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首页> 外文期刊>Natural hazards and earth system sciences >Application of a fast and efficient algorithm to assess landslide-prone areas in sensitive clays in Sweden
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Application of a fast and efficient algorithm to assess landslide-prone areas in sensitive clays in Sweden

机译：快速有效算法在瑞典敏感粘土中易滑坡地区的评估中的应用

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We refine and test an algorithm for landslide susceptibility assessment inareas with sensitive clays. The algorithm uses soil data and digitalelevation models to identify areas which may be prone to landslides and hasbeen applied in Sweden for several years. The algorithm is verycomputationally efficient and includes an intelligent filtering procedure foridentifying and removing small-scale artifacts in the hazard maps produced.Where information on bedrock depth is available, this can be included in theanalysis, as can information on several soil-type-based cross-sectional anglethresholds for slip. We evaluate how processing choices such as of filteringparameters, local cross-sectional angle thresholds, and inclusion of bedrockdepth information affect model performance. The specific cross-sectionalangle thresholds used were derived by analyzing the relationship betweenlandslide scarps and the quick-clay susceptibility index (QCSI). We testedthe algorithm in the G?ta River valley. Several different verificationmeasures were used to compare results with observed landslides and therebyidentify the optimal algorithm parameters. Our results show that even thougha relationship between the cross-sectional angle threshold and the QCSI couldbe established, no significant improvement of the overall modelingperformance could be achieved by using these geographically specific,soil-based thresholds. Our results indicate that lowering the cross-sectionalangle threshold from 1 : 10 (the general value used in Sweden) to 1 : 13improves results slightly. We also show that an application of the automaticfiltering procedure that removes areas initially classified as prone tolandslides not only removes artifacts and makes the maps visually moreappealing, but it also improves the model performance.
机译：我们优化和测试了一种在敏感粘土区域进行滑坡敏感性评估的算法。该算法使用土壤数据和数字高程模型来识别可能容易发生滑坡的区域，并且已经在瑞典应用了数年。该算法在计算上非常有效，并且包括用于识别和消除所生成灾害图中的小规模伪影的智能过滤程序。在可以获得基岩深度的信息的地方，可以将其包括在分析中，以及基于几种基于土壤类型的十字路口的信息也可以包括在内。断面的角度阈值。我们评估诸如过滤参数，局部横截面角度阈值和基岩深度信息等处理选择如何影响模型性能。通过分析滑坡陡坡与快速黏土磁化率指数（QCSI）之间的关系，得出所用的特定横截面角阈值。我们在Gta河谷测试了该算法。几种不同的验证方法被用来将结果与观测到的滑坡进行比较，从而确定最佳算法参数。我们的结果表明，即使可以建立横截面角度阈值和QCSI之间的关系，使用这些基于地理的特定土壤阈值也无法显着改善整体建模性能。我们的结果表明，将横截面角阈值从1:10（瑞典使用的通用值）降低到1:13可以稍微改善结果。我们还显示了自动过滤程序的应用程序，该程序可以删除最初归类为易发生滑坡的区域，不仅可以删除人工痕迹并使地图在视觉上更具吸引力，而且还可以改善模型性能。

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