江南造山带东段地处安徽、浙江、江西、江苏四省交界处,地质构造运动强烈,受强降雨影响,滑坡等地质灾害频发,严重影响了人民的生产生活,因此对该区域进行滑坡灾害的空间分布研究迫在眉睫.研究以江南造山带东段为研究区域,基于前期获得的区域滑坡数据库,选取高程、坡向、距断层距离、地层岩性、距水系距离5个影响因子,对因子进行分类,分析滑坡在每个类别中的滑坡点密度及面密度,绘制各影响因素与滑坡之间的关系图并开展分析.结果表明,滑坡主要发育在高程200～800m,坡向南方向;三叠系及震旦系地层内滑坡发育较多,古近系滑坡发育较少;距水系距离越大,滑坡发育越少.研究旨在深入分析江南造山带东段滑坡的分布规律以及各因素对滑坡发生的影响,研究该类地质环境下滑坡的空间分布特点可以为该地区的工程建设选址提供重要的参考依据.

Accurate assessment of seismic landslides hazard is a prerequisite and foundation for post-disaster relief of earthquakes. An Ms 5.7 earthquake occurring on September 7, 2012, in Yiliang County, Yunnan Province, China, triggered hundreds of landslides. To explore the characteristics of coseismic landslides caused by this moderate-strong earthquake and their significance in predicting seismic landslides regionally, this study uses an artificial visual interpretation method based on a planet image with 5-m resolution to obtain the information of the coseismic landslides and establishes a coseismic landslide database containing data on 232 landslides. Nine influencing factors of landslides were selected for this study: elevation, relative elevation, slope angle, aspect, slope position, distance to river system, distance to faults, strata, and peak ground acceleration. The real probability of coseismic landslide occurrence is calculated by combining the Bayesian probability and logistic regression model. Based on the coseismic landslides, the probabilities of landslide occurrence under different peak ground acceleration are predicted using a logistic regression model. Finally, the model established in this paper is used to calculate the landslide probability of the Ludian Ms 6.5 earthquake that occurred in August 2014, 78.9 km away from the macro-epicenter of the Yiliang earthquake. The probability is verified by the real coseismic landslides of this earthquake, which confirms the reliability of the method presented in this paper. This study proves that the model established according to the seismic landslides triggered by one earthquake has a good effect on the seismic landslides hazard assessment of similar magnitude, and can provide a reference for seismic landslides prediction of moderate-strong earthquakes in this region.

From 9 to 11 August 2019, the southeast coastal areas of China were hit by Typhoon Lekima, which caused a large number of shallow landslides. The typhoon resulted in a maximum rainfall of 402 mm during 3 days in Ningguo City. In this study, satellite images were acquired before and after the rainfall and visual interpretation was used to identify 414 shallow landslides in Ningguo City, and a complete database of shallow landslides caused by the typhoon-induced rainfall in Ningguo City was created. Nine landslide-influencing factors were selected-elevation, slope, aspect, strata, distance to faults, distance to rivers, distance to roads, normalized vegetation difference index, and rainfall-and the relationships between the rainfall-induced landslide distribution and the influencing factors were analyzed. The Bayesian probability method was combined with a logistic regression model to establish a landslide probability map for the study area. The real probabilities of landslide occurrence in the study area under five different rainfall conditions were calculated, and probability maps of landslide occurrence were drawn. The results of this study provide a reference for disaster prevention and reduction of typhoon rainstorm landslides in the southeast coastal areas of China and a future basis for decision making by the Ningguo government departments before a typhoon rainstorm occurs.

2019年"利奇马"台风诱发了安徽省宁国市多处山体滑坡.为研究东南沿海地区台风暴雨滑坡的分布规律,以宁国市为例展开研究,基于降雨前后的Planet卫星影像,采用人工目视解译法在ArcGIS上获取滑坡分布.根据数字高程模型(DEM)、地质图及降雨数据提取高程、坡度、坡向、地层和降雨量共5个影响因子进行统计分析.研究结果表明:研究区面积3567 km2,解译滑坡414个,滑坡总面积1.42 km2,南部区域的滑坡点密度最大;在高程[300 m,600 m)、坡度[20°,30°)、东南坡向、地层为震旦系、降雨量[300 mm,350 mm)区间的滑坡数量最多.研究结果可为进一步研究东南地区降雨滑坡的易发性评价提供基础,也可为当地防灾减灾提供参考.