Landslide risk assessment and mitigation in cities

Abstract

The number of vulnerable citizens in areas of landslide risk is rising globally due to climate change and urban growth. Landslide Early Warning Systems (LEWS) have the capability to decrease vulnerability. However, knowledge on landslide-prone areas, exposed assets and population is precondition for the installation of LEWS. In this presentation, the experiences of developing a LEWS prototype in the landslide-prone neighborhood of Bello Oriente in Medellín, Colombia are introduced. These experiences have been used for a data-driven approach using knowledge from remote sensing, geo-engineering and landscape architecture to localize landslide-prone areas suitable for low-cost and easy-touse LEWS instrumentation in the entire city. The workflow enables decision-makers to balance financial costs and the potential to protect exposed populations.