Evaluation of aeolian desertification from 1975 to 2010 and its causes in northwest Shanxi Province, China.

Abstract: Efforts to control aeolian desertification in China have focused on the arid and semiarid regions. However, the direct dust emission rates, sediment characteristics and local-scale controls, as well as the measures needed to combat desertification, remain poorly understood in northwest Shanxi Province. Aeolian desertification is regarded as an obstacle to local sustainable socioeconomic development. This paper investigated changes in aeolian desertification between 1975 and 2010 on the northwestern Shanxi Plateau. In this study, remote sensing images were used to classify land suffering from aeolian desertification into four categories: light, moderate, severe, and extremely severe. To evaluate the evolution and status of aeolian desertification as well as its causes, we interpreted and analyzed Landsat multi-spectral scanner (MSS) image (acquired in 1975) and Landsat Thematic Mapper (TM) images (acquired in 1991, 2000, 2006, and 2010) as well as meteorological and socioeconomic data. Results revealed 11,866km2, 13,362km2, 14,051km2, 13,613km2, and 12,318km2 of aeolian desertified land (ADL) in the above 5 periods, respectively. The spatial dynamics and patterns showed two stages: expansion during 1975–2000 at a rate of 87.37km2 a−1, and spatial transfer of affected areas during 2000–2010 with a net decrease of 173.27km2 a−1. During the evolution of aeolian desertification, areas of moderate ADL had the greatest dynamic response (11.45%). The factors controlling ADL dynamics were analyzed from the perspectives of two groups of factors: natural factors and human activities. Our results indicated that the climate-dominated natural factors contribute greatly to the occurrence and development of ADL. However, they are not the fundamental causes of its development. The human factors are the primary and direct driving forces responsible for the increase in ADL area. More thorough quantitative analysis, with more frequent remotely sensed data is needed to assess the driving forces in more detail. [Copyright &y& Elsevier]