Xiao Yang, Luoan Yang, Hongwei Wu, Bing Guo, Xiangzhi Huang, Wenqian Zang, Yi Zhang, Rui Zhang, Guangqiang Sun, Zhen Wang, Key Laboratory of Machine Perception (MOE), Peking University [Beijing], Key Laboratory of Digital Earth Sciences, Chinese Academy of Sciences [Changchun Branch] (CAS), Key Laboratory for Computer Network of Shandong Province [Shandong Computer Science Center], Shandong Computer Science Center, Remote Sensing Application and Test Base of National Satellite Meteorology Centre, and Chinese Academy of Agricultural Mechanization Sciences (CCCME)
Under the stress of global climate change, soil wind erosion has become a major environmental issue in the Three-River Source Region (TRSR) of China. However, few large-scale studies have been conducted on soil wind erosion owing to the lack of investigational data or complex parameters. Moreover, the uncertainty and randomness in the weight determination process cannot be avoided using the traditional method. Thus, a cloud-analytic hierarchy process (cloud-AHP) model was proposed to construct a wind erosion intensity index model for the TRSR based on seven typical land surface parameters. The following results were obtained. (1) The cloud-AHP model can better eliminate the randomness and uncertainty in the weight determination process. (2) The proposed evaluation method of wind erosion intensity has better applicability in the TRSR with overall accuracy of 93%. (3) The overall wind erosion intensity in this region is moderate. The wind erosion intensity was the largest in the Yangtze River (0.55, moderate erosion) and smallest in the source region of the Lancang River (0.50, mild erosion). (4) Significant differences are observed in the influences of various vegetation types on wind erosion intensity. Bare land exhibits the highest wind erosion intensity, whereas a coniferous forest exhibits the smallest. Moreover, grassland is a key control zone of soil and water conservation because it has the largest spatial heterogeneity of internal erosion intensity. These results can provide data and technical support for preventing and controlling soil erosion and protecting the environment in the region.