Natural environment suitability of China and its relationship with population distributions

Int J Environ Res Public Health. 2009 Dec;6(12):3025-39. doi: 10.3390/ijerph6123025. Epub 2009 Dec 1.

Abstract

The natural environment factor is one of the main indexes for evaluating human habitats, sustained economic growth and ecological health status. Based on Geographic Information System (GIS) technology and an analytic hierarchy process method, this article presents the construction of the Natural Environment Suitability Index (NESI) model of China by using natural environment data including climate, hydrology, surface configuration and ecological conditions. The NESI value is calculated in grids of 1 km by 1 km through ArcGIS. The spatial regularity of NESI is analyzed according to its spatial distribution and proportional structure. The relationship of NESI with population distribution and economic growth is also discussed by analyzing NESI results with population distribution data and GDP data in 1 km by 1 km grids. The study shows that: (1) the value of NESI is higher in the East and lower in the West in China; The best natural environment area is the Yangtze River Delta region and the worst are the northwest of Tibet and southwest of Xinjiang. (2) There is a close correlation among natural environment, population distribution and economic growth; the best natural environment area, the Yangtze River Delta region, is also the region with higher population density and richer economy. The worst natural environment areas, Northwest and Tibetan Plateau, are also regions with lower population density and poorer economies.

Keywords: GDP; GIS; NESI; natural environment; population; spatial distribution.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Conservation of Natural Resources / statistics & numerical data*
  • Demography
  • Geographic Information Systems
  • Gross Domestic Product / statistics & numerical data
  • Humans
  • Models, Statistical
  • Models, Theoretical
  • Population Growth*
  • Statistics as Topic