Rapid urban growth has historically led to changes in land use patterns and the degradation of natural resources and the urban environment. Uncontrolled growth of urban areas in the city of Quito has continued to the present day since 1960s, aggravated by illegal or irregular new settlements. The main objective of this paper is to generate spatial predictions of these types of urban settlements and land use changes in 2023, 2028 and 2038, applying the Dinamica EGO cellular automata and multivariable software. The study area was the Machachi Valley between the south of the city of Quito and the rural localities of Alóag and Machachi. The results demonstrate the accuracy of the model and its applicability, thanks to the use of 15 social, physical and climate predictors and the validation process. The analysis of the land use changes throughout the study area shows that urban land use will undergo the greatest net increase. Growth in the south of Quito is predicted to increase by as much as 35% between 2018 and 2038 where new highly vulnerable urban settlements can appear. Native forests in the Andes and forest plantations are expected to decline in the study area due to their substitution by shrub vegetation or agriculture and livestock land use. The implementation of policies to control the land market and protect natural areas could help to mitigate the continuous deterioration of urban and forest areas.

Este artículo analiza el grado de predicción alcanzado por un modelo espacial de crecimiento urbano elaborado con base en (1) el comportamiento histórico de los asentamientos formales e informales en las periferias y en (2) las variables predictoras del fenómeno utilizando técnicas geoespaciales. Se toma como estudio de caso la periferia nor‑oriental de la ciudad de Quito (Ecuador), espacio que ha sufrido una gran transformación en los últimos años. En un primer momento se construye el modelo espacial a partir de imágenes satelitales, complementadas con análisis de variables predictoras del fenómeno bajo la metodología de pesos de evidencia y autómatas celulares. Posteriormente, el análisis se centra en la validación del modelo, a través de ventanas de tamaños múltiples con función de decaimiento constante para el análisis de patrones espaciales con DinamicaEgo. Como resultado, las proyecciones generadas del modelo muestran coincidencias consistentes con la realidad y un alto porcentaje de validación.

The urban and rural areas of the Metropolitan District of Quito (DMQ) have experienced an aggressive urbanization process in the last two decades, which in many cases has changed the most appropriate land use as determined by the local government. This problem is exacerbated by poor land use planning in a city that is growing in an uncontrolled and disorderly manner toward rural areas, as well as by the accelerated growth of rural localities. This article contributes and analyzes: (1) the geographic projections of the next 50 years for urban settlements and buildings in the rural areas of the DMQ using geographic artificial intelligence techniques (cellular automata); (2) a composite index of resilience (CIR) is constructed for each rural parish of the DMQ, adapted to the characteristics and conditions of the territory for which five dimensions with equal weights, the ecological footprint, and the size of each parish were considered; finally, (3) the change in CIR is determined based on the projections of spatial urban expansion and population growth for the next 50 years. According to the results, urbanization definitely has a negative impact on CIR, although it was found that in parishes with declining population growth CIR increases.

Natural or anthropogenic urban vegetation is an important resource for urban planning, risk assessment, and sustainable development of a city. Quito is a megadiverse city due to its location and topography, but the socioeconomic diversity generates more contrasting conditions of certain behaviors and habits related to urban infrastructure. The contrasts of vegetation and green spaces in the different sectors of Quito also reflect the diversity of the city. This study examines the effects of socioeconomic conditions on the loss or increase of urban vegetation. The exploratory regression method (spatial) and logit model (non-spatial) were used to explain the socioeconomic effects on urban vegetation density at the level of urban parishes. On the one hand, the Normalized Difference Vegetation Index (NDVI) was calculated as the dependent variable based on the 2021 sentinel images. On the other hand, the independent variables were structured based on the socioeconomic level, the land valuation areas of Quito (AIVAS), and the quality of life index. This article contributes to establishing baseline information that helps structure the conditions, strategies, and investments to design and implement plans and programs for urban drainage, ecosystem benefits, and sustainable development in the city of Quito.