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A smart sustainable city (SSC) is a paradigm that encapsulates the latest lines of development in multiple fields of research. The attempt to converge towards a model of sustainable urban life, made difficult by increasing anthropic pressure and polluting activities conducted by man, is also reflected in the intentions of public institutions to take measures of environmental risk mitigation. The change towards more liveable cities must also include the adoption of more far-reaching measures in various sectors. The objective of our work was to provide an analysis in order to assess which of the Italian provincial municipalities were most closely related to the paradigm of SSCs. This aim was pursued through a comparison based on the results of a partially non-compensatory quantitative method, known as the Pena’s Distance method (DP2). The smartest and most sustainable cities, such as Siena, Milan and Padua, were not identified on the basis of common urban characteristics but rather derived from the combination of distinctive and functional elements in the pursuit of a strategic approach aimed at fully exploiting the resources of each area. Moreover, at a macro-geographical level, from the analysis emerged the presence of contiguous clusters, i.e., areas in which a major concentration of smart sustainable municipalities tended to form

Ministerio de Ciencia, Innovación y Universidades PID2019-107993GB-I00

Rail trails are non-motorised routes resulting from the conversion of disused railway lines, geared towards cycle tourism and other leisure activities. This paper seeks to highlight the potentialities and shortcomings of rail trails in Andalusia. A diagnosis is made through a SWOT matrix, with information from the management bodies and a coherent planning is applied. The results enable proposals intended to remedy the shortcomings detected and create an effective rail trail network in Andalusia, managed in a coordinated fashion and internationally comparable with regard to public usage.

Recent studies show the existence of spatial inequalities between northern, southern, and eastern Europe in the provision and use of ICT infrastructure by households and individuals. Previous studies have been carried out at national levels or for rural-urban areas without analysing the existence of spatial distribution patterns. The objective is to identify spatial patterns of ICT use in households and individ uals at a regional level in Europe. The research is carried out with two complex variables: ‘availability of broadband and daily use for commerce, banking, and e-government’ or transactional use; and, ‘use of so cial networks by broadband’ or relational use. With 233 NUT 2, the following is analysed: a) distribution and statistical dispersion of the degree of variability of ICT use; and 2) spatial autocorrelation with GIS to identify spatial patterns by calculating Moran's I and Getis-Ord global indexes, Moran’s local Anselin, and Getis-Ord Gi*. The result is that the relational use shows similar values among European regions with a uniform territorial distribution; and the spatial component is not a factor of equal magnitude for the transactional variable (which shows a spatial pattern featuring a northwest-southeast gradient).

The rail trails (converted disused railways) are infrastructures which can be reused mainly as non-motorised itineraries for hiking and cycle touring. Andalusia (Spain) has a network of 1442 km of disused railways, out of which 606 km are found in Huelva province (42.1%) as heritage from its former mining activity. The aim of this article is to devise a method which determines the real accessibility to rail trails and the volume of resident population who can reach them in a time period of 5, 10 and 15 minutes by road in a private vehicle. This process involves the determination of real accesses with accuracy and the differentiated calculation of the average speed on the different types of routes. The method is used for the three rail trails which currently exist in Huelva (98.6 km), having as a result a Map at a scale of 1:325,000.