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      A scalable method to quantify the relationship between urban form and socio-economic indexes

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      EPJ Data Science
      Springer Science and Business Media LLC

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          A Computer Movie Simulating Urban Growth in the Detroit Region

          W Tobler (1970)
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            Green space, urbanity, and health: how strong is the relation?

            To investigate the strength of the relation between the amount of green space in people's living environment and their perceived general health. This relation is analysed for different age and socioeconomic groups. Furthermore, it is analysed separately for urban and more rural areas, because the strength of the relation was expected to vary with urbanity. The study includes 250 782 people registered with 104 general practices who filled in a self administered form on sociodemographic background and perceived general health. The percentage of green space (urban green space, agricultural space, natural green space) within a one kilometre and three kilometre radius around the postal code coordinates was calculated for each household. Multilevel logistic regression analyses were performed at three levels-that is, individual level, family level, and practice level-controlled for sociodemographic characteristics. The percentage of green space inside a one kilometre and a three kilometre radius had a significant relation to perceived general health. The relation was generally present at all degrees of urbanity. The overall relation is somewhat stronger for lower socioeconomic groups. Elderly, youth, and secondary educated people in large cities seem to benefit more from presence of green areas in their living environment than other groups in large cities. This research shows that the percentage of green space in people's living environment has a positive association with the perceived general health of residents. Green space seems to be more than just a luxury and consequently the development of green space should be allocated a more central position in spatial planning policy.
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              Growth, innovation, scaling, and the pace of life in cities.

              Humanity has just crossed a major landmark in its history with the majority of people now living in cities. Cities have long been known to be society's predominant engine of innovation and wealth creation, yet they are also its main source of crime, pollution, and disease. The inexorable trend toward urbanization worldwide presents an urgent challenge for developing a predictive, quantitative theory of urban organization and sustainable development. Here we present empirical evidence indicating that the processes relating urbanization to economic development and knowledge creation are very general, being shared by all cities belonging to the same urban system and sustained across different nations and times. Many diverse properties of cities from patent production and personal income to electrical cable length are shown to be power law functions of population size with scaling exponents, beta, that fall into distinct universality classes. Quantities reflecting wealth creation and innovation have beta approximately 1.2 >1 (increasing returns), whereas those accounting for infrastructure display beta approximately 0.8 <1 (economies of scale). We predict that the pace of social life in the city increases with population size, in quantitative agreement with data, and we discuss how cities are similar to, and differ from, biological organisms, for which beta<1. Finally, we explore possible consequences of these scaling relations by deriving growth equations, which quantify the dramatic difference between growth fueled by innovation versus that driven by economies of scale. This difference suggests that, as population grows, major innovation cycles must be generated at a continually accelerating rate to sustain growth and avoid stagnation or collapse.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                EPJ Data Science
                EPJ Data Sci.
                Springer Science and Business Media LLC
                2193-1127
                December 2018
                February 2 2018
                December 2018
                : 7
                : 1
                Article
                10.1140/epjds/s13688-018-0132-1
                fdef6730-58e6-46a6-b3f4-72ef5f79f74b
                © 2018

                http://creativecommons.org/licenses/by/4.0

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