Publications by Thomas Glade
Featured Readings and List of Publications
Anthropocene Reads
All Publications by Univ.-Prof. Dr. Thomas Glade
2025
Pacheco Quevedo, R., Andrade Maciel, D., Oliveira Andrades-Filho, C., Fossa Sampaio Mexias, L., Garcia de Oliveira, G., Boelter Herrmann, P., Corrêa Alves, F., & Glade, T. (Accepted/In press). Landslide susceptibility in Rio Grande do Sul: could past landslides indicate areas affected in May 2024?. Paper presented at Brazilian Remote Sensing Symposium, Salvador, Brazil.
2024
Carraro, E., Müller, B., Jimenez Donato, Y. A., Marr, P., & Glade, T. (2024). Spatio-temporal analysis of slope deformations to establish an effective long-term monitoring of a slow-moving landslide. In Conference Proceedings INTERPRAEVENT 2024 (pp. 458-463). Article C47
Carraro, E., Flores-Orozco, A., Monsalve Martinez, J. L., Marr, P., & Glade, T. (2024). Determination of the potential shear plane of a clay-rich, deep-seated landslide using spectral induced polarization and geotechnical approaches: case study Brandstatt, Lower Austria. EGU General Assembly 2024, Wien, Austria. https://doi.org/10.5194/egusphere-egu24-17961
Zeng, T., Jin, B., Glade, T., Xie, Y., Li, Y., Zhu, Y., & Yin, K. (2024). Assessing the imperative of conditioning factor grading in machine learning-based landslide susceptibility modeling: A critical inquiry. CATENA, 236, Article 107732. https://doi.org/10.1016/j.catena.2023.107732
Xia, D., Tang, H., Glade, T., Tang, C., & Wang, Q. (2024). KNN-GCN: A Deep Learning Approach for Slope-Unit-Based Landslide Susceptibility Mapping Incorporating Spatial Correlations. Mathematical Geosciences, 56(5), 1011-1039. https://doi.org/10.1007/s11004-023-10132-3
Marr, P., Carraro, E., Jimenez Donato, Y. A., Kanta, R., & Glade, T. (2024). A Framework For Long-Term Landslide Monitoring Explored At Three Permanent Landslide Observatories In Lower Austria. In Conference Proceedings INTERPRAEVENT 2024 (pp. 20-23). Article A01
Wenzel, T., Marr, P., Glade, T., Höfler, F., Preißler, A., Adams, M., Cocuccioni, S., Pittore, M., Hürlimann, M., van Westen, C., & Atun, F. (2024). Local Natural Hazards, Cascading to Cross-Regional Risks and Impacts Along the Main Transit Route from North and South in the Austrian Alps. In International Conference on Energy and Environmental Science (pp. 359-369)
Lima, P., Jimenez Donato, Y. A., Arango, M. I., Mergili, M., Kanta, R., & Glade, T. (2024). NoeMOTION: Mobility, Hazard, and Risk Analysis of Selected Landslides in Lower Austria. Springer. SpringerBriefs in Environmental Science Vol. 1 https://doi.org/10.1007/978-3-031-55982-2
Hürlimann, M., Marr, P., Glade, T., Komendantova, N., de Zeeuw-van-Dalfsen, E., Armas, I., Kundak, S., Lantada, N., Pantaleoni Reluy, N., Wenzel, T., Alkema, D., van Westen, C., Atun, F., & Cocuccioni, S. (2024). Systemic Multi-sectoral and Multi-hazard Risk Assessment in Current and Future Scenarios. The PARATUS-Project. In International Conference on Energy and Environmental Science (pp. 425-432)
Hürlimann, M., Marr, P., Komendantova, N., Glade, T., de Zeeuw-van Dalfsen, E., Armas, I., Kundak, S., Lantada, N., Wenzel, T., Pantaleoni Reluy, N., Alkema, D., van Westen, C., Atun, F., & Cocuccioni, S. (2024). The web-based simulation and information service for multi-hazard impact chains. Design document. In Lecture Notes in Civil Engineering (pp. 425-432)
2023
Zeng, T., Wu, L., Peduto, D., Glade, T., Hayakawa, Y. S., & Yin, K. (2023). Ensemble learning framework for landslide susceptibility mapping: Different basic classifier and ensemble strategy. Geoscience Frontiers, 14(6), Article 101645. https://doi.org/10.1016/j.gsf.2023.101645
Zeng, T., Glade, T., Xie, Y., Yin, K., & Peduto, D. (2023). Deep learning powered long-term warning systems for reservoir landslides. International Journal of Disaster Risk Reduction, 94, Article 103820. https://doi.org/10.1016/j.ijdrr.2023.103820
Wang, X., Glade, T., Schmaltz, E., & Liu, X. (2023). Surveillance audio-based rainfall observation: An enhanced strategy for extreme rainfall observation. Applied Acoustics, 211, Article 109581. https://doi.org/10.1016/j.apacoust.2023.109581
Muniz Lima, P. H., Steger, S., Glade, T., & Mergili, M. (2023). Conventional data-driven landslide susceptibility models may only tell us half of the story: Potential underestimation of landslide impact areas depending on the modeling design. Geomorphology, 430(108638), 1. Article 108638. https://doi.org/10.1016/j.geomorph.2023.108638
Donato, Y. A. J., Carraro, E., Marr, P., Kanta, R., & Glade, T. (2023). Unravelling the complex dynamic of slow-moving landslides in the Flysch zone region, Lower Austria. A case study of the Hofermühle catchment.. EGU, General Assembly 2023, Wien, Austria. https://doi.org/10.5194/egusphere-egu23-10159
Carraro, E., Jimenez Donato, Y. A., Soto Bravo, F. A., Kanta, R., Marr, P., & Glade, T. (2023). Insights from a combination of surface and deep measurements to set a long-term monitoring system of a complex, slow-moving landslide in Lower Austria (Austria). EGU General Assembly 2023, Vienna, Austria. https://doi.org/10.5194/egusphere-egu23-5022
Wang, X., Wang, M., Liu, X., Zhu, L., Shi, S., Glade, T., Chen, M., Xie, Y., Wu, Y., & He, Y. (2023). Near-infrared surveillance video-based rain gauge. Journal of Hydrology, 618, Article 129173. https://doi.org/10.1016/j.jhydrol.2023.129173
Muniz Lima, P. H., Steger, S., Petschko, H., Goetz, J., Bertagnoli, M., Schweigl, J., & Glade, T. (2023). A framework to update 10-year-old landslide susceptibility predictions. Assessing the accuracy of existing landslide susceptibility models.. 1. EGU, General Assembly 2023, Wien, Austria. https://doi.org/10.5194/egusphere-egu23-7080
Muniz Lima, P. H., Moreno, M., Steger, S., Camarinha, P. I., Teixeira Coelho, L. C., Mandarino, F. C., & Glade, T. (2023). DEVELOPING A SPATIOTEMPORAL MODEL TO INTEGRATE LANDSLIDE SUSCEPTIBILITY AND CRITICAL RAINFALL CONDITIONS. A PRACTICAL MODEL APPLIED TO RIO DE JANEIRO MUNICIPALITY. In Tofani V, Casagli N, Bandecchi E, Gargini E and Armignacco D (eds.) Landslide Science for Sustainable Development. Proceedings of the 6th World Landslide Forum. Firenze, Italy: OIC S.r.l.
Marr, P., Jimenez Donato, Y. A., Carraro, E., Kanta, R., & Glade, T. (2023). The Role of Historical Data to Investigate Slow-Moving Landslides by Long-Term Monitoring Systems in Lower Austria. Land, 12(3), 659. Article 659. https://doi.org/10.3390/land12030659