Integrating socio-economic data in spatial analysis: an exposure analysis method for planning urban risk mitigation

For disaster risk management and risk-based urban planning, time-dependent knowledge on the spatial distribution of various social groups is of critical importance. However, in a highly dynamic urbanizing world data are mostly outdated, generalized, not area-wide, not reliable or even not existing. This paper explores the potential of interdisciplinary integration of social science and remote sensing to deal with the problem of area-wide and up-to-date information derivation of the spatial distribution of population, and especially the vulnerable groups. The integration of conventional socio-economic data (census and household survey data) with the structural information of the urban landscape extracted from remotely sensed data aims at assessing dynamic exposure of various social groups. The analysis was done for the case study in the tsunami and earthquake prone coastal city of Padang, West Sumatra, Indonesia. The information generated is particularly useful for giving an additional insight for urban planners, how land use and urban development shape the exposure of various social groups to natural hazards.