Abstract
The spatial structure of urban areas plays a major role in the daily life of dwellers. The current policy framework to ensure the quality of life of inhabitants leaving no one behind, leads decision-makers to seek better-informed choices for the sustainable planning of urban areas. Thus, a better understanding between the spatial structure of cities and their socio-economic level is of crucial relevance. Accordingly, the purpose of this paper is to quantify this two-way relationship. Therefore, we measured spatial patterns of 31 cities in North Rhine-Westphalia, Germany. We rely on spatial pattern metrics derived from a Local Climate Zone classification obtained by fusing remote sensing and open GIS data with a machine learning approach. Based upon the data, we quantified the relationship between spatial pattern metrics and socio-economic variables related to ‘education’, ‘health’, ‘living conditions’, ‘labor’, and ‘transport’ by means of multiple linear regression models, explaining the variability of the socio-economic variables from 43% up to 82%. Additionally, we grouped cities according to their level of ‘quality of life’ using the socio-economic variables, and found that the spatial pattern of low-dense built-up types was different among socio-economic groups. The proposed methodology described in this paper is transferable to other datasets, levels, and regions. This is of great potential, due to the growing availability of open statistical and satellite data and derived products. Moreover, we discuss the limitations and needed considerations when conducting such studies.
Highlights
How we organize space in urban areas has a decisive influence on how we live and what effects this has on our closest environment: what kind of mobility we choose, how large our ecological footprint is, how close we are to utilities, or what access we have to jobs or leisure fa cilities
The relationships we found between the spatial structure of the cities in this region and the socio-economic variables are as follows: cities with a better level of education have less open, and more continuous, built-up (PU), the distribution of open midrise is more scat tered (DEMp5), dense tree patches are furthest away from the city center (DimRA), and there is a higher density of open high-rise buildings (DC4)
Our study in the cities of North Rhine-Westphalia in Germany shows the interrelation of urban spatial structure with quality of life di mensions
Summary
How we organize space in urban areas has a decisive influence on how we live and what effects this has on our closest environment: what kind of mobility we choose, how large our ecological footprint is, how close we are to utilities, or what access we have to jobs or leisure fa cilities These are just a few of the many exemplary factors that influence the quality of life and the sustainability by its spatial design. The quality of life and sustain able development of urban and peri-urban areas depend on the successful management of their growth Both are common goals in cities around the world. It collects seventeen Sustainable Development Goals (SDGs), which aim at ending poverty by means of promoting economic growth, addressing social needs, while protecting the environment and fighting climate change
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