Assessment of Environmental Carrying Capacity Using Principal Component Analysis
Regional environmental carrying capacity (ECC) is nonlinear and spatially specific.A hierarchy index system including resources, environmental and socio-economic elements was established using an analytic hierarchy process.Principal component analysis (PCA) was used to estimate the regional size and differences of environmental carrying capacities.Main information of four principal components, i.e., carrying capacity of resources supply, carrying capacity of environmental quality, carrying capacity of social economy and carrying capacity of infrastructure construction, was extracted.The ECC evaluation value was divided into five levels of lowest carrying capacity, low carrying capacity, medium carrying capacity, high carrying capacity and highest carrying capacity, respectively.The results showed that on the whole ECC was at the medium carrying capacity level.ECC was generally highest in Guanzhong plain, followed by Loess Plateau, and was lowest in Qiba mountain.The carrying capacity of water resources and environmental quality was relatively low, and the infrastructure carrying capacity was highest among the four components.The temporal spatial variation of ECC was closely related to vulnerability of the natural resources and environment in the regions.Verification was proven that PCA was a useful tool when applied to evaluate ECC and reflect the spatial distribution of large-quantity ECC indices on a large regional scale.This study provides a basis for comprehensive understanding of resources, environment and management for regional balanced development.
Environmental Carrying Capacity Principal Component Analysis Spatial Difference Evaluation of Indicators
Yinge Liu Junhui Zhang Shaoxiong Wang Yan Wang Aling Zhao
Key Laboratory of Disaster Monitoring and Mechanism Simulating in Shaanxi Province, College of Geography and Environment,Baoji University of Arts and Sciences, Baoji, China
国际会议
桂林
英文
54-65
2018-03-23（万方平台首次上网日期，不代表论文的发表时间）