An ANN based model to analyze metropolitan growth around Melbourne, Australia

Rapid urbanization across the cities of the world, led by unprecedented population growth and infrastructure development, has led to significant expansion into the peri-urban areas. This expansion is accompanied by dynamic socio-spatial transformations posing pertinent challenges to environmental sustainability. The Greater Melbourne region, Australia's largest city, has witnessed tremendous growth over the last decade, leading to its expansion toward its peripheries. However, there have been limited studies on the nature of this urban expansion. Our study uses a combination of spatial and socio-economic parameters to develop a novel methodology comprising K-means clustering and Artificial Neural Network (ANN) to demarcate urban expansion around metropolitan Melbourne. Our results revealed a significant increase in the urban regions from 6.06% in 2013 to 9.84% in 2020. Whereas the Green wedge has declined rapidly during the same period signifying expansion of urban into the regions hitherto used for non-urban purposes. Our approach integrating spatial and socio-economic indicators provides a comprehensive understanding of the metropolitan expansion, facilitating the delineation of urban boundaries and planning effective urban management strategies.