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Correlations of Socioeconomic and Urban Patterns Observed via an Interpretable Deep Learning Model

November 2, 2020

Urbanization is a great challenge for modern societies, promising better access to economic opportunities, but widening socioeconomic inequalities. Accurately tracking this process as it unfolds has been challenging for traditional data collection methods, but remote sensing information offers an alternative way to gather a more complete view of these societal changes. By feeding neural networks with satellite images, the socioeconomic information associated with that area can be recovered.

Interpretable Deep Learning Model for Socioeconomic Status Inference from Satellite Images and Their Correlations with Urban Patterns

November 2, 2020

Cities have become the economic bedrock of modern nations and this transition will likely be continued in the coming years as an estimated three billion people will move into cities by 2030. Nevertheless, while urbanisation can entail economic dynamism and social development, it can also create enormous social challenges. The management of natural hazards and pollution, the exclusion of the poor from the city’s socioeconomic fabric and the subsequent surge of social and economic inequalities have become some of the pressing issues that modern metropolises need to address.