The Western Himalayan Syntaxis area is located near the Pamir Plateau. The geological structure is active and geological disasters occur frequently in this area. In this study, we employed the Google Earth platform and visual interpretation to identify ancient landslides in the region and to establish a regional ancient landslide database. Then, nine landslide-influencing factors (elevation, slope, aspect, curvature, distance to the river, distance to a glacier, lithology, distance to fault and distance to the epicenter of earthquakes above magnitude 5) were examined using ArcGIS software. The spatial distribution of landslides were analyzed statistically. Finally, an IV model and WoE model were used to evaluate the regional landslide hazard and the evaluation results were verified via a confusion matrix and a receiver operating characteristic (ROC) curve. The landslide database contained 7,947 landslides in this area with a total area of 3747.27 km2. Landslides were mostly developed at an elevation of 4,000–5,000 m, a slope of 15–25°, a north aspect, curvature of −0.33 to 0.33, distance to the water system of 1,000–2000 m, distance to a glacier of 2000–5,000 m, Permian sandstone, siltstone, argillaceous sandstone and Triassic siltstone, conglomerate and fine conglomerate, and distance to a fault of 20,000–50,000 m. The accuracy of the IV and WoE models was relatively high. The comprehensive accuracy of the confusion matrix of the two models was above 70% and the AUC value of the ROC curve was above 75%. The landslide database of the Western Himalayan Syntaxis was established and the landslide distribution and hazard assessment results can be used as a reference for landslide disaster prevention and mitigation and engineering construction planning in this area.

为了给地震区域的灾后重建和防灾减灾工作提供重要帮助,同时给类似滑坡灾害危险性评价提供参考,开展对2018年日本北海道地震的研究.2018-09-06日本北海道厚真町发生M w 6.6级地震,触发了大量山体滑坡,造成人员伤亡和重大财产损失,引发社会广泛关注.基于0.3 m空间分辨率的Pleiades-1卫星震前震后高清遥感卫星影像进行滑坡目视解译,共圈定12586处滑坡.选取高程、坡度、坡向、曲率、T PI(坡位指数)、距水系距离、距道路距离、距震中距离、地层岩性9个因子作为滑坡的影响因子.基于GIS平台,应用确定性系数(CF)模型开展北海道地震滑坡危险性评价,评价结果将研究区分为极低危险区、低危险区、中危险区、高危险区、极高危险区五类,得出滑坡危险性评价区划图,并利用ROC曲线对评价结果精度进行检验,正确率为85.3％,表明基于确定性系数模型得出的滑坡危险性评价结果与实际滑坡结果比较吻合.

The traditional coal preparation methods include the jigging coal preparation, the dry coal preparation, and the γ- ray coal preparation. Although these methods achieve the function of the coal preparation, they have some problems such as the low accuracy, the high cost, the long time-consuming, and the great health hazard. Aiming at these problems, a improved threshold recognition method is developed by using the x-ray image. First, the images of the coal and the gangue is obtained by using x-ray scanner, and then the gray values is obtained. Second, the thickness of the coal and the gangue is calculated. Third, the gray value and the thickness information of the coal and the gangue are combined, and the separation threshold is determined. Finally, the recognition of the coal and the gangue is realized. The experimental results show that the recognition accuracy can reach about 98%.