced concrete columns based on experimental observations – Journal of Engineering Mechanics – 2002 Others

Gardoni, P., Mosalam, K. M., Der Kiureghian, A. – Probabilistic seismic demand models and fragility estimates for RC bridges – Journal of Earthquake Engineering – 2003 Others

Sharma, N., Tabandeh, A., Gardoni, P. – Resilience analysis: A mathematical formulation to model resilience of engineering systems – Sustainable and Resilient Infrastructure – 2018 Resilience

Xu, Y., Kohtz, S., Boakye, J., Gardoni, P., Wang, P. – Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges – Reliability Engineering & System Safety – 2023 Review

Tabandeh, A., Jia, G., Gardoni, P. – A review and assessment of importance sampling methods for reliability analysis – Structural Safety – 2022 Review

Liu, S., Wang, L., Zhang, W., Sun, W., Fu, J., Xiao, T., Dai, Z. – A physics-informed data-driven model for landslide susceptibility assessment in the Three Gorges Reservoir area – Geoscience Frontiers – 2023 Susceptibility assessment (Hybrid Models)

Liu, S., Wang, L., Zhang, W., Sun, W., Wang, Y., Liu, J. – Physics-informed optimization for a data-driven approach in landslide susceptibility evaluation – Journal of Rock Mechanics and Geotechnical Engineering – 2024 Susceptibility assessment (Hybrid Models)

Zhang, W., Li, H., Li, Y., Liu, H., Chen, Y., Ding, X. – Application of deep learning algorithms in geotechnical engineering: a short critical review – Artificial Intelligence Review – 2021 Review

Zhang, W., Gu, X., Tang, L., Yin, Y., Liu, D., Zhang, Y. – Application of machine learning, deep learning and optimization algorithms in geoengineering and geoscience: Comprehensive review and future challenge – Gondwana Research – 2022 Review

Zhang, W., Xue, Y., Wang, X., Chen, S., Ji, J., Gao, Y. – Analysis of the runout distance and impact force of an actual landslide considering the effect of single rigid barrier using an SPH approach – Acta Geotechnica – 2025 Hazard modelling

Ji, J., Tong, B., Cui, H. Z., Tang, X. T., Hürlimann, M., Du, S. – A QGIS framework for physically-based probabilistic modelling of landslide susceptibility: QGIS-FORM – Environmental Modelling & Software – 2025 Susceptibility assessment (Physical Models)

Cui, H. Z., Tong, B., Wang, T., Dou, J., Ji, J. – A hybrid data-driven approach for rainfall-induced landslide susceptibility mapping: Physically-based probabilistic model with convolutional neural network – Journal of Rock Mechanics and Geotechnical Engineering – 2025 Susceptibility assessment (Hybrid Models)

Cui, H., Medina, V., Hürlimann, M., Ji, J. – Fast physically-based probabilistic modelling of rainfall-induced shallow landslide susceptibility at the regional scale considering geotechnical uncertainties and different hydrological conditions – Computers and Geotechnics – 2024 Susceptibility assessment (Physical Models)

Cui, H., Ji, J., Hürlimann, M., Medina, V. – Probabilistic and physically-based modelling of rainfall-induced landslide susceptibility using integrated GIS-FORM algorithm – Landslides – 2024 Susceptibility assessment (Physical Models)

Ji, J., Cui, H., Zhang, T., Song, J., Gao, Y. – A GIS-based tool for probabilistic physical modelling and prediction of landslides: GIS-FORM landslide susceptibility analysis in seismic areas – Landslides – 2022 Susceptibility assessment (Physical Models)

Li, X., Gao, S., Gao, R., Xu, S. – Causal spatially heterogeneous Bayesian networks with GPs and normalizing flows for seismic multi-hazard estimation – npj Natural Hazards – 2025 Hazard modelling

Li, X., Xu, S. – Scalable variational learning for noisy-OR Bayesian networks with normalizing flows for complex cascading disaster systems – npj Natural Hazards – 2025 Hazard modelling

Li, X., Yu, X., Bürgi, P. M., Wald, D. J., Hu, X., Xu, S. – Rapid building damage estimates from the M7.8 Turkey earthquake sequence via causality-informed Bayesian inference from satellite imagery – Earthquake Spectra – 2025 Vulnerability

Yu, X., Hu, X., Song, Y., Xu, S., Li, X., Song, X., Fan, X., Wang, F. – Intelligent assessment of building damage of 2023 Turkey-Syria earthquake by multiple remote sensing approaches – npj Natural Hazards – 2024 Landslide detection

Li, X., Bürgi, P. M., Ma, W., Noh, H. Y., Wald, D. J., Xu, S. – DisasterNet: Causal Bayesian networks with normalizing flows for cascading hazards estimation from satellite imagery – – 2023 Hazard modelling

Xu, S., Dimasaka, J., Wald, D. J., Noh, H. Y. – Seismic multi-hazard and impact estimation via causal inference from satellite imagery – Nature Communications – 2022 Hazard modelling

Caleca, F., Lombardo, L., Steger, S., Tanyas, H., Raspini, F., Dahal, A., Nefros, C., Mărgărint, M.C., Drouin, V., Jemec-Auflič, M., Novellino, A., Tonini, M., Loche, M., Casagli, N., Tofani, V. – Pan-European Landslide Risk Assessment: From Theory to Practice – Reviews of Geophysics – 2025 Risk assessment

Pei, T., Qiu, T. – Landslide susceptibility mapping using physics-guided machine learning: a case study of a debris flow event in Colorado Front Range – Acta Geotechnica – 2024 Susceptibility assessment (Hybrid Models)

Yang, H.Q., Zhang, L., Gao, L., Phoon, K.K., Wei, X. – On the importance of landslide management: Insights from a 32-year database of landslide consequences and rainfall in Hong Kong – Engineering Geology – 2022 Landslide mitigation

Wei, X., Gardoni, P., Zhang, L.L., Tan, L., Liu, D.S., Du, C.L., Li, H. – Improving pixel-based regional landslide susceptibility mapping – Geoscience Frontiers – 2024 Susceptibility assessment (Hybrid Models)

Wei, X., Zhang, L.L., Gardoni, P., Chen, Y.M., Tan, L., Liu, D.S., Du, C.L., Li, H. – Comparison of hybrid data-driven and physical models for landslide susceptibility mapping at regional scales – Acta Geotechnica – 2023 Susceptibility assessment (Hybrid Models)

Hungr, O., Leroueil, S., Picarelli, L. – The Varnes classification of landslide types, an update – Landslides – 2014 Concepts mechanisms

Woodard, J.B., Mirus, B.B. – Overcoming the data limitations in landslide susceptibility modeling – Science Advances – 2025 Susceptibility assessment (Physical Models)

Ouellet, S.M., Dettmer, J., Lato, M.J., Cole, S., Hutchinson, D.J., Karrenbach, M., Dashwood, B., Chambers, J.E., Crickmore, R. – Previously hidden landslide processes revealed using distributed acoustic sensing with nanostrain-rate sensitivity – Nature Communications – 2024 Landslide detection

Zhang, L.L., Zhang, J., Zhang, L.M., Tang, W.H. – Stability analysis of rainfall-induced slope failure: a review – Proceedings of the Institution of Civil Engineers - Geotechnical Engineering – 2011 Concepts mechanisms Review

Zhang, L.L., Zhang, L.M., Tang, W.H. – Rainfall-induced slope failure considering variability of soil properties – Géotechnique – 2005 Concepts mechanisms

Zhang, L.L., Fredlund, D.G., Fredlund, M.D., Wilson, G.W. – Modeling the unsaturated soil zone in slope stability analysis – Canadian Geotechnical Journal – 2014 Concepts mechanisms

Casagli, N., Intrieri, E., Tofani, V., Gigli, G., Raspini, F. – Landslide detection, monitoring and prediction with remote-sensing techniques – Nature Reviews Earth & Environment – 2023 Landslide detection Review

Ghorbanzadeh, O., Shahabi, H., Crivellari, A., Homayouni, S., Blaschke, T., Ghamisi, P. – Landslide detection using deep learning and object-based image analysis – Landslides – 2022 Landslide detection

Zekkos, D., Clark, M., Cowell, K., Medwedeff, W., Manousakis, J., Saroglou, H., Tsiambaos, G. – Enabling 3D landslide event statistics using satellite and UAV-enabled topographic differencing – Landslides – 2024 Landslide detection

Yanites, B.J., Clark, M.K., Roering, J.J., West, A.J., Pierce, J. – Cascading land surface hazards as a nexus in the Earth system – Science – 2025 Concepts mechanisms

Karantanellis, E., Marinos, V., Vassilakis, E., Christaras, B. – Object-Based Analysis Using Unmanned Aerial Vehicles (UAVs) for Site-Specific Landslide Assessment – Remote Sensing – 2020 Landslide detection

Loos, S., Lallemant, D., Baker, J., McCaughey, J., Yun, S.H., Budhathoki, N., Khan, F., Singh, R. – G-DIF: A geospatial data integration framework to rapidly estimate post-earthquake damage – Earthquake Spectra – 2020 Others

Guo, A., Hu, J., Sun, Q., Zhou, D., Chen, Y., Zheng, W., Han, B., Li, J. – Revealing Hidden Deformation Patterns in Shallow Creeping Landslides: A Data-Driven InSAR Phase Filtering Method Addressing Geometric Distortions – IEEE Transactions on Geoscience and Remote Sensing – 2025 Landslide detection

Guo, A., Sun, Q., Hu, J., Zheng, W., Gui, R., Yu, Y. – High Temporal-Frequency Estimation of Landslide Deformation Field through Joint InSAR and Hydrological Observations using Deep Learning – IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing – 2024 Landslide detection

Gong, W., Zekkos, D., Clark, M. – A physics-based machine learning-informed model for predicting regional earthquake-induced landslides – Engineering Geology – 2025 Susceptibility assessment (Hybrid Models)

Gong, W., Wang, G., Li, L., Chen, B. – A dataset and review of empirical estimation relationships for landslide runout distances – Earth Science Reviews – 2025 Others Review

Chen, B., Maurer, J., Gong, W. – Applications of UAV in landslide research: a review – Landslides – 2025 Landslide detection Review

Tacconi Stefanelli, C., Vilímek, V., Emmer, A., Catani, F. – Morphological analysis and features of the landslide dams in the Cordillera Blanca, Peru – Landslides – 2018 Concepts mechanisms

Zhang, X., Yu, W., Pun, M.O., Shi, W. – Cross-domain landslide mapping from large-scale remote sensing images using prototype-guided domain-aware progressive representation learning – ISPRS Journal of Photogrammetry and Remote Sensing – 2023 Landslide detection

Xiao, T., Zhang, L.M., Cheung, R.W.M., Lacasse, S. – Predicting spatio-temporal man-made slope failures induced by rainfall in Hong Kong using machine learning techniques – Géotechnique – 2023 Susceptibility assessment (Machine Learning Models)

Amatya, P., Kirschbaum, D., Stanley, T., Tanyas, H. – Landslide mapping using object-based image analysis and open source tools – Engineering Geology – 2021 Landslide detection

Patton, A.I., Rathburn, S.L., Capps, D.M. – Landslide response to climate change in permafrost regions – Geomorphology – 2019 Concepts mechanisms

Patton, A.I., Luna, L.V., Roering, J.J., Jacobs, A., Korup, O., Mirus, B.B. – Landslide initiation thresholds in data-sparse regions: application to landslide early warning criteria in Sitka, Alaska, USA – Natural Hazards and Earth System Sciences – 2023 Early warning

Amatya, P., Kirschbaum, D., Stanley, T. – Use of very high-resolution optical data for landslide mapping and susceptibility analysis along the Karnali highway, Nepal – Remote Sensing – 2019 Susceptibility assessment

Hong, Y., Xuan Do, H., Kessler, J., Fry, L., Read, L., Rafieei Nasab, A., Anderson, E.J. – Evaluation of gridded precipitation datasets over international basins and large lakes – Journal of Hydrology – 2022 Others

Guzzetti, F., Mondini, A.C., Cardinali, M., Fiorucci, F., Santangelo, M., Chang, K.T. – Landslide inventory maps: New tools for an old problem – Earth-Science Reviews – 2012 Landslide detection

Mondini, A.C., Guzzetti, F., Chang, K.T., Monserrat, O., Martha, T.R., Manconi, A. – Landslide failures detection and mapping using Synthetic Aperture Radar: Past, present and future – Earth-Science Reviews – 2021 Landslide detection Review

Stumpf, A., Kerle, N. – Object-oriented mapping of landslides using Random Forests – Remote Sensing of Environment – 2011 Landslide detection

Mondini, A.C., Guzzetti, F., Reichenbach, P., Rossi, M., Cardinali, M., Ardizzone, F. – Semi-automatic recognition and mapping of rainfall induced shallow landslides using optical satellite images – Remote Sensing of Environment – 2011 Landslide detection

Handwerger, A.L., Huang, M.H., Jones, S.Y., Amatya, P., Kerner, H.R., Kirschbaum, D.B. – Generating landslide density heatmaps for rapid detection using open-access satellite radar data in Google Earth Engine – Natural Hazards and Earth System Sciences – 2022 Landslide detection

Corominas, J., van Westen, C.J., Frattini, P., Cascini, L., Malet, J.P., Fotopoulou, S., Catani, F., Van Den Eeckhaut, M., Mavrouli, O., Agliardi, F., Pitilakis, K., Winter, M.G., Pastor, M., Ferlisi, S., Tofani, V., Hervás, J., Smith, J.T. – Recommendations for the quantitative analysis of landslide risk – Bulletin of Engineering Geology and the Environment – 2014 Risk assessment

Fell, R., Corominas, J., Bonnard, C., Cascini, L., Leroi, E., Savage, W.Z. – Guidelines for landslide susceptibility, hazard and risk zoning for land use planning – Engineering Geology – 2008 Risk assessment Review

Fuchs, S., Heiss, K., Hübl, J. – Towards an empirical vulnerability function for use in debris flow risk assessment – Natural Hazards and Earth System Sciences – 2007 Vulnerability

Uzielli, M., Nadim, F., Lacasse, S., Kaynia, A.M. – A conceptual framework for quantitative estimation of physical vulnerability to landslides – Engineering Geology – 2008 Vulnerability

Lahousse, T., Chang, K.T., Lin, Y.H. – Landslide mapping with multi-scale object-based image analysis – a case study in the Baichi watershed, Taiwan – Natural Hazards and Earth System Sciences – 2011 Landslide detection

Fan, X., Wang, X., Fang, C., Jansen, J.D., Dai, L., Tanyas, H., Zang, N., Tang, R., Xu, Q., Huang, R. – Deep learning can predict global earthquake-triggered landslides – National Science Review – 2025 Landslide detection

Duan, Y., Ding, M., He, Y., et al. – Projections of global road risk exposed to landslides under climate change – Communications Earth & Environment – 2025 Exposure

Chen, W., Li, X., Wang, Y., Chen, G., Liu, S. – Forested landslide detection using LiDAR data and the random forest algorithm: A case study of the Three Gorges, China – Remote Sensing of Environment – 2014 Landslide detection

Luo, H.Y., Zhang, L.M., Zhang, L.L., He, J., Yin, K.S. – Vulnerability of buildings to landslides: The state of the art and future needs – Earth-Science Reviews – 2023 Vulnerability Review

Huang, Y., Dai, Z., Zhang, W., Huang, M. – Landslide damage incurred to buildings: A case study of Shenzhen landslide – Engineering Geology – 2018 Vulnerability

Cai, J., Zhang, L., Dong, J., Guo, J., Wang, Y., Liao, M. – Automatic identification of active landslides over wide areas from time-series InSAR measurements using Faster RCNN – International Journal of Applied Earth Observation and Geoinformation – 2023 Landslide detection

Ju, L.Y., Xiao, T., He, J., Xu, W.F., Xiao, S.H., Zhang, L.M. – A simulation-enabled slope digital twin for real-time assessment of rain-induced landslides – Engineering Geology – 2025 Risk assessment

Meng, Y., Jiao, Y., Zhang, L.M. – Slope-specific rainfall thresholds for regional landslide early warning – Engineering Geology – 2025 Hazard modelling

Gariano, S.L., Melillo, M., Peruccacci, S., Brunetti, M.T. – Brief communication: Threshold and probability. The conceptual difference between ID thresholds for landslide initiation and IDF curves – Natural Hazards and Earth System Sciences – 2025 Concepts mechanisms

Chanut, M.A., Gasc-Barbier, M., Dubois, L., Dubois, S. – Automatic identification of continuous or non-continuous evolution of landslides and quantification of deformations – Landslides – 2021 Landslide detection

Zhang, S., Li, C., Peng, J., Wang, S., Chen, W., Wang, Q., Ma, P. – Physical vulnerability assessment of damaged buildings to the Shenzhen catastrophic CSW landslide – Landslides – 2024 Vulnerability

Luo, H.Y., Zhang, L.M., He, J., Yin, K.S. – Probabilistic framework to evaluate scenario-based building vulnerability under landslide run-out impacts – Engineering Geology – 2023 Vulnerability

Medina, V., Hürlimann, M., Mendoza, J.A., Furdada, G., Vaunat, J. – Implications of landslide runout modeling for vulnerability assessment: Benchmarking from a case study in the andean region – International Journal of Disaster Risk Reduction – 2025 Vulnerability

Du, W., Fu, X., Sheng, Q., Chen, J., Zhou, Y., Zheng, S. – Physics-based and data-driven long-term evolution of a landslide: From inversion to prediction – Engineering Geology – 2025 Hazard modelling

Burrows, K., Milledge, D., Walters, R.J. – Sentinel-1 SAR-based Globally Distributed Co-Seismic Landslide Detection by Deep Neural Networks – Geoscientific Model Development Discussions – 2024 Landslide detection

Ji, S., Yu, D., Shen, C., Li, W., Xu, Q. – Landslide detection from an open satellite imagery and digital elevation model dataset using attention boosted convolutional neural networks – Landslides – 2020 Landslide detection

Lu, W., Hu, Y., Zhang, Z., Liu, J. – A dual-encoder U-Net for landslide detection using Sentinel-2 and DEM data – Landslides – 2023 Landslide detection

Tang, L., Lu, W. – Mamba for Landslide Detection: A Lightweight Model for Mapping Landslides With Very High-Resolution Images – IEEE Geoscience and Remote Sensing Letters – 2024 Landslide detection

Zhang, F., Zhu, Q., Wang, Y., Liu, J., Chen, J., Li, W. – TLSTMF-YOLO: Transfer Learning and Feature Fusion Network for Earthquake-Induced Landslide Detection in Remote Sensing Images – IEEE Transactions on Geoscience and Remote Sensing – 2025 Landslide detection

Li, S., Feng, X., Xu, Q., Guo, C., Zhao, K., Zheng, G. – Physics-Informed Deep Learning for Revealing the Evolutionary Characteristics of Landslides Induced by Rainfall Process – Geophysical Research Letters – 2025 Hazard modelling

Monahan, T., Tang, T., Roberts, S., Adcock, T.A.A. – Observations of the seiche that shook the world – Nature Communications – 2025 Others

Piciullo, L., Abraham, M.T., Drøsdal, I.N., Paulsen, E.S. – An operational IoT-based slope stability forecast using a digital twin – Environmental Modelling & Software – 2025 Early warning systems

Lombardo, L., Mai, P.M. – Presenting logistic regression-based landslide susceptibility results – Engineering Geology – 2018 Susceptibility assessment (Statistical Models)

Nocentini, N., Rosi, A., Piciullo, L., Liu, Z., Segoni, S., Fanti, R. – Regional-scale spatiotemporal landslide probability assessment through machine learning and potential applications for operational warning systems: a case study in Kvam (Norway) – Landslides – 2024 Early warning systems

Lombardo, L., Opitz, T., Ardizzone, F., Guzzetti, F., Huser, R. – Space-time landslide predictive modelling – Earth-Science Reviews – 2020 Hazard modelling

Lombardo, L., Tanyas, H., Huser, R., Guzzetti, F., Castro-Camilo, D. – Landslide size matters: A new data-driven, spatial prototype – Engineering Geology – 2021 Hazard modelling

Ghorbanzadeh, O., Blaschke, T., Gholamnia, K., Meena, S.R., Tiede, D., Aryal, J. – Evaluation of Different Machine Learning Methods and Deep-Learning Convolutional Neural Networks for Landslide Detection – Remote Sensing – 2019 Landslide detection

Ghorbanzadeh, O., Xu, Y., Zhao, H., Wang, J., Zhong, Y., Zhao, D., Zang, Q., Wang, S., Zhang, F., Shi, Y., Zhu, X.X., Bai, L., Li, W., Peng, W., Ghamisi, P. – The Outcome of the 2022 Landslide4Sense Competition: Advanced Landslide Detection From Multisource Satellite Imagery – IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing – 2022 Landslide detection

Ghorbanzadeh, O., Xu, Y., Ghamisi, P., Kopp, M., Kreil, D. – Landslide4Sense: Reference Benchmark Data and Deep Learning Models for Landslide Detection – IEEE Transactions on Geoscience and Remote Sensing – 2022 Landslide detection

Ghorbanzadeh, O., Crivellari, A., Ghamisi, P., Shahabi, H., Blaschke, T. – A comprehensive transferability evaluation of U-Net and ResU-Net for landslide detection from Sentinel-2 data (case study areas from Taiwan, China, and Japan) – Scientific Reports – 2021 Landslide detection

Ghorbanzadeh, O., Meena, S.R., Blaschke, T., Aryal, J. – UAV-Based Slope Failure Detection Using Deep-Learning Convolutional Neural Networks – Remote Sensing – 2019 Landslide detection

Meena, S.R., Ghorbanzadeh, O., van Westen, C.J., Nachappa, T.G., Blaschke, T., Singh, R.P., Sarkar, R. – Rapid mapping of landslides in the Western Ghats (India) triggered by 2018 extreme monsoon rainfall using a deep learning approach – Landslides – 2021 Landslide detection

Ghorbanzadeh, O., Rostamzadeh, H., Blaschke, T., Gholaminia, K., Aryal, J. – A new GIS-based data mining technique using an adaptive neuro-fuzzy inference system (ANFIS) and k-fold cross-validation approach for land subsidence susceptibility mapping – Natural Hazards – 2018 Susceptibility assessment (Machine Learning Models)

Zhao, T., Peng, H., Xu, L., Sun, P. – Statistical landslide susceptibility assessment using Bayesian logistic regression and Markov Chain Monte Carlo (MCMC) simulation with consideration of model class selection – Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards – 2024 Susceptibility assessment (Statistical Models)

Xu, L., Yan, D., Zhao, T. – Probabilistic evaluation of loess landslide impact using multivariate model – Landslides – 2021 Hazard modelling

Li, Z., Chen, J., Cao, C., Zhang, W., Li, Y., Hu, J., Li, Z. – Detecting subtle nonlinear changes in slow-moving landslides with a hybrid InSAR change point detection framework: Methodological assessment and validation – International Journal of Applied Earth Observation and Geoinformation – 2025 Early warning

Fang, C., Fan, X., Wang, X., Nava, L., Zhong, H., Dong, X., Qi, J., Catani, F. – A globally distributed dataset of coseismic landslide mapping via multi-source high-resolution remote sensing images – Earth System Science Data – 2024 Early warning

Wei, X., Zhang, L., Luo, J., Liu, D. – A Graph Neural Network Landslide Susceptibility Mapping Method Constrained by Geographical Environment Consistency – InSAR and Deep Learning in Landslides Research – 2025 Early warning

Segoni, S., Tofani, V., Rosi, A., Catani, F., Casagli, N. – Combination of Rainfall Thresholds and Susceptibility Maps for Dynamic Landslide Hazard Assessment at Regional Scale – Frontiers in Earth Science – 2018 Early warning

Liu, D., Tang, D., Ma, J., Zhang, J., Tang, H., Leng, Y. – Critical threshold mining of landslide deformation and intelligent early-warning methods based on multi-factor fusion – Bulletin of Engineering Geology and the Environment – 2024 Early warning

Kuang, P., Li, R., Huang, Y., Wu, J., Luo, X., Zhou, F. – Landslide Displacement Prediction via Attentive Graph Neural Network – Remote Sensing – 2022 Early warning

Intrieri, E., Gigli, G., Casagli, N., Nadim, F. – Brief communication 'Landslide Early Warning System: toolbox and general concepts' – Natural Hazards and Earth System Sciences – 2013 Concepts mechanisms

Ghorbanzadeh, O., Shahabi, H., Piralilou, S.T., Crivellari, A., Cué La Rosa, L.E., Atzberger, C., Li, J., Ghamisi, P. – Contrastive Self-Supervised Learning for Globally Distributed Landslide Detection – IEEE Access – 2024 Landslide detection

Pawar, N.S., Sharma, K.V. – Comprehensive review of remote sensing integration with deep learning in landslide forecasting and future directions – Natural Hazards – 2025 Landslide detection Review

Cheng, Y., Pang, H., Li, Y., Fan, L., Wei, S., Yuan, Z., Fang, Y. – Applications and Advancements of Spaceborne InSAR in Landslide Monitoring and Susceptibility Mapping: A Systematic Review – Remote Sensing – 2025 Landslide detection Review

Zhang, Y., Meng, X., Dijkstra, T., Jordan, C., Chen, G., Zeng, R., Novellino, A. – Change detection of slow-moving landslide with multi-source SBAS-InSAR and Light-U2Net – International Journal of Applied Earth Observation and Geoinformation – 2025 Landslide detection

Reichenbach, P., Rossi, M., Malamud, B.D., Mihir, M., Guzzetti, F. – A review of statistically-based landslide susceptibility models – Earth-Science Reviews – 2018 Susceptibility assessment Review

Zhang, C., Li, Z., Yu, C., Song, C., Xiao, R., Peng, J. – An integrated framework for wide-area active landslide detection with InSAR observations and SAR pixel offsets – Landslides – 2022 Landslide detection

Rossi, M., Bornaetxea, T., Reichenbach, P. – LAND-SUITE V1.0: a suite of tools for statistically based landslide susceptibility zonation – Geoscientific Model Development – 2022 Susceptibility assessment

Urgilez Vinueza, A., Handwerger, A.L., Bakker, M., Bogaard, T. – A new method to detect changes in displacement rates of slow-moving landslides using InSAR time series – Landslides – 2022 Landslide detection

Cai, J., Zhang, L., Dong, J., Guo, J., Wang, Y., Liao, M. – Automatic identification of active landslides over wide areas from time-series InSAR measurements using Faster RCNN – International Journal of Applied Earth Observation and Geoinformation – 2023 Landslide detection

Lacroix, P., Handwerger, A.L., Bièvre, G. – Life and death of slow-moving landslides – Nature Reviews Earth & Environment – 2020 Concepts mechanisms

Thiebes, B., Bell, R., Glade, T., Jäger, S., Mayer, J., Anderson, M., Holcombe, L. – Monitoring strategies for local landslide early warning systems – Landslides – 2018 Early warning Review

Segoni, S., Piciullo, L., Gariano, S.L. – A review of the recent literature on rainfall thresholds for landslide occurrence – Landslides – 2018 Early warning Review

Guzzetti, F., Gariano, S.L., Peruccacci, S., Brunetti, M.T., Melillo, M., Rossi, M., Luciani, S. – Landslide predictions through combined rainfall threshold models – Landslides – 2024 Early warning

Intrieri, E., Carlà, T., Gigli, G. – Forecasting the time of failure of landslides at slope-scale: A literature review – Earth-Science Reviews – 2019 Early warning Review

Zhang, J., Tang, H., Zhou, B., Wen, T., Li, L. – A new early warning criterion for landslides movement assessment: Deformation Standardized Anomaly Index – Bulletin of Engineering Geology and the Environment – 2024 Early warning

Fiolleau, S., Uhlemann, S., Dufour, C., Bièvre, G., Coccia, C., Mourier, B., Labazuy, P., Malet, J.P. – Understanding slow-moving landslide triggering processes using low-cost passive seismic and inclinometer monitoring – Journal of Applied Geophysics – 2023 Early warning

Guzzetti, F., Gariano, S.L., Peruccacci, S., Brunetti, M.T., Marchesini, I., Rossi, M., Melillo, M. – Geographical landslide early warning systems – Earth-Science Reviews – 2020 Early warning Review

Sharifi, S., Macciotta, R., Hendry, M.T. – A reliability evaluation of four landslide failure forecasting methods in real-time monitoring applications – Landslides – 2024 Early warning

Liu, Z., Nadim, F., Garcia-Aristizabal, A., Mignan, A., Fleming, K., Luna, B.Q. – A three-level framework for multi-risk assessment – Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards – 2015 Risk assessment

Yang, B., Yin, K., Lacasse, S., Liu, Z. – Time series analysis and long short-term memory neural network to predict landslide displacement – Landslides – 2019 Early warning

Tehrani, F.S., Calvello, M., Liu, Z., Zhang, L., Lacasse, S. – Machine learning and landslide studies: Recent advances and applications – Natural Hazards – 2022 Review

Liu, Z., Gilbert, G., Cepeda, J.M., Lysdahl, A.O.K., Piciullo, L., Hefre, H., Lacasse, S. – Modelling of shallow landslides with machine learning algorithms – Geoscience Frontiers – 2021 Susceptibility assessment (Machine Learning)

Ng, C.W.W., Yang, B., Liu, Z.Q., Kwan, J.S.H., Chen, L. – Spatiotemporal modelling of rainfall-induced landslides using machine learning – Landslides – 2021 Hazard modelling

Chen, X.Y., Zhang, L.L., Zhang, L.M., Yang, H.Q., Liu, Z.Q., Lacasse, S., Li, J.H., Cao, Z.J. – Investigation of impact of submarine landslide on pipelines with large deformation analysis considering spatially varied soil – Ocean Engineering – 2020 Risk assessment

Nocentini, N., Rosi, A., Piciullo, L., Liu, Z., Segoni, S., Fanti, R. – Regional-scale spatiotemporal landslide probability assessment through machine learning and potential applications for operational warning systems: A case study in Kvam (Norway) – Landslides – 2024 Early warning

Tellman, B., Sullivan, J.A., Kuhn, C., Kettner, A.J., Doyle, C.S., Brakenridge, G.R., Erickson, T.A., Slayback, D.A. – Satellite imaging reveals increased proportion of population exposed to floods – Nature – 2021 Others

Xiong, J., Pei, T., Qiu, T. – A Novel Framework for Spatiotemporal Susceptibility Prediction of Rainfall-Induced Landslides: A Case Study in Western Pennsylvania – Remote Sensing – 2024 Susceptibility assessment (Hybrid Models)

Pei, T., Qiu, T., Shen, C. – Applying knowledge-guided machine learning to slope stability prediction – Journal of Geotechnical and Geoenvironmental Engineering – 2023 Susceptibility assessment (Hybrid Models)

Palese, M., Pei, T., Qiu, T., Zarembski, A.M., Shen, C., Palese, J.W. – Hazard assessment framework for statistical analysis of cut slopes using track inspection videos and geospatial information – Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards – 2023 Susceptibility assessment

Nagendra, S., Kifer, D., Mirus, B., Pei, T., Lawson, K., Manjunatha, S.B., Li, W., Nguyen, H., Qiu, T., Tran, S., Shen, C. – Constructing a large-scale landslide database across heterogeneous environments using task-specific model updates – IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing – 2022 Landslide detection

Jia, G., Gardoni, P. – State-dependent stochastic models: A general stochastic framework for modeling deteriorating engineering systems considering multiple deterioration processes and their interactions – Structural Safety – 2018 Others

Tabandeh, A., Jia, G., Gardoni, P. – Langevin importance sampling for reliability analysis – Reliability Engineering & System Safety – 2026 Others

Xiong, Z., Jia, G. – Data-driven global sensitivity analysis for group of random variables through knowledge-enhanced machine learning with normalizing flows – Reliability Engineering & System Safety – 2025 Others

Wang, Z., Jia, G. – Extended sample-based approach for efficient sensitivity analysis of group of random variables – Reliability Engineering & System Safety – 2023 Others