Although the Andean region is one of the most landslide-susceptible areas in the world, limited attention has been devoted to the topic in this context in terms of research, risk reduction practice, and urban policy. Based on the collection of landslides data of the Andean city of Quito, Ecuador, this article aims to explore the predictive power of a binary logistic regression model (LOGIT) to test secondary data and an official multicriteria evaluation model for landslide susceptibility in this urban area. Cell size resampling scenarios were explored as a parameter, as the inclusion of new “urban” factors. Furthermore, two types of sensitivity analysis (SA), univariate and Monte Carlo methods, were applied to improve the calibration of the LOGIT model. A Kolmogorov–Smirnov (K-S) test was included to measure the classification power of the models. Charts of the three SA methods helped to visualize the sensitivity of factors in the models. The Area Under the Curve (AUC) was a common metric for validation in this research. Among the ten factors included in the model to help explain landslide susceptibility in the context of Quito, results showed that population and street/road density, as novel “urban factors”, have relevant predicting power for landslide susceptibility in urban areas when adopting data standardization based on weights assigned by experts. The LOGIT was validated with an AUC of 0.79. Sensitivity analyses suggested that calibrations of the best-performance reference model would improve its AUC by up to 0.53%. Further experimentation regarding other methods of data pre-processing and a finer level of disaggregation of input data are suggested. In terms of policy design, the LOGIT model coefficient values suggest the need for a deep analysis of the impacts of urban features, such as population, road density, building footprint, and floor area, at a household scale, on the generation of landslide susceptibility in Andean cities such as Quito. This would help improve the zoning for landslide risk reduction, considering the safety, social and economic impacts that this practice may produce.

The Metropolitan Area of Quito has experienced exponential growth in recent decades, especially in peri-urban sectors. The literature has described this process as “urban sprawl”, a phenomenon that is changing the landscape by increasing land consumption and forming conurbations with the nearest populated centers. This article proposes a new, broader and more complex metropolitan structure for the metropolis of Quito, the linking of neighboring and conurbed areas to the form a new metropolitan area based on the case study of the Metropolitan District of Quito (DMQ). This new metropolitan area identification considers the interpretation of satellite images and the classification of land uses, highlighting the main urban growth areas located outside, but contiguous to the administrative limit of the DMQ, over a period of 19 years (1998 to 2017), the demographics analysis, particularly the densification of new urban peripheral areas close to the DMQ border and the mobility links of population, goods and services between human settlements that allows the configuration of urban corridors and the integration of the territory. The main findings evaluated are the need to evaluate urban planning strategies aimed at sustainable development.

En el plan urbanístico de Quito de 2011 se incorporó la zonificación “zonas de riesgo por deslizamiento”, prohibiendo nuevas edificaciones. Esta política, con débil sustento técnico, tuvo imprecisiones con impactos en la seguridad de las familias, afectando sus economías. Tras diez años de aplicación y reformas aún no solventa el problema. Ante tal situación, este análisis propone aprendizajes para futuros contextos similares. Este estudio de caso revisó planes, regulación urbanística y estudios municipales sobre riesgo de deslizamiento, desde 1990. Se trianguló con entrevistas a funcionarios, y el análisis de datos de gestión territorial. Para contrastar, se sobrepusieron espacialmente las capas de zonas de riesgos, eventos del período 2005-2017 y áreas altamente susceptibles a deslizamientos. Durante diez años, 81% (644 hectáreas) de áreas con alta amenaza de deslizamientos no fueron protegidas como zona de riesgo, liberando la generación de riesgo. Contrariamente, 25% (218 hectáreas) del área zona de riesgo no presentaba alta susceptibilidad a deslizamientos, afectando a propietarios de terrenos con restricción de uso. Recientemente el plan urbanístico del 2021 actualizó como capa de afectación a 260 mil hectáreas de las áreas con alta amenaza de deslizamientos en Quito metropolitano, donde sólo 27% de los eventos 2005-2017 coincidieron con esta alta amenaza de deslizamientos. Este último plan abre la posibilidad de precisar la planificación preventiva con instrumentos de planificación de escalas menores de territorios y se espera un plan maestro de gestión de riesgos. La zonificación 2011 para la prevención de riesgo de deslizamiento, aunque tenía un objetivo de reducción del riesgo, tuvo imprecisiones que desprotegieron territorios con alta amenaza de deslizamientos y afectó a propietarios de terrenos sin riesgo. Aunque hubo mejores estudios en el mediano plazo, la política no se actualizó sino hasta 2021. Sin embargo, la nueva capa apenas cubre el 27% de los sitios siniestrados y se ha programado que planes futuros -de escalas menores de ciudad- precisen la zonificación, pues mientras más eventos sigan ocurriendo, las variabilidades climáticas extremas serán cada vez más frecuentes.

Al no tener a la fecha del estudio un número exacto de habitantes en el Distrito Metropolitano de Quito (DMQ), contemplada desde los 10 hasta los 65 años de edad, se delimitó el área del estudio tomando como base el Censo Poblacional INEC del año 2010, mediante la selección de los polígonos censales en suelo de clasificación urbana para obtener una aproximación del tamaño de población de 1655073. Se realizó mediante Muestreo Estratificado con afijación proporcional al tamaño de sub polígonos censales: celdas en todo el Distrito, de 400*400 metros cuadrados considerada como el área caminable, los cuales fueron analizados como estratos resultando un total de 2824 celdas. Para la división estratificada del Distrito Metropolitano de Quito se consideró la densidad poblacional de cada celda para determinar el número de encuestas, excluyendo las áreas verdes, parques, quebradas, estadios y centros educativos de gran extensión por no tener significancia poblacional. Obteniendo un total de 10503 encuestas georreferenciadas por el número identificador de lote. Se determinó el peso de los estratos dentro del universo poblacional del DMQ en suelo urbano, estableciendo el número de encuestas que se debe aplicar dentro de cada celda para efectos del análisis de consumo, desplazamientos e identidad local. En particular se destacan los siguientes resultados: 25 encuestas a ser aplicadas en 27 celdas y 33 encuestas en 2 celdas, evidenciando estos como los espacios donde se está la mayor densidad local dentro del DMQ.

This article examines social vulnerability (SV) as a necessary component of landslide risk assessment in the urban area of Quito, Ecuador. Landslide susceptibility identifies where slope instability is more likely, but it does not explain which populations have fewer resources to anticipate, cope with, or recover from such events. Using 2010 census-tract data, principal component analysis (PCA) was applied to derive interpretable factors of SV. The most robust factor—structural socioeconomic precariousness—combines precarious occupational conditions, lack of access to social security or private insurance, and limited access to new technologies. This factor was combined with a previously developed landslide susceptibility map (LSM) based on events recorded between 2005 and 2017 and aggregated to census tracts. The Comparative Environmental Risk Index (CERI) was then used to interpret whether socially vulnerable groups are disproportionately located in areas of higher landslide susceptibility. Results reveal a comparatively safer and socially advantaged populations axis from the center-north toward the eastern valleys, while high-risk and socially vulnerable areas concentrate in the south and selected peripheral zones. The study provides a historical and methodological baseline and contributes a quantitative, spatial, urban approach to landslide risk inequity in an Andean city.

This article examines social vulnerability (SV) as a necessary component of landslide risk assessment in the urban area of Quito, Ecuador. Landslide susceptibility identifies where slope instability is more likely, but it does not explain which populations have fewer resources to anticipate, cope with, or recover from such events. Using 2010 census-tract data, principal component analysis (PCA) was applied to derive interpretable factors of SV. The most robust factor—structural socioeconomic precariousness—combines precarious occupational conditions, lack of access to social security or private insurance, and limited access to new technologies. This factor was combined with a previously developed landslide susceptibility map (LSM) based on events recorded between 2005 and 2017 and aggregated to census tracts. The Comparative Environmental Risk Index (CERI) was then used to interpret whether socially vulnerable groups are disproportionately located in areas of higher landslide susceptibility. Results reveal a comparatively safer and socially advantaged populations axis from the center-north toward the eastern valleys, while high-risk and socially vulnerable areas concentrate in the south and selected peripheral zones. The study provides a historical and methodological baseline and contributes a quantitative, spatial, urban approach to landslide risk inequity in an Andean city.