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A 1:10,000 scale landslide inventory map has been prepared for the area between the Furiano and Rosmarino creeks, in the Nebrodi Mountains (north-eastern Sicily, Italy), a territory highly prone to slope failures, due to the local geological and geomorphological settings and intense rainfall. The landslide inventory database included within the Hydrogeological Setting Plan of the Sicily Region has been used as a starting point for this work. The updated inventory map has been compiled through a combination of conventional approaches (i.e. aerial photo-interpretation and field surveys) and new remote sensing techniques (ground deformation measurements obtained by interferometric analysis of satellite Synthetic Aperture Radar images). The new landslide inventory consists of 566 events, classified according to their typology and state of activity. [ABSTRACT FROM PUBLISHER]

At Stromboli volcano ( Southern Italy), only few minor precursors (gas output) have been identified for 'major' Strombolian explosions. We use ground-based interferometric synthetic aperture radar ( GBIn SAR) technology to monitor the displacement rate of the summit area of Stromboli. We analysed the 2009-2011 period. The analysis of the displacement rate has been performed by dividing the summit zone monitored by the GBIn SAR into three regions, corresponding to the edge of the crater area (1 and 2), and to the slope of the NE crater (3). Pulses of rapid expansion of sector 3, of variable duration and amplitude, appear in coincidence with periods of intense activity that include lava flows and major explosions. We associate this expansion with the pressurization of the magma column that is recharged by deep-derived gas, promoting the onset of 'major explosion-dominated' activity. [ABSTRACT FROM AUTHOR]

[Display omitted] • Spatial relationships between landscape's geodiversity and biodiversity were investigated in a Mediterranean watershed of Central Tuscany, Italy. • The REEs distribution in bioavailable fractions of soils and olive drupes were detected. • A comparable scaling range was found in the La/Sm vs. La/Yb signature of topsoil and relative drupes. • Through the ML approaches the La N /Sm N ratio was mainly correlated to the hydrologic features and the La N /Yb N ratio was related to the lithological characteristics. • Using REEs signatures and ML approaches we directly assess the relation between abiotic and biotic factors. Landform diversity influences and interacts with both biodiversity and geodiversity and thus, they are key factors in the assessment of landscape resilience. However, research on the spatial relationships between landscape geodiversity and biodiversity is challenging because we are still lacking methods to link abiotic with biotic factors. The goal of this study is to explore and quantitatively assess the spatial relationship between geomorphometric factors and the relative distribution of rare earth elements (REEs) in soils and organism. Therefore, we selected a representative Mediterranean landscape characterized by ancient olive grove cultivations. The results show for different landforms and lithotypes a positive linear correlation in the lanthanum/samarium vs. lanthanum/ytterbium (La/Sm vs. La/Yb) signature between the bioavailable fraction of topsoil and olive drupe. Results of La/Yb vs. La/Sm reported as power function for olive drupes and topsoil follow comparable scaling ranges showing a power law of 0.83 and 0.71 respectively with an R2 0.96 vs. 0.71. A different scaling range behavior from topsoil to the related olive drupe was found for each parent rock material. Results of the Machine Learning (ML) modelling framework showed that the La N /Sm N in topsoil, were substantiality correlated to channel network base level, topographic wetness index, NDWI and valley depth. Under the physiographic environmental variables of the study area, the spatial distribution of La N /Yb N was mainly related to the lithological characteristics. Furthermore, NDVI was the most important variable to predict the fractionation ratio of La N /Yb N in olive drupe and the topographic channel network distance for La N /Sm N in olive drupe. Our findings provide new insights in the spatial distribution of REEs allowing an assessment of bio- and geodiversity of olive groves taking into account biophysical factors. Our research represents a starting point for future applications and modelling techniques to analyze at the catchment-scale the REEs biophysical fluxes and food traceability. [ABSTRACT FROM AUTHOR]

Abstract Technological progress in remote sensing has enabled digital representation of terrain through new techniques (e.g. digital photogrammetry) and instruments (e.g. 3D laser scanners). However, the use of old aerial images remains important in geosciences to reconstruct past landforms and detect long-term topographic changes. Administrations have recently expressed growing interest in sharing photogrammetric datasets on public repositories, providing opportunities to exploit these resources and detect natural and anthropogenic topographic changes. The SfM-MVS photogrammetric technique was applied to scanned historical black and white aerial photos of the Serra de Fontcalent (Alicante, Spain), as well as to recent high-quality digital aerial photos. Ground control points (GCPs) extracted from a LiDAR-derived three-dimensional point cloud were used to georeference the results with non-linear deformations. Two point clouds obtained with SfM-MVS were compared with the LiDAR-derived reference point cloud. Based on the result, the quality of the models was analysed through the comparison of the stages on stable areas, i.e., lands where no variations were detected, and active areas, with quarries, new infrastructures, fillings, excavations or new buildings. This study also indicates that errors are higher for old aerial photos (up to 5 m on average) than recent digital photos (up to 0.5 m). The application of SfM-MVS to open access data generated 3D models that enhance the geomorphological analysis, compared to stereophotogrammetry, and effectively detected activities in quarries and building of landfills. Highlights • Existing techniques enable the use of historical and recent aerial photos to reconstruct DEMS • An area of interest is reconstructed using historical printed and digital aerial photos, obtained from readily available resources, through Structure-from-Motion • An airbone LiDAR derived point cloud was used as a benchmark and for the extraction of ground control points • Three different stages of the landform were analysed and compared • The quality of the reconstruction and the capability of monitoring changes were analysed [ABSTRACT FROM AUTHOR]

This paper presents the preliminary results of the IPL project 196 “Development and applications of a multi-sensor drone for geohazards monitoring and mapping.” The objective of the project is to test the applicability of a multi-sensor drone for the mapping and monitoring of different types of geohazards. The Department of Earth Sciences of the University of Florence has developed a new type of drone airframe. Several survey campaigns were performed in the village of Ricasoli, in the Upper Arno river Valley (Tuscany, Italy) with the drone equipped with an optical camera to understand the possibility of this rising technology to map and characterize landslides. The aerial images were combined and analyzed using Structure-from-Motion (SfM) software. The collected data allowed an accurate reconstruction and mapping of the detected landslides. Comparative analysis of the obtained DTMs also permitted the detection of some slope portions being prone to failure and to evaluate the area and volume of the involved mass. [ABSTRACT FROM AUTHOR]

Urban expansion and city transformation are increasing reality across the world. Now more than ever it is essential to understand and map at the appropriate scale the processes happening along the verticality and horizontality of cities, to gather robust evidence underpinning strategies for sustainable management of the built environment. This paper explores how established techniques of Persistent Scatterer Interferometry (PSI) can be shaped into a novel dedicated procedure to detect vertical and horizontal urban dynamics including: use and re-use of urban space (new building construction, intentional demolition, renovation projects); exploitation of groundwater resources (induced land subsidence); interactions between new foundations, superficial deposits and bedrock geology (settlement of recent buildings); ground and slope instability affecting settled buildings; susceptibility of heritage assets to structural damages; baseline characterisation prior to planned major infrastructure construction (tunnelling and transportation networks). Florence, central Italy, is used as a demonstration site. This city includes UNESCO World Heritage List historic centre, 20 th -century residential, industrial and peri-urban quarters, and is currently in transition to metropolitan area of over 1 million of inhabitants. Velocity decomposition maps were generated based on millimetre-precise estimates of surface displacements retrieved from PSI processing of the full archives of satellite C-band radar images, including 79 ERS-1/2 descending (1992–2000), 70 ENVISAT ASAR ascending and descending (2003–2010) and 101 RADARSAT-1 ascending and descending (2003–2007). 12 macropatterns and 84 micropatterns in the final map of alert areas highlight a dualism which reflects the physical and urban geography of Florence. North-western and south-western quarters show hot spots of new building construction and regeneration projects for residential, business and tertiary service purposes, alongside issues due to groundwater exploitation and induced land subsidence up to 30–40 mm/yr. Local interactions with underlying geology and natural slope instability processes predominate in the southern and north-eastern sectors. At local scale, stable condition was found for the heritage assets and buildings located along the tracks of the planned subway railway and tramway, with motion rates averagely within ±1.5 mm/yr and localised deformation only up to −3.5 mm/yr. Structural assessment based on future PSI monitoring campaign will benefit of this baseline characterisation. [ABSTRACT FROM AUTHOR]

The Italian vessel Costa Concordia wrecked on January 13th 2012 offshore the Giglio Island (Tuscany, Italy), with the loss of 32 lives. Salvage operation of the vessel started immediately after the wreck. This operation was the largest and most expensive maritime salvage ever attempted on a wrecked ship and it ended in July 2014 when the Costa Concordia was removed from the Giglio Island, and dragged in the port of Genoa where it was dismantled. The refloating and removal phases of the Costa Concordia were monitored, in the period between 14th and 27th of July, exploiting SAR (Synthetic Aperture Radar) images acquired by the X-band COSMO-SkyMed satellite constellation in crisis mode. The main targets of the monitoring system were: (i) the detection of possible spill of pollutant material from the vessel and (ii) to exclude that oil slicks, illegally produced by other vessels, could be improperly linked to the naval convoy during its transit along the route between the Giglio Island and the port of Genoa. Results point out that the adopted monitoring system, through the use of the COSMO-SkyMed constellation, can be profitably employed to monitor emergency phases related to single ship or naval convoy over wide areas and with a suitable temporal coverage. Furthermore, the refloating and removal phases of the Costa Concordia were a success because no pollution was produced during the operations. [ABSTRACT FROM AUTHOR]

Landslide geodatabases, including inventories and thematic data, today are fundamental tools for national and/or local authorities in susceptibility, hazard and risk management. A well organized landslide geo-database contains different kinds of data such as past information (landslide inventory maps), ancillary data and updated remote sensing (space-borne and ground based) data, which can be integrated in order to produce landslide susceptibility maps, updated landslide inventory maps and hazard and risk assessment maps. Italy is strongly affected by landslide phenomena which cause victims and significant economic damage to buildings and infrastructure, loss of productive soils and pasture lands. In particular, the Messina Province (southern Italy) represents an area where landslides are recurrent and characterized by high magnitude, due to several predisposing factors (e.g. morphology, land use, lithologies) and different triggering mechanisms (meteorological conditions, seismicity, active tectonics and volcanic activity). For this area, a geodatabase was created by using different monitoring techniques, including remote sensing (e.g. SAR satellite ERS1/2, ENVISAT, RADARSAT-1, TerraSAR-X, COSMO-SkyMed) data, and in situ measurements (e.g. GBInSAR, damage assessment). In this paper a complete landslide geodatabase of the Messina Province, designed following the requirements of the local and national Civil Protection authorities, is presented. This geo-database was used to produce maps (e.g. susceptibility, ground deformation velocities, damage assessment, risk zonation) which today are constantly used by the Civil Protection authorities to manage the landslide hazard of the Messina Province. [ABSTRACT FROM AUTHOR]

Planning sustainable soil exploitation and land resource evaluation require up-to-date and accurate maps of soil properties. In that respect, geophysical techniques present particular interests given their non-invasiveness and their fast data acquisition capacity, which permit to characterize large areas with fine spatial and/or temporal resolutions. We investigated the relevancy of combining data from airborne hyperspectral (Hs), electromagnetic induction (EMI) and far-field ground-penetrating radar (GPR) for mapping soil properties, in particular soil clay content, at the field scale. Data from the three techniques were acquired at a test site in Mugello (Italy) characterized by relatively strong spatial variations of soil texture. Soil samples were collected for determining ground truth clay content. For the frequencies used in this study (200–650 MHz), the GPR surface reflection is mainly determined by soil dielectric permittivity, itself primarily influenced by soil moisture. In contrast, EMI is mostly sensitive to soil electrical conductivity, which integrates several soil properties including in particular soil moisture and clay content. Taking advantage of the complementary information provided by the two instruments, the GPR and EMI data were combined and correlated to local ground-truth clay content data to provide high-resolution clay content maps over the entire field area. Besides, a relationship was also observed between Hs data and clay content measurements, which permitted to produce a Hs-derived clay content map. EMI–GPR and Hs maps showed close spatial patterns and a relatively high correlation was observed between both clay content estimates, as well as between clay content estimates and ground-truth clay content measurements. Moreover, data fusion allowed constraining the EMI–GPR and Hs information and reduced the uncertainty of mapped clay content estimates. These results demonstrated great promise for integrated, digital soil mapping applications. [ABSTRACT FROM AUTHOR]

The management of the coastal environment is a complex issue, which needs for appropriate methodologies. Erosional processes and longshore currents present in the submerged beach represent a serious danger for both people and human infrastructures. A proper integration between traditional and innovative techniques can help in the characterization and management of the beach environment. Several different multispectral and hyperspectral techniques were used to retrieve information about the hydro and morphodynamic settings of the Pisa province coast (Tuscany, Italy). Results were validated using about 130 samples collected along the study area, between the mouths of the Serchio river and the Scolmatore canal. The composition of sand samples was evaluated by means of petrographic microscopy and grain size analyses. The same samples were analyzed using an Analytical Spectral Device (ASD) Fieldspec. The obtained sediment spectral library was used to evaluate the differences in mineralogical composition, which can be related to different source areas. Results coming from spectroscopy were compared to those obtained from the petrographic and grain size analysis. Furthermore a multispectral aerial image was used to evaluate sediment distribution along the submerged beach, to map the geomorphic features and to detect the presence of longshore and rip currents. This works suggests that optical remote sensing technique can be profitably used in order to reduce the need for expensive and time consuming conventional analysis. [ABSTRACT FROM AUTHOR]

Abstract: The composition of non-methane volatile organic compounds (hereafter VOCs) in i) the cover soil, at depths of 30, 50 and 70 cm, and ii) gas recovery wells from Case Passerini landfill site, (Florence, Italy) was determined by GC-MS. The study, based on the analysis of interstitial gases sampled along vertical profiles within the cover soil, was aimed to investigate the VOC behaviour as biogas transits from a reducing to a relatively more oxidizing environment. A total of 48 and 63 different VOCs were identified in the soil and well gases, respectively. Aromatics represent the dominant group (71.5% of total VOC) in soil gases, followed by alkanes (6.8%), ketones (5.7%), organic acids (5.2%), aldehydes (3.0%), esters (2.6%), halogenated compounds (2.1%) and terpenes (1.3%). Cyclics, heterocyclics, S-bearing compounds and phenols are ≤1%. In the wells the VOC composition is characterized by higher concentrations of cyclic (7.6%) and S-bearing compounds (2%) and lower concentrations of O-bearing compounds. The vertical distribution of VOCs in the cover soil shows significant variations: alkanes, aromatics and cyclics decrease at decreasing depth, whereas an inverse trend is displayed by the O-bearing species. Total VOC and CH4 concentrations at a depth of 30 cm in the soil are comparable, inferring that microbial activity is likely affecting VOCs at a very minor extent with respect to CH4. According to these considerations, to assess the biogas emission impact, usually carried out on the sole basis of CO2 and CH4 emission rates, the physical–chemical behaviour of VOCs in the cover soil, regulating the discharge of these highly contaminant compounds in ambient air, has to be taken into account. The soil vertical distribution of these species can be used to better evaluate the efficiency of oxidative capability of intermediate and final covers. [Copyright &y& Elsevier]

• This study presents the analysis of the ground deformation measured using 26 years of satellite SAR data. • We investigated the driven factors of subsidence in a densely urbanized area. • Data retrieved by several boreholes and geotechnical investigations were used to model the building load and to validate remote sensing data. • The comparison between the consolidation curve and the time series suggests that SAR data can be used to evaluate the consolidation process. This paper shows the results of the comparison between Multi-temporal Synthetic Aperture Radar (MTInSAR) products derived from different sensors (C-band ERS 1/2, Envisat, Sentinel-1 and X-band COSMO-SkyMed) and geotechnical data to investigate the driving factors of subsidence which affect a freight terminal located along the a coastal plain of Tuscany (central Italy). MTInSAR data have been acquired in a very long period, between 1992 and 2018 and were analyzed in terms of subsidence rates and deformation time series at building scale. The obtained results show that the oldest buildings are still affected by a deformation rate close to −5 mm/yr, whereas recent buildings register rates around −40 mm/yr. Time series of deformation suggest that the deformation rates decrease over time following time-dependent trend that approximates the typical consolidation curve for compressible soils. The geotechnical and stratigraphical analysis of the subsurface data (boreholes, cone penetration tests and dilatometer tests) highlights the presence of a 15 m thick layer formed of clay characterized by poor geotechnical characteristics. The comparison among InSAR data, subsurface geological framework and geotechnical reconstruction suggests a possible evaluation of the timing of the primary and secondary consolidation processes. [ABSTRACT FROM AUTHOR]

Extreme rainfall events represent one of the main triggers of landslides. As climate change continues to reshape global weather patterns, the frequency and intensity of such events are increasing, amplifying landslide occurrences and associated threats to communities. In this contribution, we analyze relationships between landslide occurrence and extreme rainfall events by using a "glass-box" machine learning model, namely Explainable Boosting Machine. What sets these models as a "glass-box" technique is their exact intelligibility, offering transparent explanations for their predictions. We leverage these capabilities to model the landslide occurrence induced by an extreme rainfall event in the form of spatial probability (i.e., susceptibility). In doing so, we use the heavy rainfall event in the Misa River Basin (Central Italy) on September 15, 2022. Notably, we introduce a rainfall anomaly among our set of predictors to express the intensity of the event compared to past rainfall patterns. Spatial variable selection and model evaluation through random and spatial routines are incorporated into our protocol. Our findings highlight the critical role of the rainfall anomaly as the most important variable in modeling landslide susceptibility. Furthermore, we leverage the dynamic nature of such a variable to estimate landslide occurrence under different rainfall scenarios., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)