Loess soils are characterized by metastable microstructure, high porosity and water-sensitivity. These soils have always been problematic soils and attracted attention from researchers all over the world. In the prese...Loess soils are characterized by metastable microstructure, high porosity and water-sensitivity. These soils have always been problematic soils and attracted attention from researchers all over the world. In the present study, three loess soils extracted at various depths from the Loess Plateau of China, i.e. Malan(Q_3), upper Lishi(Q_2~2) and lower Lishi(Q_2~1) loess soils, were studied. Single oedometer-collapse tests were performed on intact loess specimens to investigate the collapse behavior of three loess soils. The microstructure and chemical composition of each loess before and after collapse test were characterized using scanning electron microscopy(i.e. SEM) and energy dispersive spectroscopy(i.e. EDS) techniques. The microstructural evolution due to wetting collapse was interpreted qualitatively and quantitatively in terms of the pore morphology properties. The results suggest that:(1) the collapse potential of each loess may rise again after a round of rise and drop, which could be failure of the new-developed stable structure under quite high vertical pressure. It implies that loess may collapse even if it has collapsed.(2) Q_3, Q_2~2 and Q_2~1 loess have different types of microstructure, namely, granule, aggregate and matrix type of microstructure, respectively.(3) The microstructural evolution due to loading and wetting is observed from a granule type to an aggregate type and finally to a matrix type of structure. The variations in distributions of pore morphology properties indicate that collapse leads to a transformation of large-sized pores into small-sized pores, re-orientation and remolding of soil pores due to particle rearrangement.(4) A porous structure is essential for loess collapse; however, the non-water-stability of bonding agents promotes the occurrence of collapse under the coupling effect of loading and wetting.展开更多
Landslide hazard mapping is a fundamental tool for disaster management activities in Loess terrains. Aiming at major issues with these landslide hazard assessment methods based on Naive Bayesian classification techniq...Landslide hazard mapping is a fundamental tool for disaster management activities in Loess terrains. Aiming at major issues with these landslide hazard assessment methods based on Naive Bayesian classification technique, which is difficult in quantifying those uncertain triggering factors, the main purpose of this work is to evaluate the predictive power of landslide spatial models based on uncertain Naive Bayesian classification method in Baota district of Yan＇an city in Shaanxi province, China. Firstly, thematic maps representing various factors that are related to landslide activity were generated. Secondly, by using field data and GIS techniques, a landslide hazard map was performed. To improve the accuracy of the resulting landslide hazard map, the strategies were designed, which quantified the uncertain triggering factor to design landslide spatial models based on uncertain Naive Bayesian classification method named NBU algorithm. The accuracies of the area under relative operating characteristics curves（AUC） in NBU and Naive Bayesian algorithm are 87.29% and 82.47% respectively. Thus, NBU algorithm can be used efficiently for landslide hazard analysis and might be widely used for the prediction of various spatial events based on uncertain classification technique.展开更多
基金the National Key Research and Development Program of China (2017YFD0800501)the National Natural Science Foundation of China (Grant No. 41772323)+2 种基金the Shaanxi Science and Technology Bureau (Grant No.2016KW-030)the Geological Survey Bureau of China (DD20189270)the Key Laboratory for Geohazard in Loess Area, Ministry of Land and Resources (Grant No. KLGLAMLR201502)
文摘Loess soils are characterized by metastable microstructure, high porosity and water-sensitivity. These soils have always been problematic soils and attracted attention from researchers all over the world. In the present study, three loess soils extracted at various depths from the Loess Plateau of China, i.e. Malan(Q_3), upper Lishi(Q_2~2) and lower Lishi(Q_2~1) loess soils, were studied. Single oedometer-collapse tests were performed on intact loess specimens to investigate the collapse behavior of three loess soils. The microstructure and chemical composition of each loess before and after collapse test were characterized using scanning electron microscopy(i.e. SEM) and energy dispersive spectroscopy(i.e. EDS) techniques. The microstructural evolution due to wetting collapse was interpreted qualitatively and quantitatively in terms of the pore morphology properties. The results suggest that:(1) the collapse potential of each loess may rise again after a round of rise and drop, which could be failure of the new-developed stable structure under quite high vertical pressure. It implies that loess may collapse even if it has collapsed.(2) Q_3, Q_2~2 and Q_2~1 loess have different types of microstructure, namely, granule, aggregate and matrix type of microstructure, respectively.(3) The microstructural evolution due to loading and wetting is observed from a granule type to an aggregate type and finally to a matrix type of structure. The variations in distributions of pore morphology properties indicate that collapse leads to a transformation of large-sized pores into small-sized pores, re-orientation and remolding of soil pores due to particle rearrangement.(4) A porous structure is essential for loess collapse; however, the non-water-stability of bonding agents promotes the occurrence of collapse under the coupling effect of loading and wetting.
基金Projects(41362015,51164012) supported by the National Natural Science Foundation of ChinaProject(2012AA061901) supported by the National High-tech Research and Development Program of China
文摘Landslide hazard mapping is a fundamental tool for disaster management activities in Loess terrains. Aiming at major issues with these landslide hazard assessment methods based on Naive Bayesian classification technique, which is difficult in quantifying those uncertain triggering factors, the main purpose of this work is to evaluate the predictive power of landslide spatial models based on uncertain Naive Bayesian classification method in Baota district of Yan＇an city in Shaanxi province, China. Firstly, thematic maps representing various factors that are related to landslide activity were generated. Secondly, by using field data and GIS techniques, a landslide hazard map was performed. To improve the accuracy of the resulting landslide hazard map, the strategies were designed, which quantified the uncertain triggering factor to design landslide spatial models based on uncertain Naive Bayesian classification method named NBU algorithm. The accuracies of the area under relative operating characteristics curves（AUC） in NBU and Naive Bayesian algorithm are 87.29% and 82.47% respectively. Thus, NBU algorithm can be used efficiently for landslide hazard analysis and might be widely used for the prediction of various spatial events based on uncertain classification technique.
