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Slow tourism is a sustainable way of traveling: it is not based on the consumption of resources and at the same time is linked to the discovery of local places and traditions. This kind of tourism, which favors a harmonious and responsible development of the territory, is spreading more and more in Italy as a form that best responds to the new restrictions and needs related to the health emergency. More precisely, paths have become one of the most successful and appreciated declinations of slow tourism. A comprehensive strategy has been defined by the Region of Sardinia aimed at diversifying the tourist offer where the paths are becoming an integral part of the island's tourism product portfolio, together with other types of tourism related to culture, sport, food, nature. Within this scenario, this paper investigates the role of the paths in the tourist development of the Sardinia Region. It takes the Sulcis Iglesiente area as a research area. Here, the establishment of the Santa Barbara Mining Path (SBP), in a sensitive area marked by intense mining activity, offers the opportunity to set up an initial assessment of the effects of these initiatives in terms of enhancing the landscape and developing the communities settled. The authors analyze and highlight some of the principles potentially replicable to implement a structured walkability strategy at the regional level. Within this framework, the authors define a methodology to compare, by specific index proposal, the new concepts of SBPs with the first SBP realized in Sardinia. more...

Large-scale urban development projects featured over the past thirty years have shown some critical issues related to the implementation phase. Con-sequently, the current practice seems oriented toward minimal and wide-spread interventions meant as urban catalyst. This planning practice might solve the problem of limited reliability of large developments’ feasibility studies, but it rises an evaluation demand related to the selection of coali-tion of projects within a multidimensional and multi-stakeholders deci-sion-making context. This study aims to propose a framework for the generation of coalitions of elementary actions in the context of urban regeneration processes and for their evaluation using a Multi Criteria Decision Analysis approach. The proposed evaluation framework supports decision makers in exploring dif-ferent combinations of actions in the context of urban interventions taking into account synergies, i.e. positive or negative effects on the overall per-formance of an alternative linked to the joint realization of specific pairs of actions. The proposed evaluation framework has been tested on a pilot case study dealing with urban regeneration processes in the city of Milan (Italy). more...

The derivation of surface temperature from thermal images requires a proper modelling of the spectral characteristics of the observed surfaces, in particular emissivity. Several possible approaches have been developed in literature. A first category of methods relies on the availability of multiple bands in the thermal region, while a second family of methods, which can be applied also with a single channel sensor, requires the derivation of emissivity values from ancillary data. The methodology, discussed in the present paper, involves the use of hyperspectral images acquired by an AISA Eagle 1 K sensor installed on board an aircraft platform. Data are composed of 61 bands in the visible and near-infrared region. A supervised classification approach was adopted to derive a map of the main materials appearing in the scene, with special attention to roofing materials. The presented analyses were performed in a portion of the urban area of Treviso (Italy), where two aerial surveys, one with a thermal sensor and the second with the AISA sensor, were carried out in 2011. All the presented activities were conducted in the framework of the European project “EnergyCity - Reducing energy consumption and CO2 emissions in cities across Central Europe”. more...

Different applications of underwater acoustics frequently rely on the calculation of transmissions loss (TL), which is obtained from predictions of acoustic pressure provided by an underwater acoustic model. Such predictions are computationally intensive when dealing with three-dimensional environments. Parallel processing can be used to mitigate the computational burden and improve the performance of calculations, by splitting the computational workload into several tasks, which can be allocated on multiple processors to run concurrently. This paper addresses an Open MPI based parallel implementation of a three-dimensional ray tracing model for predictions of acoustic pressure. Data from a tank scale experiment, providing waveguide parameters and TL measurements, are used to test the accuracy of the ray model and the performance of the proposed parallel implementation. The corresponding speedup and efficiency are also discussed. In order to provide a complete reference runtimes and TL predictions from two additional underwater acoustic models are also considered. Foreign Courses Program of CNPq Brazilian Navy more...

In our time people and devices constantly generate data. User activity generates data about needs and preferences as well as the quality of their experiences in different ways: i. e. streaming a video, looking at the news, searching for a restaurant or a an hotel, playing a game with others, making purchases, driving a car. Even when people put their devices in their pockets, the network is generating location and other data that keeps services running and ready to use. This rapid developments in the availability and access to data and in particular spatially referenced data in a different areas, has induced the need for better analysis techniques to understand the various phenomena. Spatial clustering algorithms, which groups similar spatial objects into classes, can be used for the identification of areas sharing common characteristics. The aim of this paper is to analyze the performance of three different clustering algorithms i.e. the Density-Based Spatial Clustering of Applications with Noise algorithm (DBSCAN), the Fast Search by Density Peak (FSDP) algorithm and the classic K-means algorithm (K-Means) as regards the analysis of spatial big data. We propose a modification of the FSDP algorithm in order to improve its efficiency in large databases. The applications concern both synthetic data sets and satellite images. more...

People interact with a place by building mental models according to their priority and experience. The geospatial and social dimensions with the massive introduction of mobile devices are changing the context use of the Web and strengthening the link between spatial, social and digital experiences in a even more social-space-basedinformation architecture. The paper ---based on a case study--- tries to investigate and propose by a conceptual and social-anthropological perspective, the design of a mobile application through Geo-location and Augmented Reality. The aim is to offer the unusual experience of visiting the Cimitero Monumentale di Milano, in real time & place, contextual information as biographical, architectural and artistic notes near gravestones, tombs and funerary monuments establishing a relational experience between people and the reale and digital space. more...

The phenomenon of Urban Heat Island is shown by an increase in temperature that mostly affects urban areas in comparison with the surrounding rural areas. This increase in temperature becomes problematic during the heat waves when it can give rise to problems of energy and health. The factors affecting this phenomenon are related to the morphology and location of the urban area, to the characteristics of building and roads materials, to the shape of urban structure. The paper investigates the phenomenon of UHI by analyzing in particular the influence of major urban planning features: the average height of buildings, the building density, the coverage ratio, the percentage of impermeable surface. The study was carried out starting from the analysis of a real case within the Province of Naples. The identification of areas liable to heat islands has been done by working out a thermal map of the Province of Naples through the creation of hyper-spectral satellite images using remote sensing techniques. This map has allowed to select some sample areas within which the main urban planning parameters have been detected through remote sensing techniques or spatial analysis. For each parameter, correlation curves "temperature - urban planning parameter" have been worked out. The main result is the development of an abacus that allows to estimate the expected temperature changes according to the decrease or increase of each urban parameter. more...

Calibrating land-use change models requires a time-series of reliable and consistent land-use maps, which are often not available. Medium resolution satellite images have a temporal and spatial resolution that is ideally suited for model calibration, and could therefore be an important information source to improve the performance of land-use change models. In this research, a calibration framework based on remote sensing data is proposed for the MOLAND model. Structural land-use information was first inferred from the available medium resolution satellite images by applying supervised classification at the level of predefined regions using metrics that describe the distribution of sub-pixel estimations of artificial sealed surfaces. The resulting maps were compared to the model output with a selected set of spatial metrics. Based on this comparison, the model was recalibrated according to five scenario's. While the selected metrics generally demonstrated a low sensitivity to changes in model parameters, some improvement was nevertheless noted for one particular scenario. more...