Urban growth simulation in different scenarios using the SLEUTH model: A case study of Hefei, East China

PLoS One. 2019 Nov 7;14(11):e0224998. doi: 10.1371/journal.pone.0224998. eCollection 2019.

Abstract

As uncontrolled urban growth has increasingly challenged the sustainable use of urban land, it is critically important to model urban growth from different perspectives. Using the SLEUTH (Slope, Land use, Exclusion, Urban, Transportation, and Hill-shade) model, the historical data of Hefei in 2000, 2005, 2010, and 2015 were collected and input to simulate urban growth from 2015 to 2040. Three different urban growth scenarios were considered, namely a historical growth scenario, an urban planning growth scenario, and a land suitability growth scenario. Prediction results show that by 2040 urban built-up land would increase to 1434 km2 in the historical growth scenario, to 1190 km2 in the urban planning growth scenario, and to 1217 km2 in the land suitability growth scenario. We conclude that (1) exclusion layers without effective limits might result in unreasonable prediction of future built-up land; (2) based on the general land use map, the urban growth prediction took the governmental policies into account and could reveal the development hotspots in urban planning; and (3) the land suitability scenario prediction was the result of the trade-off between ecological land and built-up land as it used the MCR -based (minimum cumulative resistance model) land suitability assessment result. It would help to form a compact urban space and avoid excessive protection of farmland and ecological land. Findings derived from this study may provide urban planners with interesting insights on formulating urban planning strategies.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Calibration
  • China
  • City Planning*
  • Computer Simulation*
  • Geography
  • Models, Theoretical*
  • Urban Population*

Associated data

  • figshare/10.6084/m9.figshare.8024873

Grants and funding

This research was supported by the Fundamental Research Funds for the Central Universities of China, 2018ZDPY07 to LC.