A landslide risk index for municipal land use planning in Portugal - Pereira, Susana (2020)
In Portugal landslides caused 237 fatalities and >1600 displaced people in the period 1865-2015. Spatial distribution and temporal patterns of slope instability can be related with a complex set of natural and human factors responsible for generating damages. It is essential to develop new methodologies to synthetize risk dimensions to contribute to the landslide risk management at the municipal level. This work proposed a municipal landslide risk index (LRI) considering three risk dimensions: hazard, exposure and physical vulnerability of buildings. The hazard dimension includes the landslide susceptibility performed at the national scale, the probability of weather types associated with landslides and an extreme precipitation susceptibility index. The exposure dimension considered the population density and the number of buildings, whereas the average physical vulnerability of the buildings was computed using four statistical variables from the official census: (i) construction technique and construction materials; (ii) reinforced structure; (iii) number of floors; and (iv) conservation status. Each variable includes different classes that were empirically weighted. After evaluating the three risk dimensions and the LRI, a cluster analysis was performed in order to identify the most important landslide risk drivers in each municipality. Exposure is the main driving force of LRI in the metropolitan areas of Lisbon and Porto, while the hazard is more relevant in the NW municipalities and the physical vulnerability is the major driving force in the south of the country. This methodological approach contributes to a comprehensive and synthetized knowledge about the landslide risk driving forces within the 278 Portuguese municipalities. In addition, it contributes to the diversification and context-oriented strategies of landslide risk management that still lacks in most of the national-level risk governance processes. Finally, this methodology can be generalized to other geographical contexts, improving the risk management, land use planning and the disaster risk reduction.