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Earthquake-induced rubble in urbanized areas must be mapped and characterized. Location, volume, weight and constituents are key information in order to support emergency activities and optimize rubble management. A procedure to work out the geometric characteristics of the rubble heaps has already been reported in a previous work, whereas here an original methodology for retrieving the rubble&rsquo, s constituents by means of active and passive remote sensing techniques, based on airborne (LiDAR and RGB aero-photogrammetric) and satellite (WorldView-3) Very High Resolution (VHR) sensors, is presented. Due to the high spectral heterogeneity of seismic rubble, Spectral Mixture Analysis, through the Sequential Maximum Angle Convex Cone algorithm, was adopted to derive the linear mixed model distribution of remotely sensed spectral responses of pure materials (endmembers). These endmembers were then mapped on the hyperspectral signatures of various materials acquired on site, testing different machine learning classifiers in order to assess their relative abundances. The best results were provided by the C-Support Vector Machine, which allowed us to work out the characterization of the main rubble constituents with an accuracy up to 88.8% for less mixed pixels and the Random Forest, which was the only one able to detect the likely presence of asbestos.

The meadow froghopper, Philaenus spumarius L., is endemic in Italy and was not considered a harmful species until 2014, when the olive quick decline syndrome (OQDS) showed up in Apulia (southern Italy). It was immediately suspected and then verified as the main vector of Xylella fastidiosa, the bacterium responsible for the disease. Currently, EU Directives consider the fight against P. spumarius compulsory in member states and recommend Integrated Pest Management (IPM), both in uncultivated and cultivated infested areas, to minimise the environmental impact of chemical pesticides. This should be based on an improved knowledge of the vector with its seasonal trends and feeding habits linked to specific herbaceous species. In this context, our field study was aimed to improve the understanding of the vector nutritional behaviour, especially at its critical nymph stage, by monitoring its presence on different herbaceous target species, using its typical feeding foams as key indicator. The study area was in Lazio region (central Italy), dedicated to olive growing and still unaffected by the X. fastidiosa plague. Over twoyears, during the nymph development period, field data have been acquired over the test area and then analysed by coupling statistical (ANOVA), geographical information system (GIS) and geo-referenced field sampling approaches. Results highlighted that P. spumarius exhibits significant preferences for specific herbaceous plants, especially at its early development stages, detectable by tenuous spittle. This indicates female oviposition activity, which seems also not influenced by olive tree proximity. Furthermore, the non-host plant species identified here could be suitable for creating green barriers for limiting the vector diffusion to contiguous areas where sensible plantations are growing. In the final section, applied implications arising from the present findings for P. spumarius population management are discussed.