Urban development trend analysis and spatial simulation based on time series remote sensing data: A case study of Jinan, China

PLoS One. 2021 Oct 7;16(10):e0257776. doi: 10.1371/journal.pone.0257776. eCollection 2021.

Abstract

Uncontrolled urban growth detracts from healthy urban development. Understanding urban development trends and predicting future urban spatial states is of great practical significance. In order to comprehensively analyze urbanization and its effect on vegetation cover, we extracted urban development trends from time series DMSP/OLS NTL and NDVI data from 2000 to 2015, using a linear model fitting method. Six urban development trend types were identified by clustering the linear model parameters. The identified trend types were found to accurately reflect the on-ground conditions and changes in the Jinan area. For example, a high-density, stable urban type was found in the city center while a stable dense vegetation type was found in the mountains to the south. The SLEUTH model was used for urban growth simulation under three scenarios built on the urban development analysis results. The simulation results project a gentle urban growth trend from 2015 to 2030, demonstrating the prospects for urban growth from the perspective of environmental protection and conservative urban development.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Cities
  • City Planning / trends
  • Cluster Analysis
  • Conservation of Natural Resources
  • Environmental Monitoring*
  • Humans
  • Linear Models
  • Remote Sensing Technology*
  • Urban Renewal / standards*
  • Urbanization / trends*

Associated data

  • figshare/10.6084/m9.figshare.14923011

Grants and funding

This work was supported by the General Program of National Natural Science Foundation of China [51878393] and scientific Research Fund of Young Teachers in Shandong Jianzhu University (X19088Z0101).