Abstract
In recent decades, developing countries have experienced an increase in the impact of natural disasters due to ongoing climate change and the sustained expansion of urban areas. The intrinsic vulnerability of settlements, due to poverty and poor governance, as well as the lack of tools for urban occupation planning and mitigation protocols, has made such impacts particularly severe. Cuenca (Ecuador) is a significant example of a city that in recent decades has experienced considerable population growth (i.e. exposure) and an associated increase in loss due to landslide occurrence. Despite such effects, updated urban planning tools are absent, so an evaluation of multitemporal exposure to landslides and related risks is required. In this perspective, a potential urban planning tool is presented based on updated data depicting the spatial distribution of landslides and their predisposing factors, as well as population change between 2010 and 2020. In addition, a multitemporal analysis accounting for changes in exposure between 2010 and 2020 and an estimation of relative landside risk was carried out. Due to the absence of spatially distributed population data, energy supply contract data have been used as a proxy of the population. The results show that the current higher exposure and related relative risk are estimated for parishes (parroquias) located in the southern sector of the study area (i.e. Turi, Santa Ana, Tarqui, Nulti, Banos and Paccha). Moreover, the exposure multitemporal analysis indicates that most parishes located in the hilly areas bounding the city centre (i.e. Sayausi, San Joaquin, Tarqui, Sidcay, Banos, Ricaurte, Paccha and Chiquintad) are experiencing sustained population growth and will be potentially exposed to an increased risk with a consistently growing trend. The obtained relative risk map can be considered a valuable tool for guiding land planning, land management, occupation restriction and early warning strategy adoption in the area. The methodological approach used, which accounts for landslide susceptibility and population variation through proxy data analysis, has the potential to be applied in a similar context of growing population cities in low- to mid-income countries, where data usually needed for a comprehensive landslide risk analysis are non-existing or only partially available.