Dienst van SURF
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There has been a rapidly growing number of studies of the geographical aspects of happiness and well-being. Many of these studies have been highlighting the role of space and place and of individual and spatial contextual determinants of happiness. However, most of the studies to date do not explicitly consider spatial clustering and possible spatial spillover effects of happiness and well-being. The few studies that do consider spatial clustering and spillovers conduct the analysis at a relatively coarse geographical scale of country or region. This article analyses such effects at a much smaller geographical unit: community areas. These are small area level geographies at the intra-urban level. In particular, the article presents a spatial econometric approach to the analysis of life satisfaction data aggregated to 1,215 communities in Canada and examines spatial clustering and spatial spillovers. Communities are suitable given that they form a small geographical reference point for households. We find that communities’ life satisfaction is spatially clustered while regression results show that it is associated to the life satisfaction of neighbouring communities as well as to the latter's average household income and unemployment rate. We consider the role of shared cultural traits and institutions that may explain such spillovers of life satisfaction. The findings highlight the importance of neighbouring characteristics when discussing policies to improve the well-being of a (small area) place.
Since the European Union wants to reduce the oil dependence of the transportation system, the uptake of alternative vehicle technologies are stimulated in the member states. In the Netherlands, stimulation is already largely implemented in the form of a comprehensive charging infrastructure. This infrastructure is widely used by the electric vehicle drivers and thus there may occur a form of competition for the charging points. In this paper we address this problem by predicting the short-term availability of charging points at a given location and time by using the historical charging data in a space-time series model. The model shows better accuracy with respect to a naive method for short term predictions up to one day. This will allow charging point operators to provide customers with the service of looking up estimated charging point availability in the nearby future.
Void street interfaces (VSIs) – building plinths with restricted visual interaction, accessibility, and public use – constitute an urban feature often associated with undermining the public domain, limiting free access and preventing interaction between social groups. Moreover, VSIs have been described as products of inequality designed to segregate and hinder integration between public and private urban spaces. This study assesses VSIs across six cities in Brazil, a country notable for its profound inequality and sociospatial fragmentation. The main aims of this research are: (i) to develop and test a predictive model for VSIs using socioeconomic indicators drawn from open-source ground-truth data; (ii) to identify the variance of VSI within selected case studies. In the development phase of the predictive model, data from the city of Recife are used to build the model. The testing phase involves the analysis of VSIs in the cities of Fortaleza, Salvador, Belo Horizonte, Curitiba and Porto Alegre. The model can potentially assist urban planners in better understanding and locating VSIs and mitigating undesirable outcomes.
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