Andrea Manconi

Last Name

Manconi

First Name

Andrea

ORCID

0000-0003-2930-4422

Organisational unit

01659 - Lehre Erd- und Planetenwissenschaften

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Publications1 - 10 of 67

Mechanisms of Reservoir Impoundment-induced Large Deformation of the Guobu Slope at the Laxiwa Hydropower Station, China: Preliminary Insights from Remote Sensing and Numerical Modelling
Lesche, Moritz; Wang, Liang; Manconi, Andrea; et al. (2024)
Environmental Engineering Science ~ Engineering Geology for a Habitable Earth: IAEG XIV Congress 2023 Proceedings, Chengdu, China. Volume 4: Technological Innovation and Application for Engineering Geology
The construction/operation of ultrahigh arch dams may impose significant perturbations to surrounding mountains, resulting in landslide motions of rock slopes and endangering the safety of hydropower systems and human habitats. For example, the Laxiwa Hydropower Station in China witnessed its nearby Guobu slope displacing significantly after the reservoir impoundment and having so far displaced up to ~40 m. It is of great importance to understand the mechanisms driving this large deformation. Here, we present some preliminary results from a combined remote sensing and numerical modelling investigation of this slope before, during, and after the reservoir impoundment. Analysis based on the differential interferometric synthetic aperture radar (DInSAR) data indicates that the slope had already been actively creeping at a rate of ~10 cm/year (e.g. in years of 2003-2005). We develop a geological model including different rock mass compartments and various discontinuity structures as well as a realistic representation of the suspended ancient landslide. We model the coupled hydro-mechanical and creep behaviour of the slope in response to reservoir impoundment. A good agreement is reached between the simulation results and field measurements of slope displacement time series recorded at different elevations of the slope surface. Our results show that the reservoir impoundment causes notable pressure changes at the toe region of the slope, leading to strong deformations (under coupled poroelastic and primary creep effects) that propagate upslope with the ancient landslide partially reactivated. These deformations tend to decelerate significantly after the impoundment due to the transition to secondary creeps.
Rapid mapping of landslides using satellite SAR imagery: A progressive learning approach
Prakash, Nikhil; Manconi, Andrea; Mondini, Alessandro Cesare (2025)
Applied Computing and Geosciences
Rapid detection of landslides after an exceptional event is critical for planning effective disaster management. Previous works have typically used machine learning-based methods, including the recently popular deep-learning approaches, to identify characteristics surface features from satellite remote sensing data, especially from optical images. However, data acquisition from optical images is not possible in cloudy conditions, leading to unpredictable delays in any mapping task from future events. These methods also rely on large manually labelled inventories for training, which is often not available before the event. In this work, we propose an active training strategy to generate a landslide map after an event using the first available synthetic-aperture radar (SAR) image and improve it once subsequent cloud-free optical images are acquired. The proposed active learning workflow can start with a small (∼100m2) and incomplete inventory,- and can grow the extent and completeness in iterative steps with manual updates after each step. This significantly reduces the slow manual mapping typically required for generating a large training inventory. We designed our experiments to map the landslides triggered by the Mw 6.6 Hokkaido Eastern Iburi earthquake of 2018 in Japan using sequentially ALOS-2 (SAR) and PlanetScope (Optical) scenes in the order they are acquired. The choice of active learning prioritizes speed over accuracy. However, we note only a modest reduction in performance (∼10% drop in F1 and MCC scores), with our method allowing a preliminary landslide inventory to be completed within a single day. This is of major importance in disaster response, improving performance and reducing the potential subjectivity associated with manual mapping.
Automated Detection of Lunar Rockfalls Using a Convolutional Neural Network
Bickel, Valentin; Lanaras, Charis; Manconi, Andrea; et al. (2018)
IEEE Transactions on Geoscience and Remote Sensing
Monitoring the displacement of large alpine rock slope instabilities with L-band SAR interferometric techniques
Strozzi, Tazio; Jones, Nina; Agliardi, Federico; et al. (2025)
EGUsphere
Large rock slope instabilities develop over long periods and creep slowly over hundreds or thousands of years, until they undergo a 'slow to fast' evolution towards catastrophic collapse. Capturing this transition is key to manage related risks, especially considering ongoing climate change scenarios and human activities, that are expected to strongly influence geohazards. However, this is a challenging task due to the complexity of the underlying processes. Long-term, area-wide monitoring of slope movements is essential to understand landslide dynamics and evolution. Despite being widely used for landslide investigations, C-band SAR interferometry datasets suffer from decorrelation in vegetated areas and fast movements, limiting displacement retrieval in alpine regions. Emerging L-band systems, with reduced temporal decorrelation, can complement higher-frequency data by enabling measurements also in vegetated areas and capturing larger displacements. This work aims at analysing the potential benefits and limitations of L-band SAR interferometry applied to alpine landslide monitoring and at understanding if these data can help in mitigating current shortcomings of C-band SAR interferometry. We explore three different scenarios of large alpine slope instabilities in the European Alps, that threaten important economic and societal assets. We perform site-specific analysis, validation and interpretation of L-band SAR interferometry products derived from ALOS-2 PALSAR-2 and SAOCOM-1 satellite imagery, as well as of terrestrial data acquired by the GAMMA L-band SAR (GLSAR) instrument. Our results highlight the contributions of L-band InSAR products to the practical characterisation and interpretation of large rock slope instabilities and provide important recommendations for the recently launched L-band satellite SAR missions ALOS-4 PALSAR-3 and NISAR, as well as for the future L-band satellite SAR mission ROSE-L.
Classification of Seismic Events with Deep Learning Strategies: Insights from the Moosfluh Landslide
Dazzi, Nadir; Manconi, Andrea; Prakash, Nikhil; et al. (2020)
EGUsphere
Rockfalls affect steep slopes in several geographic regions. Different systems from remote to in-situ instruments are used for their detection and study. In this scenario, seismic signals produced by the detachment, bouncing, and rolling of rockfalls are being increasingly used for the detection and classification of such events. This is typically done by using different manual, semi-automatic and/or automatic signal processing strategies. In this work, we applied a new Deep Learning (DL) algorithm in order to test the performance on the automatic classification of seismic signals. We applied the method to seismic data acquired by a low-cost Raspberry Shake 1D seismometer (sampling rate 50Hz) in order to discriminate rockfall from not-rockfall events occurred at the Moosfluh active slope region in Wallis (CH). Here we present the methodology and show the results obtained on a continuous record of more than 2-years of seismic data. The performance accuracy of the DL approach reached values larger than 90%. Our results show that the application of DL strategies in this context can be very useful and save time on seismic data classification.
Investigation of slope instabilities in NW Bhutan as derived from systematic DInSAR analyses
Dini, Benedetta; Manconi, Andrea; Loew, Simon (2019)
Engineering Geology
From toppling to sliding: progressive evolution of the Moosfluh Landslide, Switzerland
Glueer, Franziska; Loew, Simon; Manconi, Andrea; et al. (2019)
Journal of Geophysical Research: Earth Surface
This paper presents a detailed analysis of a dramatic rock slope acceleration that occurred in fall 2016 at the Moosfluh Landslide, located at the glacier tongue of the Great Aletsch Glacier (Switzerland). The acceleration that occurred in 2016 was unanticipated and exposed the valley bottom and an adjacent damned lake to high risk. This acceleration occurred in an active deep‐seated gravitational slope deformation (DSGSD) controlled primarily by deep block‐flexural toppling. In 2013, a highly accurate displacement monitoring system was developed and installed in the surroundings of the Great Aletsch Glacier, including a time‐lapse camera, GNSS, and robotic total stations. This monitoring system provided unique data during the 2016 slope acceleration which are used in this study to assess failure mechanisms, landslide volumes, and subsurface displacement geometry. Based on a novel displacement vector analysis, we find that three retrogressive secondary rockslides developed during the first six weeks of the slope acceleration, with rupture surface depths of 30 to 40 m, and estimated volumes between 1 and 4 Mm³. These rockslides display complex deformation features, including head and lateral scarps, which developed during the slope acceleration. The kinematics of these secondary rockslides changed through time, from primarily toppling to combined toppling and sliding. Our results provide a uniquely detailed understanding of the spatial and temporal evolution of deformation features and movement kinematics that occur when several sectors of a slowly moving DSGSD transitions into rapid rockslides.
Satellitenfernerkundung der räumlichen und zeitlichen Entwicklung der Oberflächendeformationen
Jones, Nina; Manconi, Andrea; Loew, Simon (2022)
Schweizerische Zeitschrift für Forstwesen
Die Bewegungen und die kinematische Interpretation des Rutschungskomplexes von Brienz/Brinzauls (GR) sind Gegenstand detaillierter Untersuchungen. Sie liefern Grundlagen, um die Gefährdung des Dorfes zu beurteilen und entsprechende Massnahmen zu planen. Neben den klassischen Methoden Total Station (TPS), Global Navigation Satellite Systems (GNSS) und Inklinometer kommen auch terrestrische Radarinterferometrie und digitale Bildanalyse zum Einsatz. Dieser Artikel beschreibt neue Methoden der Integration Satelliten-basierter Radar-Interferometrie (DInSAR) und der digitalen Bildkorrelationsanalyse, die ein flächendeckendes Abbild des Verschiebungsverhaltens in drei Dimensionen generieren. In der Folge beschreiben wir die Stapelung differenzieller Interferogramme von C-, L- und X-Band-Radar-Satellitendaten sowie die Integration von Ergebnissen der Interferometrie mit digitaler Korrelation von hochaufgelösten optischen und Radarbildern der Jahre 2015 bis 2020. Auf der Basis dieser Resultate werden anschliessend verschiedene Verformungskomponenten des Rutschungskomplexes ermittelt, die für die Ermittlung von Rutschungskompartimenten und ihrer Kinematik wesentlich sind. Die Ergebnisse werden mit existierenden GNSS-Messdaten validiert.
Integration of Multi-Sensor L-Band DInSAR Surface Motion Products for Landslide Monitoring
Strozzi, Tazio; Caduff, Rafael; Bernhard, Philipp; et al. (2025)
IGARSS 2025 - 2025 IEEE International Geoscience and Remote Sensing Symposium
L-band SAR interferometry has shown a great potential for the efficient mapping and monitoring of mass movements in alpine environments. Satellite SAR data at L-band are currently being collected among others by ALOS-2 PALSAR-2 since 2014 and SAOCOM-1 since 2018. In addition, we are acquiring high-resolution L-band SAR imagery with a car-borne system. These different L-band sensors collect data with various time intervals and viewing geometries, which need to be integrated to be effectively exploited by users. In this paper we present our first experiments in this respect at three sites in Italy and Switzerland, characterized by slope deformations of different type, size and rate of movement. Forall sites, we present the L-band results of the three sensors, emphasizing their complementarity and peculiarities.
Patterns of reversible ground surface deformations in crystalline rock slopes
Oestreicher, Nicolas K.; Loew, Simon; Roques, Clément; et al. (2019)
Geophysical Research Abstracts

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