Volume 34, Issue 2 (2025)

Grid-World Modeling of Area-Population Dynamics Based on Data for Indian Cities

Dvarkesh Ghatol${ }^{1,2}$
Muhammad Alfas${ }^1$
Akshay Mattoo${ }^{1,3}$
Shaurya Shriyam${ }^1$
${ }^1$Department of Mechanical Engineering, Indian Institute of
Technology Delhi
${}^2$CNH Industrial, Gurugram, India
${}^3$Google, Hyderabad, India

Abstract

Among the major applications of network science, significant attention has been paid to modeling smart cities and mobility. Modeling cities and urban systems is also important from the perspective of policy-making toward sustainable development. By representing cities or areas in a city as nodes and the population flow among them using edges, we try to build network models that capture the essence of urban systems and growth patterns. Our simulations are based on predefined parameters and specific rules to govern area and population growth. We primarily model area expansion and population growth dynamics using two grid-based models. The first model uses real-world data, whereas the second model is inspired by cellular automata and implemented in two versions: random and contiguous. We also computed complexity metrics based on approximate entropy and found that the complexity values associated with area-population growth dynamics were always higher in the random cases as compared to their contiguous counterparts. We have also shown validation results and shared interesting insights based on our simulation runs.

Keywords: urban informatics; simulation modeling; cellular automata; complexity estimation

Cite this publication as:
D. Ghatol, M. Alfas, A. Mattoo and S. Shriyam, “Grid-World Modeling of Area-Population Dynamics Based on Data for Indian Cities,” Complex Systems, 34(2), 2025 pp. 161–201.
https://doi.org/10.25088/ComplexSystems.34.2.161