Modelling the spatial extent of urban growth using a cellular automata-based model: a case study for Quito, Ecuador

ABSTRACT

Since the late 1980s, the city of Quito shows a considerable expansion of urban land. This study generates plausible scenarios of urban growth that can be applied within urban planning and used for applications, such as projections of transportation needs, or air pollution exposure. We develop a methodology to map urban growth using the LUCIA model. The urban growth is estimated based on land use maps, regulatory constraints, population, proximity, suitability, accessibility to main roads, urban areas, and sub-centralities. The model considers the complex topography of Quito by defining the driving forces according to the elevation of the terrain. The model is calibrated for the period 2000–2016 and satisfactorily evaluated for 2018 applying a cell by cell and spatial pattern comparison. We analyse the effect on the result assessment if small errors nearby the actual and simulated urban land are considered as correct, finding an increase of 30% in the accuracy for one cell of distance. We apply the model to predict the urban growth of Quito between 2016 and 2040. Results show that, if the current trend continues, the urban land will increase by 84% with a continuous fragmentation that stabilizes around the year 2025.

KEYWORDS:

• Urban growth
• land use change
• spatial modelling
• cellular automata
• quito

Acknowledgments

This study is part of Ph.D. studies funded by SENECYT, Ecuador, Grant ID: CZ02-000105-2018.

We would like to thank the Municipality of Quito, the Ministry of Environment, the Ministry of Agriculture and the National Statistic and Census Institute of Ecuador for providing most of the data utilized in this study.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data Availability Statement

Data are available on request from the authors. The data that support the findings of this study are available from the corresponding author upon reasonable request.

Additional information

Funding

This work was supported by the Secretary of Higher Education, Science, Technology and Innovation of Ecuador SENECYT [CZ02-000105-2018].