Articles | Volume 17, issue 10
https://doi.org/10.5194/nhess-17-1779-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-17-1779-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
GB-InSAR monitoring of slope deformations in a mountainous area affected by debris flow events
William Frodella
CORRESPONDING AUTHOR
Department of Earth Sciences, University of Firenze, Via La Pira 4, 50121 Florence, Italy
Teresa Salvatici
Department of Earth Sciences, University of Firenze, Via La Pira 4, 50121 Florence, Italy
Veronica Pazzi
Department of Earth Sciences, University of Firenze, Via La Pira 4, 50121 Florence, Italy
Stefano Morelli
Department of Earth Sciences, University of Firenze, Via La Pira 4, 50121 Florence, Italy
Riccardo Fanti
Department of Earth Sciences, University of Firenze, Via La Pira 4, 50121 Florence, Italy
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Cited
17 citations as recorded by crossref.
- Establishing Reliable Slope Stability Hazard Map Based on GIS‐Based Tool in Conjunction with Finite Element Methods F. Sengani et al. 10.1155/2022/3384143
- Near-real-time seismic monitoring improves deep-seated landslides early warning, Jiuxianping, China L. Feng et al. 10.1016/j.enggeo.2025.108231
- Advancing Ground-Based Radar Processing for Bridge Infrastructure Monitoring C. Michel & S. Keller 10.3390/s21062172
- Learning in an interactive simulation tool against landslide risks: the role of strength and availability of experiential feedback P. Chaturvedi et al. 10.5194/nhess-18-1599-2018
- Expecting the expected – learning from the past to provide forward scenarios through geomorphic change detection, monitoring and modeling G. Bossi et al. 10.1186/s40677-024-00292-7
- Machine learning based landslide susceptibility mapping models and GB-SAR based landslide deformation monitoring systems: Growth and evolution B. Ganesh et al. 10.1016/j.rsase.2022.100905
- Development characteristics and hazard analysis of debris flow along the Emei to Mianning section of the Chengdu–Kunming Railway E. Qiu et al. 10.3389/feart.2024.1473444
- Exploring the initiating mechanism, monitoring equipment and warning indicators of gully-type debris flow for disaster reduction: a review Y. Du et al. 10.1007/s11069-024-06742-7
- How robust are landslide susceptibility estimates? U. Ozturk et al. 10.1007/s10346-020-01485-5
- HVSR Analysis of Rockslide Seismic Signals to Assess the Subsoil Conditions and the Site Seismic Response A. Lotti et al. 10.1155/2018/9383189
- Kinematic Reconstruction of a Deep-Seated Gravitational Slope Deformation by Geomorphic Analyses S. Morelli et al. 10.3390/geosciences8010026
- Deformation monitoring and evaluation of unstable slope based on ground-based and spaceborne SAR images Y. Wang et al. 10.1117/1.JRS.16.034505
- Insights into the evolution of a post-failure rock slope R. Gerstner et al. 10.1007/s10064-025-04249-4
- Probabilistic rainfall thresholds in Chibo, India: estimation and validation using monitoring system A. Dikshit & N. Satyam 10.1007/s11629-018-5189-6
- Post-Disaster High-Frequency Ground-Based InSAR Monitoring and 3D Deformation Reconstruction of Large Landslides Using MIMO Radar X. Shi et al. 10.3390/rs17183183
- Preface: Landslide early warning systems: monitoring systems, rainfall thresholds, warning models, performance evaluation and risk perception S. Segoni et al. 10.5194/nhess-18-3179-2018
- Multi-Phase-Center Sidelobe Suppression Method for Circular GBSAR Based on Sparse Spectrum Y. Wang et al. 10.1109/ACCESS.2020.3010584
17 citations as recorded by crossref.
- Establishing Reliable Slope Stability Hazard Map Based on GIS‐Based Tool in Conjunction with Finite Element Methods F. Sengani et al. 10.1155/2022/3384143
- Near-real-time seismic monitoring improves deep-seated landslides early warning, Jiuxianping, China L. Feng et al. 10.1016/j.enggeo.2025.108231
- Advancing Ground-Based Radar Processing for Bridge Infrastructure Monitoring C. Michel & S. Keller 10.3390/s21062172
- Learning in an interactive simulation tool against landslide risks: the role of strength and availability of experiential feedback P. Chaturvedi et al. 10.5194/nhess-18-1599-2018
- Expecting the expected – learning from the past to provide forward scenarios through geomorphic change detection, monitoring and modeling G. Bossi et al. 10.1186/s40677-024-00292-7
- Machine learning based landslide susceptibility mapping models and GB-SAR based landslide deformation monitoring systems: Growth and evolution B. Ganesh et al. 10.1016/j.rsase.2022.100905
- Development characteristics and hazard analysis of debris flow along the Emei to Mianning section of the Chengdu–Kunming Railway E. Qiu et al. 10.3389/feart.2024.1473444
- Exploring the initiating mechanism, monitoring equipment and warning indicators of gully-type debris flow for disaster reduction: a review Y. Du et al. 10.1007/s11069-024-06742-7
- How robust are landslide susceptibility estimates? U. Ozturk et al. 10.1007/s10346-020-01485-5
- HVSR Analysis of Rockslide Seismic Signals to Assess the Subsoil Conditions and the Site Seismic Response A. Lotti et al. 10.1155/2018/9383189
- Kinematic Reconstruction of a Deep-Seated Gravitational Slope Deformation by Geomorphic Analyses S. Morelli et al. 10.3390/geosciences8010026
- Deformation monitoring and evaluation of unstable slope based on ground-based and spaceborne SAR images Y. Wang et al. 10.1117/1.JRS.16.034505
- Insights into the evolution of a post-failure rock slope R. Gerstner et al. 10.1007/s10064-025-04249-4
- Probabilistic rainfall thresholds in Chibo, India: estimation and validation using monitoring system A. Dikshit & N. Satyam 10.1007/s11629-018-5189-6
- Post-Disaster High-Frequency Ground-Based InSAR Monitoring and 3D Deformation Reconstruction of Large Landslides Using MIMO Radar X. Shi et al. 10.3390/rs17183183
- Preface: Landslide early warning systems: monitoring systems, rainfall thresholds, warning models, performance evaluation and risk perception S. Segoni et al. 10.5194/nhess-18-3179-2018
- Multi-Phase-Center Sidelobe Suppression Method for Circular GBSAR Based on Sparse Spectrum Y. Wang et al. 10.1109/ACCESS.2020.3010584
Discussed (final revised paper)
Latest update: 18 Oct 2025
Short summary
A local scale GB-InSAR system was implemented for mapping and monitoring slope landslide residual deformations and for early warning purposes in case of landslide reactivations, with the aim of assuring the safety of the valley inhabitants and the personnel involved in the post-event recovery phase. The here presented methodology could represent a useful contribution to a better understanding of landslide phenomena and decision making process during the post-emergency management activities.
A local scale GB-InSAR system was implemented for mapping and monitoring slope landslide...
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