EO-Based Low-Cost Frameworks to Address Global Urban Data GAPS on Deprivation and Multiple Hazards

Abstract

A continuously growing number of urban inhabitants in Low-and Middle-income Country (LMIC) cities live in deprived areas. Such areas are under-serviced and characterized by poor living and environmental conditions, where the unplanned morphology interacts with physical hazards. While such areas proliferate, climate change has increasingly severe impacts on them. Deprived areas are often located in high-risk zones, e.g., flood zones. However, the absence of global databases on such areas is an obstacle to locate and prioritize hotspots of deprived communities exposed to climate change. Consequently, quantifying the numbers of exposed inhabitants is not possible, though it is required in support of the Sustainable Development Goals (SDGs) (e.g., 11, 13) and local adaptation strategies. Earth observation (EO) that allows producing such data fall short of providing city-level information due to computational constraints and unsolved methodological challenges related to scalability and transferability. This paper presents a framework to combine EO data with data on hazards (e.g., storms, floods) that impact urban areas and, in particular, deprived communities. First results in pilot cities show that deprived communities are systematically more exposed to physical hazards as compared to formal built-up areas. These problems are expected to intensify in the context of climate change, as most hazards will increase in their severity and frequency.