Fuzzy logic modelling to assess high resolution spatial urban climatic risk impact in Valparaiso, Chile

Nicolás Alamos; Marco Billi; Catalina Amigo; Anahí Urquiza; Patricio Winckler; Larraguibel, Cristian; Contreras Manuel .E.; Ariel Muñoz; Jose Tomas Videla; Vargas, Viviana; Jessica Casanova; Antonio Ugalde; Carlos Valdebenito

Abstract

This collection of maps contains a set of 5 layers assessing the risk of the population of the Viña del Mar - Valparaiso conurbation (Chile) in the face of threats of extreme heat, storm surges, floods, forest fires and landslides. The maps have a resolution at the chilean census block level. The layers show as available attributes the overall level of risk and its components: threat (A), exposure (E), sensitivity (S) and response capacity (CR). To estimate the risk, the indices of A, E, S and CR are combined through a fuzzy logic methodology, which considers the use of causality rules co-constructed and validated with local experts and stakeholders. It should be considered that the values ​​presented by each census block on the maps represent an ordering of risk (and of A, E, S and CR), where higher values ​​indicate a greater risk than apples with lower values. The results are ordinal, ranging from mild, through moderately mild, to moderate, high or very high. Moreover, they are not absolute values, but rather relative to the specific case study and should not comparable or extrapolated to other study areas.

Más información

Fecha de publicación: 2021
URL: https://osf.io/2xtvs/