Messy maps: Qualitative GIS representations of resilience

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Abstract

To include qualitative aspects of flood resilience, such as emotion, social connections and experience, into urban planning, we present a methodology incorporating innovative and experimental map visualisations of informal settlements. The concept of resilience in urban planning is often deployed in technocratic ways using quantitative tools such as geographic information systems (GIS). Yet in the urban Global South, where high proportions of the population live in informal settlements, the knowledge infrastructures used by public authorities leave little room for participation and consideration of local experience. We outline arts-based workshop activities and a qualitative GIS methodology to map resilience as defined by informal settlement residents in two case study cities, Nairobi (Kenya) and Cape Town (South Africa), with applicability across the urban Global South. For each city, four map layers were generated: (i) flood footprints showing resident's spatial knowledge of floods; (ii) georeferenced, narrated 360° photo spheres capturing different perspectives about a space; (iii) spatial social network maps showing residents connections to formal and informal actors before/during floods; (iv) multimedia pop-ups communicating contextual details missing from traditional GIS maps. We show how these prototype maps can be integrated within planning knowledge infrastructures. For spatially imprecise qualitative aspects of resilience in informal settlements, placing markers on a map makes them visible in ways that planners can begin to engage with. Although challenges remain, we found openness in Nairobi and Cape Town by city-level actors to use qualitative forms of evidence, and that the contextual detail aided their retention and understanding of resilience.

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Taylor, F. E., Millington, J. D. A., Jacob, E., Malamud, B. D., & Pelling, M. (2020). Messy maps: Qualitative GIS representations of resilience. Landscape and Urban Planning, 198. https://doi.org/10.1016/j.landurbplan.2020.103771

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