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国土资源遥感  2017, Vol. 29 Issue (s1): 27-33    DOI: 10.6046/gtzyyg.2017.s1.05
  技术方法 本期目录 | 过刊浏览 | 高级检索 |
地质灾害体遥感变化信息检测及趋势分析
何超
中国地质大学(北京)地球科学与资源学院,北京 100083
Detection of remote sensing change information and trend analysis of geological hazards
HE Chao
School of Earth Science and Resources, China University of Geosciences(Beijing), Beijing 100083, China
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摘要 北京市地质灾害发育明显,区内地质构造、地层岩性复杂、降水分布不均,且周边山区人类工程活动非常强烈,存在有大量的突发性地质灾害,极大威胁周边地区人们的生命财产安全。在充分研究遥感变化检测理论的基础上,以多源、多时相国产卫星高空间分辨率遥感数据为数据源,采用遥感技术并结合地理信息系统等其他方法手段,探索出主成分比值法变化检测方法是较适合提取研究区灾害体变化信息的有效方法。通过变化量估算和趋势分析,确定地质灾害体变化量频率及强度,以此预测其危险程度,并提出防治措施及建议。
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袁德有
袁林
关键词 初始化盲信号分解非负矩阵分解(NMF)谱线形状信息量差异    
Abstract:Because of its complicated tectonics and lithology as well as uneven distribution of the precipitation, Beijing region has developed many geological hazards. Also, there are a number of human engineering activities in the mountain area of Beijing, which will lead to sudden hazards. These sudden hazards are threatening the people and their property safety. Based on remote sensing change detection theory, the authors used the multi-source, multi-temporal domestic satellite data with high resolution to analyze the hazards in Beijing. The authors utilized the remote sensing technology in combination with other methods and means of geographic information systems to analyze the hazards. Among the methods, the authors found that the principal component ratio method is the best. The authors also established the elevation models and the time changing trends model to forecast the degree of danger of geological hazard body in the study area.
Key wordsinitialization    blind signal separation    non-negative matrix factorization(NMF)    spectral shape    information dissimilarity
收稿日期: 2017-06-01      出版日期: 2017-11-24
基金资助:中国地质调查局地质调查项目“全国自然资源遥感综合调查与信息系统建设”(编号: 121201203000160011)资助
作者简介: 何 超(1993-),男,硕士,主要从事自然资源遥感调查及监测等研究工作。Email: 394699280@qq.com。
引用本文:   
何超. 地质灾害体遥感变化信息检测及趋势分析[J]. 国土资源遥感, 2017, 29(s1): 27-33.
HE Chao. Detection of remote sensing change information and trend analysis of geological hazards. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(s1): 27-33.
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http://www.gtzyyg.com/CN/10.6046/gtzyyg.2017.s1.05      或      http://www.gtzyyg.com/CN/Y2017/V29/Is1/27
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[1] 袁德有, 袁林. 基于谱线形状与信息量差异的高光谱解混NMF初始化方法[J]. 国土资源遥感, 2017, 29(4): 114-119.
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