Investigating Coupled Impacts of Climate Change and Socioeconomic Transformation on Desertification by Using Multitemporal Landsat Images: A Case Study in Central Xilingol, China

Abstract

A case study is conducted in Xilingol Rangeland, Inner Mongolia, China, to investigate the driving factors of temporal dynamics of desertification by using time-series Landsat images. The spectral characters of sand dunes and urban lands in the arid and semiarid grassland environments are very similar, and thus, it is hard to discriminate them with traditional image classifiers. Nine available scenes of Landsat images without cloud cover from 1985 to 2010 are chosen for the case study. An object-oriented image classification (OOIC) is developed to classify sand dunes. The classification results are assessed with the ground reference points in 1985, 2004, and 2010, the land-cover maps produced from other classifiers in literature, and Google Earth historical aerial photo archives. Second, the areas of sand dunes derived from OOIC at the nine times are extrapolated into a 26-year time-series data set from 1985 to 2010 by applying several extrapolation techniques commonly used in regional geographic studies. Afterward, six climate factors and nine socioeconomic variables during the same study period along with the sand dune area are composed into a completed data set to investigate the coupled impacts of climate change and socioeconomic transformation on the temporal dynamics of desertification. Three types of regression models (climate model, economic model, and the coupled model) are explored, respectively, to examine which factors contribute more to the desertification dynamics. The findings confirm that the desertification process in Xilingol Rangeland is very complicated although it shows a strong causal relationship with several socioeconomic factors.