Dynamic association of slope movements in the Uttarakhand Himalaya: a critical review on the landslide susceptibility assessment

IF 4.5 3区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
Harish Khali, Kishan Singh Rawat, Rajat Subhra Chatterjee
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引用次数: 0

Abstract

Slope movement, the surface expressions as seated scars are the variety of surface deformation mechanisms on the earth’s outer crust. These slow-deformation mechanisms can be visualized easily, if in-situ geotechnical observations, GNSS synopticity (regional), and space-borne (Microwave) spatio-temporal data structured and interpreted accordingly. Globally, several techniques are adapted for the slope failure analysis and their zonation. Thus, the most directed with geospatial technologies. Wide area assessment, mapping, and monitoring are some complex tasks only possible and could be addressed with the space borne datasets. Their outcomes help users to implement area strategies viz. in susceptibility and vulnerability. Landslide Susceptibility mapping (LSM) quantify the problem very effectively. In LSM, soft computing analytical skills among various participatory and triggering factors for the application of complex models are required for ground simulation. In this article critical review of LSM over Uttarakhand Himalaya was primarily focussed which analyze various sections including- participatory/triggering factors, datasets, different models, and validation practices. The study exhibits multiple avenues and future pathways for various research windows, such as LSM-SAR refinement, orographic climatic and changing factor relationship, high-quality data coupling with drone/Unmanned Aerial Vehicle (UAV) data, etc. Such analysis implicates the cost-effectiveness of strategies in effective planning and management.
北阿坎德邦喜马拉雅地区斜坡运动的动态关联:滑坡易感性评估的重要回顾
斜坡运动,其表面表现形式为座痕,是地球外地壳表面形变机制的多种表现形式。如果对现场岩土观测、GNSS天气(区域)和星载(微波)时空数据进行相应的结构化和解释,这些缓慢变形机制就可以很容易地可视化。在全球范围内,几种技术适用于边坡破坏分析及其分区。因此,最直接的是地理空间技术。广域评估、制图和监测是一些复杂的任务,只有通过空间载数据集才能解决。其结果有助于用户实施区域战略,即易感性和脆弱性。滑坡敏感性制图(LSM)非常有效地量化了这一问题。在LSM中,对复杂模型应用的各种参与因子和触发因子的软计算分析能力是进行地面模拟的必要条件。在这篇文章中,对北阿坎德邦喜马拉雅地区的LSM进行了批判性的回顾,主要集中在分析各个部分,包括参与/触发因素、数据集、不同的模型和验证实践。该研究为不同的研究窗口展示了多种途径和未来路径,如LSM-SAR细化、地形气候和变化因子关系、高质量数据与无人机/无人机(UAV)数据的耦合等。这种分析涉及战略在有效规划和管理方面的成本效益。
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来源期刊
Geomatics Natural Hazards & Risk
Geomatics Natural Hazards & Risk GEOSCIENCES, MULTIDISCIPLINARY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
7.70
自引率
4.80%
发文量
117
审稿时长
>12 weeks
期刊介绍: The aim of Geomatics, Natural Hazards and Risk is to address new concepts, approaches and case studies using geospatial and remote sensing techniques to study monitoring, mapping, risk mitigation, risk vulnerability and early warning of natural hazards. Geomatics, Natural Hazards and Risk covers the following topics: - Remote sensing techniques - Natural hazards associated with land, ocean, atmosphere, land-ocean-atmosphere coupling and climate change - Emerging problems related to multi-hazard risk assessment, multi-vulnerability risk assessment, risk quantification and the economic aspects of hazards. - Results of findings on major natural hazards
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