SCI期刊（影响因子4.959）《Journal of Cleaner Production》，2017, 142： 677C687

 

Exploring the factors influencing ecological land change for China's BeijingCTianjinCHebei Region using big data

谢花林^*，何亚芬，谢雪

江西财经大学江西省生态文明制度建设协同创新中心

Abstract: With the advent of big data, such data regarding the harmonious relationship of “people-land-time” have also gradually entered into the fields of natural resource management. Ecological land is one of the important natural resources and is fundamental to maintaining ecological security. Ecological land change can lead to a series of eco-environmental problems, including water shortages, soil erosion, increased drought intensity, ecosystem damage, and biodiversity loss. Based on relevant sets of big data, including spatial land data, soil data, DEM, climatic data, and socio-economic data, this study explores the factors influencing ecological land change during the period of 2000C2005 in China's BeijingCTianjinCHebei Region. The results show that the factors influencing different types of ecological land change have substantial differences. For forest land coverage change, Slope type, Soil organic matter (SOM) content, Farmer's population percentage, and Landform type are the most important independent variables. However, for grassland change, altitude, distance to the primary road and GDP per capita are the most important spatial determinants. Regarding the wetland change, farmer's population percentage, GDP per capita and altitude are the most important factors influencing wetland changes. This study indicates that natural and social-economic factors can affect ecological land change in China's BeijingCTianjinCHebei Region.

Key words: Ecological land; Big data; Logistic regression model; Land resource management