汶川地震滑坡遥感信息提取及灾害危险性评价研究

黄豆豆

     【中文摘要】 地震滑坡是一种常见的地震次生灾害,因其巨大的致灾力而广泛引起人们的关注。目前,单体滑坡的稳定性评价和滑坡预报研究已取得了较为深入的研究成果,但在向区域滑坡稳定性评价推广时会遇到许多困难。随着遥感和地理信息技术的发展,作为一种新的调查、监测途径和手段,在地震滑坡领域已得到广泛运用。2008年5月12日,四川省汶川县发生Ms 8.0强震,直接导致数万人死亡,数十万人受伤,同时地震诱发大量的滑坡、崩塌和泥石流等地质灾害,给当地人民带来了极大的影响。为了有效避免次生灾害对灾区造成进一步的危害,本文选取重灾区——汶川县作为研究区域,基于地震滑坡原理,利用遥感与地理信息技术,综合各种数字滑坡技术获取滑坡信息,全面分析了研究区内滑坡与各影响因子间的相关性特征,运用信息量法与逻辑回归模型进行灾害危险性评价,并对两种方法进行了比较分析,主要研究内容如下1)基于遥感数据,论述了一系列数字图像处理技术(影像融合、影像校正),研究获取影响滑坡灾害因素信息的方法,并对研究区地震滑坡特征进行分析。(2)按照指标体系所确定的指标因子进行数据采集,并按照统一的数字研究环境框架的规范进入GIS数据库,建立研究区域滑...更多坡空间数据库,包括滑坡分布数据库和滑坡因子数据库,为研究区域地质灾害预警信息系统建设提供了丰富的滑坡灾害基础数据。(3)选取高程、坡度、坡向、岩性、地震断裂、烈度以及水系因子7个评价因子,采用信息量法与逻辑回归模型进行滑坡灾害危险性评价,将研究区滑坡危险性划分为极轻度、轻度、中度、高度和极高危险五个级别,合理地反映区内滑坡灾害发育的总体特征。(4)将信息量模型与逻辑回归模型进行比较分析,发现逻辑回归法能较好地避免滑坡危险度区划研究中评价因子选择及权重赋值的主观性,具有更高的评价精度。在GIS支持下对研究区遥感影像进行解译和信息提取,获取其地震滑坡特性,获得了汶川地区一些预测和危险性分析的结果,对于该地区震后恢复重建、居民地选址、次生灾害的预警与防治等工作都有一些建设性的指导意义。

【英文摘要】 As a kind of secondary disaster caused by strong earthquake, the earthquake-induced landslide has drawn much attention in the world due to the severe hazard. Nowadays, researches on single landslides have been carried out more successfully comparing to the ones on regional landslides. To a certain degree, remote sensing and GIS, as new kinds of tools for investigation and monitor, have been used in many researches on landslide susceptibility and hazard mapping.The Ms 8.0 Wenchuan earthquake, occurred on 12 May 2008 in Sichuan Province, made a great many houses collapsed and hundreds thousand people injured. Meanwhile, damage caused by earthquake-induced landslides, collapse and debris flow became the major part of total losses. In order to remove threat from the secondary disasters effectively, this study used information value method and logistic regression, coupled with techniques of remote sensing and GIS, to generate susceptibility maps, taking the case of Wenchuan County. Main con...更多tent and production can be summarized as follows1) Based on the remote sensing data, this paper introduces the significance of digital image processing technology (e.g. data fusion and ortho-rectification), illustrates the procedures and techniques of information extraction and analyses the characteristics of earthquake-induced landslides in the research area.(2) To perform the potential analysis, it was necessary to establish spatial database of landslides containing landslides’attributes and variables contributing to landslide in the study area. The database following the unified standard of digital surrounding can provide plenty of basic data for advanced process.(3) Seven factors controlling landslide occurrence have been taken account into the susceptibility assessment, including elevation, slop, aspect, lithology, seismic intensity, distance to faults and rivers. According to the probability that predicts the possibility of landslide occurrence calculated applying information value method and logistic regression separately, the study zone was ultimately categorized into five classes, specifically,“extremely low”,“low”,“moderate”,“high”and“very high”. These results have been proved to reflect closely the spatial distributions of landslides in the study area.(4) It has been found that the predictive capability of logistic regression model appears to be more accurate comparing to information value method. It is mostly because logistic regression could reduce effectively the subjectivity in selection of evaluation factors and weight assignment.In sum, this paper extracts some information from remote sensing data, analyses the characteristic of earthquake-induced landslides under a GIS environment and accordingly generates the susceptibility maps in Wenchuan County, which undoubtedly contributes to recovered construction, location of habitation and prevention of secondary disasters in the study area.

【中文关键词】 地理信息系统; 地震; 滑坡; 危险性评价; 信息提取; 遥感
【英文关键词】 GIS; Earthquake; landslide; susceptibility assessment information extraction; remote sensing
【毕业论文目录】
摘要 4-6
ABSTRACT 6-7
图目录 11-12
表目录 12-13
第1章 绪论 13-23
    1.1 选题背景及研究意义 13-14
    1.2 国内外研究进展 14-19
        1.2.1 遥感数据获取 14-16
        1.2.2 滑坡信息提取 16-18
        1.2.3 滑坡危险性评价 18-19
    1.3 研究内容 19
    1.4 研究思路及组织结构 19-23
第2章 地震滑坡及遥感数据预处理 23-33
    2.1 滑坡概述 23-24
        2.1.1 滑坡定义 23-24
        2.1.2 滑坡的诱发因素 24
    2.2 地震滑坡特性 24-28
        2.2.1 岩体性质及结构类型 24-25
        2.2.2 地质构造条件 25-26
        2.2.3 地形地貌 26-27
        2.2.4 水文地质 27
2.2.6 降雨 28
    2.3 遥感数据预处理 28-31
        2.3.1 遥感图像选取 28-29
        2.3.2 遥感图像处理 29-31
    2.4 本章小结 31-33
第3章 汶川地震滑坡信息提取与分析 33-49
    3.1 研究区概况 33-35
        3.1.1 研究区地理位置 33-34
        3.1.2 地质环境条件 34-35
    3.2 滑坡信息提取过程 35-39
        3.2.1 数据 35-36
        3.2.2 图像处理方法 36-37
        3.2.3 基于遥感的滑坡信息提取 37-39
    3.3 滑坡分布特征解析 39-40
    3.4 滑坡影响因子提取与特征分析 40-48
        3.4.1 地形地貌因子提取与分析 40-43
        3.4.2 岩性类因子 43-44
        3.4.3 地震因子 44-47
        3.4.4 水系因子 47-48
    3.5 本章小结 48-49
第4章 汶川地震滑坡危险性评价 49-61
    4.1 基于GIS 的滑坡评价原理 49-51
        4.1.1 信息量模型 49-50
        4.1.2 Logistic 回归模型 50-51
    4.2 滑坡危险性评价流程 51-52
    4.3 基于信息量的滑坡危险性评价过程 52-57
        4.3.1 因子图层的准备 52-53
        4.3.2 各图层各类别信息量值计算 53-54
        4.3.3 图层叠加分析与分类 54-56
        4.3.4 评价结果与分析 56-57
    4.4 基于LOGISTIC 回归的滑坡危险性评价过程 57-59
        4.4.1 数据准备 57
        4.4.2 逻辑回归系数计算 57
        4.4.3 图层计算与分类 57-58
        4.4.4 评价结果与分析 58-59
    4.5 两种评价方法对比分析 59-60
    4.6 本章小结 60-61
第5章 结论与展望 61-63
    5.1 主要结论 61-62
    5.2 问题与展望 62-63
参考文献 63-67
致谢 67-68