Leveraging Urban Growth Models (UGM) for Sustainable Urban Planning and Climate Resilient Cities: A Bibliometric Analysis

Abstract

Speedy technological, social, political, demographic, and urban developments continued to change the scale of the cities worldwide. Therefore, it becomes essential to model urban growth to minimize future uncertainties. Therefore, it is critical to investigate how cities grow and how researchers investigate which factors influence city growth. Using bibliometric methods, this study intends to pinpoint the publishing patterns and expansion potential of Urban Growth Modelling (UGM) works, providing a better understanding and possible future research paths. All published articles on the 'Urban Growth model' from Scopus were identified and analyzed using the Bibliometric R-package and VOSviewer software. 218 publications were identified from 1983 to 2023, published in 103 journals, and 25 book chapters contributed by 557 authors, with a 2.7 collaboration Index and 2.56 authors per document. The high-frequency keywords used in recent years are urban growth, land use, remote sensing, urban planning, cellular automaton, urban development, modeling, urbanization, Geographic Information System (GIS), and land use change. Research papers published in Computers, Environment, and Urban Systems are the most cited, with 1047 total citations, h-index 13. The most active country was China, with a total of 38 documents. The most cited paper for UGM research is titled 'Modelling urban growth in Atlanta using logistic regression' , which received over 378 citations. The study's findings offer milestones, a starting point for important research productivity data, and an understanding of how UGM research has evolved. This will help to estimate and assess the rate of urbanization, its location, and the consequences of before and after development before it gets stranded in unsuitable and unsustainable pathways.