Soil salt crust can change the structure of aeolian soil and improve its resistance to wind erosion. Four ions (Na+, Ca2+, Cl−, and SO42−) with high contents in aeolian soil were selected for a salt crust experiment. The experiment set a variety of gradients of soil salt contents and salt mixing ratios of Na2SO4 and CaCl2. The physical properties of the salt crust were tested, and the wind erosion resistance of the salt crust was discussed. The results showed that the soil salt contents and salt mixing ratio influenced the resistance of the salt crust, especially in terms of its compressive strength and toughness. The former affected the compressive strength of the salt crust by changing the amount of cemented soil salt. The latter affected the kinds of crystals by changing the ion ratio, thus changing the structure of the salt crust and affecting its wind erosion resistance. The wind erosion resistance of the salt crust is complicated by the interaction between the soil salt content and salt mixing ratio. A multilayer crust can be formed in mixed salt, which has a strong wind erosion resistance. This result provides new findings on flowing sand soil and a new method for the treatment of flowing sand soil.

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Avalanche disasters are extremely destructive and catastrophic, often causing serious casualties, economic losses and surface erosion. However, far too little attention has been paid to utilizing remote sensing mapping avalanches quickly and automatically to mitigate calamity. Such endeavors are limited by formidable natural conditions, human subjective judgement and insufficient understanding of avalanches, so they have been incomplete and inaccurate. This paper presents an objective and widely serviceable method for regional auto-detection using the scattering and interference characteristics of avalanches extracted from Sentinel-1 SLC images. Six indices are established to distinguish avalanches from surrounding undisturbed snow. The active avalanche belts in Kizilkeya and Aktep of the Western TianShan Mountains in China lend urgency to this research. Implementation found that smaller avalanches can be consistently identified more accurately in descending images. Specifically, 281 and 311 avalanches were detected in the ascending and descending of Kizilkeya, respectively. The corresponding numbers on Aktep are 104 and 114, respectively. The resolution area of single avalanche detection can reach 0.09 km2. The performance of the model was excellent in all cases (areas under the curve are 0.831 and 0.940 in descending and ascending of Kizilkeya, respectively; and 0.807 and 0.938 of Aktep, respectively). Overall, the evaluation of statistical indices are POD > 0.75, FAR < 0.34, FOM < 0.13 and TSS > 0.75. The results indicate that the performance of the innovation proposed in this paper, which employs multivariate comprehensive descriptions of avalanche characteristics to actualize regional automatic detection, can be more objective, accurate, applicable and robust to a certain extent. The latest and more complete avalanche inventory generated by this design can effectively assist in addressing the increasingly severe avalanche disasters and improving public awareness of avalanches in alpine areas.

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