Article
Geosciences, Multidisciplinary
Alessandro Cesare Mondini, Fausto Guzzetti, Kang-Tsung Chang, Oriol Monserrat, Tapas Ranjan Martha, Andrea Manconi
Summary: Landslides are geomorphological processes with serious threats to people, property, and the environment on all continents. Investigators have shown increasing interest in using Synthetic Aperture Radar (SAR) imagery for landslide detection and mapping, but challenges remain to be faced for effective utilization.
EARTH-SCIENCE REVIEWS
(2021)
Article
Environmental Sciences
Lucio Di Matteo, Riccardo Cardinali, Valentina Cerboni, Fabio Guadagnano, Giorgio Piagnani, Claudia Ribaldi, Biagio Marco Sotera, Corrado Cencetti
Summary: The study integrates different data sources to investigate a complex landslide, including aerial photography, geotechnical monitoring data, and satellite measurements. It demonstrates that satellite products can reliably monitor landslide mass displacements when ground instrumentations are no longer operating. Understanding the landslide behavior to rainfall conditions can provide important insights for urban planners to re-evaluate hazard and risk classification and implement effective mitigation techniques.
Article
Environmental Sciences
Gianmarco Bonaldo, Amedeo Caprino, Filippo Lorenzoni, Francesca da Porto
Summary: Satellite interferometry is a powerful tool for monitoring structural displacements. This paper proposes a methodology for remotely detecting displacements and assessing building criticalities using satellite interferometric data. The methodology was applied to a case study in Rome for an eight-year-long monitoring period.
Proceedings Paper
Geosciences, Multidisciplinary
R. Vassallo, J. De Rosa, C. Di Maio, D. Reale, S. Verde, G. Fornaro
Summary: In this study, basal and superficial displacements of two landslides in overconsolidated clayey soils were monitored using inclinometers and GPS. Difficulty was encountered in monitoring the mostly North-South displacement orientations using satellite interferometry. By analyzing COSMO-SkyMed DInSAR data, the kinematic history of the urbanized area of the landslides over the last 20 years was reconstructed, even in areas where ground-based displacement data were limited or unavailable. The effectiveness of the remedial measures implemented in the area on displacement rates was also evaluated.
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022)
(2022)
Article
Environmental Sciences
Jan Jelenek, Veronika Kopackova-Strnadova
Summary: The study introduces a new processing scheme combining radar and optical satellite data to map landscape changes triggered by earthquakes, such as landslides and coastal uplift. The scheme was tested on the 2016 Kaikoura earthquake in New Zealand and proved to be effective in detecting changes in a comprehensive manner, providing valuable insights for earthquake impact assessment and prioritizing field work.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Geosciences, Multidisciplinary
M. L. Velez, E. Bustos, L. Euillades, M. Blanco, J. F. S. Lopez, I. Barbero, M. Berrocoso, A. Gil Martinez, J. G. Viramonte
Summary: The study on Cerro Blanco Volcanic Complex reveals a slowdown in subsidence velocity since 1992, decreasing from 2.6 cm/yr to 0.87 cm/yr. By processing DInSAR data and using GPS as a complementary tool, a circular deformation pattern of about 12 km diameter related to subsidence centered at CBVC throughout the entire period was found. Analytical inverse modelling was used to infer the main characteristic of the source responsible for the measured displacement, with the best-fitting solution corresponding to a spherical source located between 9 and 14 km from the surface with a volume decrease of about 0.013 km(3)/yr for the entire period.
JOURNAL OF SOUTH AMERICAN EARTH SCIENCES
(2021)
Article
Construction & Building Technology
Felipe Orellana, Peppe J. V. D'Aranno, Silvia Scifoni, Maria Marsella
Summary: Monitoring structural stability in urban areas and infrastructure networks is crucial for population security. DInSAR technique provides precise measurements of building deterioration, and GIS application ensures long-term spatial and temporal records for effective management.
Article
Geosciences, Multidisciplinary
Almendra Brasca Merlin, Andres Solarte, Laura M. Bellis, Claudio Carignano, Marcela Cioccale, Manuel Delgado, Marcelo Scavuzzo, Juan P. Arganaraz
Summary: The investigation aimed to assess landslides in the steep West-facing slope of the Sierras Chicas mountains in central Argentina using Differential SAR interferometry (DInSAR) and statistical modeling. Sentinel-1 was found to be the most suitable source of images for interferometry applications, while Cosmo Skymed imagery showed poor coherence in the study area. Generalized Linear Models identified slope degree, distance to roads, and fire frequency as the main factors explaining landslide occurrence on the west escarpment of the Sierras Chicas.
JOURNAL OF SOUTH AMERICAN EARTH SCIENCES
(2021)
Article
Environmental Sciences
Haonan Jiang, Timo Balz, Francesca Cigna, Deodato Tapete
Summary: This study utilized high-resolution COSMO-SkyMed StripMap HIMAGE scenes to monitor long-term land subsidence in Wuhan, revealing several observable subsidence zones and investigating the underlying mechanisms through soil mechanics analysis.
Article
Engineering, Aerospace
K. C. Niraj, Sharad Kumar Gupta, Dericks Praise Shukla
Summary: This paper uses DInSAR and MTInSAR techniques to study surface displacement in the Kotrupi Region. DInSAR accurately measures displacements but is limited by various factors, while MTInSAR uses data from multiple periods to reduce atmospheric disturbances and unwrapping errors. The results show significant deformation in the Kotrupi area after a landslide, with MTInSAR providing more accurate results compared to DInSAR.
ADVANCES IN SPACE RESEARCH
(2022)
Article
Remote Sensing
Xin Yao, Yiping Chen, Donglie Liu, Zhenkai Zhou, Veraldo Liesenberg, Jose Marcato Junior, Jonathan Li
Summary: The study utilized the average-DInSAR method to detect displacements on tableland escarpments and confirmed that these movements were induced by underground coal mining. This method proved to be simple and effective for detecting pre-failure displacements in areas with similar geological conditions, aiding in the formulation of early warning strategies for landslides.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Environmental Sciences
Jeong-Won Park, Hyun-Cheol Kim, Anton Korosov, Denis Demchev, Stefano Zecchetto, Seung Hee Kim, Young-Joo Kwon, Hyangsun Han, Chang-Uk Hyun
Summary: High-resolution X-band SAR sensors such as KOMPSAT-5 and COSMO-SkyMed show higher accuracies and feasibility for sub-daily monitoring of sea ice drift compared to wide-swath C-band SARs.
Article
Environmental Sciences
Luca Pulvirenti, Giuseppe Squicciarino, Elisabetta Fiori, Laura Candela, Silvia Puca
Summary: The Italian Space Agency recently deployed the COSMO-SkyMed Second Generation (CSG) satellite, and developed a methodology to detect floods using high-resolution single SAR images, based on image segmentation and fuzzy logic. Comparisons with maps produced by the Copernicus Emergency Service demonstrated the reliability of the methodology.
Article
Environmental Sciences
Deodato Tapete, Arianna Traviglia, Eleonora Delpozzo, Francesca Cigna
Summary: This study utilized satellite DEM data at higher resolution to map tells in the Near and Middle Eastern region, demonstrating the potential of the Italian Space Agency's COSMO-SkyMed Synthetic Aperture Radar in archaeological mapping.
Article
Environmental Sciences
Emil Bayramov, Giulia Tessari, Martin Kada, Saida Aliyeva, Manfred Buchroithner
Summary: This study assessed differential vertical and horizontal deformations for the offshore Kashagan oilfield using SAR images and PS-InSAR technique. The results showed that the differential vertical deformation velocity was between -4 mm/y and 4 mm/y, while the differential horizontal deformation velocity was between -4 mm/y and 5 mm/y. Hotspots of differential vertical deformation were observed in the oilfield areas installed on piles. The study concluded that the Kashagan oilfield had not been significantly impacted by differential vertical and horizontal deformations.
Article
Environmental Sciences
Simone Fiaschi, Eoghan P. Holohan, Michael Sheehy, Mario Floris
Article
Environmental Sciences
Alessandro Caporali, Mario Floris, Xue Chen, Bilbil Nurce, Mauro Bertocco, Joaquin Zurutuza
Article
Environmental Sciences
Xue Chen, Vladimiro Achilli, Massimo Fabris, Andrea Menin, Michele Monego, Giulia Tessari, Mario Floris
Summary: Mass movements pose a serious threat to the stability of human structures worldwide, and a study combining various monitoring techniques has shown the relationship between ground deformations and damages to individual buildings.
Article
Engineering, Aerospace
Xue Chen, Yueze Zheng, Junhuan Peng, Mario Floris
Summary: This study proposes a method for estimating river water levels under bridges using high-resolution SAR images. The method accurately estimates the water level oscillation under the Badong Yangzte River Bridge on the Yangtze River and demonstrates efficiency in estimating river water levels.
ADVANCES IN SPACE RESEARCH
(2021)
Article
Engineering, Geological
Sansar Raj Meena, Lucas Pedrosa Soares, Carlos H. Grohmann, Cees van Westen, Kushanav Bhuyan, Ramesh P. Singh, Mario Floris, Filippo Catani
Summary: Event-based landslide inventories are crucial for understanding the causal relationship between triggering events and landslides, and for subsequent risk studies. This study explores the potential of U-Net and machine learning approaches for automated landslide detection in the Himalayas. The results suggest that the U-Net model performs slightly better than other methods in landslide detection.
Article
Environmental Sciences
Nicusor Necula, Mihai Niculita, Simone Fiaschi, Rinaldo Genevois, Paolo Riccardi, Mario Floris
Summary: Landslides pose an increasing threat to urbanized areas and affected communities, prompting the need for advanced techniques like MT-InSAR for landslide investigation and monitoring. The study in Eastern Romania demonstrates the effectiveness of using SAR images and numerical modeling to identify active landslides and understand their mechanisms.
Article
Multidisciplinary Sciences
Kushanav Bhuyan, Hakan Tanyas, Lorenzo Nava, Silvia Puliero, Sansar Raj Meena, Mario Floris, Cees van Westen, Filippo Catani
Summary: In the past decade, the mapping of landslides over space has gained increasing attention and achieved good results. However, multi-temporal inventories are rare, even with manual landslide mapping. In this study, a deep learning strategy using transfer learning was proposed to adapt the Attention Deep Supervision Multi-Scale U-Net model for landslide detection tasks in new areas. The method demonstrated the ability to generate multi-temporal landslide inventories over large areas.
SCIENTIFIC REPORTS
(2023)
Article
Environmental Sciences
Massimo Fabris, Mattia Battaglia, Xue Chen, Andrea Menin, Michele Monego, Mario Floris
Summary: Land subsidence poses a serious threat to many areas around the world, and combining GNSS and InSAR techniques can provide more comprehensive and detailed information for monitoring. In this study, the proposed approach was successfully applied in the Po River Delta in Italy, extracting high-resolution deformation maps and revealing high land subsidence rates along the coastal area.
Article
Geography, Physical
Kushanav Bhuyan, Sansar Raj Meena, Lorenzo Nava, Cees van Westen, Mario Floris, Filippo Catani
Summary: Repeated temporal mapping of landslides is crucial for studying their movement patterns and triggers. However, traditional methods of visual interpretation from remote sensing images are time-consuming. Recent advancements in deep learning models provide a faster and more accurate way of mapping landslides, but have not been applied to multi-temporal mapping in the Himalayas. This study proposes a new strategy using separate training samples to create multi-temporal landslide inventories.
GISCIENCE & REMOTE SENSING
(2023)
Article
Environmental Sciences
Amedeo Caprino, Silvia Puliero, Filippo Lorenzoni, Mario Floris, Francesca da Porto
Summary: Structural Health Monitoring (SHM) is a powerful tool for assessing the health condition of buildings. The application of multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) techniques using high-resolution SAR satellite images has enabled precise and cost-effective monitoring of structures, but its effectiveness in this field has not been comprehensively validated. This paper compares interferometric data with on-site measurements of displacements to evaluate the effectiveness of MT-InSAR in monitoring a Civic Tower in L'Aquila, Italy. The results indicate that both methods are consistent in measuring displacement trends of the building, highlighting the potential and limitations of using InSAR techniques for SHM.
Editorial Material
Environmental Sciences
Massimo Fabris, Mario Floris
Article
Engineering, Geological
Lorenzo Nava, Edoardo Carraro, Cristina Reyes-Carmona, Silvia Puliero, Kushanav Bhuyan, Ascanio Rosi, Oriol Monserrat, Mario Floris, Sansar Raj Meena, Jorge Pedro Galve, Filippo Catani
Summary: Accurate early warning systems for landslides can significantly reduce fatalities and economic losses. This study assesses and compares seven deep learning methods for forecasting landslide displacement and finds that MLP, GRU, and LSTM models can make reliable predictions in all scenarios, while the Conv-LSTM model performs best in highly seasonal landslides.
Article
Geosciences, Multidisciplinary
Angelo Ballaera, Anna Breda, Mario Floris, Giovanni Monegato, Giacomo Tedesco, Gianluca Marcato
Summary: The study aims to define a preliminary geological model of the Passo Mauria tunnel, designed to provide a safer connection for tourism and economic activities. The survey stage focuses on investigating the presumed entrances of the tunnel and describing the geology of the study area. Aerial photogrammetric survey helps reconstruct the geometry of inaccessible areas. The study also predicts the behavior of the rock mass during tunnel excavation and identifies sections with similar mechanical properties.
RENDICONTI ONLINE DELLA SOCIETA GEOLOGICA ITALIANA
(2023)
Article
Geosciences, Multidisciplinary
Sansar Raj Meena, Silvia Puliero, Kushanav Bhuyan, Mario Floris, Filippo Catani
Summary: This study used statistical ensemble and machine learning models for landslide susceptibility mapping in Belluno province, Italy, and evaluated the importance of conditioning factors. The results showed that removing the least important features did not impact the overall accuracy.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
(2022)
Proceedings Paper
Geosciences, Multidisciplinary
Giulia Tessari, Silvia Puliero, Lisa Beccaro, Andrey Giardino, Mario Floris, Andrea Marzoli, Fumitaka Ogushi, Paolo Pasquali
2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019)
(2019)