基于改进鱼骨模型的岩溶塌陷区风险评价——以柳州地区为例
文章以广西柳州地区岩溶塌陷区为研究实例,对研究区岩溶塌陷的主要影响因素进行了野外实地调查和分析。考虑了鱼骨模型中各要素之间的联系以及要素断裂的分级影响,建立了断裂的分级缓冲区,进而划分了五个综合要素图层,基于改进的鱼骨模型对各影响因素矢量数据格式的要素图层进行空间叠加分析,绘制出＂柳州地区岩溶塌陷风险预测区划图＂。由区划图可知,已发现的塌陷群75%以上均落在强风险与中等风险区内,强风险区和中等风险区总分布范围约为研究区总面积的一半,主要分布在柳州地区中南部,覆盖层厚度较薄,较容易发生岩溶塌陷。已发现塌陷群25%以下分布在弱风险区以及很弱风险区内,主要分布在柳州地区的北部和西部,发生岩溶塌陷的概...
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| Published in | 中国岩溶 Vol. 34; no. 1; pp. 64 - 71 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
中国地质大学 北京,北京,100083%中国地质大学 武汉,湖北 武汉,430074
2015
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-4810 |
| DOI | 10.11932/karst20150109 |
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| Abstract | 文章以广西柳州地区岩溶塌陷区为研究实例,对研究区岩溶塌陷的主要影响因素进行了野外实地调查和分析。考虑了鱼骨模型中各要素之间的联系以及要素断裂的分级影响,建立了断裂的分级缓冲区,进而划分了五个综合要素图层,基于改进的鱼骨模型对各影响因素矢量数据格式的要素图层进行空间叠加分析,绘制出＂柳州地区岩溶塌陷风险预测区划图＂。由区划图可知,已发现的塌陷群75%以上均落在强风险与中等风险区内,强风险区和中等风险区总分布范围约为研究区总面积的一半,主要分布在柳州地区中南部,覆盖层厚度较薄,较容易发生岩溶塌陷。已发现塌陷群25%以下分布在弱风险区以及很弱风险区内,主要分布在柳州地区的北部和西部,发生岩溶塌陷的概率较小。建议城市规划和建设选择在很弱风险区和弱风险区进行。 |
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| AbstractList | P642.26; 文章以广西柳州地区岩溶塌陷区为研究实例，对研究区岩溶塌陷的主要影响因素进行了野外实地调查和分析。考虑了鱼骨模型中各要素之间的联系以及要素断裂的分级影响，建立了断裂的分级缓冲区，进而划分了五个综合要素图层，基于改进的鱼骨模型对各影响因素矢量数据格式的要素图层进行空间叠加分析，绘制出“柳州地区岩溶塌陷风险预测区划图”。由区划图可知，已发现的塌陷群75%以上均落在强风险与中等风险区内，强风险区和中等风险区总分布范围约为研究区总面积的一半，主要分布在柳州地区中南部，覆盖层厚度较薄，较容易发生岩溶塌陷。已发现塌陷群25%以下分布在弱风险区以及很弱风险区内，主要分布在柳州地区的北部和西部，发生岩溶塌陷的概率较小。建议城市规划和建设选择在很弱风险区和弱风险区进行。 文章以广西柳州地区岩溶塌陷区为研究实例,对研究区岩溶塌陷的主要影响因素进行了野外实地调查和分析。考虑了鱼骨模型中各要素之间的联系以及要素断裂的分级影响,建立了断裂的分级缓冲区,进而划分了五个综合要素图层,基于改进的鱼骨模型对各影响因素矢量数据格式的要素图层进行空间叠加分析,绘制出＂柳州地区岩溶塌陷风险预测区划图＂。由区划图可知,已发现的塌陷群75%以上均落在强风险与中等风险区内,强风险区和中等风险区总分布范围约为研究区总面积的一半,主要分布在柳州地区中南部,覆盖层厚度较薄,较容易发生岩溶塌陷。已发现塌陷群25%以下分布在弱风险区以及很弱风险区内,主要分布在柳州地区的北部和西部,发生岩溶塌陷的概率较小。建议城市规划和建设选择在很弱风险区和弱风险区进行。 |
| Abstract_FL | Taking the karst collapse area in Liuzhou of Guangxi as an example,this study conducted field in-vestigations and analysis to the major controlling and influencing factors of the karst collapse.Considering the relationship of these factors in the fish bone model and the grading influence of fractures,we established the grading buffers of fractures,and thus determined five feature layers of those comprehensive factors. Based on the improved fish bone model,we made spatial overlay analysis on the feature layers of each factor 's vector data format,and prepared a zoning map of the risk prediction.It is shown that more than 75% of the discovered collapse groups fall in the areas with a high risk or a moderate risk,which approximately ac-count for half of the total research areas and are mainly located in the central and southern portions of the study area.These areas have thin covers,and frequent karst collapse is common.Less than 25% of the dis-covered collapse groups are in the areas with a low risk or a very low risk,which are mainly distributed in the north and west of the study area.Urban planning and construction should select those areas with a low risk or a very low risk.This study has effectively predicted the risk of karst collapse in Liuzhou city. |
| Author | 崔玉良 王根厚 李志勇 |
| AuthorAffiliation | 中国地质大学（北京）,北京100083 中国地质大学（武汉）,湖北武汉430074 |
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| Author_FL | LI Zhi-yong WANG Gen-hou CUI Yu-liang |
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| DOI | 10.11932/karst20150109 |
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| DocumentTitleAlternate | Risk assessment of karst collapse areas based on the improved fish bone model： An example of the Liuzhou area in Guangxi Province |
| DocumentTitle_FL | Risk assessment of karst collapse areas based on the improved fish bone model:An example of the Liuzhou area in Guangxi Province |
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| Keywords | risk assessment of karst collapse 矢量数据 vector data spatial overlay analysis 空间叠加分析 塌陷风险评价 Liuzhou area 柳州地区 分级缓冲区 graded buffer of fracture |
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| Notes | Liuzhou area;vector data; spatial overlay analysis; graded buffer of fracture; risk assessment of karst collapse 45-1157/P CUI Yu-liang , WANG Gen-hou , LI Zhi-yong （ 1. China University of Geoscience（Beijing） ,Beijing 100083 ,china; 2. China University of Geoscience（Wuhan ）, Hubei Wuhan 430074 ,China） Taking the karst collapse area in Liuzhou of Guangxi as an example,this study conducted field investigations and analysis to the major controlling and influencing factors of the karst collapse.Considering the relationship of these factors in the fish bone model and the grading influence of fractures,we established the grading buffers of fractures,and thus determined five feature layers of those comprehensive factors.Based on the improved fish bone model,we made spatial overlay analysis on the feature layers of each factor＇s vector data format,and prepared a zoning map of the risk prediction.It is shown that more than 75% of the discovered collapse groups fall in the areas with a high risk or a moderate risk,which |
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| Publisher | 中国地质大学 北京,北京,100083%中国地质大学 武汉,湖北 武汉,430074 |
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| SubjectTerms | 分级缓冲区 塌陷风险评价 柳州地区 矢量数据 空间叠加分析 |
| Title | 基于改进鱼骨模型的岩溶塌陷区风险评价——以柳州地区为例 |
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