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动态观测数据驱动的滑坡灾害精准模拟分析方法

朱庆,  丁雨淋,  苗双喜,  曹振宇

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文章导航 > 西南交通大学学报  > 2016 >  29(2): 396-403.
朱庆, 丁雨淋, 苗双喜, 曹振宇. 动态观测数据驱动的滑坡灾害精准模拟分析方法[J]. 西南交通大学学报, 2016, 29(2): 396-403. doi: 10.3969/j.issn.0258-2724.2016.02.019
引用本文: 朱庆, 丁雨淋, 苗双喜, 曹振宇. 动态观测数据驱动的滑坡灾害精准模拟分析方法[J]. 西南交通大学学报, 2016, 29(2): 396-403. doi: 10.3969/j.issn.0258-2724.2016.02.019
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ZHU Qing, DING Yulin, MIAO Shuangxi, CAO Zhenyu. Precise Simulation Method for Dynamic Data Driven Landslide Hazards[J]. Journal of Southwest Jiaotong University, 2016, 29(2): 396-403. doi: 10.3969/j.issn.0258-2724.2016.02.019
Citation: ZHU Qing, DING Yulin, MIAO Shuangxi, CAO Zhenyu. Precise Simulation Method for Dynamic Data Driven Landslide Hazards[J]. Journal of Southwest Jiaotong University, 2016, 29(2): 396-403. doi: 10.3969/j.issn.0258-2724.2016.02.019
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动态观测数据驱动的滑坡灾害精准模拟分析方法

doi: 10.3969/j.issn.0258-2724.2016.02.019
基金项目: 

国家自然科学基金资助项目(41471320,41501421)

国家高分专项(民用部分)重大专项资助项目(03-Y30B06-9001-13/15)

四川省测绘地理信息局科技支撑项目(J2013CX04)

详细信息
    作者简介:

    朱庆(1966-),博士,2013年起至今任职于西南交通大学,现为地球科学与环境工程学院特聘教授,博士生导师.E-mail:zhuq66@263.net;丁雨淋(1986-),女,博士,2015年起至今任职于西南交通大学,现为地球科学与环境工程学院副教授,研究方向为虚拟地理环境、地理信息系统、摄影测量. E-mail:rainforests@126.com

    朱庆(1966-),博士,2013年起至今任职于西南交通大学,现为地球科学与环境工程学院特聘教授,博士生导师.E-mail:zhuq66@263.net;丁雨淋(1986-),女,博士,2015年起至今任职于西南交通大学,现为地球科学与环境工程学院副教授,研究方向为虚拟地理环境、地理信息系统、摄影测量. E-mail:rainforests@126.com

Precise Simulation Method for Dynamic Data Driven Landslide Hazards

    摘要
  • 摘要: 受全球极端气候变化和人类活动影响,复杂滑坡灾害时空演变过程复杂,其时空演变的高突变性、高隐蔽性、高动态性,以及孕育环境的时空异质性与不确定性等十分突出,复杂地形地质条件下滑坡灾害模拟分析已经成为世界性难题.为此,本文提出动态观测数据驱动的滑坡灾害精准模拟分析方法,设计了动态数据驱动的复杂滑坡灾害精准模拟分析框架,阐释了滑坡灾害过程时空变化的显式语义描述,任务驱动的空天地一体化观测数据规划与调度,计算与存储融合的复杂滑坡灾害实时数据组织与管理,变化驱动的多源动态观测数据实时接入与自主加载,多源动态观测数据在线智能处理,复杂滑坡灾害模拟模型参数智能率定等关键技术,为滑坡灾害链的全链条防灾减灾提供科学理论支撑.

     

    Abstract: As the consequences of climate changes and human activities, precise modeling of landslide hazards in complicated topographical and geological environments has become a serious problem in the world. The cruxes of simulation of the landslides lie in the high mutability and dynamism of the spatial-temporal evolution, and the heterogeneity and uncertainty of the disaster-pregnant environment. To solve this problem, this paper proposes a novel dynamic data driven approach for the precise simulation of landslide hazards. After introducing the theoretical framework with graphic illustration, several core technologies are explained, including the explicit semantic description of landslide spatio-temporal changes, task-driven planning and scheduling of space-air-ground observational data, real-time geo-processing database engine linking calculations and storage, change driven dynamic observations injection, online multisource observational data intelligent geo-processing, and intelligent model parameter calibration. The proposed method is expected to provide a strong scientific theoretical support for the whole disaster prevention and reduction process in dealing with major landslide disasters.

     

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  • 收稿日期:  2015-10-08
  • 刊出日期:  2016-04-25

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