scholarly journals A multi-scale methodological approach for slow-moving landslide risk mitigation in urban areas, southern Italy

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Settimio Ferlisi ◽  
Giovanni Gullà ◽  
Gianfranco Nicodemo ◽  
Dario Peduto
Keyword(s):  
Urban Areas ◽  
Southern Italy ◽  
Risk Mitigation ◽  
Methodological Approach ◽  
Landslide Risk ◽  
Multi Scale ◽  
Slow Moving

scholarly journals Small-scale analysis to rank municipalities requiring slow-moving landslide risk mitigation measures: the case study of the Calabria region (southern Italy)

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Giovanni Gullà ◽  
Gianfranco Nicodemo ◽  
Settimio Ferlisi ◽  
Luigi Borrelli ◽  
Dario Peduto
Keyword(s):  
Southern Italy ◽  
Risk Mitigation ◽  
Mitigation Measures ◽  
Economic Losses ◽  
Phase Method ◽  
Small Scale ◽  
Landslide Risk ◽  
Calabria Region ◽  
Slow Moving ◽  
Gis Environment

AbstractThis paper proposes a three-phase method that combines multi-source (i.e. topographic, thematic, monitoring) input data in a GIS environment to rank—at small (1:250,000) scale—administrative units (e.g. municipalities) based on their exposure to slow-moving landslide risk within a selected area (e.g. a region) and, accordingly, detect those primarily requiring mitigation measures. The method is applied in the Calabria region (southern Italy) where several municipalities are widely affected by slow-moving landslides that systematically cause damage to buildings and infrastructure networks resulting in significant economic losses. The results obtained are validated based on the information gathered from previous studies carried out at large (municipal) scale. The work undertaken represents a first, fundamental step of a wider circular approach that can profitably facilitate the decision makers in addressing the issue of the slow-moving landslide risk mitigation in a sustainable way.

scholarly journals Full integration of geomorphological, geotechnical, A-DInSAR and damage data for detailed geometric-kinematic features of a slow-moving landslide in urban area

Landslides ◽  
2020 ◽  
Author(s):  
Dario Peduto ◽  
Mariantonia Santoro ◽  
Luigi Aceto ◽  
Luigi Borrelli ◽  
Giovanni Gullà
Keyword(s):  
Urban Areas ◽  
Structural Model ◽  
Risk Mitigation ◽  
Integrated Approach ◽  
Mitigation Strategies ◽  
Landslide Risk ◽  
Conditioning Factors ◽  
Source Data ◽  
Slow Moving ◽  
Set Up

Abstract The reconnaissance, mapping and analysis of kinematic features of slow-moving landslides evolving along medium-deep sliding surfaces in urban areas can be a difficult task due to the presence and interactions of/with anthropic structures/infrastructures and human activities that can conceal morphological signs of landslide activity. The paper presents an integrated approach to investigate the boundaries, type of movement, kinematics and interactions (in terms of damage severity distribution) with the built environment of a roto-translational slow-moving landslide affecting the historic centre of Lungro town (Calabria region, southern Italy). For this purpose, ancillary multi-source data (e.g. geological-geomorphological features and geotechnical properties of geomaterials), both conventional inclinometer monitoring and innovative non-invasive remote sensing (i.e. A-DInSAR) displacement data were jointly analyzed and interpreted to derive the A-DInSAR-geotechnical velocity (DGV) map of the landslide. This result was then cross-compared with detailed information available on the visible effects (i.e. crack pattern and width) on the exposed buildings along with possible conditioning factors to displacement evolution (i.e. remedial works, sub-services, etc.). The full integration of multi-source data available at the slope scale, by maximizing each contribution, provided a comprehensive outline of kinematic-geometric landslide features that were used to investigate the damage distribution and to detect, if any, anomalous locations of damage severity and relative possible causes. This knowledge can be used to manage landslide risk in the short term and, in particular, is propaedeutic to set up an advanced coupled geotechnical-structural model to simulate both the landslide displacements and the behavior of interacting buildings and, therefore, to implement appropriate risk mitigation strategies over medium/long period.

scholarly journals Debris-flow susceptibility assessment through cellular automata modeling: an example from 15–16 December 1999 disaster at Cervinara and San Martino Valle Caudina (Campania, southern Italy)

2003 ◽  
Vol 3 (5) ◽  
pp. 457-468 ◽  
Author(s):  
G. Iovine ◽  
S. Di Gregorio ◽  
V. Lupiano
Keyword(s):  
Cellular Automata ◽  
Debris Flow ◽  
Urban Areas ◽  
Debris Flows ◽  
Soil Cover ◽  
Southern Italy ◽  
Landslide Risk ◽  
Campania Region ◽  
Optimal Values ◽  
Debris Flow Susceptibility

Abstract. On 15–16 December 1999, heavy rainfall severely stroke Campania region (southern Italy), triggering numerous debris flows on the slopes of the San Martino Valle Caudina-Cervinara area. Soil slips originated within the weathered volcaniclastic mantle of soil cover overlying the carbonate skeleton of the massif. Debris slides turned into fast flowing mixtures of matrix and large blocks, downslope eroding the soil cover and increasing their original volume. At the base of the slopes, debris flows impacted on the urban areas, causing victims and severe destruction (Vittori et al., 2000). Starting from a recent study on landslide risk conditions in Campania, carried out by the Regional Authority (PAI –Hydrogeological setting plan, in press), an evaluation of the debris-flow susceptibility has been performed for selected areas of the above mentioned villages. According to that study, such zones would be in fact characterised by the highest risk levels within the administrative boundaries of the same villages ("HR-zones"). Our susceptibility analysis has been performed by applying SCIDDICA S3–hex – a hexagonal Cellular Automata model (von Neumann, 1966), specifically developed for simulating the spatial evolution of debris flows (Iovine et al., 2002). In order to apply the model to a given study area, detailed topographic data and a map of the erodable soil cover overlying the bedrock of the massif must be provided (as input matrices); moreover, extent and location of landslide source must also be given. Real landslides, selected among those triggered on winter 1999, have first been utilised for calibrating SCIDDICA S3–hex and for defining "optimal" values for parameters. Calibration has been carried out with a GIS tool, by quantitatively comparing simulations with actual cases: optimal values correspond to best simulations. Through geological evaluations, source locations of new phenomena have then been hypothesised within the HR-zones. Initial volume for these new cases has been estimated by considering the actual statistics of the 1999 landslides. Finally, by merging the results of simulations, a deterministic susceptibility zonation of the considered area has been obtained. In this paper, aiming at illustrating the potential for debris-flow hazard analyses of the model SCIDDICA S3–hex, a methodological example of susceptibility zonation of the Vallicelle HR-zone is presented.

scholarly journals Landslide Characteristics and Evolution: What We Can Learn from Three Adjacent Landslides

2021 ◽  
Vol 13 (22) ◽  
pp. 4579
Author(s):  
Dongdong Yang ◽  
Haijun Qiu ◽  
Yaru Zhu ◽  
Zijing Liu ◽  
Yanqian Pei ◽  
...  
Keyword(s):  
Time Series ◽  
Risk Mitigation ◽  
Landslide Risk ◽  
Significant Heterogeneity ◽  
Interferometric Synthetic Aperture Radar ◽  
Antecedent Precipitation ◽  
Surface Time ◽  
Field Investigations ◽  
Landslide Processes ◽  
Slow Moving

Landslide processes are a consequence of the interactions between their triggers and the surrounding environment. Understanding the differences in landslide movement processes and characteristics can provide new insights for landslide prevention and mitigation. Three adjacent landslides characterized by different movement processes were triggered from August to September in 2018 in Hualong County, China. A combination of surface and subsurface characteristics illustrated that Xiongwa (XW) landslides 1 and 2 have deformed several times and exhibit significant heterogeneity, whereas the Xiashitang (XST) landslide is a typical retrogressive landslide, and its material has moved downslope along a shear surface. Time-series Interferometric Synthetic Aperture Radar (InSAR) and Differential InSAR (DInSAR) techniques were used to detect the displacement processes of these three landslides. The pre-failure displacement signals of a slow-moving landslide (the XST landslide) can be clearly revealed by using time-series InSAR. However, these sudden landslides, which are a typical catastrophic natural hazard across the globe, are easily ignored by time-series InSAR. We confirmed that effective antecedent precipitation played an important role in the three landslides’ occurrence. The deformation of an existing landslide itself can also trigger new adjacent landslides in this study. These findings indicate that landslide early warnings are still a challenge since landslide processes and mechanisms are complicated. We need to learn to live with natural disasters, and more relevant detection and field investigations should be conducted for landslide risk mitigation.

Assessing Seismic Resilience of School Educational Sector. An attempt to establish the initial conditions in Calabria Region, Southern Italy

2021 ◽  
Author(s):  
Cora Fontana ◽  
Eleonora Cianci ◽  
Massimiliano Moscatelli
Keyword(s):  
Urban Areas ◽  
Southern Italy ◽  
Initial Conditions ◽  
Risk Mitigation ◽  
School Buildings ◽  
Calabria Region ◽  
Structural Improvement ◽  
First Case ◽  
School Sector ◽  
Seismic Resilience

<p>School education constitutes one of the strategic functions to be recovered after an earthquake. The structural improvement of school buildings together with the strengthening of the administrators’ capacity to react positively following an earthquake are key factors that contribute to social vulnerability’s reduction. Nevertheless, in Italy, the issue of risk reduction policies related to school sector is not yet consolidated in the institutional agendas. Observing the last major Italian earthquakes what remains predominant is school buildings’ damage degree with consequent interruption of the system functionality. Among the causes: the building heritage vulnerability and the lack of risk mitigation policies, capable of building a resilient community for future earthquakes. That of resilience is considered a relevant paradigm to address the issue of how to strengthen the school sector’s capacity to ensure the buildings physical safety and to guarantee the maintenance of the school function, looking at pre and post-event phases.</p><p>The paper proposes a set of indicators and a methodology for a preliminary assessment of the educational sector’s seismic resilience, in terms of initial conditions. The method has been tested on a first case study: Calabria Region, Southern Italy. The results show that spatial differences in the educational sector’s seismic resilience are evident. Except for some large urban areas, the less resilient areas are grouped mainly in the southern part of the Region, while the most resilient ones are located mostly in the central-northern sector. The ambition is to identify a repeatable approach, useful as guidelines for school seismic prevention policies.</p>

scholarly journals InSAR Monitoring of Landslide Activity in Dominica

2021 ◽  
Vol 13 (4) ◽  
pp. 815
Author(s):  
Mary-Anne Fobert ◽  
Vern Singhroy ◽  
John G. Spray
Keyword(s):  
Risk Mitigation ◽  
Disaster Mitigation ◽  
Aerial Images ◽  
Landslide Inventory ◽  
Landslide Risk ◽  
Susceptibility Map ◽  
Interferometric Synthetic Aperture Radar ◽  
Rainfall Events ◽  
Susceptibility Maps ◽  
Digital Elevation

Dominica is a geologically young, volcanic island in the eastern Caribbean. Due to its rugged terrain, substantial rainfall, and distinct soil characteristics, it is highly vulnerable to landslides. The dominant triggers of these landslides are hurricanes, tropical storms, and heavy prolonged rainfall events. These events frequently lead to loss of life and the need for a growing portion of the island’s annual budget to cover the considerable cost of reconstruction and recovery. For disaster risk mitigation and landslide risk assessment, landslide inventory and susceptibility maps are essential. Landslide inventory maps record existing landslides and include details on their type, location, spatial extent, and time of occurrence. These data are integrated (when possible) with the landslide trigger and pre-failure slope conditions to generate or validate a susceptibility map. The susceptibility map is used to identify the level of potential landslide risk (low, moderate, or high). In Dominica, these maps are produced using optical satellite and aerial images, digital elevation models, and historic landslide inventory data. This study illustrates the benefits of using satellite Interferometric Synthetic Aperture Radar (InSAR) to refine these maps. Our study shows that when using continuous high-resolution InSAR data, active slopes can be identified and monitored. This information can be used to highlight areas most at risk (for use in validating and updating the susceptibility map), and can constrain the time of occurrence of when the landslide was initiated (for use in landslide inventory mapping). Our study shows that InSAR can be used to assist in the investigation of pre-failure slope conditions. For instance, our initial findings suggest there is more land motion prior to failure on clay soils with gentler slopes than on those with steeper slopes. A greater understanding of pre-failure slope conditions will support the generation of a more dependable susceptibility map. Our study also discusses the integration of InSAR deformation-rate maps and time-series analysis with rainfall data in support of the development of rainfall thresholds for different terrains. The information provided by InSAR can enhance inventory and susceptibility mapping, which will better assist with the island’s current disaster mitigation and resiliency efforts.

scholarly journals The Geo-Social Model: A Transdisciplinary Approach to Flow-Type Landslide Analysis and Prevention

2021 ◽  
Vol 13 (5) ◽  
pp. 2501
Author(s):  
Valentina Acuña ◽  
Francisca Roldán ◽  
Manuel Tironi ◽  
Leila Juzam
Keyword(s):  
Urban Areas ◽  
Risk Perceptions ◽  
Risk Prevention ◽  
Social Model ◽  
Experimental Methodology ◽  
Landslide Risk ◽  
Sociocultural Environment ◽  
Flow Type ◽  
Complex Interactions ◽  
Municipal Level

Landslide disaster risks increase worldwide, particularly in urban areas. To design and implement more effective and democratic risk reduction programs, calls for transdisciplinary approaches have recently increased. However, little attention has been paid to the actual articulation of transdisciplinary methods and their associated challenges. To fill this gap, we draw on the case of the 1993 Quebrada de Macul disaster, Chile, to propose what we label as the Geo-Social Model. This experimental methodology aims at integrating recursive interactions between geological and social factors configuring landslide for more robust and inclusive analyses and interventions. It builds upon three analytical blocks or site-specific environments in constant co-determination: (1) The geology and geomorphology of the study area; (2) the built environment, encompassing infrastructural, urban, and planning conditions; and (3) the sociocultural environment, which includes community memory, risk perceptions, and territorial organizing. Our results are summarized in a geo-social map that systematizes the complex interactions between the three environments that facilitated the Quebrada de Macul flow-type landslide. While our results are specific to this event, we argue that the Geo-Social Model can be applied to other territories. In our conclusions, we suggest, first, that landslides in urban contexts are often the result of anthropogenic disruptions of natural balances and systems, often related to the lack of place-sensitive urban planning. Second, that transdisciplinary approaches are critical for sustaining robust and politically effective landslide risk prevention plans. Finally, that inter- and trans-disciplinary approaches to landslide risk prevention need to be integrated into municipal-level planning for a better understanding of—and prevention of—socio-natural hazards.

scholarly journals Integration of Satellite InSAR with a Wireless Network of Geotechnical Sensors for Slope Monitoring in Urban Areas: The Pariana Landslide Case (Massa, Italy)

2021 ◽  
Vol 13 (13) ◽  
pp. 2534
Author(s):  
Andrea Ciampalini ◽  
Paolo Farina ◽  
Luca Lombardi ◽  
Massimiliano Nocentini ◽  
Veronica Taurino ◽  
...  
Keyword(s):  
Urban Areas ◽  
Temporal Evolution ◽  
Monitoring Program ◽  
Slope Instability ◽  
Time Data ◽  
Public Authorities ◽  
Slope Movements ◽  
Multi Temporal ◽  
Slow Moving ◽  
Slope Monitoring

Slow to extremely slow landslides in urban areas may cause severe damage to buildings and infrastructure that can lead to the evacuation of local populations in case of slope accelerations. Monitoring the spatial and temporal evolution of this type of natural hazard represents a major concern for the public authorities in charge of risk management. Pariana, a village with 400 residents located in the Apuan Alps (Massa, Tuscany, Italy), is an example of urban settlement where the population has long been forced to live with considerable slope instability. In the last 30 years, due to the slope movements associated with a slow-moving landslide that has affected a significant portion of the built-up area, several buildings have been damaged, including a school and the provincial road crossing the unstable area, leading to the need for an installation of a slope monitoring system with early warning capabilities, in parallel with the implementation of mitigation works. In this paper, we show how satellite multi-temporal interferometric synthetic aperture radar (MT-InSAR) data can be effectively used when coupled with a wireless sensor network made of several bar extensometers and a borehole inclinometer. In fact, thanks to their wide area coverage and opportunistic nature, satellite InSAR data allow one to clearly identify the spatial distribution of surface movements and their long-term temporal evolution. On the other hand, geotechnical sensors installed on specific elements at risk (e.g., private buildings, retaining walls, etc.), and collected through Wi-Fi dataloggers, provide near real-time data that can be used to identify sudden accelerations in slope movements, subsequently triggering alarms. The integration of those two-monitoring systems has been tested and assessed in Pariana. Results show how a hybrid slope monitoring program based on the two different technologies can be used to effectively monitor slow-moving landslides and to identify sudden accelerations and activate a response plan.

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