Abstract
In the last few decades the magnitude and impacts of planetary urban transformations have become increasingly evident to scientists and policymakers. The ability to understand these processes remained limited in terms of territorial scope and comparative capacity for a long time: data availability and harmonization were among the main constraints. Contemporary technological assets, such as remote sensing and machine learning, allow for analyzing global changes in the settlement process with unprecedented detail. The Global Human Settlement Layer (GHSL) project set out to produce detailed datasets to analyze and monitor the spatial footprint of human settlements and their population, which are key indicators for the global policy commitments of the 2030 Development Agenda. In the GHSL, Earth Observation plays a key role in the detection of built-up areas from the Landsat imagery upon which population distribution is modelled. The combination of remote sensing imagery and population modelling allows for generating globally consistent and detailed information about the spatial distribution of built-up areas and population. The GHSL data facilitate a multi-temporal analysis of human settlements with global coverage. The results presented in this article focus on the patterns of development of built-up areas, population and settlements. The article reports about the present status of global urbanization (2015) and its evolution since 1990 by applying to the GHSL the Degree of Urbanisation definition of the European Commission Directorate General for Regional and Urban Policy (DG-Regio) and the Statistical Office of the European Communities (EUROSTAT). The analysis portrays urbanization dynamics at a regional level and per country income classes to show disparities and inequalities. This study analyzes how the 6.1 billion urban dwellers are distributed worldwide. Results show the degree of global urbanization (which reached 85% in 2015), the more than 100 countries in which urbanization has increased between 1990 and 2015, and the tens of countries in which urbanization is today above the global average and where urbanization grows the fastest. The paper sheds light on the key role of urban areas for development, on the patterns of urban development across the regions of the world and on the role of a new generation of data to advance urbanization theory and reporting.
Highlights
The understanding that the majority of the global population lives in urban areas is a decade old [1,2,3]
In the article we propose a deeper and more thematic analysis with Global Human Settlement Layer (GHSL) data explicitly focusing on the urban component of the GHSL data (Urban Centres and Urban Clusters) elaborating further on the broad policy messages on human settlements derived from GSHL data contained in The Atlas of the Human Planet 2016 [29]
The analysis is organized in six thematic areas: in the first, we track the spatial expansion of built-up areas and the demographic change in urban areas per region of the world; in the second we provide figures about the planetary reach of the process of urbanization; in the third, we report on the concentration of people in urban areas and the dispersion of built-up areas; in the fourth, we combine the degree of urbanization and agglomeration at national level; in the fifth, we present the different paces of urbanization disaggregating countries in income classes; in the last section we present key uneven aspects of urbanization
Summary
The understanding that the majority of the global population lives in urban areas is a decade old [1,2,3]. The measurements of observable human presence on Earth can provide a basis for spatially explicit definition of urban surfaces To this end, one product generally used is the global urban map created from the moderate resolution imaging (MODIS) data circa 2001–2002 [10]. One product generally used is the global urban map created from the moderate resolution imaging (MODIS) data circa 2001–2002 [10] This product maps the very high-density built-up environment, which allows us to identify major cities and delineate their high-density built-up areas. It overcomes some gaps observed in earlier global maps derived from other sources [11], such as inconsistencies in urban definition, scale, and data quality; this product offers a single-epoch perspective on human settlements [8]
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