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Landslides represent a severe geohazard in many countries. The availability of inventories depicting the spatial and temporal distribution of landslides is crucial for assessing landslide susceptibility and risk for territorial planning or investigating landscape evolution. Nevertheless, these inventories are usually affected by limitations due to their nonpublic availability and inhomogeneities in characterization and mapping. Such problems are fully recognizable by the analysis of the multiple landslide inventories of the Campania region, which is one of the Italian regions with the highest exposure to landslide hazard and risk. On this basis, a revised Landslide Inventory of the Campania region (LaICa), resulting from the processing of multiple existing landslide inventories, has been reconstructed. It aims to (i) provide a new geodatabase that is able to overcome issues derived from the coexistence of multiple inventories and (ii) provide a methodological paradigm able to support the reorganization of existing official inventories. The implication of LaICa, with its 83,284 records, will possibly improve the assessment of landslide susceptibility and then reassess the related risk. Measurement(s) landslide Technology Type(s) Data Set [ABSTRACT FROM AUTHOR]

This paper focuses on Deep-Seated Gravitational Slope Deformations (DSGSDs) identified in the Molise region (Italy), along the central-southern sector of the Apennines chain. These phenomena were detected and mapped through a combination of aerial-photo interpretation, morphological analyses, and field surveys, integrated through satellite SAR interferometry (InSAR). The obtained general map is organized in different sections: inventory map with identification of DSGSDs and main geological and orographic features, geostructural scheme, representative cross sections, list and characteristics of DSGSDs, geomorphometric maps, landslides map, and seismotectonic setting. This study allowed us to realize a complete inventory of DSGSDs in the Molise region and define the main characteristics of each phenomenon. Through this research, it was possible to establish a general correlation between the analyzed deformations and the geological and geomorphological setting of the region as well as with its geodynamic context. [ABSTRACT FROM AUTHOR]

The occurrence of geological events such as landslides is one of the main causes of damage along linear infrastructures: Damage to transport infrastructures, as roads, bridges, and railways, can restrict their optimal functions and contribute to traffic accidents. The frequent and accurate monitoring of slope instability phenomena and of their interaction with existing man-made infrastructures plays a key role in risk prevention and mitigation activities. In this way, the use of high-resolution X-band synthetic aperture radar (SAR) data, characterized by short revisiting times, has demonstrated to be a powerful tool for a periodical noninvasive monitoring of ground motion and superstructure stability, aimed at improving the efficiency of inspection, repairing, and rehabilitation efforts. In the present work, we suggest a semiautomatic GIS approach, which, by using satellite radar interferometry data and results of geomorphological field survey integrated in a qualitative vulnerability matrix, allows to identify sections with different levels of damage susceptibility, where detailed conventional in situ measurements are required for further analysis. The procedure has been tested to investigate landslide-induced effects on a linear infrastructure in Campania Region (Italy), the Provincial Road "P.R. 264", which is affected, along its linear development, by several slope instabilities. COSMO-SkyMed interferometric products, as indicator of ground kinematics, and results of in situ damage survey, as indicator of consequences, have been merged in a qualitative 4 × 4 matrix, thus obtaining a vulnerability zoning map along a linear infrastructure in January 2015. Furthermore, an updating of landslide inventory map is provided: In addition to 24 official landslides pre-mapped in 2012, 30 new events have been identified, and corresponding intensity and state of activity has been detected. [ABSTRACT FROM AUTHOR]

The Cinque Terre National Park (38 km2) has recently recorded a remarkable increase in tourists involved in outdoor activities such as hiking. However, due to the actual slope degradation issues that affect this outstanding terraced landscape, hiking trails are increasingly threatened by the impact of landslides. This produces severe landslide-related risk scenarios for hikers. In this study, a landslide inventory map (at 1:45000 scale) has been prepared through the revision/update of previous database and the analysis of air-photos and satellite images coupled with field surveys. Furthermore, a quantitative evaluation of the interaction between landslides and hiking trails has been performed by the definition of a Footpath Landslide Index. More than 400 landslides were identified highlighting that these phenomena represent the main source of hazard. The findings of this study reveal that side-hill trails are the most hazardous since hikers can be potentially affected by flow-like or fast-moving landslides. [ABSTRACT FROM AUTHOR]

The Apennine provinces of Campania Region (southern Italy), Benevento, Avellino and Salerno, are known for their ‘unstable towns’ suffering periodic damage from landslides. Their identification and mapping are very challenging tasks, since boundary mapping under urban settlements is not always possible without time-consuming field analysis of building damage and/or expensive mid-term diffuse ground-surface deformation monitoring. To overcome this problem, an inventory of town-damaging landslides, guided by available Permanent Scatterers (PS) ground-deformation data, was prepared. It provides an updated tool suitable to guide future land planning and historical site restoration in the Apennine provinces of Campania Region. Our fourteen Map Sheets show active and local reactivation of suspended/dormant landslides. Overall, 356 landslides were identified, amongst which 162 were identified as flows, 101 as slides, 1 as a spreads and 92 as complex landslides. To supplement our maps, a simplified distribution analysis based on major landslide morphometric characteristics was completed. [ABSTRACT FROM AUTHOR]

The paper shows an innovative methodology which can be used to forecast the spatial and temporal evolution of the buildings’ structural vulnerability in urban settlements affected by slow-moving intermittent landslides. Multi-level and integrated analysis, of conventional and innovative monitoring techniques with structural analysis methods for damage assessment allows to estimate, at different levels of accuracy, future conditions of damage and local failures of single buildings and building aggregates. To this purpose, in the last decade, Satellite Radar Interferometry and in particular the Differential SAR Interferometry (DInSAR) technique has been successfully applied as a remote-sensing tool in several analyses aimed at prediction and mitigation of buildings’ damage induced by slow-moving landslides. The proposed methodology has been here applied to the urban settlement of Moio della Civitella (Salerno province, Italy). [ABSTRACT FROM AUTHOR]

This work presents the ideal combination of space-borne and ground-based (GB) Interferometric Synthetic Aperture Radar (InSAR) applications. In the absence of early investigation reporting and specialized monitoring, the Zhongbao landslide unexpectedly occurred on 25 July 2020, forming a barrier lake that caused an emergency. As an emergency measure, the GB-InSAR system was installed 1.8 km opposite the landslide to assess real-time cumulative deformation with a monitoring frequency of 3 min. A zone of strong deformation was detected, with 178 mm deformation accumulated within 15 h, and then a successful emergency warning was issued to evacuate on-site personnel. Post-event InSAR analysis of 19 images acquired by the ESA Sentinel-1 from December 2019 to August 2020 revealed that the landslide started in March 2020. However, the deformation time series obtained from satellite InSAR did not show any signs that the landslide had occurred. The results suggest that satellite InSAR is effective for mapping unstable areas but is not qualified for rapid landslide monitoring and timely warning. The GB-InSAR system performs well in monitoring and providing early warning, even with dense vegetation on the landslide. The results show the shortcomings of satellite InSAR and GB-InSAR and a clearer understanding of the necessity of combining multiple monitoring methods. [ABSTRACT FROM AUTHOR]

In most countries, landslides have caused severe socioeconomic impacts on people, cities, industrial establishments, and lifelines, such as highways, railways, and communication network systems. Socioeconomic losses due to slope failures are very high and they have been growing as the built environment expands into unstable hillside areas under the pressures of growing populations. Human activities as the construction of buildings, transportation routes, dams, and artificial canals have often been a major factor for the increasing damage due to slope failures. When recovery actions are not durable from an economic point of view, increasing the population's awareness is the key strategy to reduce the effects of natural and anthropogenic events. Starting from the case study of the Pan-American Highway (the Ecuadorian part), this article shows a multi-approach strategy for infrastructure monitoring. The combined use of (i) DInSAR technique for detection of slow ground deformations, (ii) field survey activities, and (iii) the QPROTO tool for analysis of slopes potentially prone to collapse allowed us to obtain a first cognitive map to better characterize 22 km of the highway between the cities of Cuenca and Azogues. This study is the primary step in the development of a landslide awareness perspective to manage risk related to landslides along infrastructure corridors, increasing user safety and providing stakeholders with a management system to plan the most urgent interventions and to ensure the correct functionality of the infrastructure. [ABSTRACT FROM AUTHOR]

Rainfall-induced shallow landslides represent a serious threat in hilly and mountain areas around the world. The mountainous landscape of the Cinque Terre (eastern Liguria, Italy) is increasingly popular for both Italian and foreign tourists, most of which visit this outstanding terraced coastal landscape to enjoy a beach holiday and to practice hiking. However, this area is characterized by a high level of landslide hazard due to intense rainfalls that periodically affect its rugged and steep territory. One of the most severe events occurred on 25 October 2011, causing several fatalities and damage for millions of euros. To adequately address the issues related to shallow landslide risk, it is essential to develop landslide susceptibility models as reliable as possible. Regrettably, most of the current land-use and urban planning approaches only consider the susceptibility to landslide detachment, neglecting transit and runout processes. In this study, the adoption of a combined approach allowed to estimate shallow landslide susceptibility to both detachment and potential runout. At first, landslide triggering susceptibility was assessed using Machine Learning techniques and applying the Ensemble approach. Nine predisposing factors were chosen, while a database of about 300 rainfall-induced shallow landslides was used as input. Then, a Geographical Information System (GIS)-based procedure was applied to estimate the potential landslide runout using the "reach angle" method. Information from such analyses was combined to obtain a susceptibility map describing detachment, transit, and runout. The obtained susceptibility map will be helpful for land planning, as well as for decision makers and stakeholders, to predict areas where rainfall-induced shallow landslides are likely to occur in the future and to identify areas where hazard mitigation measures are needed. [ABSTRACT FROM AUTHOR]

Climate change has increased the likelihood of the occurrence of disasters like wildfires, floods, storms, and landslides worldwide in the last years. Weather conditions change continuously and rapidly, and wildfires are occurring repeatedly and diffusing with higher intensity. The burnt catchments are known, in many parts of the world, as one of the main sensitive areas to debris flows characterized by different trigger mechanisms (runoff-initiated and debris slide-initiated debris flow). The large number of studies produced in recent decades has shown how the response of a watershed to precipitation can be extremely variable, depending on several on-site conditions, as well as the characteristics of precipitation duration and intensity. Moreover, the availability of satellite data has significantly improved the ability to identify the areas affected by wildfires, and, even more importantly, to carry out post-fire assessment of burnt areas. Many difficulties have to be faced in attempting to assess landslide risk in burnt areas, which present a higher likelihood of occurrence; in densely populated neighbourhoods, human activities can be the cause of the origin of the fires. The latter is, in fact, one of the main operations used by man to remove vegetation along slopes in an attempt to claim new land for pastures or construction purposes. Regarding the study area, the Camaldoli and Agnano hill (Naples, Italy) fires seem to act as a predisposing factor, while the triggering factor is usually represented by precipitation. Eleven predisposing factors were chosen and estimated according to previous knowledge of the territory and a database consisting of 400 landslides was adopted. The present work aimed to expand the knowledge of the relationship existing between the triggering of landslides and burnt areas through the following phases: (1) Processing of the thematic maps of the burnt areas through band compositions of satellite images; and (2) landslide susceptibility assessment through the application of a new statistical approach (machine learning techniques). The analysis has the scope to support decision makers and local agencies in urban planning and safety monitoring of the environment. [ABSTRACT FROM AUTHOR]

• A tool to detect spatio-temporal landslide-induced effects on buildings is presented. • Building performace is investigated by DInSAR and structural analyses. • Pre- and post-repair intervention is analyzed by DInSAR time-series. Slow-moving landslides are a natural hazard which affects wide areas in the world and often are cause of significant damage to structures and infrastructures. Analysis of landslide evolution and of their interaction with existing man-made structures plays a key role in risk prevention and mitigation activities. To this purpose, a considerable interest towards innovative approaches has grown among the scientific community and land management institutions. In this work, Synthetic Aperture Radar data acquired by C-band and X-band sensors, combined with numerical analyses, have been successfully applied as a tool to detect spatial and temporal landslide-induced effects, in terms of deformations and structural behavior of a building affected by ground instability. Such approach has been applied to Moio della Civitella urban settlement (Salerno province, Italy), whose whole territory is interested by several slow-moving landslides. In detail, performance of a masonry building aggregate and the efficacy of restoration works have been investigated through an integrated assessment of displacement time-series pre- and post-repair intervention, and structural analysis performed with numerical code. Historical DInSAR data have permitted firstly the interpretation of building displacement time-series corresponding to pre- and post-works configurations; subsequently, the analysis of interpolated interferometric products has allowed to define gradient maps of vertical and horizontal displacements and to identify part of aggregate which can suffer a greater susceptibility to damage as a consequence of deformation gradients. Finally, the comparison of satellite and numerical data showed a substantial agreement with local failures and damage surveyed, thus confirming the capability of DInSAR technique to investigate building performance where no in situ displacement measurements were available. [ABSTRACT FROM AUTHOR]

The integration of data from different sources can be very helpful in understanding the mechanism, the geometry, the kinematic, and the area affected by complex instabilities, especially when the available geotechnical information is limited. In this work, the suitability of different techniques for the study of a deep-seated landslide affecting a bridge in Alcoy (Spain) is evaluated. This infrastructure presents such severe damage that has rendered the bridge unusable, which prevents normal access to an important industrial area. Differential SAR Interferometry (DInSAR) and terrestrial Light Detection and Ranging (LiDAR) remote sensing techniques have been combined with ground displacement monitoring techniques, such as inclinometers and conventional geological and geotechnical investigation, electrical-seismic tomography, damage, and topographic surveys, to determine the boundaries, mechanism, and kinematics of the landslide. The successful case study that is illustrated in this work highlights the potential and the need for integrating multi-source data for the optimal management of complex landslides and the effective design of remedial measurements. [ABSTRACT FROM AUTHOR]

Kinematic characterization of a landslide at large, small, and detailed scale is today still rare and challenging, especially for long periods, due to the difficulty in implementing demanding ground surveys with adequate spatiotemporal coverage. In this work, the suitability of space-borne synthetic aperture radar sub-pixel offset tracking for the long-term monitoring of the Slumgullion landslide in Colorado (US) is investigated. This landslide is classified as a debris slide and has so far been monitored through ground surveys and, more recently, airborne remote sensing, while satellite images are scarcely exploited. The peculiarity of this landslide is that it is subject to displacements of several meters per year. Therefore, it cannot be monitored with traditional synthetic aperture radar differential interferometry, as this technique has limitations related to the loss of interferometric coherence and to the maximum observable displacement gradient/rate. In order to overcome these limitations, space-borne synthetic aperture radar sub-pixel offset tracking is applied to pairs of images acquired with a time span of one year between August 2011 and August 2013. The obtained results are compared with those available in the literature, both at landslide scale, retrieved through field surveys, and at point scale, using airborne synthetic aperture radar imaging and GPS. The comparison showed full congruence with the past literature. A consistency check covering the full observation period is also implemented to confirm the reliability of the technique, which results in a cheap and effective methodology for the long-term monitoring of large landslide-induced movements. [ABSTRACT FROM AUTHOR]

Flow-like landslides triggered by rainfall are a major concern in the peri-Vesuvian region of southern Italy. On December 19th, 2019, a landslide occurred along the Crocelle slope (Sarno Mountains), which had previously experienced a similar event in February 1986. This study was conducted to assess the characteristics of this event in terms of triggering and propagation conditions and, with reference to the 1986 landslide, to evaluate the evolution of residual landslide hazards at recurring landslide sites. Data collection included field surveys, visual analysis of a Unmanned Aerial Vehicle (UAV)-based photogrammetric model, geotechnical laboratory testing, rainfall and slope stability analysis, and propagation modeling. Results suggest that the landslide i) originated below a trail, ii) involved an initial volume of 450 m3, which did not significantly grow due to the limited entrainment of slope sediments, iii) was initiated after 13 h of rainfall (return period ∼4 years), and iv) propagated along a channel with an estimated velocity of up to 10 m/s. Comparison of the 2019 event with the 1986 event revealed a significant difference in terms of landslide magnitude (i.e., volume), potentially due to the occurrence of multiple events, which may have led to the temporal depletion of available materials along a slope repeatedly affected by landslides, and possibly to the different behavior of primary layered deposits (involved in the 1986 event) compared to reworked deposits (involved in the 2019 event). This suggests a reduction in the residual landslide hazard associated with a decrease in the expected magnitude and frequency of prospective events. • The 2019 Palma Campania landslide was initiated following 13 h of precipitation; • The landslide encompassed reworked pyroclastic deposits underneath a trail; • The landslide propagated within a channel with a velocity of up to 10 m/s; • Slope failure is facilitated by prior hydrological conditions; • Slope-scale landslide hazard potentially decreases due to multiple landslides. [ABSTRACT FROM AUTHOR]

Deep-seated landslides are important agents of relief shaping and can have substantial impact on human settlements. Many examples are present in the Campania region of southern Italy, where the association of complex lithostratigraphic and structural geologic conditions might have effect on landslide initiation and evolution. On this basis and considering the effect that the deep-seated landslide have had in the last years on the urban settlement, the Buonalbergo landslide was analyzed in terms of decadal kinematics and geological control and insights in prospective evolution were provided. The analysis of data derived by geological and landslide field mapping, settlement damage analysis, Persistent Differential Interferometry SAR data analysis, and Finite Elements stability analysis revealed i) the approximately constant rate movement of the landslide in the last three decades with a consistent enlargement of its area, ii) the presence of a large overturned anticline, characterized by a complex lithostratigraphic arrangement and multiple discontinuity sets, iii) the presence of faults responsible for morphological depression development, iv) a rotational mechanism characterizing the upper sector of the landslide and the ongoing translational sliding of blocks located at its toe and v) the effect of potential pore pressure scenarios on prospective kinematics (i.e. single to multiple stages creep) with the observed constant rate movement potentially related to a pore pressure at the landslide base ranging between 300 and 400 kPa. Result interpretation suggests i) the role of the structural and lithostratigraphic setting of the slope as predisposing factor for landslide development, ii) the potential of fold-related fabric in controlling landslide geometry and fragmentation, iii) the possible occurrence of multiple landslide events affecting the slope affected by the deep-seated landslide and iv) the potential of hydrologic conditions in modulating landslide velocity and evolution toward slope failure. The relevance of results is related to the representativeness of the Buonalbergo landslide as common process in the Apennine context in terms of potential long-term morphologic evolution of the slope and the existence of many landslides that develop in similar geological conditions driving sediment production and inducing persistent topographic changes in mountainsides. [ABSTRACT FROM AUTHOR]