Cellular Automata Calibration Model to Capture Urban Growth

U. Kumar; C. Mukhopadhyay; T. V. Ramachandra

doi:10.21701/bolgeomin.125.3.002

Autores/as

U. Kumar Energy & Wetlands Research Group, Centre for Ecological Sciences [CES] - Department of Management Studies, Indian Institute of Science - International Institute of Information Technology
C. Mukhopadhyay Department of Management Studies, Indian Institute of Science
T. V. Ramachandra Energy & Wetlands Research Group, Centre for Ecological Sciences [CES] - Centre for Sustainable Technologies (astra) - Centre for Infrastructure, Sustainable Transportation and Urban Planning [CiSTUP]

DOI:

https://doi.org/10.21701/bolgeomin.125.3.002

Palabras clave:

automatas celulares, crecimiento urbano, gestión, inteligencia artificial, modelo de uso del suelo

Resumen

Muchos problemas medioambientales a nivel regional son la consecuencia de actividades antrópicas que involucran cambios en el uso del suelo. Los datos temporales de usos del suelo con aspectos sociales son críticos en el seguimiento de las relaciones causa y efecto sobre variables de interés con los efectos del contexto sobre el comportamiento, o con los procesos de interacción humana con el medioambiente y son también de utilidad para la gestión de la urbanización de las ciudades. Muchas ciudades están sufriendo, en la actualidad, una rápida urbanización y remodelación con propósitos económicos con nuevas carreteras, mejora de infraestructuras, etc. surgiendo la necesidad de entender la dinámica del proceso de crecimiento urbano para la planificación de los recursos naturales. Los autómatas celulares (AC), una técnica de inteligencia artificial basada en el uso de píxeles, estados, vecindades y reglas de transición son útiles en el modelado de los procesos de crecimiento urbano debido a su habilidad para ajustar dichos modelos espaciales complejos utilizando reglas sencillas y efectivas. Este trabajo desarrolla el calibrado de un modelo de AC teniendo en cuenta la dinámica espacial y temporal del crecimiento urbano. La efectividad de esta técnica se demuestra por la captura de los patrones de crecimiento de la ciudad de Bangalore, una ciudad de la India, utilizando datos históricos de teledetección y de población.

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