Evaluating Urban Quality: Indicators and Assessment Tools for Smart Sustainable Cities

2018 Sustainability  
The analysis of urban sustainability is key to urban planning, and its usefulness extends to smart cities. Analyses of urban quality typically focus on applying methodologies that evaluate quality objectives at environmental, urban, and building levels. Research has shown that a system of indicators can be useful for developing qualitative and quantitative descriptors of urban environments. The first step in this study was to formulate a methodology to measure the quality of urban life based on
more » ... investigative checklists and objective and subjective indicators, aggregated to develop an index to evaluate a city's level of smart urban quality. The second step was to apply this methodology to evaluate the city of Cagliari (Italy) at the neighbourhood scale, which is considered by literature the most suitable as a self-sufficient spatial unit for showing redevelopment results. In addition to sharing its research findings, this study aims to verify whether the methodology can be applied to similar urban contexts. The main outcomes of this research pertain to opportunities to numerically measure both objective and subjective aspects that affect urban quality. In this way, the most critical areas to be requalified have been highlighted in order to prepare policies congruent with the local context. Sustainability 2018, 10, 575 2 of 18 human societies via ICT and behavioural changes [10] . Cities have recently become aware of this concept, by producing data particularly in terms of energy [11] and transport [12] and developing smart management strategies for using the cities' resources more effectively and for decreasing the costs and waste that urban living generates [10] , also in term of wellbeing and inclusion. Giffinger and Gudrun [13] rely on traditional and neoclassical theories of urban growth and development to evaluate criteria for ranking smart cities, and include an assessment in the quality of life in their ranking. Many researchers [4, [14] [15] [16] [17] [18] [19] [20] [21] [22] argue that the quality of life may not represent a separate dimension of a smart sustainable city, given that all the actions undertaken in the other areas of city management should also have the objective of raising the quality of life and urban competitiveness. Ibrahim et al. [4] underlines as "a smart sustainable city is evolving as an urban space that tends to solve urban problems and improve quality of life of citizens, making urban development more sustainable" (p. 530). According to Fleischmann and Heuser [23] and Chourabi et al. [24] , the transformation of an ordinary non-smart city to a smart city also entails networking its technological components with its political and institutional components. Public actions, administered in a discretionary manner, have been used to manage critical planning issues that include the depopulation of historical centres, the deterioration of suburbs, mobility problems, difficulties inherent in managing public property, the incoherent super-positioning of spreading cities, and a loss of interest in social places [25] . Governments at all levels are now embracing the both notion of sustainability and smartness, by developing specific policies and programs that target sustainable development, economic growth, a better quality of life for citizens, and the creation of happiness [14] . Several cities-including Barcelona, Amsterdam, Berlin, Manchester, and Edinburgh-have undertaken transformation projects and smart city initiatives to better serve their citizens and enhance their quality of life. Until now, researchers have used two basic approaches to examine the quality of urban life: the objective approach, which is typically confined to analysing and reporting secondary data-usually aggregate data that are mainly available from official government data collections, including the census, at different geographic or spatial scales-and the subjective approach, which uses social survey methods to collect primary data at the disaggregate or individual level, and focuses on peoples' behaviours and assessments, or their qualitative evaluations of different aspects of urban life [26] . Since 2014, 34 Organisation for Economic Cooperation and Development (OECD) countries have attempted to collect data about people's well-being several times a year. Comparisons have been made using nine criteria-these include access to services, civic engagement, the environment, individual incomes, employment, and education-with open data being made available to researchers and citizens [27] . Also in Europe, different organisations are now trying to identify the best indices for quantifying/evaluating urban smartness. For example, the Finnish Technical Research Centre has created the CITYkeys project (2015)(2016)(2017) [28], funded by the European Union HORIZON 2020 programme [29] , which is developing performance indicators and data collection procedures to monitor and compare smart city solutions across European cities. Research institutes including VTT (coordinator, Finland), AIT (Austria), and TNO (Netherlands) have cooperated with five cities-Rotterdam, Tampere, Vienna, Zagreb, and Zaragoza-and EUROCITIES to define needs, analyse results, and develop recommendations for the use of performance indicators. Given this dynamic evolutive background, it has become necessary to understand and evaluate how cities and territories are changing. The city must become a powerful generator of value, beginning with its own spatial, social, cultural, and relational resources. The new creative city has to provide opportunities for real development that are not only quantitative but also increasingly qualitative that positively influence the domains of collective assets and economic and social capital [30] . This research aims to document an accurate and flexible procedure for evaluating the urban quality of medium-density neighbourhoods, using an approach that combines both objective and subjective Sustainability 2018, 10, 575 3 of 18
doi:10.3390/su10030575 fatcat:rdqc434ekret7a7ojkr2x3i65y