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Long-term coupling coordination analysis between urbanization and the ecological environment in global cities: insights from remote sensing

  • Yuan Yuan
  • , Zuoqi Chen
  • , Congxiao Wang
  • , Zhan Pan
  • , Wenkang Gong
  • , Mingna Pan
  • , Bailang Yu*
  • *Corresponding author for this work
  • East China Normal University
  • Fuzhou University
  • Yunnan Normal University
  • Ministry of Education of the People's Republic of China

Research output: Contribution to journalArticlepeer-review

Abstract

Global urbanization has accelerated economic growth while intensifying environmental pressures, leading to uneven urbanization–environment interactions across the Global North and Global South. Although numerous studies have examined urbanization–environment coordination, few provide globally comparable, long-term, and intra-urban assessments within a unified framework. To address this gap, this study evaluates urbanization–environment coordination in Global North and Global South cities at a 1,000 m resolution from 2001 to 2020 using multi-source remote sensing data and a coupling coordination degree (CCD) model. Three main findings emerge. First, global CCD improved steadily from 2001 to 2020. Second, disparities between the Global North and Global South persisted but gradually narrowed, largely driven by accelerated improvements in Global South cities after 2010. Third, intra-urban patterns differed systematically: in emerging Global South cities, CCD improvements were concentrated in central areas, whereas in mature Global North cities, gains were more evident in peripheral zones. These findings indicate that urbanization–environment coordination follows distinct spatial pathways across development contexts and that city-level trends are closely associated with intra-urban spatial dynamics. By linking long-term inter-city trends with intra-urban spatial patterns, this study provides a globally consistent perspective on urbanization–environment coordination and offers implications for spatially differentiated urban planning.

Original languageEnglish
Article number2690328
JournalGIScience and Remote Sensing
Volume63
Issue number1
DOIs
StatePublished - 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  2. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Coupling coordination degree (CCD)
  • nighttime light (NTL)
  • remote sensing
  • spatiotemporal analysis
  • urban sustainable development

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