Polycentric Urbanization and Sustainable Development in China

Abstract

This paper addresses urbanization in the context of China's efforts to meet its commitments regarding the United Nations’ Sustainable Development Goals (SDGs). This paper focuses specifically on governmental policies to promote polycentricity, with multiple urban centers of a similar scale within metropolitan areas, rather than a traditional single, dominant central business district. Polycentric urban forms have the potential to reduce average commuting times, thereby impacting greenhouse gas emissions. Polycentricity may also enhance access to employment and other opportunities for marginalized households. To this end, we examine the nexus between emerging polycentric urbanization patterns in Chinese cities and modes of governance at the national and local levels. Changsha, in Hunan province, is selected as a case study to illuminate the issues. Our analysis shows that fiscal considerations and other national and local governance imperatives can play a crucial role in determining how urbanization evolves. While China is unique in many ways, there are also important commonalities with other countries in the global South that are experiencing rapid urbanization, so the insights generated here may be more broadly applicable.

A Review of the Effects of Urban and Green Space Forms on the Carbon Budget Using a Landscape Sustainability Framework

“…However, some researchers believe that the city size affects the level of emission reduction, and the construction of multiple centers in small cities may not reduce emissions [87]. From the perspective of sustainable urban development, polycentric cities increase the chances of marginalized families obtaining employment and other opportunities [217]. They prevent excessive resource concentration and low resource efficiency and contribute to the sustainable development of the urban green economy.…”

Polycentric Spatial Structure Evolution and Influencing Factors of the Kunming–Yuxi Urban Agglomeration: Based on Multisource Big Data Fusion

“…Current urban identification studies involving economy, population and employment also adhere to these results [33,34]. In 2003, McMillen developed a complex but accurate method for identifying the polycentric spatial structure based on census data, defined the urban subcenter as an area far away from the core city but with a population density significantly higher than the average threshold, measured using methods such as locally weighted regression and employment index [35], and this method has been widely recognized and has significantly promoted the study of urban polycentricity [36,37]. However, the center of the urban agglomeration is actually formed by the joint action of multiple elements, which makes different data show some differences in studying the polycentric structure of the urban agglomeration [38][39][40][41].…”