A Study on the Influencing Factors of China’s Ecological Footprint Based on EEMD–GeoDetector

Abstract

Ecological footprint (EF) is used to measure the energy and resources that are consumed by human beings, and it is used to calculate the energy that ecological services can provide to determine the gap between human behavior and what the earth can tolerate so as to ensure that human activities and sustainable development fall within this range. Therefore, it is crucial to research the influencing factors of EF. In this study, the ensemble empirical mode decomposition (EEMD) method was used to decompose China’s per capita ecological footprint from 1961 to 2018 into four intrinsic mode functions (IMFs) and a residual (R) and to conduct factor detection and interaction detection on both each obtained sequence and the original sequence. In order to examine the contributing factors, 15 independent variables representing the economic, social, and environmental pillars of sustainable development were chosen. The outcome under the interaction factor is more logical than the result under the single factor. Under the interaction factor of climate, the short-term changes in the number of doctors per 1000 people, long-term population density, carbon dioxide emissions, and average life expectancy interact with each other and the trend in CO2 emissions to affect the change in ecological footprint.