The Walkability of the Cities

The issue of city walkability is nowadays a theme in evidence. The chapter proposes a two-level reasoning. At the city level, the goal is to recognize the parts where actions aimed at improving walkability can be more effective. The second level is more detailed: lacking pedestrian paths' specific graphs, the urban space is modeled through a raster with 1x1 m. cells. Considering a series of criteria, an impedance has been assigned to each cell (i.e., the cost of travelling the cell on foot). This approach is applied to the city of Torino (Italy), but it is largely generalizable. To calculate this impedance, inter alia, the Torino geo-topographic database was used. The elaborations described in this chapter are seen as an aid to stakeholders to reason on city walkability and to compare different points of view in an explicit and articulated way.

A Territorial Dimension Can Be Useful for Managing Long-Term Regional Road Safety

Analysis of road crashes at the local level is necessary for targeting and implementing effective countermeasures. This chapter presents a contribution to this task. It describes the research carried out in Piedmont, Italy, where an exploratory approach has been used to link road crash data with information about the spatial characteristics of urban settlements. The analytic strategy is developed in three steps. First, fine-grained spatial data for road crashes, land use, traffic counts, and population distribution are linked by GIS methods. Second, a selection of the data is implemented at the municipality level and processed through a cluster analysis to identify territorial accident profiles. Finally, to show their analytic potential, one case study is discussed that considers road segments as main observation units.

Towards Knowledge-Based Spatial Planning

For millennia, spatial planning has been based on human knowledge about the context and its environment together with some objectives of development. Now, with artificial intelligence and especially knowledge engineering, practices of spatial planning can be renovated. Presently, novel practices can be designed. In addition to human collective knowledge, some new chunks of knowledge can be introduced, coming from physical laws, administrative regulations, standards, data mining, and best practices. By big data analytics, some regularities and patterns can be discovered, which again will lead to new actions towards cities: in other words, there is a virtuous circle linking smart territories and big data that can be the basis for novel spatial planning. The role of this chapter will be to analyze those new chunks of knowledge and to explain how human knowledge, possibly coming from different stakeholders, can be harmonized with machine-processable knowledge as to be the basis for territorial intelligence.

Defining Urban Planning Strategy Through Social Media Application

Social networks in the public sphere support the process of innovation that aims to make the action of the municipalities more efficient and participatory. Due to their characteristics, social media seem to be able to contribute significantly to the development of e-governance and e-democracy as tools based on dialogue and on the enhancement of the contribution of users-citizens or, more generally, of users-local stakeholders. Web 4.0 and social media are progressively taking on a role of primary importance in the contemporary socio-economic context, contributing to change not only the processes and methods of communication of individuals, citizens and businesses, but also the organization and business management itself. In the new dimension of the Web 4.0 the user's behavior is not predetermined, but the user can derive and autonomously build the services, as the web is decentralized and enriched by the experiences of the users who participate in the definition and improvement of content.

A Planning Model for Cognitive Cities

A city is a real-time function with constantly changing variables. Rapid urbanization of the cities and increase in a number of mega cities has made the entire urban management complex. With many parameters involved in it, urban data has started to resemble the characteristics of big data. The nexus between spatial cognition and the frequency of data collection of an urban system explains the role of big data analysis in performance monitoring of the urban systems. Urban data collection and analysis can be possible through participatory planning and participatory citizens. This chapter focuses on understanding the correlation between spatial cognition and participatory planning.

Researching and Enabling Youth Geographies in the Digital and Material City

This contribution presents the methodologies and the results of an action-research project called Teencarto carried out by the University of Turin and the City of Turin. The project involved more than 600 teenagers from 16 high schools, in a massive process of community mapping aiming at producing a representation of their urban geography. Data collected has been analyzed to make evident the way teenagers use the city as well as how they imagine a better city. The mapping process is based on First Life, a map-based social network, which aims at reconnecting digital and real spaces, using cartographic representations and crowdsourcing. The teenagers' geographies emerging from this large-scale mapping activity reveal the crucial role of four types of “piazza” (Italian word for square) as meeting points: real squares, green squares, commercial hybrid squares, and nightlife squares.

Semantic Spatial Representation and Collaborative Mapping in Urban and Regional Planning

This chapter focuses on the theme of the spatial representation of cities and the territory and the collaborative construction of territorial knowledge. The described research concerns the “OnToMap. Mappe di Comunità 3.0” project, focused on the definition of a methodology that implements a semantic representation of territory. That type of representation supports the description of big and open data and of its properties in a unified language. OnToMap enables the sharing of information on the web by providing an integrated perspective on territorial data, as demonstrated in an experimentation with Ph.D. students of the Politecnico di Torino. OnToMap is also part of the H2020 funded project WeGovNow, based on the integration of GIS tools, VGI practices and Web 3.0 applications: an example of citizens' involvement in the urban redevelopment process of Parco Dora in Turin, which aims was make more inclusive (in terms of empowerment) and efficient urban planning policies.

Defining Energy Criteria in the Absence of Open Data

The urban decision processes should be optimized according to the current “green” context. Despite the literature advocating for an open availability of data to facilitate higher quality science and a more effective science-policy boundary, one of the main challenges when dealing with energy processes is the absence of accurate data. This chapter aims at illustrating a stakeholder-oriented approach based on multi-criteria analyses (MCA) in defining the set of evaluation criteria and their relevance in supporting the development of “what if” urban energy retrofitting scenarios. In this regard, the SRF method has been used highlighting that the most important criteria for the problem in exam are related to economic and environmental aspects. In this context, big data visualization and geographical locations of the alternative scenarios, producing presentation features and performing spatial operations are fundamental. Hence, the authors supported the decision process through MC-SDSS to optimize the urban decision purposes. The results of this chapter are part of the national project EEB.

Big Data and High-Performance Analyses and Processes

The period of vast information and examination has arrived and is changing the world significantly. The field of information frameworks ought to be at the bleeding edge of comprehension and deciphering the effect of the two innovations and administration to lead the endeavors of business to inquire about in the information period. In this chapter, the author investigates administrative issues of business change coming about because of the original appropriation and inventive uses of information sciences in business. The author ends by giving an analysis of big data that covers all the analytical processes and future research headings.

Ecosystem Service Evaluation for Landscape Planning Policies

Ecosystem services (ES) are the subject of a constantly growing attention at the international level. Although in the most recent years significant progresses in ES evaluation have been made, important methodological challenges still exist. Among these, data availability is perhaps the most urgent one. High quality, spatially explicit, appropriate to the evaluation scale, and accessible data are needed to pursue an effective and reliable ES evaluation. These criteria drove the selection of data in a research relating to the assessment and valuation of forest ecosystem services (FES) in the Sardinia Region. However, it is not always possible to reach such data-quality targets. Big data could be an important resource to fill information gaps in the field of ES evaluation, though certain big data limitations suggest their careful management. Starting from the current research's outcomes with regard to assessment and valuation of FES in the Sardinia Region, the role of big data for supporting ES evaluation is eventually addressed.