Applying the GM(1,1) model to simulate and predict the ecological footprint values of Suzhou city, China

The ecological footprint value (abbreviated as EF) is the quantitative indicator on evaluating the sustainable development status of a region. How to simulate the EF’s trend with a long-time data series has been heatedly discussed. The economic development of Suzhou, one of the most developed cities in Yangtze Delta, China, has been accelerated in the past 20 years, and it is necessary to evaluate the influence of the socioeconomic growth on local natural resources. The EF values of Suzhou from 1999 to 2018 were calculated and simulated using both the ARIMA model and the GM(1,1) model. The ARIMA model has been used in the prediction of EF values in several cases. However, the EF data series of the city consisted of white noise and could not be fitted by the ARIMA model. The GM(1,1) model, an approach forecasting nonlinear data series, was not found in the studies of the EF simulation. Through the model precision test, the GM(1,1) model introduced fit the EF data series well and was considered to be appropriate to simulate the EF values for Suzhou. The fitting performance was accurate, and the EF values of the city could be forecasted by the model in short term. With the proposed model, the ecological sustainability status of the city was analyzed.