| 动态数据驱动多模型耦合的滑坡稳定性分析方法 |
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| 引用本文： | 张波,唐萌萌,刘润泽.动态数据驱动多模型耦合的滑坡稳定性分析方法[J].测绘与空间地理信息,2017(6). |
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| 作者姓名： | 张波 唐萌萌 刘润泽 |
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| 作者单位： | 1. 黑龙江地理信息工程院,黑龙江哈尔滨,150081;2. 黑龙江省第五测绘地理信息工程院,黑龙江哈尔滨,150081;3. 黑龙江工业学院,黑龙江鸡西,158100 |
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| 摘 要： | 我国是一个地质灾害频发的国家,滑坡作为典型地质灾害具有时间分布上的突发性、空间分布的随机性、影响因素的复杂性的特点,受地形、地质、水文和人文因素复杂影响下的滑坡稳定性分析成为科学研究的前沿热点。传统滑坡稳定性分析基于静态的物理模型,其模型通常建立在一定的假设基础上,模型抽象,参数时变、空变,导致对滑坡稳定性分析难以满足防灾减灾的时效性、准确性需求。因此,本文提出了一种基于动态数据驱动的多模型耦合的滑坡稳定性分析方法,利用天空地一体化监测数据,建立了一套依靠动态传感数据实时驱动的地形-水文-滑坡机理耦合的滑坡稳定性分析框架,阐述了基于知识规则的监测数据智能清洗方法,数据驱动的多模态监测数据实时接入与自主加载,多模型耦合机制,监测数据与滑坡机理模型动态同化算法,从而提高了滑坡稳定性分析的时效性和准确性,变被动减灾为主动防灾。
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| 关 键 词： | 多模态监测数据 滑坡稳定性分析 多模型耦合 动态同化 |
Dynamic Data Driven Multi-model Coupled for Analyzing the Stability of Landslide |
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| ZHANG Bo,TANG Meng-meng,LIU Run-ze.Dynamic Data Driven Multi-model Coupled for Analyzing the Stability of Landslide[J].Geomatics & Spatial Information Technology,2017(6). |
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| Authors: | ZHANG Bo TANG Meng-meng LIU Run-ze |
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| Abstract: | Geological disasters occurred frequently in China,as a typical geological disaster,Sudden and randomness Landslide have the characteristic of break out suddenly in times,randomness in space and complexity of impact factor,and which are complicated impacted by topography,geology,hydrology and human factors,so Landslide stability analysis becomes hot spot of scientific research.Traditional method based on static data driven analysis method of single model,have the disadvantages of model abstraction too much,parameter varying from times and space,which is difficult to meet the timeliness,accuracy requirements of disaster prevention and mitigation.Therefore,a new approach "Dynamic Data Driven Multi-model Coupled for Analyzing the Stability of Landslide" is proposed,which include than knowledge-guided data cleaning intelligently method,data driven multimodal monitoring data real-time access and independent load,multi-model coupling mechanism and the assimilation between monitoring data and dynamic mechanism model.Attain the goal of improve the timeliness and accuracy of landslide stability analysis;shift the situation from passive disaster mitigation to active prevention of disaster mitigation. |
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| Keywords: | multimodal monitoring data the landslide stability analysis multi-model coupled dynamic assimilation |
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