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Landslide Mitigation Informatics (LIMIT): Effective decision-making for complex landslide geohazards.

Landslide Mitigation Informatics (LIMIT): Effective decision-making for complex landslide geohazards.
滑坡缓解信息学(LIMIT):复杂滑坡地质灾害的有效决策。
批准号:
NE/T005653/1
负责人:
Michael Lim
金额:
$15.53万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --

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中文摘要
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英文摘要
Landslides or the threat of landslides can cause significant economic disruption and pose a risk to life. Relatively small events can affect wide areas, particularly where the primary road network is sparse and there is limited scope for rerouting and diversion. Rainfall triggers the majority of landslides in the U.K. and national level 24-hr forecasts exist (for emergency response agencies), but there is uncertainty surrounding what combination(s) of duration and intensity trigger slope failures on a site specific level and why similar events do not always lead to the same event/no-event outcome. These knowledge gaps are critical where decisions must actively be made to warn users of (or close) linear infrastructure such as roads and rail in order to saves lives and costs. This lack of specificity, combined with the high costs of traditionally instrumenting known 'at risk' locations, hinders effective decision-making for key authorities and their partners. As a result many essential components of the environment are not monitored in advance, or on a wide-scale / high-resolution (spatial and temporal) basis. LIMIT will make use of and develop the next generation of low-cost and low-power integrated network (and networks of networks) sensors combined with edge processing and multi-threshold trigger based streaming of key data in near real-time to allow decisions underpinned by advanced theories of failure mechanics. The result is low cost, wide coverage provision of data that analyses the state of the environment and forecasts future behaviour at higher spatial and temporal resolutions than previously possible, integrated into a seamless 'data chain' from site to decision-makers. Data and key derivations based on fundamental process science are automatically ingested/shared into a newly constructed digital environment via an intelligent hierarchical platform. The outputs are fit for national data sets and modelling; policy makers deciding on sensor networks for monitoring evolving risk due to long-term environmental changes; operational decision-makers tasked with real-time management of acute threats to life; right though to data provision and two-way engagement with the individuals at risk. Innovative low-cost, in situ near real-time data streaming/processing sensors resiliently linked to an integrated portal with automated reporting offers a viable and transformative solution to end-user challenges.The LIMIT feasibility study will generate new field validated intelligent monitoring informatics, underpinned by advanced theories of failure mechanics, to provide critical data on the increasing likelihood and then the occurrence of slope failures in real-time.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
Detection and forecasting of shallow landslides: lessons from a natural laboratory
浅层滑坡的检测和预报:自然实验室的经验教训
DOI: 10.1080/19475705.2022.2041108
发表时间: 2022
期刊: Geomatics, Natural Hazards and Risk
影响因子: --
作者: [Bainbridge R]
通讯作者: Bainbridge R
DOI: 10.3390/rs13050893
发表时间: 2021-02
期刊: Remote. Sens.
影响因子: --
作者: [Muhammad Waqas Khan;S. Dunning;Rupert Bainbridge;James Martin;A. Diaz-Moreno;H. Torun;Nanlin Jin;J. Woodward;M. Lim]
通讯作者: Muhammad Waqas Khan;S. Dunning;Rupert Bainbridge;James Martin;A. Diaz-Moreno;H. Torun;Nanlin Jin;J. Woodward;M. Lim
DOI: 10.3390/s20185107
发表时间: 2020-09-08
期刊: Sensors (Basel, Switzerland)
影响因子: --
作者: [Tsapparellas G, Jin N, Dai X, Fehringer G]
通讯作者: Fehringer G
The predictability of shallow landslides: lessons from a natural laboratory
浅层滑坡的可预测性:来自自然实验室的教训
DOI: --
发表时间: 2020
期刊: Earth ArXiv
影响因子: --
作者: [Bainbridge R]
通讯作者: Bainbridge R
Nuna: Effective mitigation and adaptation to changing ground conditions for resilient coastal futures
  • 批准号:
    NE/X005658/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $80.04万
  • 财政年份:
    2022
  • 负责人:
    Michael Lim
  • 依托单位:
IRES: Philadelphia-Singapore Optics Research Experience for Undergraduates
  • 批准号:
    1559410
  • 项目类别:
    Standard Grant
  • 资助金额:
    $22.1万
  • 财政年份:
    2016
  • 负责人:
    Michael Lim
  • 依托单位:
RUI: Characterization and Control of Electron Dynamics in an Ultracold Plasma
  • 批准号:
    0613659
  • 项目类别:
    Standard Grant
  • 资助金额:
    $18.9万
  • 财政年份:
    2006
  • 负责人:
    Michael Lim
  • 依托单位:
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