Estimation of urban ecosystem services value: A case study of Chengdu, Southwestern China

  • Xiaoai Dai
  • , Brian Alan Johnson
  • , Penglan Luo
  • , Kai Yang
  • , Linxin Dong
  • , Qiang Wang
  • , Chao Liu
  • , Naiwen Li
  • , Heng Lu*
  • , Lei Ma
  • , Zhengli Yang
  • , Yuanzhi Yao
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

Research on the service values of urban ecosystems is a hot topic of ecological studies in the current era of rapid urbanization. To quantitatively estimate the ecosystem service value in Chengdu, China from the perspectives of natural ecology and social ecology, the technologies of remote sensing (RS) and geographic information system (GIS) are utilized in this study to extract the land use type information from RS images of Chengdu in 2003, 2007, 2013 and 2018. Subsequently, a driver analysis of the ecosystem services of Chengdu was performed based on socioeconomic data from the last 16 years. The results indicated that: (1) from 2003 to 2018, the land utilization in Chengdu changed significantly, with the area of cultivated lands, forest lands and water decreasing remarkably, while the area of construction lands dramatically increased. (2) The ecosystem services value (ESV) of Chengdu decreased by 30.92% in the last 16 years, from CNY 2.4078 × 1010 in 2003 to CNY 1.6632 × 1010 in 2018. Based on a future simulation, the ESV is further predicted to be reduced to CNY 1.4261 × 1010 by 2033. (3) The ESV of Chengdu showed a negative correlation with the total population, the urbanization rate and the per capita GDP of the region, indicating that the ESV of the studied region was inter-coupled with the socioeconomic development and can be maintained at a high level through rationally regulating the socioeconomic structure.

Original languageEnglish
Article number207
Pages (from-to)1-24
Number of pages24
JournalRemote Sensing
Volume13
Issue number2
DOIs
StatePublished - 2 Jan 2021
Externally publishedYes

Keywords

  • Driver analysis
  • Ecology
  • Land use change
  • Remote sensing
  • Urbanization

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