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River flows and associated suspended sediment (SS) transport are intermittent processes possessing fluctuations over a large range of time scales and space, making it challenging to develop predictive models that are applicable across timescales and rivers. A concept of “effective timescales of connectivity” has been used to define the timeframe over which sediment (dis)connectivity occurs, whereby parts of the catchment are “switched on and off” as a response of events with varying frequency-magnitude relationships and antecedent soil moisture. These concepts provide excellent frameworks to understand temporal variability and identify relevant timescales for sediment transport, but do not help in the knowledge of mechanisms for temporal variability in SS transport. The complexity and scale dependency of processes driving SS transport stress the need to detect how sediment generation, storage, and transport are linked across different timescales. Furthermore, the mechanisms that produce travel time distributions over many orders of magnitude are not known precisely. To this end, in this study we have considered SS transport as a fractal system. By approaching SS transport dynamics as a fractal system, it is assumed that patterns of variation in SS transport exist over different timescales, while linkages across those temporal scales are expressed as fractal power-laws.This work aims to defines the link between (i) sediment transport and deposition and (ii) fractal geometry and fractal storage time distributions in streams.Here, we present case study where fractals are used to describe and predict patterns over different spatial or temporal scales of dynamics in SSCs. We have considered in these studies the statistics and the dynamics of streamflow, SSCs and associated grain size distribution at event based by considering respectively their probability distribution function and Fourier power spectra.We set up a natural experiment site of a first-order mixed bedrock and alluvial stream channel by using LISST instrument coupling with LIDAR remote sensing measurement. Here we obtain high-resolution observations of streambed topography and continuously long-term measurements of suspended sediment in natural experimental site located in an agricultural watershed of a Chianti area (Florence, Italy).The LISST is a submersible laser diffraction particle size analyzer for measuring suspended particle size (range from 2.50 µm to 500 µm), its volume concentration at different time step and depth. We set up at time interval equal to 5 minutes of sample rate.Preliminary results obtained indicate large fluctuations with heavy tails, and long-range properties, characterized by extreme events much more frequent than what is found for a Gaussian process.Hence, insights into the degree of fractal power of a SS transport system may provide a useful basis to evaluate and develop the most appropriate predictive models and management strategies.

Geomorphodiversity is a new emerging topic in earth sciences. Landform diversity influences and interacts with both biodiversity and geodiversity. Hence, there is an increased awareness of the need to understand patterns of geomorphodiversity in different landscapes facing the actual global change. An increasing body of evidence indicates that global climate change is taking place and that it will have important effects on biological processes over the next decades, such as yields and the quality of products, the distribution and outbreak potential of pests in a vast range of crops species, and across all land uses and landscapes.A new approach of landform geodiversity and biodiversity evaluation is proposed, based on the geomorphometric-biogeochemical signature of several geodynamic settings of the Tuscany region. Starting from a geomorphometry approach, the geostatistical and geostochastic modelling enables to quantify, describe, and compare different landforms, providing an objective and useful tool to delineate the signature and the bio-geocomplexity of landforms. The geochemical approach is based on the detection of REEs pattern distribution and fractionation signatures as tools for tracing natural geochemical processes and soil-plant interactions to compare landforms of different origins. Using both REEs and the 87Sr/86Sr ratio it was possible to compare landscapes of different origins and ages. In addition, bioinformatics were used to evaluate species–environment relationships, and to determine factors explaining changes in bacterial composition developed on eleven contrasting lithologies.Whereas most authors have focused on mountainous, coastal and/or continental areas, for the first time a study of this type is applied to different landforms that support a centuries-old Mediterranean olive groves.The general aims of this work is to define a conceptual framework and test a new methodology to improve the knowledge related to the interaction between chemico-physical and biological soil processes able to shape landforms at various spatio-temporal scales. In particular, we will discuss the role of bio-geomorphic interactions influencing the nutrient/mineral content in olive fruit for geographic authentication, healthy food production and a healthy, biodiverse environment.

Radar-based rainfall estimation represents an effective tool for hydrological modelling. Nevertheless, this data type is subject to systemic and natural perturbations that need to be considered before to use it. Because of that and to improve data quality, corrections based on raingauge observations are frequently adopted. Here, we compared the efficacy of different radar-raingauge merging procedures over a regional raingauge-radar network focusing on a selected number of rainfalls events.We adopted the methods: 1) Kriging with External Drift (KED) interpolation (Wackernagel 1998), 2) Probability-Matching-Method (PMM, Rosenfeld et al., 1994), and 3) a kriging mixed method exploiting the Conditional Merging (CM) process (Sinclair-Pegram, 2005) based on elaborations available at DPCN (Italian National Civil Protection Department). These methods have been applied on the Tuscany Regional Territory using raingauge recorded rainfalls at 15’ time-step and CAPPI (Constant altitude plan position indicator) reflectivity data at 2000/3000/5000 m at 5’ and 10’.Relationships describing precipitation VS radar reflectivity were integrated and elaborated as part of the development of the merging procedures, while the comparison involved the analysis of variance and diversity coefficients. Kriging-based elaborations showed different spatial patterns depending on the applied procedure, with patterns closer to radar variability when using DPCN, and more reflecting the gauge data structure when adopting KED. The probabilistic method (PMM), instead, had the advantage of integrating the gauge data while preserving the spatial radar patterns, confirming interesting perspectives.

The monitoring of stone alteration represents a key factor in the knowledge and prediction of the status of conservation of building stones in the urban framework. A continuous monitoring requires a non-destructive analytical approach and, possibly, a simple, low-cost and effective tool to study the decay processes. Previous studies demonstrated the capability of the SWIR hyperspectral technique to gain information on the degree of sulfation of carbonate stone surfaces. In this study we aim at setting up a protocol to investigate on-site the sulfation degree of the white marble cladding surfaces of the worldwide-famous Santa Maria del Fiore Cathedral in Florence (Italy). The proposed protocol couples information by SWIR hyperspectral and colorimetric techniques. We have proved that, in selected areas investigated at a distance of nine years, the colour and the mineralogical changes (i.e., sulfation) are significantly greater than the relative uncertainties of the two methods. Moreover, the proposed protocol results rapid, repeatable and fully not invasive.

The UNESCO Chair on Prevention and Sustainable Management of Geo-Hydrological Hazards, University of Florence has been a member of the International Consortium on Landslides (ICL) since 2002. It was designated as one of World Centres of Excellence (WCoE) for Landslide Risk Reduction five times for 2008–2011, 2011–2014, 2014–2017, 2017–2020 and 2020–2023, with a project entitled “Advanced Technologies for Landslides”. In this paper, we describe the activities carried out by the UNESCO Chair as a member of ICL and as WCoE, and its contribution to the risk reduction policies promoted by the 2020 Kyoto Commitment.

Soil erosion by water is one of the most widespread forms of soil degradation responsible for relevant agricultural productivity losses. Under climate change, soil erosion is expected to increase mostly for a rising of the frequency of extreme and localised events. In intense hydrological phenomena such as flooding, and soil erosion, the spatiotemporal extent significantly impacts these phenomena, especially in extreme events. Therefore, an approach directed to better refine to understand such dynamics is recommended.Here, we present the MSCA – SED RUNS project, focusing on the extreme rainfall effects on soil erosion using ground-weather-radar observations and hydrological modelling at regional scale (namely in Tuscany, central Italy).The approach, based on statistical analysis and modelling methods, aims to: 1) Quantifying, over the last decade, the spatiotemporal distribution of extreme rainfalls / runoff and soil erosion, 2) Building a platform to model runoff and soil erosion for extreme events, 3) Simulating in real-time runoff and soil erosion as a precursor of for a regional-warning-system for extreme weather events.Rainfall data will be provided by the national and regional institutions such as LaMMA Consortium (Tuscany Meteorological Agency) and the “Italian Civil Protection”, whose radar dataset of the national network (DPCN) covers the 2010–2020 period, with a spatial resolution of 1 km in a 10-mins time-step.The project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie, Grant Agreement n. 101033236.

Soil erosion by water is one of the most widespread forms of soil degradation in Europe, where the relevant annual cost for agricultural productivity loss is estimated to be around 295 million euros. Under climate changes, soil erosion due to rainfall is dramatically increasing, for the most part because of an increasing of the frequency of extreme, localised events.Here, we present the MSCA-Horizon2020 project, focused on understanding and quantifying extreme rainfall effects on soil erosion, by means of ground-based weather-radar observations and hydrological modelling at regional scale (namely in Tuscany, central Italy).In critical hydrological phenomena, such as intense surface runoff, flooding and soil erosion, the spatiotemporal extent is crucial in the development of the processes. This feature significantly affects the impact and the evolution of critical phenomena, especially during extreme events. Therefore, an approach directed to refine as much as possible the knowledge of these dynamics is recommended both at the monitoring and the modelling level.Using an approach based on statistical analyses of rainfall data from ground-based radar and modelling, this project aims to: 1) Quantify on historical data the spatiotemporal distribution of extreme rainfalls / runoff and soil erosion over the last years, 2) Build a platform to model runoff and soil erosion during extreme events in real-time, 3) Simulate in real-time runoff and soil erosion behaviours related to extreme rainfalls, integrating the current regional-warning-system for the extreme weather events.

The identification of the type and extent of the area damaged by natural hazards such as wildfires using Earth Observation data can contribute to a better understanding of the processes affecting the Man-Nature system and, thereby, Man’s capability for sustainable land management. Fire effects are not limited to vegetation and litter cover and composition but include topsoil properties, both of which contribute to the enhanced hydrological and geomorphological activity typically observed in recently burnt areas. The present study focusses on fire-induced changes in topsoil properties, vegetation and ground cover and how this latter parameter can be acquired via satellite multi- and hyperspectral analysis for the determination of soil erosion model ground cover inputs. This objective has been achieved via the comparison of field ground cover data with multi and hyperspectral satellite derived data. Hence, we applied both types of ground cover data – i.e. field and satellite-based to the same erosion model to assess how the different model input values affected the differences between predicted and observed soil erosion rates. To this end, the present study applied the modified Morgan-Morgan-Finney (MMF) erosion model to a pine plantation that had recently been burnt by the dramatic, June-2017 Pedrógão wildfire in Central Portugal. The MMF model was calibrated against the observed plot-scale erosion rates and the seasonal patterns therein, operating on the effective hydrological depth, fire severity impact and ground cover. Furthermore, we tested satellite and field based burn severity assessments and compared both model predictions with the field erosion measurements at plot scale. Additionally, the MMF input parameters linked to vegetation cover were estimated from field observations as well as various remotely-sensed indexes derived from Sentinel-2 MSI (MultiSensing Instrument) and PRISMA (HyperSpectral Precursor of the Applicative Mission) hyperspectral data. The results showed that remote sensing data can provide valuable estimates of post-fire vegetation recovery for parameterization of the MMF model for the first post-fire year. An important condition, however, is that the spatio-temporal resolution of the satellite-based data match the spatial patterns in fire severity on the one hand, and, on the other, the changes in soil erosion processes with time-since-fire. Therefore, factors such as pre-fire fuel load, vegetation composition and topsoil properties will require careful consideration when extrapolating the current results to other burnt areas.

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. This work was partially funded by the University of Alicante, Spain, under Projects vigrob-157 GRE14-04, and GRE15-19; the University of Florence Earth Science Department, Italy; the Spanish Ministry of Economy and Competitiveness (MINECO), Spain, and EU FEDER, under Projects TIN2014-55413-C2-2-P and TEC2017-85244-C2-1-P and the Spanish Ministry of Education, Culture and Sport, Spain, under project PSX17/00439.

Wildfires have affected global forests and the Mediterranean area with increasing recurrency and intensity in the last years, with climate change resulting in reduced precipitations and higher temperatures. To assess the impact of wildfires on the environment, burned area mapping has become progressively more relevant. Initially carried out via field sketches, the advent of satellite remote sensing opened new possibilities, reducing the cost uncertainty and safety of the previous techniques. In the present study an experimental methodology was adopted to test the potential of advanced remote sensing techniques such as multispectral Sentinel-2, PRISMA hyperspectral satellite, and UAV (unmanned aerial vehicle) remotely-sensed data for the multitemporal mapping of burned areas by soil–vegetation recovery analysis in two test sites in Portugal and Italy. In case study one, innovative multiplatform data classification was performed with the correlation between Sentinel-2 RBR (relativized burn ratio) fire severity classes and the scene hyperspectral signature, performed with a pixel-by-pixel comparison leading to a converging classification. In the adopted methodology, RBR burned area analysis and vegetation recovery was tested for accordance with biophysical vegetation parameters (LAI, fCover, and fAPAR). In case study two, a UAV-sensed NDVI index was adopted for high-resolution mapping data collection. At a large scale, the Sentinel-2 RBR index proved to be efficient for burned area analysis, from both fire severity and vegetation recovery phenomena perspectives. Despite the elapsed time between the event and the acquisition, PRISMA hyperspectral converging classification based on Sentinel-2 was able to detect and discriminate different spectral signatures corresponding to different fire severity classes. At a slope scale, the UAV platform proved to be an effective tool for mapping and characterizing the burned area, giving clear advantage with respect to filed GPS mapping. Results highlighted that UAV platforms, if equipped with a hyperspectral sensor and used in a synergistic approach with PRISMA, would create a useful tool for satellite acquired data scene classification, allowing for the acquisition of a ground truth.

In urban environments, degradation processes affecting both natural and artificial carbonate materials commonly result in the formation of sulphate-based deposits (i.e., black crusts). Hyperspectral techniques may provide ready-to-use information on the degree of sulphation of carbonate stone, hence helping to monitor the conservation state of carbonate stone monuments. In this study, the Short-Wave InfraRed (SWIR) hyperspectral technique was tested on the world-famous marble-made Loggia di Baccio d’Agnolo in Santa Maria del Fiore Cathedral of Florence (Italy), affected by extensive “black crust” formation. A SWIR method based on a portable spectroradiometer (ASD Fieldspec® 3) was applied to verify the efficacy of different cleaning methods (i.e., laser, chemical and microbial). The interpretation of the SWIR spectra was based on a full-profile approach, in which the calcite and gypsum contributions were evaluated by weighing the best fit simulated contributions of reference compounds. The technique was able to provide in real time semi-quantitative determinations of the amount of gypsum developed on the stone surface, demonstrating to be a fast and handy routine tool during restoration of artworks.

In the last years, the use of Unmanned Aerial Vehicles (UAVs) has developed rapidly across several field of earth sciences application, including landslides characterisation and monitoring, therefore providing a strong support for hazard and risk management activities especially with the introduction and advances in the miniaturization of traditional and new generation sensors. The flexibility, low cost, easy operability, and rapidness of intervention in emergency situation gives to these instruments, a strong potential in opening up a vast new area of opportunities in remote sensing for observation, measuring, mapping, monitoring, and management in various landslide environment. Unless initially only air photography was the main application for UAVs, recently new sensors, both passive and active, are being increasingly used. This paper, through some case studies on landslide investigations, aims at giving an overview on several sensors and techniques using UAVs platform addressed to landslide detection, characterization and monitoring.

The soil surface albedo decreases with an increasing biochar application rate as a power decay function, but the net impact of biochar application on soil temperature dynamics remains to be clarified. The objective of this study was to assess the potential of infrared thermography (IRT) sensing by monitoring soil surface temperature (SST) with a high spatiotemporal and thermal resolution in a scalable agricultural application. We monitored soil surface temperature (SST) variations over a 48 h period for three treatments in a vineyard: bare soil (plot S), 100% biochar cover (plot B), and biochar-amended topsoil (plot SB). The SST of all plots was monitored at 30 min intervals with a tripod-mounted IR thermal camera. The soil temperature at 10 cm depth in the S and SB plots was monitored continuously with a 5 min resolution probe. Plot B had greater daily SST variations, reached a higher daily temperature peak relative to the other plots, and showed a faster rate of T increase during the day. However, on both days, the SST of plot B dipped below that of the control treatment (plot S) and biochar-amended soil (plot SB) from about 18:00 onward and throughout the night. The diurnal patterns/variations in the IRT-measured SSTs were closely related to those in the soil temperature at a 10 cm depth, confirming that biochar-amended soils showed lower thermal inertia than the unamended soil. The experiment provided interesting insights into SST variations at a local scale. The case study may be further developed using fully automated SST monitoring protocols at a larger scale for a range of environmental and agricultural applications.

Landslides are one of the most relevant geohazards worldwide, causing direct and indirect costs and fatalities. Italy is one of the countries most affected by mass movements, and the Molise region, southern Italy, is known to be susceptible to erosional processes and landslides. In January 2003, a landslide in the municipality of Agnone, in the Colle Lapponi-Piano Ovetta (CL-PO) territory, occurred causing substantial damage to both structures and civil infrastructure. To investigate the evolution of the landslide-affected catchment over approximately one century, different data were taken into account: (i) literature information at the beginning of the twentieth century; (ii) historical sets of aerial optical photographs to analyse the geomorphological evolution from 1945 to 2003; (iii) SAR (Synthetic Aperture Radar) data from the ERS1/2, ENVISAT and COSMO-SkyMed satellites to monitor the displacement from 1992 to 2015; (iv) traditional measurements carried out through geological and geomorphological surveys, inclinometers and GPS campaigns to characterize the geological setting of the area; and (v) recent optical photographs of the catchment area to determine the enlargement of the landslide. Using the structure from motion technique, a 3D reconstruction of each set of historical aerial photographs was made to investigate the geomorphological evolution and to trace the boundary of the mass movements. As a result, the combination of multitemporal and multitechnique analysis of the evolution of the CL-PO landslide enabled an assessment of the landslide expansion, which resulted in a maximum length of up to approximately 1500 m. A complete investigation of the past and present deformational sequences of the area was performed to potentially plan further mitigation and prevention strategies to avoid possible reactivations. This work was partially funded by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO); the State Agency of Research (AEI); and the European Funds for Regional Development (FEDER) under projects TEC2017-85244-C2-1-P and TIN2014-55413-C2-2-P and the Spanish Ministry of Education, Culture and Sport under project PRX17/00439.

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.

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.

Land subsidence is defined as the lowering of ground surface that can be caused by both natural and anthropogenic factors such as the natural compaction of sediments and the groundwater over-pumping.This work aims at investigating recent subsidence in the Sibari plain located in Calabria Region (Italy) by means of SAR (Synthetic Aperture Radar) Interferometry technique. In particular, PSI (Persistent Scatterer Interferometry) data acquired by different satellite sensors and spanning the period 1992-2011 were exploited for detecting the phenomenon in the area. In this study, implementations of PSI data and the PS-Time software were used respectively to map the spatial distribution of terrain deformation rates and to analyze the temporal evolution patterns of the displacements. The results demonstrated that recent subsiding movements are mostly due to human activities, as they are only recorded in site-specific urban areas. Moreover, the detailed PS Time Series analysis highlighted that, in these areas, subsidence has positively decreased or stabilized from the second semester of the year 2010.

Land subsidence is a common natural hazard striking extensive areas worldwide, with severe impacts on economy and environment. Subsidence has been recognized as one of geohazards needing research efforts and knowledge transfer at international level, especially when urban fabrics and infrastructures are directly involved in the land settling. Policies and solutions for land subsidence management can be different. Despite this variability, where mitigation methods need to be adopted, mapping, monitoring and simulation of subsidence have to precede their design and implementation. In this framework, Earth Observation (EO) and remote sensing have a major role to play. Satellite Synthetic Aperture Radar Interferometry, thanks to its wide spatial coverage and its millimeter accuracy, provides a valuable contribution in the management of hazard posed by subsidence-related deformation. The ESA-GMES Terrafirma project (2003–2014) has worked for the promotion of the persistent scatterer interferometry, a family of techniques ideally suited for the assessment of magnitude of surface deformations associated with subsidence phenomena. Within the Terrafirma Project a series of products, based on the integration of EO technologies and in situ data, has been established and delivered to a wide community of end user. Three case studies, outcomes of the Terrafirma project, are presented: the wide area of Rome (Italy), the Anthemountas basin and the Kalochori village (Greece). These case studies have been selected with the purpose of showing the essential contribution of interferometric data during the main activities that must be covered when dealing with geohazard investigations (i.e., mapping, monitoring and modeling). These three case studies are meant to be representative of the suite of services delivered by the Terrafirma project to specific end users with the legal mandated to manage the geohazard.

The Department of Earth Sciences of Florence (DST) has developed a new type of drone chassis., Several survey campaigns were performed in Ricasoli village, 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 to characterize landslides. The aerial RGB images were analysed and combined using SfM (Structure from Motion) software. The comparative analysis of the obtained DTMs allowed an accurate reconstruction and mapping of the detected landslides. The collected data also allowed to precisely detect some slope portions prone to failure and to evaluate the area and volume of the involved masses.

We set up an early warning system for rainfall-induced landslides in Tuscany (23 000 km2). The system is based on a set of state-of-the-art intensity-duration rainfall thresholds (Segoni et al., 2014b), makes use of LAMI rainfall forecasts and real-time rainfall data provided by an automated network of more than 300 rain-gauges. The system was implemented in a WebGIS to ease the operational use in civil protection procedures: it is simple and intuitive to consult and it provides different outputs. Switching among different views, the system is able to focus both on monitoring of real time data and on forecasting at different lead times up to 48 h. Moreover, the system can switch between a very straightforward view where a synoptic scenario of the hazard can be shown all over the region and a more in-depth view were the rainfall path of rain-gauges can be displayed and constantly compared with rainfall thresholds. To better account for the high spatial variability of the physical features, which affects the relationship between rainfall and landslides, the region is subdivided into 25 alert zones, each provided with a specific threshold. The warning system reflects this subdivision: using a network of 332 rain gauges, it allows monitoring each alert zone separately and warnings can be issued independently from an alert zone to another. An important feature of the warning system is the use of thresholds that may vary in time adapting at the conditions of the rainfall path recorded by the rain-gauges. Depending on when the starting time of the rainfall event is set, the comparison with the threshold may produce different outcomes. Therefore, a recursive algorithm was developed to check and compare with the thresholds all possible starting times, highlighting the worst scenario and showing in the WebGIS interface at what time and how much the rainfall path has exceeded or will exceed the most critical threshold. Besides forecasting and monitoring the hazard scenario over the whole region with hazard levels differentiated for 25 distinct alert zones, the system can be used to gather, analyze, visualize, explore, interpret and store rainfall data, thus representing a potential support to both decision makers and scientists.

The potential of repeat-pass space borne SAR (Synthetic Aperture Radar) interferometry has been exploited to investigate spatial patterns of land subsidence in the Anthemountas basin, in the northern part of Greece. The PSI (Persistent Scatterer Interferometry) approach, based on the processing of long series of SAR acquisitions, has been applied to forty-two images acquired in 1995–2001 by ERS1/2 satellites. Interferometric results have been analyzed at a basin scale as support for land motion mapping and at local scale for the characterization of ground motion events affecting the village of Perea in the Thermaikos municipality and the "Macedonia" international airport. PSI results revealed a moderate subsidence phenomenon along the wider coastal zone of Anthemountas basin corresponding to intense groundwater extraction. Highest values, exceeding 20 mm yr−1, were measured in the airport area where the thickest sequence of compressible Quaternary sediments occurs. Intense subsidence has been detected also in the Perea village (maximum deformation up to 10–15 mm yr−1), where a series of fractures, causing damages to both buildings and infrastructure, occurred in 2005–2006. Furthermore, a linear pattern of deformation, elongated parallel to the major normal Thermi fault, has been observed, indicating movements with a probable tectonic component.

In the context of environmental monitoring, it is very important to improve systems for the identification, assessment and management of environmental risks through the use and integration of analytical techniques combined with hyperspectral airborne sensing technologies. Remote-sensing applications are varied, but nevertheless an accurate mapping of the soil required the use of complex scientific instruments installed on airplanes or helicopters. The high integration of electronics, combined with the computing power of modern processors, allows the development of integrated and compact hyperspectral systems installed on drones.1 The drone era poses new challenges to optical devices design: they shall be light, compact and robust, easy to assemble and to control. This work explains the optical system design of HYDRACAM (HYperspectral DRone Advanced CAMera), an instrument devoted to hyperspectral imaging by using an electro-optical liquid crystal tunable filter combined with a commercial camera. The commercial ray tracing software Zemax/OpticStudio2 was used to perform the optical design. The main challenge was to manufacture a low cost optical device, containing the mass and the total length to suit a drone payload. A huge effort was made in order to combine strict constraints (such as the filter narrow entrance aperture and its acceptance angle) with ambitious optical performance requirements (high spatial resolution, large field of view). First, a description of the work done to find a trade-off between cost and opto-mechanical constraints is provided: the choice of the commercial objective, the choice of the custom lenses materials and shapes and some optical design original solutions are addressed. Then, the details of the optical performance analysis are discussed.

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.

This work shows that PSI measurements provide support in the quantitative evaluation of known subsidence process and that the analysis of time series allows effective detection of the temporal evolution trends of the phenomenon, such as changes or deceleration in displacement rates, not otherwise visible by merely considering the average velocity.

We propose a novel set of indexes to classify the information content of Persistent Scatterers (PS) and rate the health of engineering structures at urban to local scale. PS are automatically sampled and grouped via ‘control areas’ coinciding with the building and its surrounding environment. Density over the ‘control areas’ and velocity of PS are converted respectively into: Completeness of Information Index (Ici) that reflects the PS coverage grade; and Conservation Criticality Indexes (Icc) which rate the health condition of the monument separately for the object and surrounding control areas. The deformation pattern over the structure is classified as isolated (i) or diffused (d) based on the Velocity Distribution Index (Ivd). Both Ici and Icc are rated from A to E classes using a colour-coded system that intentionally emulates an energy-efficiency scale, to encourage the exploitation of PS by stakeholders and end-users in the practise of engineering surveying. Workability and reliability of the classification indexes are demonstrated over the urban heritage of Florence, Italy, using well established ERS-1/2 (1992–2000) descending, ENVISAT (2003–2010) ascending and descending PS datasets. The indexes are designed in perspective of handling outputs from InSAR processing of higher-resolution time series.

The use of InSAR (Interferometric Synthetic Aperture Radar) products has greatly increased in the last years because of the technological advances in terms of both acquisition sensors and processing algorithms. The development of multi-interferogram techniques and the availability of free SAR analysis tools has significantly increased the number of worldwide applications of satellite measurements for mapping and monitoring geohazards. InSAR techniques excel in determining ground deformation in urban areas, where the coherence of the radar images is high, and the obtainable results are particularly reliable. Thus, measuring urban subsidence has always been one of the main targets of the InSAR analysis. In this paper, we present a brief review on the applications, in the last decades, of both single and multi-interferogram techniques to monitor ground lowering in urban areas along the Italian Peninsula. Because of its geological context, Italy is prone to slow natural subsidence phenomena sometimes aggravated and accelerated, especially along the coasts and in urbanized areas, by anthropogenic factors (i.e., groundwater overexploitation, consolidation in recent urban expansion, geothermal activities). The review will show how the interferometric data allowed the scientific community to increase the knowledge of the phenomena, map their spatial distribution, and reconstruct their temporal evolution. The final goal of the review is to demonstrate the added value of InSAR data in supporting groundwater management and urban development in Italy.

In this paper, the authors describe the architecture of a multidisciplinary data acquisition and visualization platform devoted to the management of coastal environments. The platform integrates heterogeneous data acquisition sub-systems that can be roughly divided into two main categories: remote sensing systems and in situ sensing systems. Remote sensing solutions that are going to be implemented include aerial and underwater data acquisition while in situ sensing solutions include the use of Radio Frequency IDentification (RFID) tracers, Wireless Sensor Networks and imaging techniques. All the data collected by these subsystems are stored, integrated and fused on a single platform that is also in charge of data visualization and analysis. This last task is carried out according to the paradigm of Augmented Virtuality that foresees the augmentation of a virtually reconstructed environment with data collected in the real world. The described solution proposes a novel holistic approach where different disciplines concur, with different data acquisition techniques, to a large scale definition of coastal dynamics, in order to better describe and face the coastal erosion phenomenon. The overall framework has been conceived by the so-called Team COSTE, a joint research team between the Universities of Pisa, Siena and Florence.

[object ObjecStone-built Cultural Heritage is subjected to decay in urban environment over the centuries, due to surface interaction and reaction with natural atmospheric agents and, particularly in the last centuries, air pollutants. The Short wave Infrared (SWIR) characterisation of stone surface through portable instruments is attracting increasing interest in the field of Cultural Heritage. In this study, SWIR hyperspectral investigation of carbonate rocks, undergoing acid attack under laboratory conditions was performed with the aim of providing useful quantitative information on the degree of sulfation of the surfaces of carbonate stone. Six marble and six travertine specimens were attacked by aqueous solutions of H2SO4 at variable acid concentrations leading to the formation of gypsum. The reacted surfaces of stones were then investigated by a portable SWIR spectroradiometer. The resulting spectra were thus modelled through a full profile approach, in order to obtain a reliable and efficient fitting procedure. Thus, the SWIR characterisation of sulfated carbonate surfaces seems to be a promising, ready-to-use technique for monitoring the conservation state of carbonate stone monuments (e.g. facades, statues). This method could provide valuable support both for restoration practices and for continuous monitoring of stone alteration over time, when assessing the best strategy of intervention and conservation against sulfation processes of historical buildings.

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.

In the last decade, the combination of rapid development of low cost and small Unmanned Aerial Vehicles (UAVs), improved battery technology and conventional sensors (Optical and LiDAR) in terms of cost and dimensions, led to new opportunities in environmental remote-sensing and 3D surface modelling. A long term monitoring campaign was performed in Ricasoli village, in the Upper Arno river Valley (Tuscany, Italy), to understand the possibility of this rising technology to characterize and to monitor landslides. The RGB and multispectral imageries were analyzed and combined using SfM (Structure from Motion) software, in order to obtain high resolution orthomosaics, point clouds and 3D digital terrain models (DTM). The comparative analysis of the obtained DTMs allowed a very accurate reconstruction and mapping of the detected landslides. The collected data also allowed to precisely detect some slope portions prone to failure and to evaluate the area and volume of the involved masses as well as displacement rates.