Detecting Inequalities from Earth Observation–Derived Global Societal Variables

Urban Inequalities from Space Remote Sensing and Digital Image Processing(2024)

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AbstractSocietal inequalities manifest at a range of scales, from coarse (inter-continent) to fine (intra-city). Satellite-measured night-time lights (NTL) have shown value for capturing and estimating socioeconomic characteristics, including economic activity, well-being, and poverty. However, multi-scale mapping and visualization of inequalities, especially their relative gradations and spatial patterns, have remained a challenge. To narrow this gap, we developed an approach that combines globally available built-up surface, population density, and night-time light intensity data. The integration of these earth observation-derived variables through a spatial visualization frame reveals patterns of societal inequalities at different scales. Our findings suggest that: (1) Outlining and mapping settlements using night-time lights alone underrepresent settlements of low-income countries, as both rural and suburbia of larger cities of the Global South are scarcely lit at night. (2) Combining population and built-up density that spatially locate people on the surface of the Earth with NTL provides insights on deprivation related to the lack of electricity and the services that come with it. (3) Night-time lights and inequality maps are the results of many factors that need to be addressed at different scales. A body of scientific literature that we review has just started to describe the variety of night-time light sources and the spatial variation within and across countries. New, fine-resolution NTL, population, and built-up density that are now becoming available may provide additional insights.
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