Abstract

Manifold socio-economic processes shape the built and natural elements in urban areas. They thus influence both the living environment of urban dwellers and sustainability in many dimensions. Monitoring the development of the urban fabric and its relationships with socio-economic and environmental processes will help to elucidate their linkages and, thus, aid in the development of new strategies for more sustainable development. In this study, we identified empirical and significant relationships between income, inequality, GDP, air pollution and employment indicators and their change over time with the spatial organization of the built and natural elements in functional urban areas. We were able to demonstrate this in 32 countries using spatio-temporal metrics, using geoinformation from databases available worldwide. We employed random forest regression, and we were able to explain 32% to 68% of the variability of socio-economic variables. This confirms that spatial patterns and their change are linked to socio-economic indicators. We also identified the spatio-temporal metrics that were more relevant in the models: we found that urban compactness, concentration degree, the dispersion index, the densification of built-up growth, accessibility and land-use/land-cover density and change could be used as proxies for some socio-economic indicators. This study is a first and fundamental step for the identification of such relationships at a global scale. The proposed methodology is highly versatile, the inclusion of new datasets is straightforward, and the increasing availability of multi-temporal geospatial and socio-economic databases is expected to empirically boost the study of these relationships from a multi-temporal perspective in the near future.

Highlights

  • Urban form organizes people, space and flows

  • We identified the spatio-temporal metrics that were more relevant in the models: we found that urban compactness, concentration degree, the dispersion index, the densification of built-up growth, accessibility and land-use/land-cover density and change could be used as proxies for some socio-economic indicators

  • It has a mean error of 10,101 United State dollars (USD) (RMSE), representing 12.3% of the total range of the Gross domestic product per capita (GDP)

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Summary

Introduction

Urban form organizes people, space and flows. Urban areas are simultaneously shaped by economic and demographic processes; social relations; legal and political systems; and historical, cultural and climate contexts; etc. The urbanization process affects dwellers in many dimensions. One impact concerns cities, where air pollution and its impact on health, inequality and environmental degradation are increasing threats as a consequence of rapid growth [3]. The development of urban areas is conditioned by manifold local and regional factors and by global trends that contain drivers and consequences. Earth Observation (EO) provides the tools to remotely capture resulting urban expansion and allows the characterization of urban environments spatially across time at different scales. It allows the measurement from coarse to fine patterns of urban form and dynamics in a consistent way [4]

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