摘要
介绍了测度可持续发展的生态足迹分析的计算方法,在此基础上提出了生态足迹和生态承载力的预测模型:在生态足迹的预测方面采用消费预测模型和人口模型相结合的方法,在生态承载力的预测方面采用地理元胞自动机和地理信息系统技术相结合的方法。以甘肃省河西走廊地区为例,采用以上模型方法计算了1995、2000年的生态足迹和生态承载力,预测了2005年的生态足迹和生态承载力,结果表明:河西走廊地区的生态足迹在逐年上升,生态承载力前5年上升后5年下降。采用该模型方法计算与预测生态足迹和生态承载力,具有快速、准确、可操作性强的特点,但预测具有一定的局限性。
In recent years the ecological footprint（EF）,originally developed by Wackernagel and Rees in the mid-1990s（Wackernagel M and Rees W,1996,1997）,has gained much attention in ecological economics.This method tracks natural resources consumption of a nation or a region and translates them into biologically productive land area,which is required to produce the resources and to assimilate the wastes.EF calculation should be based on different scales（globe,nation,region,city or individual） of consumption.And then we can compare the EF and the ecological capacity（EC） of the same scale to determine the ecological status of this scale.Most of the researchers used statistical data and models to calculate EF and EC;however,the calculation is static.Moreover,the theory and methodology of EF and EC prediction have not been developed in literature so far.This paper is one of the few quantitative studies of EF and EC predictions. In the paper,the concept,theory and method of ecological footprint are introduced which can measure the goal of sustainability.On the basis of it,the study brings forward the method of EF and EC prediction.In terms of EF prediction,the method of combining consumption model with population model is adopted while for EC prediction the method of combining geographical cellular automata with GIS is used.The above models and methods are employed to calculate EF and EC in 1995 and 2000 and predict them in 2005 in Hexi Corridor.The result shows that EF is continually increasing,and EC ascended in the anterior five years and will descend in the posterior five years.This calculation and prediction model method is characterized by accuracy,speediness and high operability but the prediction method is of limitation to a certain degree.
出处
《地理研究》
CSCD
北大核心
2007年第5期940-948,共9页
Geographical Research
基金
中国科学院知识创新工程重大项目课题(KZCX-10-09)
