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Spatial data collected worldwide from a huge number of locations is frequently used in environmental and climate studies. Spatial modelling for this type of data presents both methodological and computational challenges. In this work we illustrate a computationally efficient non-parametric framework in order to model and estimate the spatial field while accounting for geodesic distances between locations. The spatial field is modelled via penalized splines (P-splines) using intrinsic Gaussian Markov Random Field (GMRF) priors for the spline coefficients. The key idea is to use the sphere as a surrogate for the Globe, then build the basis of B-spline functions on a geodesic grid system. The basis matrix is sparse as is the precision matrix of the GMRF prior, thus computational efficiency is gained by construction. We illustrate the approach with a real climate study, where the goal is to identify the Intertropical Convergence Zone using high-resolution remote sensing data.

We explored the variability of the Egyptian shelf zone circulation connected to atmospheric forcing by means of a numerical simulation of the general circulation. A high resolution model grid was used at 1/60° horizontal resolution and 25 sigma layers. The simulation was carried out using the most recent version of the Princeton Ocean Model (POM). The initialised model was run the whole year of 2006 using the analysis forcing data for the same year obtained from ECMWF and MFS (Mediterranean Forecasting System, Pinardi et al., 2003). The model skills were evaluated by means of the root mean square error (RMSE) and correlations. The Egyptian Shelf Model (EGYSHM) simulation suggests the presence of an Egyptian Shelf Slope Current (ESSC), which is flowing eastward at different depths in the domain. We found that the maximum velocity of the ESSC [0.25 m/s] is located near the continental slope during the summer time, while in winter the velocity of ESSC is weaker [0.12 m/s] in the same location. The ESSC appears to be directly affected by Mersa-Matruh gyre system. EGYSHM reproduced the main region circulation patterns, especially after adding the Nile River outflow. We found that wind stress is crucial to force the circulation of the Egyptian shelf zone. EGYSHM SST was significantly correlated to satellite SST in all months at a 95% confidence limit, with a maximum of 0.9743 which was obtained in May 2006. The RMSE between EGYSHM and Argo floats salinity data was about 0.09. We compared our results with satellite altimetry to verify the positions and shapes of mesoscale features.

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This study addresses a novel application of global navigation satellite system-reflectometry (GNSS-R) delay-Doppler maps (DDMs), namely sea target detection. In contrast with other competing remote sensing technologies, such as synthetic aperture radar and optical systems, typically exploited in the field of sea target detection, GNSS-R systems could be employed as satellite constellations, so as to fulfill the temporal requirements for near real-time ships and sea ice sheets monitoring. In this study, the revisit time offered by GNSS-R systems is quantitatively evaluated by means of a simulation analysis, in which three different realistic GNSS-R missions are simulated and analyzed. Then, a sea target detection algorithm from spaceborne GNSS-R DDMs is described and assessed. The algorithm is based on a sea clutter compensation step and uses an adaptive threshold to take into account spatial variations in the sea background and/or noise statistics. Finally, the sea target detector algorithm is tested and validated for the first time ever using experimental GNSS-R data from the U.K. TechDemoSat-1 dataset. Performance is assessed by providing the receiver operating characteristic curves, and some preliminary experimental results are presented.

In this paper, we introduce a novel framework for small reservoirs extraction in semiarid environment. The task is accomplished through the introduction of a pseudoprobability index derived from multitemporal synthetic aperture radar RGB images. These products are characterized by the ease of interpretation for nonexpert users, and the possibility to be processed using simple algorithms, allowing, in this case, for the definition of an ad hoc band ratio for feature extraction. The reliability of the proposed approach is demonstrated through a case study in Burkina Faso in which 19 reservoirs up to about 6000 m $^2$ extent were tested. The obtained accuracy with respect to the available ground truth is higher than 88%.

Synthetic Aperture Radar (SAR) images are greatly affected by the speckle noise. In order to improve SAR data readability by human interpreters and information extraction performed by computer programs, a despeckling preprocessing step is mandatory. The authors recently presented a despeckling algorithm based on the a priori knowledge of the local topography. In this paper, an experimental sensitivity analysis of the aforementioned despeckling algorithm is conducted and the main results are discussed. In particular, the sensitivity of the filter against surface parameters and scattering behavior is analyzed. A comprehensive understanding of the role of the Digital Elevation Model resolution and the coregistration step is also provided.

This paper presents a methodology aimed to acquire traffic flow data through the employment of unmanned aerial vehicles (UAVs). The study is focused on the determination of driving behavior parameters of road users and on the reconstruction of traffic flow Origin/Destination matrix. The methodology integrates UAV flights with video image processing technique, and the capability of geographic information systems, to represent spatiotemporal phenomena. In particular, analyzing different intersections, the attention of the authors is focused on users’ gap acceptance in a naturalistic drivers’ behavior condition (drivers are not influenced by the presence of instruments and operators on the roadway) and on the reconstruction of vehicle paths. Drivers’ level of aggressiveness is determined by understanding how drivers decide that a gap is crossable and, consequently, how their behavior is critical in relation to a moving stream of traffic with serious road safety implications. The results of these experiments highlight the usefulness of the UAVs technology, that combined with video processing technique allows the capture of real traffic conditions with a good level of accuracy.

Soil moisture is important in the triggering of many types of landslides. However, in situ soil moisture data are rarely available in hazardous zones. The advanced remote sensing technology could provide useful soil moisture information. In this study, an assessment has been carried out between the latest version of the European Space Agency Climate Change Initiative soil moisture product and the landslide events in a northern Italian region in the 14-year period 2002–2015. A clear correlation has been found between the satellite soil moisture and the landslide events, as over four-fifths of events had soil wetness conditions above the 50% regional soil moisture line. Attempts have also been made to explore the soil moisture thresholds for landslide occurrences under different environmental conditions (land cover, soil type, and slope). The results showed slope distribution could provide a rather distinct separation of the soil moisture thresholds, with thresholds becoming smaller for steeper areas, indicating dryer soil condition could trigger landslides at hilly areas than in plain areas. The thresholds validation procedure is then carried out. Forty five rainfall events between 2014 and 2015 are used as test cases. Contingency tables, statistical indicators, and receiver operating characteristic analysis for thresholds under different exceedance probabilities (1%–50%) are explored. The results have shown that the thresholds using 30% exceedance probability provide the best performance with the hitting rate at 0.92 and the false alarm at 0.50. We expect this study can provide useful information for adopting the remotely sensed soil moisture in the landslide early warnings.

Remote sensing techniques allow monitoring the Earth surface and acquiring worthwhile information that can be used efficiently in agro-hydrological systems. Satellite images associated to computational models represent reliable resources to estimate actual evapotranspiration fluxes, ETa, based on surface energy balance. The knowledge of ETa and its spatial distribution is crucial for a broad range of applications at different scales, from fields to large irrigation districts. In single plots and/or in irrigation districts, linking water volumes delivered to the plots with the estimations of remote sensed ETa can have a great potential to develop new cost-effective indicators of irrigation performance, as well as to increase water use efficiency. With the aim to assess the irrigation system performance and the opportunities to save irrigation water resources at the “SAT Llano Verde” district in Albacete, Castilla-La Mancha (Spain), the Surface Energy Balance Algorithm for Land (SEBAL) was applied on cloud-free Landsat 5 Thematic Mapper (TM) images, processed by cubic convolution resampling method, for three irrigation seasons (May to September 2006, 2007 and 2008). The model allowed quantifying instantaneous, daily, monthly and seasonal ETa over the irrigation district. The comparison between monthly irrigation volumes distributed by each hydrant and the corresponding spatially averaged ETa, obtained by assuming an overall efficiency of irrigation network equal to 85%, allowed the assessment of the irrigation system performance for the area served by each hydrant, as well as for the whole irrigation district. It was observed that in all the investigated years, irrigation volumes applied monthly by farmers resulted generally higher than the corresponding evapotranspiration fluxes retrieved by SEBAL, with the exception of May, in which abundant rainfall occurred. When considering the entire irrigation seasons, it was demonstrated that a considerable amount of water could have been saved in the district, respectively equal to 26.2, 28.0 and 16.4% of the total water consumption evaluated in the three years.

In this paper, we present a technique for improving the representation of built-up features in model-based multitemporal synthetic aperture radar (SAR) RGB composites. The proposed technique exploits the multitemporal adaptive processing (MAP3) framework to generate an a priori information which is used to implement an adaptive selection of the coherence window size. Image texture is used to support the coherence information in case of decorrelation. The coherence information, powered by texture analysis, and combined with backscattering amplitude, provides a unique representation of built-up features. This allows for an immediate detection of urban agglomerates by human operators, and is an advantaged starting point for urban area extraction algorithms.

Interpreting synthetic aperture radar (SAR) images may be a very challenging task, even for expert users. One of the main reasons is the multiplicative speckle noise typical of coherent acquisition systems. Therefore, despeckling can be expected to play a key role in the full exploitation of SAR imagery potential. However, even state-of-the-art despeckling algorithms neglect the physical phenomena hidden behind SAR imagery. Image acquisition depends on electromagnetic scattering, which is also at the basis of speckle noise. Taking into account scattering issues into more physical-based despeckling algorithms may only benefit the overall performance. In this paper, we propose a scattering-based (SB) version of the SAR block-matching 3D (BM3D) filter, named SB-SARBM3D. SARBM3D can be arguably considered as one of the most promising and accurate despeckling algorithms, providing a good compromise between speckle reduction and detail preservation. We modify the original algorithm so as to exploit the prior information available on the imaged scene, taken into account based on scattering concepts. The new algorithm is tested in a variety of different and complementary simulated scenarios, and its performance is assessed objectively by means of numerous synthetic parameters. Moreover, comparison with different state-of-the-art despeckling algorithms is performed on some actual SAR images, both inherent to natural and urbanized areas, for subjective evaluation. Thanks to the prior information, SB-SARBM3D outperforms the original algorithm in terms of both speckle reduction and detail preservation. Moreover, it reduces the annoying artifacts introduced sometimes by SARBM3D in homogeneous areas of the image.

We introduce a new architecture for feature extraction from multitemporal synthetic aperture radar (SAR) data. Its the purpose is to combine classic SAR processing and geographical object-based image analysis to provide a robust unsupervised tool for information extraction from time series images. The architecture takes advantage from the characteristics of the recently introduced RGB products of the Level-1 $\alpha$ and Level-1 $\beta$ families, and employs self-organizing map clustering and object-based image analysis. In particular, the input products are clustered using color homogeneity and automatically enriched with a semantic attribute referring to clusters’ color, providing a preclassification mask. Then, in the frame of an application-oriented object-based image analysis, opportune layers measuring scattering and geometric properties of candidate objects are evaluated, and an appropriate rule-set is implemented in a fuzzy system to extract the feature of interest. The obtained results have been compared with those given by existing techniques and turned out to provide high degree of accuracy and negligible false alarms. The discussion is supported by an example concerning small reservoir mapping in semiarid environment.

19 p. This paper reports the latest developments for the photogrammetric open‐source tool called GRAPHOS (inteGRAted PHOtogrammetric Suite). GRAPHOS includes some recent innovations in the image‐based 3D reconstruction pipeline, from automatic feature detection/description and network orientation to dense image matching and quality control. GRAPHOS also has a strong educational component beyond its automated processing functions, reinforced with tutorials and didactic explanations about algorithms and performance. The paper highlights recent developments carried out at different levels: graphical user interface (GUI), didactic simulators for image processing, photogrammetric processing with weight parameters, dataset creation and system evaluation SI

Terraces are the most distinctive sign of human activity on the shape of the Earth surface. Their construction has increased the soils permeability and reduced the slope gradient of mountains since those territories could be exploited both for agricultural and habitable purposes. Over the last decades, they have been the subject of a quick abandonment due to their scarce competitiveness. This has caused some environmental problems, such as soil degradation and hydrological instability. Minori in Italy is one of the most ancient municipalities in the Mediterranean area characterized by the presence of terraces. This paper intends to develop a method for automatic extraction of terraces from historical and contemporaneous aerial photos using an Object-based Image Analysis (OBIA) approach. Historic photos from 1956, acquired by the Geographical Military Institute (IGM), and a contemporaneous block of RGB and multispectral images, taken in 2017 of the study area have been processed to generate a high resolution Digital Elevation Model (DEM) and detailed orthophotos. Subsequently, the OBIA classification has been applied for producing a binary map of terraced and not terraced landscapes for both datasets. Orthophoto resolution was equal to 240 mm, 7 mm and 15 mm for the historical, RGB and multispectral pictures, respectively. DEM resolution results equal to 480 mm and 0.19 mm for the historical and RGB set of data. The R2 between the check points and the estimated values, generated during the metric reconstructions of the two obtained DEMs, resulted equal to 0.99 for both datasets (1956 and 2017). The classification accuracy of the generated binary maps (terraced/not terraced landscapes) were equal to 93% and 98%, respectively. The developed approach looks promising for the historical and contemporaneous datasets. That outcome is essential because it allows to detect terraces position and to compare them over the years in order to analyse their evolution and geomorphological changes.

LiDAR and photogrammetry data are integrated to study an Early Jurassic extensional synsedimentary structure in the Italian Southern Alps. Airborne LiDAR data helped in getting geologic information in areas covered by vegetation, photogrammetry was applied to produce a high-resolution 3D textured model of the inaccessible parts of the outcrop. LiDAR and photgrammetric data were merged together producing a multi-resolution model. Key geologic boundaries and faults bounding the synsedimentary structure were digitized in a 3D geomodeling environment. The reconstruction yielded information about the structure kinematics and accumulated displacements.

In this paper, we present a new framework for the RGB composition of SAR data. The proposed processing chain aims at providing products particularly oriented toward the end-user community, thus characterized by a high degree of interpretability and by the possibility to be processed with simple algorithms for information extraction. The physical rationale of the proposed RGB products is presented through examples highlighting their principal properties. Finally, their suitability with applications is demonstrated through two activities dealing with urban area and land cover mapping.

In 2014, Wiley and the Zoological Society of London launched Remote Sensing in Ecology and Conservation, an open-access journal that aims to support communication and collaboration among experts in remote sensing, ecology and conservation science. Remote sensing was from the start understood as the acquisition of information about an object or phenomenon through a device that is not in physical contact with the object, thus including camera traps, field spectrometry, terrestrial and aquatic acoustic sensors, aerial and satellite monitoring as well as ship-borne automatic identification systems. The primary goals of this new journal were, and still are, to maximize the understanding and uptake of remote sensing-based techniques and products by the ecological and conservation communities, prioritizing findings that advance the scientific basis of, and applied outcomes from, ecology and conservation science; and to identify ecological challenges that might direct development of future remote sensors and data products. In October 2015, the first issue of the journal was published, with four other issues produced in 2016 and four to be published in 2017. As Remote Sensing in Ecology and Conservation is about to complete its second full year of publication and is working towards a first impact factor score in early 2019, the time has come to reflect on how the journal has done to date, what impact it has had, which niches it has successfully filled and where the journal is yet to meet its full potential. By sharing our successes and experiences so far with our contributors and readers, we hope to demonstrate how Remote Sensing in Ecology and Conservation has swiftly gained significant visibility and status among scientists and practitioners interested in natural resource management. Fil: Pettorelli, Nathalie. The Zoological Society Of London; Reino Unido Fil: Nagendra, Harini. Azim Premji University; India Fil: Rocchini, Duccio. Università Degli Studi Di Trento; Italia Fil: Rowcliffe, Marcus. The Zoological Society Of London; Reino Unido Fil: Williams, Rob. Oceans Initiative; Estados Unidos Fil: Ahumada, Jorge. Conservation International; Estados Unidos Fil: de Angelo, Carlos Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina Fil: Atzberger, Clement. Universitat Fur Bodenkultur Wien; Austria Fil: Boyd, Doreen. Science and Technology Facilities Council of Nottingham. Rutherford Appleton Laboratory; Reino Unido. University of Nottingham; Estados Unidos Fil: Buchanan, Graeme. Royal Society For The Protection Of Birds; Reino Unido Fil: Chauvenet, Alienor. University of Queensland; Australia Fil: Disney, Mathias. Colegio Universitario de Londres; Reino Unido Fil: Duncan, Clare. Deakin University; Australia Fil: Fatoyinbo, Temilola. NASA Goddard Space Flight Center; Estados Unidos Fil: Fernandez, Nestor. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; España Fil: Haklay, Muki. Colegio Universitario de Londres; Reino Unido Fil: He, Kate. Murray State University Murray; Estados Unidos Fil: Horning, Ned. American Museum of Natural History; Estados Unidos Fil: Kelly, Natalie. Australian Antarctic Division; Australia Fil: de Klerk, Helen. Stellenbosch University; Sudáfrica Fil: Liu, Xuehua. Tsinghua University; China Fil: Merchant, Nathan. Centre for Environment, Fisheries and Aquaculture Science; Reino Unido Fil: Paruelo, José. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Roy, Helen. NERC Centre for Ecology & Hydrology; Reino Unido Fil: Roy, Shovonlal. University of Reading; Reino Unido Fil: Ryan, Sadie. University of Florida; Estados Unidos Fil: Sollmann, Rahel. University of California at Davis; Estados Unidos Fil: Swenson, Jennifer. University of Duke; Estados Unidos Fil: Wegmann, Martin. Universität Würzburg; Alemania

Ground motions recorded in near-fault areas have some specific characteristics that differ substantially from those recorded in far-fault regions. One of the main features of near-fault records is the pulse-like shape caused by forward-directivity effect. This peculiarity may lead to much more severe damage to bridge structures located in near-fault regions. However, both current Chinese and European codes for seismic design of highway bridges nearly have no consideration on near-fault seismic actions. In this study, typical regular highway bridges in China are idealized as single-degree-of-freedom (SDOF) systems. Then, the Makris mathematical model for the pulse-like records is used to perform a parametric analysis on a settled SDOF system. Effect of key parameters, such as the half-pulse number (n), fundamental period (T0), pulse period (Tp) and the peak velocity (Vp) from the mathematical model, on responses of SDOF systems are analyzed. The potential degradation phenomenon which might happen under near-fault earthquake ground motions is also considered by comparing the ductility coefficient spectrum. The results show that all the key parameters had a significant effect on both linear and nonlinear response spectrum and seismic response. The stiffness degradation phenomenon will lead to a larger ductility coefficient and the Vp is the most effective factor for the response under the near-fault mathematical input.

In this work, two processes related to the onset and the evolution of large-scale rockfalls have been analysed by means of remote sensing techniques. First, the number of rock bridges as a proportion of pre-existing fractures has been estimated in a newly formed landslide scarp by analysing the spectral information of the rock mass in terrestrial laser scanner (TLS) and unmanned aerial vehicle (UAV) photogrammetric point clouds. Second, the fragmentation of the rock mass after failure has been assessed by comparing the percentage of newly formed fractures in the scarp and in the deposit. For this purpose, an orthophoto of the landslide deposit was classified using an object-based method. The presented workflow gained new data on the intact rock breakage during and after failure, and consequently deepened knowledge about rock failure and fragmentation mechanisms.

We propose a strategy to evaluate the performance of a radar sounder for the subsurface exploration of the Europa icy crust and, in particular, the possibility to detect liquid water at the base of the ice shell. The approach integrates the information coming from experimental measurements of the dielectric properties of icy materials, thermal models related to different crustal scenarios, and numerical simulations of radar signal propagation. The radar response has been evaluated in terms of cumulative attenuation, signal-to-noise ratio (SNR), and reflectivity. Our simulations indicate that a subsurface radar operating at 9 MHz can identify shallow-buried targets and to detect the ice/water interface in various thermal scenarios. Under our assumptions the ice/water interface can be detected almost down to a depth of 15 km under a conductive ice shell, whereas for a convective ice shell, the maximum depth is about 12 km (in the cold downwelling plume). We also discuss the possibility to detect shallow targets associated with interfaces between pure water ice and $\text{MgSO}_{4} \cdot 11 \text{H}_{2}{\rm O}$ ice mixtures at various salt contents, using the data of laboratory dielectric measurements.

The seismic actions used to design long structures, as bridges, should be attentively evaluated, since, due to seismic wave propagation through soil, at distant foundation points signals are different. Signal frequency content varies from point to point for at least two reasons: soil-wave interaction; wave traveling time from one point to the other. Asynchronous seismic waves produce distortions at the bridge foundations which are usually not considered in design practice. In this paper, the responses of two RC bridges, one with deck supported by traditional bearing and one by Lead Rubber Bearings (isolators), subjected to asynchronous or synchronous signals were studied. These signals were generated at the surface starting from the EW components of the main shock recorded at two recording stations (AQA, AQV) near L'Aquila city (Italy) on 4-06-2009. The soil distortions which produce maximum stresses on deck or on piers were evaluated for the two bridges (non-isolated and isolated) in case of synchronous and non-synchronous excitations. The first results are discussed to understand the effects of asynchronous excitation on the responses of the two bridges.

The seismic behavior of Chinese RC (Reinforced Concrete) bridge piers with insufficient seismic details, severely damaged after an earthquake and then repaired and retrofitted by rapid interventions is investigated. The proposed interventions are applied on the damaged steel rebar and concrete parts in plastic hinge zone to guarantee the proper plastic dissipation of the seismic energy and the necessary shear strength and ductility improvements. New longitudinal shaped rebars and concrete jackets are used to substitute the pier damaged parts. Two repair and retrofitting procedures are presented and applied on 1:6 scaled pier specimens designed on the base of Chinese codes [1]-[3]: the first one uses an self-compacting concrete to build the concrete jacket and carbon Fiber Reinforced Polymer (CFRP) wrapping to assure the seismic improvements; the second one uses an ultra-high performance fiber reinforced concrete (UHPFRC) with steel fiber to build the concrete jacket and to assure the seismic upgrading allowing time and cost saving. The results of the first experimental tests on 1:6 scaled pier specimens repaired and retrofitting by the two procedures, are compared and discussed.

There is a growing need for numerical models simulating the non-linear behavior of Reinforced Concrete (RC) elements under seismic loads into inelastic range, and for capacity models assessing the deformation capacity of RC members, with emphasis on non-conforming existing buildings. As far as nonlinear modeling is concerned, several approaches have been proposed by different authors; among them, empirical-based macromodels for lumped plasticity modeling (e.g. Haselton et al., 2008) can represent an effective compromise between accuracy and simplicity. They have the great advantage of providing a complete characterization of the nonlinear response, accounting for all of the deformation mechanisms, and their reliability is based on the use of experimental data. They also allow evaluating error/dispersion measures of the simulated response compared to the experimental data they are based on, which can be suitably used for taking into account modeling uncertainties in seismic fragility analyses of RC frames. With regard to capacity models, different approaches have been proposed for the assessment of the deformation capacity of RC members, also for pre-normative purposes; in particular, as far as the seismic assessment of existing RC buildings is concerned, different capacity models have been developed for the ultimate deformation capacity of nonconforming elements subjected to different failure modes (e.g. Elwood and Moehle, 2005; Zhu et al., 2007). In this study, a nonlinear response macromodel is proposed for a specific type of member, i.e. RC columns with plain bars. To this end, a database of tests on RC columns with plain bars is collected from literature. The specimens have different axial load, material properties, geometry, and longitudinal and transverse reinforcement ratio. Force-displacement data are collected and processed for each specimen. The backbone of the experimental response is evaluated for each test, and predictive equations are developed for characteristics points, namely yielding, maximum strength, ultimate (conventional collapse) and zero resistance conditions, based on a statistical analysis of data.

Ground motions in proximity to the causative fault of an earthquake are significantly affected in many cases by forward-directivity effects. The resulting seismic action on bridge is characterized by an important pulse type motion that is not considered in many international structural designed codes. In this paper, the effects of near-fault ground motions applied on regular highway bridges with design parameters selected by a sampling method, are discussed and compared with the ones of the same bridges subjected to far-fault earthquakes. Time history analyses were performed on fiber element bridge models by means of OpenSees considering seven near-fault earthquake input records with significant velocity pulse selected worldwide from the PEER database considering the same site conditions, and the El-centro earthquake record as ordinary far-field earthquake. The results are analyzed in term of top pier drift ratio, pier slenderness ratio, PGA and earthquake intensity parameters.

This paper contributes to the existing literature on the analysis of spatial time series presenting a new clustering algorithm called COFUST, i.e. COpula-based FUzzy clustering algorithm for Spatial Time series. The underlying idea of this algorithm is to perform a fuzzy Partitioning Around Medoids (PAM) clustering using copula-based approach to interpret comovements of time series. This generalisation allows both to extend usual clustering methods for time series based on Pearson’s correlation and to capture the uncertainty that arises assigning units to clusters. Furthermore, its flexibility permits to include directly in the algorithm the spatial information. Our approach is presented and discussed using both simulated and real data, highlighting its main advantages.

The seismic signals, recorded at different surface points during the propagation of the seismic waves through soil, show differences due to the soil-wave interaction. The seismic design actions should be evaluated properly in case of distant foundation points as these differences can be great. In this paper, asynchronous seismic signals are generated at surface starting from a few well-known recordings for the same seismic event. The EW accelerometric components of the main shock recorded at two recording stations (AQA, AQV) near L'Aquila city (Italy) on 4-06-2009 are the generation inputs. The seismic wave propagates along the direction between AQA and AQV. These signals are representative of a possible asynchronous excitation applied on a bridge. Five arrays of asynchronous accelerograms are generated at the foundations of the bridge to perform statistical elaboration of the results. Different bridge positions are supposed along the propagation direction of the wave to evaluate the spatial variability of the generated signals. The generated signals at AQA and AQV stations are compared with the available recordings at the same points (generation inputs) in term of power spectra, acceleration and displacement response spectra. Finally, the most detrimental soil distortions for the bridge deck are calculated for some bridge positions.

The kinematic response of flexible piles in inhomogeneous soil is explored under harmonic and seismic excitation. The system under investigation consists of a long fixed-head pile embedded in viscoelastic soil with stiffness varying continuously with depth. A generalized power-law function is employed to describe the variable soil stiffness. The problem is treated numerically by means of a Beam-on-Dynamic-Winkler-Foundation (BDWF) model based on a layer transfer-matrix (Haskel-Thompson) formulation. This study aims at: (a) investigating numerical and modeling aspects related to Winkler analyses of soil-pile kinematic interaction in a non-homogeneous soil; (b) exploring soil-pile kinematic interaction as affected by varying subsoil conditions under harmonic oscillations; (c) providing a novel closed-form expression for the kinematic interaction factor of pile-head over free-field response as a function of a single dimensionless frequency controlling the physical phenomenon and (d) elucidating the beneficial role of piles in the reduction of seismic loading imposed on pile-supported structures in terms of spectral acceleration for different pile-soil configurations and earthquake motions. Results show that: (a) large-diameter piles in soils with very low stiffness at shallow depths may substantially reduce the seismic acceleration imposed on structures and (b) the role of pile diameter becomes less important for strongly inhomogeneous soils. The latter indicates that even small-diameter piles may induce substantial filtering of ground motion if embedded in soft clays, which may be of importance in pile design practice.

In this paper, we introduce an innovative method to map small reservoirs in semi-arid environment. The proposed technique is based on the exploitation of the recently introduced Level-1α RGB SAR composite, and it is based on change-detection. In particular, we introduce a user-oriented water index defined by a weighted ratio of the bands composing the RGB product. The performance of the method are evaluated by comparison with other popular segmentation techniques of the same complexity in order to demonstrate its reliability. Finally, an applications concerning hydrology, i.e the estimation of reservoir bathymetry starting from area measurements, is presented to underline the usefulness of remote sensing in multidisciplinary contexts.

Unreinforced Masonry (URM) infills are widely used in Reinforced Concrete (RC) structures in Mediterranean countries. URM infills are subjected to the seismic action in their plane, i.e. in the In Plane (IP) direction, and in the Out Of Plane (OOP) direction. The IP displacement demand reduce the OOP capacity and vice-versa: this phenomenon is called IP-OOP interaction. A large number of studies has been carried out on the IP behaviour of infills, while their OOP response and the IP-OOP interaction have been less investigated. In this paper, a review of code and literature provisions concerning URM infills OOP behaviour is presented together with a review of the experimental tests carried out to investigate the infills OOP response and the effects of the IP-OOP interaction. An experimental database is collected to assess the effectiveness of literature and code provisions and to propose new empirical formulations both for predicting infills OOP strength, stiffness and displacement capacity and for modelling the effects of IP displacement demand on the OOP behavior and vice versa. A state of art on infills OOP behaviour and IP-OOP interaction modelling is presented. Most of these distributed-plasticity models are not based on experimental evidences and do not allow taking into account the IP and OOP stiffness degradation due to OOP and IP actions, respectively. A lumped-plasticity macro-model based on the proposed empirical formulations and conceived to represent the IP and the OOP behavior taking into account the mutual interaction effects is defined. Part of the proposed modelling strategy is a routine that removes the whole infill panel from the structural model in case of its IP or OOP collapse. The proposed model is used for an example application showing the effects of taking into account or neglecting the IP-OOP interaction phenomena during structural analyses.

The need to quickly and accurately estimate the number of involved people, dead and the injured, missing people and homeless represent a topic issue in the emergency management and disaster planning. Obviously, such an estimation is closely related to the evaluation of building damage scenario for the area of interest. To this aim, it may be used different methodological approaches for the evaluation of seismic vulnerability at large-scale, consisting of empirical or mechanical methodologies, more or less simplified and that require a different level of detail in input parameters. In present work, a simplified mechanical method - PushOver on Shear Type models (POST) - for seismic vulnerability assessment of infilled RC building is briefly recalled [1,2,3]. The methodology allows the definition of building structural characteristic through a simulated design procedure in compliance with design code prescriptions, professional practice and seismic classification of the area of interest at the time of construction. The evaluation of non-linear static response is performed through a simplified model, considering the contribution of both RC columns and infill panels to lateral resistance, based on Shear Type assumption. Seismic capacity assessment is made in the SPO2IDA framework [4] for different performance levels, defined according to the damage classification proposed by [5]. Finally, the use of a Monte Carlo simulation approach allows the derivation of fragility curves for different damage states (DSs). Therefore, predicted damage scenario is derived from POST methodology for a database consisting of 7597Moment Resisting Frame (MRF) residential RC buildings located in the Abruzzi region, which after the 2009 catastrophic earthquake have been charged to post-earthquake usability assessment procedure [6]. Due to the use of spatially extended and massive amount of data, the reference unit is the class of building. The choice of key parameters for the identification of classes is carried out evaluating their impact on the observed damage collected through post-earthquake survey. Then, within each class, the remaining parameters are assumed as random variables chosen in appropriate distributions evaluated from data collected during the post-earthquake survey. Correlation values among the variable of each class are evaluated. Predicted damage scenario is then compared with damage scenario based on post-earthquake data.

In this study, spatially distributed estimates of regional actual evapotranspiration (ET) were obtained using a revised procedure of the so called “triangle method” to parameterize the Priestley–Taylor ϕ coefficient. In the procedure herein proposed, named Time-Domain Triangle Method (TDTM), the triangular feature space was parameterized considering pairs of T s –VI values obtained by exploring, for each pixel, only their temporal dynamics. This new method was developed using time series products provided by MODIS and MSG-SEVIRI sensors. Moreover the proposed procedure does not depend on ancillary data, and it is only based on remotely sensed vegetation indices and day–night time land surface temperature differences. Two different test areas located in Sicily were selected for testing and validating the approach. Satellite ET rates were validated versus directly measured fluxes of mass (ET) obtained by eddy covariance (EC) towers during the observation period 2010–2012. The proposed approach predicts daily ET rates with an acceptable level of accuracy for practical purposes; therefore, the TDTM can be considered as a simple and effective tool to easily estimate, at regional scale, spatial and temporal changes of this key-variable related to water resource management, agriculture, ecology and climate change.

The work done deals with the concept of Volunteered Geographic Information and is based on the use of a mobile mapping collection tool to retrieve geographical data from an urban fieldwork. The research has been carried on during the academic year 2014/2015, involving students from the course of Geography of Networks within the post graduate degrees in ‘Economics’ and ‘Business’ of the University of Trieste (Italy). The intent was testing the potential of crowdsourcing in retrieving data using a bottom up approach, relying on a set of trained and aware ‘urban sensors’ as data collectors. This allowed us to derive first-hand geographical data concerning a particular topic and analyze its spatial distribution by means of Geographical Information Systems and spatial analytical tools. The topic studied was represented by the urban ‘movida’, the analysis of the areas of the city that are more or less active during the days and during the week. This major aim was also coupled with an ancillary one, as the coverage of Wi-Fi hotspots and networks over the urban area of Trieste. It is known that many Italian cities still do not allow a very wide coverage of wireless networks to access the Internet. The city of Trieste, on the border between Italy and Slovenia, is suited with a certain degree of coverage, particularly in main roads and squares, thanks to free Wi-Fi coverage managed by the municipality and an academic network of Eduroam system, quite spread over European and world cities hosting universities and research centers.

Augmenting spectral data with spatial information for image classification has recently gained significant attention, as classification accuracy can often be improved by extracting spatial information from neighboring pixels. In this paper, we propose a new framework in which active learning (AL) and hierarchical segmentation (HSeg) are combined for spectral–spatial classification of hyperspectral images. The spatial information is extracted from a best segmentation obtained by pruning the HSeg tree using a new supervised strategy. The best segmentation is updated at each iteration of the AL process, thus taking advantage of informative labeled samples provided by the user. The proposed strategy incorporates spatial information in two ways: 1) concatenating the extracted spatial features and the original spectral features into a stacked vector and 2) extending the training set using a self-learning-based semi-supervised learning (SSL) approach. Finally, the two strategies are combined within an AL framework. The proposed framework is validated with two benchmark hyperspectral datasets. Higher classification accuracies are obtained by the proposed framework with respect to five other state-of-the-art spectral–spatial classification approaches. Moreover, the effectiveness of the proposed pruning strategy is also demonstrated relative to the approaches based on a fixed segmentation.

We propose a new approach to synthetic aperture radar (SAR) despeckling, based on the combination of multiple alternative estimates of the same data. The many despeckling methods proposed in the literature possess different and often complementary strengths and weaknesses. Given a reliable pixelwise characterization of the image, one can take advantage of this diversity by selecting the most appropriate combination of estimators for each image region. Following this paradigm, we develop a simple algorithm where only two state-of-the-art despeckling tools, characterized by complementary properties, are linearly combined. To ensure the smooth combination of contributes, thus avoiding new artifacts, we propose a novel soft classification method, where a basic estimate of homogeneity is improved through nonlocal and multiresolution processing steps. The results of a number of experiments conducted on both synthetic and real-world SAR images are very promising, thus confirming the potential of the proposed approach.

In this study the integration of Sentinel-1 InSAR (Interferometric Synthetic Aperture Radar) and GPS (Global Positioning System) data was performed to estimate the three components of the ground deformation field due to the Mw 6.0 earthquake occurred on August 24th, 2014, in the Napa Valley, California, USA. The SAR data were acquired by the Sentinel-1 satellite on August 7th and 31st respectively. In addition, the GPS observations acquired during the whole month of August were analyzed. These data were obtained from the Bay Area Regional Deformation Network, the UNAVCO and the Crustal Dynamics Data Information System online archives. The data integration was realized by using a Bayesian statistical approach searching for the optimal estimation of the three deformation components. The experimental results show large displacements caused by the earthquake characterized by a predominantly NW-SE strike-slip fault mechanism., The research has been supported by the “Marco Polo” project by the University of Bologna (UNIBO), the Spanish Ministry of Economy and Competitiveness research project ESP2013-47780-557 C2-1-R and the EU 7th FP MED-SUV project (contract 308665).

Over the last few years topographical techniques have developed an exponential trend towards simplifying and speeding, both survey operations and analysis of data collected reaching at the same time ever higher levels of accuracy. Among the technologies that are increasingly taking the field in this context is part of the Mobile Mapping System (MMS) that, on any mobile platform, combines sensors and measurement systems designed to provide a 3D position of the platform and, at the same time, capable to acquire geographic data without the aid of control points on the ground. The study reported concerns the verification of the reliability metrics and a qualitative MMS in order to evaluate its behavior in a particularly insidious as it can be an urban park; in particular, we report a series of experiments carried out from 2012 to the present in which we tried to test the potential of the system, comparing it with data from systems more “traditional”, and to exploit all the products in an integrated survey carried out in dynamic mode.

Site selection for waste disposal is a complex task that should meet the requirements of communities and stakeholders. In particular the problems of disposal of damp olive residues and the wastewater left over from the mechanical pressing of the olives has induced the local administration “Città Metropolitana di Roma Capitale”, following the directives of the law n˚ 574/96, to individuate the areas in which is permitted to spread the refuse to be used as compost; such refuse must respect the requirements as to “quality” as defined by the characteristics established by the law of October 19, 1984, n˚ 748, and its successive modifications. The areas in question have been determined by carrying out a comparison between the maps of the hydrological network, the morphology of the terrain, and that pertaining to protected areas, paying particular attention to terrains with a higher permeability in order to avoid the seepa ge of the residue waters into the underground water table.

The conditional intensity function of a space–time branching model is defined by the sum of two main components: the long-run term intensity and short-run term one. Their simultaneous estimation is a complex issue that usually requires the use of hard computational techniques. This paper deals with a new mixed estimation approach for a particular space–time branching model, the Epidemic Type Aftershock Sequence model. This approach uses a simultaneous estimation of the different model components, alternating a parametric step for estimating the induced component by Maximum Likelihood and a non-parametric estimation step, for the background intensity, by FLP (Forward Predictive Likelihood). Moreover, proper graphical tools for diagnostics have been developed and collected, together with the used implemented code in a R package here introduced, named etasFLP .

Incorporating disparate features from multiple sources can provide valuable diverse information for remote sensing data analysis. However, multisource remote sensing data require large quantities of labeled data to train robust supervised classifiers, which are often difficult and expensive to acquire. A mixture-of-kernel approach can facilitate the construction of an effective formulation for acquiring useful samples via active learning (AL). In this paper, we propose an ensemble multiple kernel active learning (EnsembleMKL-AL) framework that incorporates different types of features extracted from multisensor remote sensing data (hyperspectral imagery and LiDAR data) for robust classification. An ensemble of probabilistic multiple kernel classifiers is embedded into a maximum disagreement-based AL system, which adaptively optimizes the kernel for each source during the AL process. At the end of each learning step, a decision fusion strategy is implemented to make a final decision based on the probabilistic outputs. The proposed framework is tested in a multisource environment, including different types of features extracted from hyperspectral and LiDAR data. The experimental results validate the efficacy of the proposed approach. In addition, we demonstrate that using ensemble classifiers and a large number of disparate but relevant features can further improve the performance of an AL-based classification approach.

Thermal infrared (TIR) time series are exploited by many methods based on Earth observation (EO), for such applications as agriculture, forest management, and meteorology. However, due to physical limitations, data acquired by a single sensor are often unsatisfactory in terms of spatial or temporal resolution. This issue can be tackled by using remotely sensed data acquired by multiple sensors with complementary features. When nonreal-time functioning or at least near real-time functioning is admitted, the measurements can be profitably fed to a sequential Bayesian algorithm, which allows to account for the correlation embedded in the successive acquisitions. In this work, we focus on applications that allow the batch processing of the whole data sequences acquired in a fixed time interval. In this case, multiple options for improving the final product are offered by the Bayesian framework, based on both sequential and smoothing techniques. We consider several such Bayesian strategies and comparatively assess their performances in practical applications and through real thermal data acquired by the SEVIRI and MODIS sensors, encompassing the presence of multiple disturbance source, e.g., the cloud coverage of the illuminated scene.

Piles have been used to increase the stability of landslides in static regime for many decades, as they provide resistance against a laterally moving soil mass by transferring the loads into more stable underlying ground. Nevertheless, the presence of such a reinforcement has beneficial effects even under seismic shaking. The paper aims at proposing a simple procedure for the estimation of permanent displacements of slopes stabilized with piles. The method is made up of 3 different stages: (a) evaluation of stability conditions of the natural slope and the ultimate load offered by the piles; (b) combination of the two ingredients above, through limit equilibrium considerations, to assess the critical acceleration of the reinforced slope; (c) use of the classical Newmark method to calculate the permanent displacement under specified input motions. A parametric study is also performed to quantify the beneficial effect of piles under earthquake shaking.

Earthquakes can cause significant damages to industrial liquid storage tanks resulting in losses of functionality, fires or environmental contamination due to the leakage of hazardous chemicals. Typical damages of ground supported tanks during past earthquakes were in the form of cracking at the corner of the bottom plate and compression buckling of tank wall due to uplift, sliding of the base, anchorage failure, sloshing damage around the roof, failure of piping systems and plastic deformation of base plate. Liquid tanks can be also located at some elevated positions due to operational purposes. This makes them susceptible to collapse due to increased base shears and overturning moments. The seismic response of elevated tanks has been widely investigated in the past considering different materials and configurations of support structures. This paper addresses the problem of elevated tanks with particular attention focused on the steel storage tanks resting on short RC columns. The vulnerability of a real example of elevated tanks is assessed though the probabilistic analysis performed using non-linear lumped mass models. Consequently different fragility curves are built for identifying the most important damage states and calculating the corresponding probability of occurrence. The results show how the support structure, especially when composed by RC columns, is the most influencing one, whereas the remaining damage states have a limited influence.

Buried steel pipes are commonly used in oil and gas industry for transmitting hydrocarbon products. Fault crossing is considered as one of the most important extreme events. Buried steel pipes are more vulnerable to compressive strains as compared to tensile strains. In this study, a numerical study is carried out on a simplified numerical model to determine the seismic demand on steel pipes at fault crossings. The proposed model permits plastic hinge formation in the pipe due to incrementally applied fault movements, allow determining the critical length of the pipeline and measure strains developed on the tension and compression sides in the pipe. Based on the analyses carried out on the simple model and previous studies, two performance levels are defined for pipelines; namely, fully functional and partially functional.

A new methodology for the study and evaluation of the seismic response of buildings is presented in this paper. The method involves the use of nonlinear time-history analysis on equivalent multi-degrees of freedom stick models, defined according to the classification given in FEMA440 Report. The steps for implementing the method and obtaining the equivalent model are described in the article. For the validation of the method, the results obtained from the stick models were compared to that obtained by time-history analysis on detailed finite element models of the structures (using the definition of detailed model described in FEMA440). The engineering parameters considered in the comparison are top displacements, interstorey drifts, forces at the floor and base shear. The results of the conducted analyses on the equivalent stick models match satisfactorily, in an excellent way in certain cases, those of the analyses carried out on detailed models. The time-history analyses on the stick models, allowing a considerable saving in terms of both computational effort and time for numerical solution and post-processing of results, could make this kind of analysis more attractive and feasible for a daily design, and comparable in terms of costs with pushover procedures.

Concrete gravity dams represent a relevant part of the 500 large dams existing in Italy. Most of them were built following obsolete seismic design criteria, so they need to be verified with modern seismic analyses according to the new Italian Code on Dams (2014). Many of the parameters utilized in this evaluation are affected by large uncertainties. In the paper we present a procedure based on Monte Carlo simulation which evaluates the probability of exceedance of the sliding equilibrium of the dam obtained via static or response spectrum analysis in case of seismic action, as well as the probability of exceedance of different sliding displacements via nonlinear dynamic analyses. The application to four seismic sites (of different seismic hazard) and to three dams with different heights is presented.

Acquiring current, accurate land-use information is critical for monitoring and understanding the impact of anthropogenic activities on natural environments. Remote sensing technologies are of increasing importance because of their capability to acquire information for large areas in a timely manner, enabling decision makers to be more effective in complex environments. Although optical imagery has demonstrated to be successful for land cover classification, active sensors, such as light detection and ranging (LiDAR), have distinct capabilities that can be exploited to improve classification results. However, utilization of LiDAR data for land cover classification has not been fully exploited. Moreover, spatial-spectral classification has recently gained significant attention since classification accuracy can be improved by extracting additional information from the neighboring pixels. Although spatial information has been widely used for spectral data, less attention has been given to LiDAR data. In this work, a new framework for land cover classification using discrete return LiDAR data is proposed. Pseudo-waveforms are generated from the LiDAR data and processed by hierarchical segmentation. Spatial features are extracted in a region-based way using a new unsupervised strategy for multiple pruning of the segmentation hierarchy. The proposed framework is validated experimentally on a real dataset acquired in an urban area. Better classification results are exhibited by the proposed framework compared to the cases in which basic LiDAR products such as digital surface model and intensity image are used. Moreover, the proposed region-based feature extraction strategy results in improved classification accuracies in comparison with a more traditional window-based approach.

The geodetic datum, and its possible descriptions, of the Italian cadastral networks are analyzed, in order to provide a solution to fit the cadastral sheets to modern map contents and grids, using just their corner crosshair data. Analyzing the extension of the Genova 1902 datum to the whole Italian territory, it occured that the transformation error is acceptable only in the original survey area of the respective triangulation net. For Souther Italy and Sicily (Sicilia), the errors exceed the 20 meters. The Molodensky-type transformation parameters of the Castanea della Furie 1910 and the Guardia Vecchia (Sardinia) datums are provided using only their fundamental point coordinates, without error estimation. While these datums are not correctly checked at their whole application are, we suggest to define local datums of the Bessel ellipsoid, using the Bessel and WGS84coordinates of the respective cadastral grid origins and use them for geo-reference as a basis of the local Cassini grids.