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Using Google Earth software as a platform, this study has established an integrated database of both old and new landslides in Baoshan City, Yunnan Province, China, and analyzed their development characteristics together with distribution rules, respectively. Based on the results, a total of 2 427 landslides occurred in the study area, including 2 144 new landslides and 283 old landslides, with a total area of about 104.8 km2. The new landslides are mostly in small-scales with an area less than 10 000 m2, while the area of individual old landslide is mostly larger than 10 000 m2. By analyzing the relationship between the two types of landslides and eight impact factors (i.e., elevation, slope angle, slope aspect, slope position, lithology, fault, regional Peak Ground Acceleration (PGA), and average annual rainfall), the different individual influencing factors, distribution regularities and mechanisms of the two types of landslides are revealed. In detail, the main influencing factors of new landslides are elevation, slope angle, slope aspect, slope position, lithology, regional PGA and average annual rainfall, while the influencing factors of old landslides are mainly elevation, slope angle, and lithology. This study provides basic data and support for landslide assessment and further disaster reduction in Baoshan City. Besides, it also provides new constraints in deeply understanding the effect of different topographic and geological conditions, historical earthquakes, rainfall and other factors on the occurrence mechanisms of both new landslides and old landslides.  相似文献
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An MW6.6 earthquake occurred in eastern Hokkaido, Japan on September 6th, 2018. Based on the pre-earthquake image from Google Earth and the post-earthquake image from high resolution (3 m) planet satellite, we manually interpret 9 293 coseismic landslides and select 7 influencing factors of seismic landslide, such as elevation, slope, slope direction, road distance, flow distance, peak ground acceleration (PGA) and lithology. Then, 9 293 landslide points are randomly divided into training samples and validation samples with a proportion of 7:3. In detail, the training sample has 6 505 landslide points and the validation sample has 2 788 landslide points. The hazard risk assessment of seismic landslide is conducted by using the information value method and the study area is further divided into five risk grades, including very low risk area, low risk area, moderate risk area high risk area and very high risk area. The results show that there are 7 576 landslides in high risk area and very high risk area, accounting for 81.52% of the total landslide number, and the landslide area is 22.93 km2, accounting for 74.35% of the total area. The hazard zoning is in high accordance with the actual situation. The evaluation results are tested by using the curve of cumulative percentage of hazardous area and cumulative percentage of landslides number. The results show that the success rate of the information value method is 78.50% and the prediction rate is 78.43%. The evaluation results are satisfactory, indicating that the hazard risk assessment results based on information value method may provide scientific reference for landslide hazard risk assessment as well as the disaster prevention and mitigation in the study area.  相似文献
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