Landslide susceptibility assessment in expansion areas of the rapidly growing city of Cuenca (Ecuador)

Mariano Di Napoli¹, Mariagiulia Annibali Corona², Luigi Guerriero², Pietro Miele², Massimo Ramondini³, Chester Sellers⁴ & Diego Di Martire^2
1Department of Earth, Environmental and Life Sciences, University of Genoa, Genoa, 16132, Italy.
²Department of Earth, Environment and Resources Sciences, Federico II University of Naples, Naples, 80126, Italy.
³Department of Civil, Architectural and Environmental Engineering, Federico II University of Naples, Naples, 80125, Italy.
⁴Instituto Ecuatoriano de Regimen Seccional (IERSE), University of Azuay, EC-01.01.981, Cuenca 010107, Ecuador.
Corresponding author e-mail: mariagiulia.annibalicorona@unina.it

Landslides can have significant effects on settlements and human life, especially when mobilized volumes are large and runout velocity is high. In case of high- intensity events, landslide mitigation is not always possible so that the best way to prevent disasters is to reduce the exposed value in susceptible areas. Landslide risk assessment is a fundamental tool for reducing loss induced by landslides, especially considering the impact of high-intensity landslides on the socio- economic development of developing countries. Risk mitigation requires, at least, to be based on a susceptibility scenario and on inventory of existing settlements. On this basis, a study concerning landslide impacting settlements in the city of Cuenca (Ecuador) has been carried out using a landslide inventory database (LID) and supply energy contract database representing a proxy of buildings presence. The susceptibility analysis indicates that most of the slope surrounding the city of Cuenca, where the greatest urban expansion has taken place, is highly prone to instability. In addition, multi-temporal supply energy contract analysis highlights that expansion of urban areas is occurring at a steady rate and such extension is corresponding to an increase in areas susceptible to landslide.

Landslide susceptibility, Machine learning algorithm MaxEnt; growing city, Cuenca, Ecuador.