IMHE OpenIR  > 山地灾害与地表过程重点实验室
黄土滑坡灾害空间格局及其空间尺度依赖性研究
Alternative TitlePATTERN ANALYSIS OF LOESS LANDSLIDES AND THEIR SCALE DEPENDENCY
邱海军1,2,3; 胡胜1,2; 崔鹏3; 杨冬冬1,2; 许博健1,2; 朱兴华4; 何毅1,2
Corresponding Author崔鹏
2017
Source Publication第四纪研究
ISSN1001-7410
Volume37Issue:2Pages:307-318
Abstract

黄土滑坡既是黄土地区广泛分布的一种特殊的地貌成分,也是一种灾害性的地质过程。滑坡的空间格局体现了区域滑坡基本数量特征与空间属性。本文借鉴生态学中点格局分析方法即O-ring统计,利用Programita软件对黄土地区不同尺度下黄土滑坡灾害的空间分布模式与关联性开展了的研究。结果表明:1)O-ring统计能很好地分析区域滑坡的空间分布格局;2)大型滑坡对滑坡总体积有着重要的控制作用;3)最大的黄土滑坡体积概率密度出现在体积为10~5m~3附近,且概率密度曲线存在明显的偏转效应;4)区域上,滑坡的空间分布模式及其关联性具有对尺度的依赖性;5)不同规模类型区域黄土滑坡具有不同的分布模式,大型滑坡主要呈随机分布状态,而中型和小型滑坡则都表现为小空间尺度上显著的集群分布到大空间尺度上的随机分布,总体上表现为随着空间尺度的变大而聚集程度逐渐减小的趋势;6)不同规模类型黄土滑坡之间的空间关联性均呈现小空间尺度上正相关、大空间尺度上不相关或负相关的特征。在中小空间尺度上,中型与小型滑坡的空间关联性最强;但是大空间尺度上,不同规模级滑坡之间没有任何的关联性;7)大型滑坡具有自疏效应,一个大型滑坡周围一般很少会出现另外一个大型滑坡;而小型滑坡之间、小型滑坡与大型滑坡之间则存在明显的亲和性;小型滑坡一般会成群出现,或者分布在大型滑坡周围。

Other Abstract

Loess landslides are widespread on the Chinese Loess Plateau. Steep topography and frequent extreme weather conditions lead to a higher landslide susceptibility in the study area. It is well known that landslide inventory is important to investigate the landslide distribution, to determine landslide hazard and risk assessment, and to study the evolution of landscapes. So a detailed inventory of 291 loess landslides was developed through existing data sets, remote sensing image interpretation and local field surveys in Baota District (36°23' ~ 37°03'N, 109°15' ~ 109°56'E),middle reaches of the Yanhe River, Shaanxi Province, China. The study area covers an area of approximately 2222.84km~2. The elevation ranges between 814m and 1522m above sea level, with an average of 1147m. Loess landslide distributions were mapped and transferred to a GIS platform for further analysis. The overwhelming majority of loess landslides in this study area are small and medium scale landslides. The volume of individual loess landslides varies largely. Loess landslide volume spans the range from less than 10~4m~3 to more than 10~6m~3. The large and very large loess landslides determine the total landslide volume in the study area. The 10 largest loess landslides account for 26.35% of the total landslide volume, and 20 largest landslides account for 38.91% of the total landslide volume. Natural landslides exist scaling properties revealed by power law relationships. The frequency-volume distribution is important information to determine landslide hazard. So we determine the probability density of loess landslide volumes using kernel density estimation. The results indicated that there exhibits heavy tailed behavior or rollover effect for their frequency-volume distribution. These noncumulative heavy-tailed distribution is negative power law when the landslide volume is more than 1.5* 10~5m~3, with exponent 1.29. The spatial pattern shows the quantitative characteristics and spatial properties of regional landslides. However, few have focused on quantitative relationship on spatial pattern. To solve these problems, we firstly divided the loess landslides into 3 classes according to landslide volume: large, medium,and small-scale loess landslide. Moreover, the point pattern analysis method, O-ring statistics, was employed firstly to analyze the spatial patterns of regional loess landslides on the Loess Plateau of China. Using Programita software, the spatial distribution patterns and spatial associations of different spatial scale landslides are analyzed. The results indicated that the distributions of all the loess landslides show a clumped distribution when the spatial scales is less than 18km, and the distribution shows a regular or random distribution when the spatial scale is more than 18km. The distributions of large-scale loess landslides in space were not sensitivity to spatial scale. The spatial pattern of large-scale loess landslides shows a random distribution. Medium and small-scale loess landslides were characterized by the cluster in small spatial scale and random in large spatial scale respectively. The distribution of all the loess landslides shows a random pattern at the large spatial scale. The spatial associations depend on the spatial scale. There are different spatial associations on the different loess landslide types.

Keyword滑坡 空间格局 黄土 O-ring
Subject AreaP642.22 ; P694 ; P941.74
DOI10.11928/j.issn.1001-7410.2017.02.09
Indexed ByCSCD ; 北大中文核心
Language中文
CSCD IDCSCD:5944978
Funding Organization中国科学院国际合作局对外合作重点项目(批准号:131551KYSB20160002) ; 国家自然科学基金项目(批准号:41401602)和陕西省自然科学基础研究计划资助项目(批准号:2014JQ2-4021)
Citation statistics
Cited Times:10[CSCD]   [CSCD Record]
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/18685
Collection山地灾害与地表过程重点实验室
Affiliation1.西北大学城市与环境学院
2.西北大学地表系统与灾害研究院
3.中国科学院水利部成都山地灾害与环境研究所
4.长安大学地质工程与测绘学院
First Author Affilication中国科学院水利部成都山地灾害与环境研究所
Recommended Citation
GB/T 7714
邱海军,胡胜,崔鹏,等. 黄土滑坡灾害空间格局及其空间尺度依赖性研究[J]. 第四纪研究,2017,37(2):307-318.
APA 邱海军.,胡胜.,崔鹏.,杨冬冬.,许博健.,...&何毅.(2017).黄土滑坡灾害空间格局及其空间尺度依赖性研究.第四纪研究,37(2),307-318.
MLA 邱海军,et al."黄土滑坡灾害空间格局及其空间尺度依赖性研究".第四纪研究 37.2(2017):307-318.
Files in This Item:
File Name/Size DocType Version Access License
黄土滑坡灾害空间格局及其空间尺度依赖性研(2602KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Application Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[邱海军]'s Articles
[胡胜]'s Articles
[崔鹏]'s Articles
Baidu academic
Similar articles in Baidu academic
[邱海军]'s Articles
[胡胜]'s Articles
[崔鹏]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[邱海军]'s Articles
[胡胜]'s Articles
[崔鹏]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 黄土滑坡灾害空间格局及其空间尺度依赖性研究.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.