A comparative study of landslide susceptibility mapping using weight of evidence,logistic regression and support vector machine and evaluated by SBAS-InSAR monitoring: Zhouqu to Wudu segment in Bailong River Basin,China

The determining of landslide-prone areas in mountainous terrain is essential for land planning and hazard mitigation. In this paper, a comparative study using three statistical models including weight of evidence model (WoE), logistic regression model (LR) and support vector machine method (SVM) was undertaken in the Zhouqu to Wudu segment in the Bailong River Basin, Southern Gansu, China. Six conditionally independent environmental factors, elevation, slope, aspect, distance from fault, lithology and settlement density, were selected as the explanatory variables that may contribute to landslide occurrence based on principal component analysis (PCA) and Chi-square test. The relation between landslide distributions and these variables was analyzed using the three models and the results then used to calculate the landslide susceptibility (LS). The performance of the models was then evaluated using both the highly accurate deformation signals produced by using the Small Baseline Subset Interferometric Synthetic Aperture Radar technique and Receiver Operating Characteristic (ROC) curve. Results show more deformation points in areas with high and very high LS levels, and also more stable points in areas with low and very low LS levels for the SVM model. In addition, the SVM has larger area under the ROC curve. It indicates that the SVM has better prediction accuracy and classified ability. For the interpretability, the WoE derives the class of factors that most contributed to landsliding in the study area, and the LR reveals that factors including elevation, settlement density and distance from fault played major roles in landslide occurrence and distribution, whereas the SVM cannot provide relative weights for the variables. The outperformed SVM could be employed to determine potential landslide zones in the study area. Outcome of this research would provide preliminary basis for general land planning such as choosing new urban areas and infrastructure construction in the future, as well as for landslide hazard mitigation in Bailong River Basin.     

西藏成煤大地构造基本特征——西藏板块构造及其演化

西藏是介于古代南北大陆板块之间的过渡地带,自石炭纪以来,依次经历了前特提斯洋→古特提斯洋→特提斯洋的兴衰变迁过程:金沙江、怒江、雅鲁藏布三条缝合线分别是不同地史时期南北大陆坂块的分界线。本文总结了西藏板块构造的基本特征,论述了板块构造对西藏成煤条件的控制作用,认为西藏板块构造的特殊演化经历,是造成西藏各成煤期含煤性普遍不好的主要根源。指出昌都板片成煤条件相对较好,是西藏的主要找煤远景区。     

Coupling typhoon rainfall forecasting with overland-flow modeling for early warning of inundation

Taiwan suffers from an average of three or four typhoons annually, and the inundation caused by the heavy precipitation that is associated with typhoons frequently occurs in lowlands and floodplains. Potential inundation maps have been widely used as references to set up non-structural strategies for mitigating flood hazards. However, spatiotemporal rainfall distributions must be addressed to improve the accuracy of inundation forecasting for emergency response operations. This study presents a system for 24-h-ahead early warning of inundation, by coupling the forecasting of typhoon rainfall with the modeling of overland flow. A typhoon rainfall climatology model (TRCM) is introduced to forecast dynamically the spatiotemporal rainfall distribution based on typhoon tracks. The systematic scheme for early warning of inundation based on the spatiotemporal downscaling of rainfall and 2D overland-flow modeling yields not only the extent of inundation, but also the time to maximum inundation depth. The scheme is superior to traditional early warning method referring to the maximum extent and depth of inundation determined from conditional uniform rainfall. Analytical results show that coupling TRCM with an overland-flow model yields satisfactory inundation hydrographs for warning of the extent and peak time of inundation. This study also shows that the accuracy of forecasting spatiotemporal rainfall patterns determines the performance of inundation forecasting, which is critical to emergency response operations.     

石膏热学性质的实验研究

用差示扫描１热仪测定石膏（ＣａＳＯ＿４·２Ｈ２Ｏ）的脱水活化能；用红外光谱仪研究掺入微量Ｅｕ￣（３＋），Ｍｎ￣（２＋），Ｐｂ￣（２＋）后，在不同温度煅烧下产物的红外光谱图，并测定其热发光性质；对石膏以及掺杂后的热学性质进行了讨论。     

西藏高原大地电磁深探测———亚东—巴木错沿线地区壳幔电性结构

摘 要　 展示了超宽频带大地电磁深探测所获得的西藏亚东—巴木错沿线地区电性结构图像; 阐述了西藏中、南部特殊的壳幔电性特征。     

Investigations and assessment of the landslide hazards of Fengdu county in the reservoir region of the Three Gorges project on the Yangtze River

The spatial database of landslides in Fengdu County of the reservoir region of the Three Gorges project (TGP) on the Yangtze River was compiled from a variety of different sources including field investigations on landslides, existing catalogues and archives on landslides, reports of meteorological events and human engineering activities that triggered slope failures. The major factors that are found to have affected the slope stabilities are outlined, and an assessment and zonation of landslide hazards of the region is made using an integrated information model, which is divided into destructive, disastrous, likely disastrous and essentially non-disastrous areas from the assessment of landslide hazards. The destructive and disastrous areas are respectively 1.9 and 13.8% of the total region, mostly being nearby townships, highways along the south bank of the Yangtze River and residential quarters along two flanks of the Yangtze River and its distributaries, that will impose direct impact to highway transportation and residential lives, and may effect to some degree the navigation of the Yangtze River, reservoir banks, and building of cities and towns.     

Time–frequency characteristics and trend feature of the ENPEMF signal before Lushan $${{\varvec{M}}}_{{\varvec{w}}}$$ M w 6.6 earthquake via DE-DDTFA method

Natural Hazards - The Earth's natural pulse electromagnetic field (ENPEMF) signal, is generally considered to be a nonlinear or nonstationary signal received from our instrument, placed on the...     

The 2010 Yushu earthquake triggered landslide hazard mapping using GIS and weight of evidence modeling

The Yushu County, Qinghai Province, China, April 14, 2010, earthquake triggered thousands of landslides in a zone between 96°20′32.9″E and 97°10′8.9″E, and 32°52′6.7″N and 33°19′47.9″N. This study examines the use of geographic information system (GIS) technology and Bayesian statistics in creating a suitable landslide hazard-zone map of good predictive power. A total of 2,036 landslides were interpreted from high-resolution aerial photographs and multi-source satellite images pre- and post-earthquake, and verified by selected field checking before a final landslide-inventory map of the study area could be established using GIS software. The 2,036 landslides were randomly partitioned into two subsets: a training dataset, which contains 80 % (1,628 landslides), for training the model; and a testing dataset 20 % (408 landslides). Twelve earthquake triggered landslide associated controlling parameters, such as elevation, slope gradient, slope aspect, slope curvature, topographic position, distance from main surface ruptures, peak ground acceleration, distance from roads, normalized difference vegetation index, distance from drainages, lithology, and distance from all faults were obtained from variety of data sources. Landslide hazard indices were calculated using the weight of evidence model. The landslide hazard map was compared with training data and testing data to obtain the success rate and predictive rate of the model, respectively. The validation results showed satisfactory agreement between the hazard map and the existing landslide distribution data. The success rate is 80.607 %, and the predictive rate is 78.855 %. The resulting landslide hazard map showed five classes of landslide hazard, i.e., very high, high, moderate, low and very low. The landslide hazard evaluation map should be useful for environmental recovery planning and reconstruction work.     

Trace element and REE geochemistry of fine- and coarse-grained sands in the Ordos deserts and links with sediments in surrounding areas

In addition to mineral analyses, REE and trace element geochemical characteristics of fine- and coarse-grained sands in the Ordos deserts and other sediments in surrounding areas are investigated.Commonly the samples consist of quartz, feldspar and muscovite and less clinochlore, dolomite and ankerite. In few samples muscovite is absent.REE and trace compositions are spatially uniform for the same grain-size sands, suggesting that they could have the same sources or/and were well homogenized. However, fine- and coarse-grained sands in the Ordos deserts show different REE and trace element compositions. Fine-grained sands show higher contents of REE and trace elements than those of coarse-grained sands. They differ in Eu anomalies and (La/Yb)_N ratios although both fractions are characterized by the steep LREE and smooth HREE patterns. The fine- and coarse-grained sands are also distinct in some characteristic element ratios (e.g., Th/Co, La/Sc, Th/Sc and Y/Ni).REE and trace element patterns of the two different grain-size fractions are closely associated with geological properties of individual sources rather than the mineralogical differentiation induced by wind sorting. The coarse-grained sands mainly resulted from sandstone weathering in the Ordos deserts and movements of coarse particles by wind. REE and trace element patterns of fine-grained sands in the Ordos deserts differ from those of sandstones in the Ordos deserts, the alluvial sands in the surrounding mountains and the coarse fluvial sands in the Yellow River. They resemble the fine fluvial sands in the Yellow River. In addition, arid areas of Northwest China such as the Tarim Basin and the Alxa Plateau should not be ruled out as the source of the fine-grained sands in the Ordos deserts because these arid areas reserve plenty of fine-grained sediments and also located in the upwind directions of the Ordos deserts.