中文摘要：

利用mathcad2001和matlab6．5软件，计算了中国1961年-2005年生态足迹和生态承载力，通过经验模态分解（EMD）方法对其进行分析，在此基础上，建立动力学模型对其未来进行预测，希望能通过对中国生态足迹动态研究，建立一个带有周期波动的动力学预测模型，为研究长时间序列的动态变化提供一个全新的研究方法。通过EMD分析后我们可以得到研究要素的不同时间尺度的演化曲线，将这些曲线看成是系统在不同时间尺度下的特解，则可以根据不同时间尺度的EMD分量的曲线够建起对应的动力模型，如趋势项一般对应于指数或线形动力方程，大尺度的周期分量一般可以对应于正弦或与余弦形式的动力方程，最后我们建立一个总的动力预测模型。研究结果表明：随着生态足迹的增大和生态承载力的减小，中国未来20年的生态赤字越来越大，由2006年的-0．932到2025年的-1.632，接近2倍，发展处于不可持续状态。经验模态分解（EMD）方法能很好的分解出生态足迹和生态承载力的波动周期，符合它们的发展规律，并用动力学预测了它们的发展态势，经拟合表明，预测的结果与实际值误差较小。这说明基于EMD的动力学预测模型是科学的。

英文摘要：

In this article, we calculated the ecological footprint and ecological carrying capacity of China from 1961 to 2005 using the empirical mode decomposition （EMD） method and constructed a dynamic model for future prediction. This approach provides a new dynamic forecasting method with cyclical fluctuations for studying long time-series. We can derive the evolution curves of different time scales with EMD, to provide a solution for the system under different time scales. Based on the different time scales, we built momentum models with the corresponding curves, for example, the general trend corresponding to the index or linear dynamic equations. The cycles of large-scale components can generally be related to the dynamic equation of the sine or cosine. We then established a general dynamic forecasting model for long time-series. The results show that EMD is better for decomposing the fluctuation cycles of ecological footprint and ecological carrying capacity, as it conforms to their development laws and accurately forecasts their development trends. The errors between forecast results and actual values are acceptably small. As China＇s ecological footprint increases and ecological carrying capacity decreases, the country＇ s ecological deficit is expected to increase from -0.932 to - 1.623 in the next twenty years. This situation represents unsustainable development, and the government should work to reduce the national ecological footprint. There are two measures the government can utilize to achieve sustainable development. They can either enhance ecological carrying capacity or reduce the consumption component of the ecological footprint. Due to the finite supply of resources and ecological services, the optimization of resource distribution and intensification should be used to improve resource use efficiency in an environmentally friendly way. At present, we should vigorously develop high-tech industries to increase productivity, control population growth, and improve consumption structure and patterns.