Implementation and calibration of a new irregular cellular automata-based model for local urban growth simulation: The MUGICA model
Cellular automata (CA) based models have traditionally employed regular grids to represent the geographical environment when simulating urban growth or land use change. Over the last two decades, the scientific community has introduced the use of other spatial structures in an attempt to represent t...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universidad de Alcalá (UAH) |
| Repositorio: | e_Buah Biblioteca Digital Universidad de Alcalá |
| Idioma: | inglés |
| OAI Identifier: | oai:ebuah.uah.es:10017/36866 |
| Acceso en línea: | http://hdl.handle.net/10017/36866 https://dx.doi.org/10.1177/2399808317709280 |
| Access Level: | acceso abierto |
| Palabra clave: | Irregular Cellular automata Model calibration Urban simulation Urban growth Geografía Geography |
| Sumario: | Cellular automata (CA) based models have traditionally employed regular grids to represent the geographical environment when simulating urban growth or land use change. Over the last two decades, the scientific community has introduced the use of other spatial structures in an attempt to represent the processes simulated by these models more realistically. Cadastre parcels are a good choice when simulating urban growth at local scales, where pixels or regular cells do not represent the geographic space properly. Furthermore, the implementation and calibration of key factors such as accessibility and suitability has not been sufficiently explored in models employing irregular structures. This paper presents a fully calibrated model to simulate urban growth: MUGICA (Model for Urban Growth simulation using Irregular Cellular Automata). The model uses the irregular structure of the cadastre and its smallest unit: the cadastral parcel. The factors included are based on the traditional NASZ (Neighbourhood, Accessibility, Suitability and Zoning Status) modelling schema, frequently employed in other models. Each factor was implemented and calibrated for the irregular structure employed by the model, and a new approach was explored to introduce a random component that would reproduce illegal growth. Several versions of MUGICA were produced to calibrate the model within the period 2000-2010. The results obtained from the simulations were compared against observed growth for 2010, adapting the traditional confusion matrix to irregular space. A new metric is proposed, called growth simulation accuracy (GSA), which measures how well the model locates urban growth. |
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