Modeling Urban Growth Patterns with Correlated Percolation
Hernan A. Makse, Jose S. Andrade, Michael Batty, Shlomo Havlin, H. Eugene Stanley
Abstract
We propose and test a model that describes the morphology of cities, the scaling of the urban perimeter of individual cities, and the area distribution of systems of cities. The model is also consistent with observable urban growth dynamics, our results agreeing both qualitatively and quantitatively with urban data. The resulting growth morphology can be understood from interactions among the constituent units forming an urban region, and can be modeled using a correlated percolation model in the presence of a gradient.
Create a lesson
Related papers
Coupling spherical p-spin systems
Riccardo Cipolloni, Leticia F. Cugliandolo
Bias-Induced Crossover in Absolute Capacity of Dense Associative Memory
Yuto Sakurai, Takeaki Shimokawa, Kazunori Iwata et al.
Latent kinetic Ising models of neural spike trains
Davide Ghio, David Saad
Nonlocal Magic across the Many-Body Localization Crossover
Shan-Zhong Li, Zhi Li
Statistical levels and spatial modes of Fock-space heterogeneity in many-body localization crossovers
Yu-Jing Liu, Chen Cheng
Disorder-Tailored Delocalization
Yeongjun Kim, Supriyo Ghosh, Sergej Flach