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Vegetation Baseline and Urbanization Development Level: Key Determinants of Long-Term Vegetation Greening in China’s Rapidly Urbanizing Region

  • Ke Zeng
  • , Mengyao Ci
  • , Shuyi Zhang
  • , Ziwen Jin
  • , Hanxin Tang
  • , Hongkai Zhu
  • , Rui Zhang
  • , Yue Wang
  • , Yiwen Zhang
  • , Min Liu*
  • *此作品的通讯作者
  • East China Normal University
  • Institute of Eco-Chongming (IEC)

科研成果: 期刊稿件文章同行评审

摘要

Urban vegetation shows significant spatial differences due to the combined effects of natural and human factors, yet fine-scale evolutionary patterns and their cross-scale feedback mechanisms remain limited. This study focuses on the Yangtze River Delta (YRD), the top economic area in China. By integrating data from multiple Landsat sensors, we built a high—resolution framework to track vegetation dynamics from 1990 to 2020. It generates annual 30-m Enhanced Vegetation Index (EVI) data and uses a new Vegetation Green—Brown Balance Index (VBI) to measure changes between greening and browning. We combined Mann-Kendall trend analysis with machine—learning based attribution analysis to look into vegetation changes across different city types and urban—rural gradients. Over 30 years, the YRD’s annual EVI increased by 0.015/10 a, with greening areas 3.07 times larger than browning. Spatially, urban centers show strong greening, while peri—urban areas experience remarkable browning. Vegetation changes showed a city-size effect: larger cities had higher browning proportions but stronger urban cores’ greening trends. Cluster analysis finds four main evolution types, showing imbalances in grey—green infrastructure allocation. Vegetation baseline in 1990 is the main factor driving the long-term trend of vegetation greenness, while socioeconomic and climate drivers have different impacts depending on city size and position on the urban—rural continuum. In areas with low urbanization levels, climate factors matter more than human factors. These multi-scale patterns challenge traditional urban greening ideas, highlighting the need for vegetation governance that adapts to specific spatial conditions and city—unique evolution paths.

源语言英语
文章编号2449
期刊Remote Sensing
17
14
DOI
出版状态已出版 - 7月 2025

联合国可持续发展目标

此成果有助于实现下列可持续发展目标:

  1. 可持续发展目标 11 - 可持续城市和社区
    可持续发展目标 11 可持续城市和社区
  2. 可持续发展目标 13 - 气候行动
    可持续发展目标 13 气候行动

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