Characterization of coastal environment by means of hyper- and multispectral techniques

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

Building Fuzzy Elevation Maps from a Ground-based 3D Laser Scan for Outdoor Mobile Robots

Mandow, A; Cantador, T.J.; Reina, A.J.; Martínez, J.L.; Morales, J.; García-Cerezo, A. "Building Fuzzy Elevation Maps from a Ground-based 3D Laser Scan for Outdoor Mobile Robots," Robot2015: Second Iberian Robotics Conference, Advances in Robotics, (2016) Advances in Intelligent Systems and Computing, vol. 418. This is a self-archiving copy of the author’s accepted manuscript. The final publication is available at Springer via http://link.springer.com/book/10.1007/978-3-319-27149-1.The paper addresses terrain modeling for mobile robots with fuzzy elevation maps by improving computational speed and performance over previous work on fuzzy terrain identification from a three-dimensional (3D) scan. To this end, spherical sub-sampling of the raw scan is proposed to select training data that does not filter out salient obstacles. Besides, rule structure is systematically defined by considering triangular sets with an unevenly distributed standard fuzzy partition and zero order Sugeno-type consequents. This structure, which favors a faster training time and reduces the number of rule parameters, also serves to compute a fuzzy reliability mask for the continuous fuzzy surface. The paper offers a case study using a Hokuyo-based 3D rangefinder to model terrain with and without outstanding obstacles. Performance regarding error and model size is compared favorably with respect to a solution that uses quadric-based surface simplification (QSlim).This work was partially supported by the Spanish CICYT project DPI 2011-22443, the Andalusian project PE-2010 TEP-6101, and Universidad de Málaga-Andalucía Tech

Tracking morphological changes and slope instability using spaceborne and ground-based SAR data

Stromboli (Aeolian Archipelago, Italy) is an active volcano that is frequently affected by moderate to large mass wasting, which has occasionally triggered tsunamis. With the aim of understanding the relationship between the geomorphologic evolution and slope instability of Stromboli, remote sensing information from space-born Synthetic Aperture Radar (SAR) change detection and interferometry (InSAR) and Ground Based InSAR (GBInSAR) was compared with field observations and morphological analyses. Ground reflectivity and SqueeSAR⢠(an InSAR algorithm for surface deformation monitoring) displacement measurements from X-band COSMO-SkyMed satellites (CSK) were analysed together with displacement measurements from a permanent-sited, Ku-band GBInSAR system. Remote sensing results were compared with a preliminary morphological analysis of the Sciara del Fuoco (SdF) steep volcanic flank, which was carried out using a high-resolution Digital Elevation Model (DEM). Finally, field observations, supported by infrared thermographic surveys (IRT), allowed the interpretation and validation of remote sensing data. The analysis of the entire dataset (collected between January 2010 and December 2014) covers a period characterized by a low intensity of Strombolian activity. This period was punctuated by the occurrence of lava overflows, occurring from the crater terrace evolving downslope toward SdF, and flank eruptions, such as the 2014 event. The amplitude of the CSK images collected between February 22nd, 2010, and December 18th, 2014, highlights that during periods characterized by low-intensity Strombolian activity, the production of materials ejected from the crater terrace towards the SdF is generally low, and erosion is the prevailing process mainly affecting the central sector of the SdF. CSK-SqueeSAR⢠and GBInSAR data allowed the identification of low displacements in the SdF, except for high displacement rates (up to 1.5 mm/h) that were measured following both lava delta formation after the 2007 eruption and the lava overflows of 2010 and 2011. After the emplacement of the 2014 lava field, high displacements in the central and northern portions of the SdF were recorded by the GBInSAR device, whereas the spaceborne data were unable to detect these rapid movements. A comparison between IRT images and GBInSAR-derived displacement maps acquired during the same time interval revealed that the observed displacements along the SdF were related to the crumbling of newly emplaced 2014 lava and of its external breccia. Detected slope instability after the 2014 flank eruption was related to lava accumulation on the SdF and to the difference in the material underlying the 2014 lava flow: i) lava flows and breccia layers related to the 2002â03 and 2007 lava flow fields in the northern SdF sector and ii) loose volcaniclastic deposits in the central part of the SdF. This work emphasizes the importance of smart integration of spaceborne, SAR-derived hazard information with permanent-sited, operational monitoring by GBInSAR devices to detect areas impacted by mass wasting and volcanic activity

Integration between ground based and satellite SAR data in landslide mapping: The San Fratello case study

AbstractThe potential use of the integration of PSI (Persistent Scatterer Interferometry) and GB-InSAR (Ground-based Synthetic Aperture Radar Interferometry) for landslide hazard mitigation was evaluated for mapping and monitoring activities of the San Fratello landslide (Sicily, Italy). Intense and exceptional rainfall events are the main factors that triggered several slope movements in the study area, which is susceptible to landslides, because of its steep slopes and silty–clayey sedimentary cover.In the last three centuries, the town of San Fratello was affected by three large landslides, developed in different periods: the oldest one occurred in 1754, damaging the northeastern sector of the town; in 1922 a large landslide completely destroyed a wide area in the western hillside of the town. In this paper, the attention is focussed on the most recent landslide that occurred on 14 February 2010: in this case, the phenomenon produced the failure of a large sector of the eastern hillside, causing severe damages to buildings and infrastructures. In particular, several slow-moving rotational and translational slides occurred in the area, making it suitable to monitor ground instability through different InSAR techniques.PS-InSAR™ (permanent scatterers SAR interferometry) techniques, using ERS-1/ERS-2, ENVISAT, RADARSAT-1, and COSMO-SkyMed SAR images, were applied to analyze ground displacements during pre- and post-event phases. Moreover, during the post-event phase in March 2010, a GB-InSAR system, able to acquire data continuously every 14min, was installed collecting ground displacement maps for a period of about three years, until March 2013. Through the integration of space-borne and ground-based data sets, ground deformation velocity maps were obtained, providing a more accurate delimitation of the February 2010 landslide boundary, with respect to the carried out traditional geomorphological field survey. The integration of GB-InSAR and PSI techniques proved to be very effective in landslide mapping in the San Fratello test site, representing a valid scientific support for local authorities and decision makers during the post-emergency management

INNODIA Master Protocol for the evaluation of investigational medicinal products in children, adolescents and adults with newly diagnosed type 1 diabetes

Background The INNODIA consortium has established a pan-European infrastructure using validated centres to prospectively evaluate clinical data from individuals with newly diagnosed type 1 diabetes combined with centralised collection of clinical samples to determine rates of decline in beta-cell function and identify novel biomarkers, which could be used for future stratification of phase 2 clinical trials. Methods In this context, we have developed a Master Protocol, based on the “backbone” of the INNODIA natural history study, which we believe could improve the delivery of phase 2 studies exploring the use of single or combinations of Investigational Medicinal Products (IMPs), designed to prevent or reverse declines in beta-cell function in individuals with newly diagnosed type 1 diabetes. Although many IMPs have demonstrated potential efficacy in phase 2 studies, few subsequent phase 3 studies have confirmed these benefits. Currently, phase 2 drug development for this indication is limited by poor evaluation of drug dosage and lack of mechanistic data to understand variable responses to the IMPs. Identification of biomarkers which might permit more robust stratification of participants at baseline has been slow. Discussion The Master Protocol provides (1) standardised assessment of efficacy and safety, (2) comparable collection of mechanistic data, (3) the opportunity to include adaptive designs and the use of shared control groups in the evaluation of combination therapies, and (4) benefits of greater understanding of endpoint variation to ensure more robust sample size calculations and future baseline stratification using existing and novel biomarkers