GIS and google earth engine cloud platform to assess social resilience in flood-prone urban areas: The under-researched Bni Makada district (Tangier, Morocco)

Climate change and socio-economic development increase the frequency and gravity of flooding. Accordingly, flood prevention has become an urgent challenge, and the development of robust risk management strategies is now paramount to cope with even more complex flooding patterns and mitigate their harmful consequences. Given this, enhancing overall resilience to flooding is a key priority, so that communities can effectively and efficiently tackle the potential repercussions. This study aims to develop a composite index SRI (Social Resilience Index) for assessing and mapping social resilience in Bni Makada urban district (Tangier, Morocco). SRI is computed by assigning equal weights −a transparent method favored for its lack of subjective bias in complex multidimensional assessments- and mapped using GIS (Geographic Information System), while recognizing that such weighting scheme, identified as the default setting in index construction and applied in 44 index methodologies ( Beccari, 2016 ), represents one legitimate option among several, with no universally best choice existing ( Tate, 2012 ). To derive this index, a collection of social and economic data must be gathered, including: − number of vulnerable persons, − potential flood-prone areas and – RSPI (Relative Spatial Poverty Index) based on a range of indicators associated with spatial economic concentration, spatial distribution of built-up areas, POIs (Points of Interest), as well as air pollution. For this, the Google Earth Engine platform was leveraged, providing a wide range of recent data to be exploited. The findings reveal a spatial disparity in terms of social resilience to flooding. The SRI empowers smart decisions, ensuring safer futures.