针对地质灾害隐患识别水平还不够高,灾害发生在“台账外”的问题,风险斜坡识别已成为新时代区域地质灾害调查的主要目标。基于贵州省最新地质灾害样本数据库,通过加权确定系数法(weighted coefficient of determination,CF)分析滑坡及...针对地质灾害隐患识别水平还不够高,灾害发生在“台账外”的问题,风险斜坡识别已成为新时代区域地质灾害调查的主要目标。基于贵州省最新地质灾害样本数据库,通过加权确定系数法(weighted coefficient of determination,CF)分析滑坡及崩塌的影响因子的敏感性,划分出4个危险性值域。结合专家经验,各因子影响权重排序依次为人类工程活动、斜坡结构、坡度、地下水特征、坡形、坡高。再利用层次分析法(analytic hierarchy process,AHP)获得7项影响因子的权重大小,形成了快速有效的斜坡危险性打分体系。利用历史典型点进行验证与修正并结合新增地质灾害案例,9处典型历史灾害点原始斜坡危险性与灾害的规模及灾情大小呈线性关系,满足斜坡演变趋势,4处典型风险斜坡中滑坡范围线均位于风险范围线内,变形破坏特征与指标敏感性和权重较为一致,判别结果与实际情况基本相符。通过此方法,最终完成了全省88个县域内78622个斜坡单元的风险斜坡识别,共计查出风险斜坡18196处,将其及时纳入管控对象并提出防治建议,最大限度避免突发性地质灾害发生而造成人民生命财产损失。展开更多
This study explores a comparative study of three susceptibility assessment models based on remote sensing(RS) and geographic information system(GIS). The Lenggu region(China) was selected as a case study. At first, a ...This study explores a comparative study of three susceptibility assessment models based on remote sensing(RS) and geographic information system(GIS). The Lenggu region(China) was selected as a case study. At first, a landslide inventory map was compiled using data from existing geology reports, satellite imagery, and coupling with field observations. Subsequently, three models were built to map the landslide susceptibility using analytical hierarchy process(AHP), fuzzy logic(FL) and certainty factors(CF). The resulting models were validated and compared using areas under the curve(AUC). The AUC plot estimation results indicated that the three models are promising methods for landslide susceptibility mapping. Among the three methods, CF model has highest prediction accuracy than the other two models. Similarly, the outcome of this study reveals that streams, faults, slope and elevation are the main conditioning factors of landslides. Especially, the erosion of streams plays a key role of the landslide occurrence. These landslide susceptibility maps, to some extent, reflect spatial distribution characteristics of landslides in alpine-canyon region of southwest China, and can be used for land planning and hazard risk assessment.展开更多
基金Supported by the National Natural Science Foundation of China(41602354)the Chongqing Research Program of Basic Research and Frontier Technology(2017jcyjAX0300)the Fundamental Research Funds for the Central Universities(XDJK2016B027)
文摘This study explores a comparative study of three susceptibility assessment models based on remote sensing(RS) and geographic information system(GIS). The Lenggu region(China) was selected as a case study. At first, a landslide inventory map was compiled using data from existing geology reports, satellite imagery, and coupling with field observations. Subsequently, three models were built to map the landslide susceptibility using analytical hierarchy process(AHP), fuzzy logic(FL) and certainty factors(CF). The resulting models were validated and compared using areas under the curve(AUC). The AUC plot estimation results indicated that the three models are promising methods for landslide susceptibility mapping. Among the three methods, CF model has highest prediction accuracy than the other two models. Similarly, the outcome of this study reveals that streams, faults, slope and elevation are the main conditioning factors of landslides. Especially, the erosion of streams plays a key role of the landslide occurrence. These landslide susceptibility maps, to some extent, reflect spatial distribution characteristics of landslides in alpine-canyon region of southwest China, and can be used for land planning and hazard risk assessment.
