Susceptibility assessment of colluvium landslides along the Changyang section of Qingjiang River using Logistic regression and random forest methods
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摘要:
清江流域地质环境背景条件复杂,特别是沿清江库岸地质灾害频发;而过往的地质灾害易发性评价多针对行政区域范围,鲜有针对库岸带的专门评价,并且所用评价指标体系的针对性以及评价方法的可靠性仍有进一步提升的空间。为构建一套更加符合清江流域库岸带地质灾害发育特征的易发性评价指标体系,获得更加准确、适用性强的易发性区划成果,以清江流域渔峡口—资丘段为研究区,以两岸涉水斜坡体为研究对象,以斜坡单元为评价单元,构建坡度、坡向、高差、坡型、归一化植被指数、地形湿度指数、斜坡结构类型、工程地质岩组、堆积层厚度、河谷演化类型等10个指标组成的易发性评价体系;采用基于归一化确定性系数的Logistic回归和随机森林方法构建评价模型并得到不同易发性区划成果。评价结果显示:高易发区主要分布于清江干流渔峡口东—资丘东段左岸顺向斜坡体的中−下部涉水区域,且Logistic回归模型在地形地貌复杂的库岸段的适用性要优于随机森林模型。研究表明:所选堆积层厚度及河谷演化类型指标很好地代表了清江库岸段的独特地质背景条件特点;在非行政区划范围的特定研究区且当历史滑坡样本数量有限的情况下,Logistic回归模型能够较好地学习灾害发育规律并具备可靠的易发性预测能力。
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关键词:
- 堆积层滑坡 /
- Logistic回归 /
- 随机森林 /
- 易发性评价
Abstract:The geological and environmental background conditions of the Qingjiang River Basin are highly complex, particularly with frequent geological disasters along the Qingjiang reservoir bank. Previous susceptibility assessment for geological disasters was mostly focused on administrative areas and seldom specialized evaluations for the reservoir bank zone. Furthermore, there is still room for improvement in the evaluation index system, as well as in the pertinence and reliability of the evaluation method. To address these shortcomings, a more suitable susceptibility evaluation index system was constructed to obtain accurate and applicable susceptibility zoning results. The Yuxiakou to Ziqiu section of the Qingjiang River Basin was chosen as the research area, with the wading slope body on both sides of the river selected as the research object and the slope unit chosen as the evaluation unit. A susceptibility evaluation system composed of ten indicators, including slope, aspect, elevation range, slope type, NDVI, TWI, slope structure type, engineering geological rock formation, accumulation thickness, and valley evolution, was constructed.The logistic regression and random forest methods were used to construct the evaluation model based on the normalized certain factors, and different susceptibility zoning results were obtained. According to the evaluation results, the high-prone areas were mainly distributed in the middle to lower water wading areas of the left bank from the east of Yuxiakou to the east of Ziqiu, along the main stream of the Qingjiang River. The logistic regression model showed better applicability in the reservoir-bank section with complex topography and landforms. The research revealed that the accumulation thickness and valley evolution indicators were effective in representing the unique geological background conditions of the Qingjiang reservoir bank. The logistic regression model was able to learn the developmental law of disasters and has a reliable susceptibility prediction ability.
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Key words:
- accumulation thickness /
- Logistic regression /
- random forest /
- susceptibility assessment
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表 1 评价指标来源及处理方式
Table 1. Sources and processing methods of the evaluation indicators
评价指标 来源 数据类型 子类划分方式说明 坡度 5mDEM(栅格) 连续型 (1)归一化植被指数、地形湿度指数:用K-means聚类法将指标分为5个子类区间
(2)堆积层厚度:由野外实测堆积层点数据通过经验贝叶斯克里金法插值为面数据,用K-means聚类法分为5个子类区间
(3)工程地质岩组分为6个子类区间:Ⅱ-1(坚硬−较坚硬碎屑岩)、Ⅱ-4(较坚硬碎屑岩)、Ⅲ-1(坚硬碳酸盐岩)、Ⅲ-2(坚硬碳酸盐岩夹碎屑岩)、Ⅲ-3(较坚硬碳酸盐岩)、Ⅲ-4(较坚硬碳酸盐岩夹碎屑岩)
(4)斜坡结构类型分为4个:顺向坡、斜向坡、横向坡、逆向坡
(5)河谷演化类型分为2个:迁移性河谷、持续性河谷
(6)坡向分为8个:北-东北-东-东南-南-西南-西-西北
(7)坡型分为3个:凸形坡、平直坡、凹形坡高差 5mDEM(栅格) 连续型 归一化植被指数 Landsat8-OLT(栅格) 连续型 地形湿度指数 5mDEM(栅格) 连续型 距断层距离 线数据(矢量) 连续型 堆积层厚度 点数据(矢量) 连续型 工程地质岩组 面数据(矢量) 分类型 斜坡结构类型 面数据(矢量) 分类型 河谷演化类型 面数据(矢量) 分类型 坡向 5mDEM(栅格) 分类型 坡型 5mDEM(栅格) 分类型 -
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