Landslide susceptibility shows the spatial likelihood of landslide occurrence in a specific geographical area and is a relevant tool for mitigating the impact of landslides worldwide. As such, it is the subject of countless scientific studies. Many methods exist for generating a susceptibility map, mostly falling under the definition of statistical or machine learning. These models try to solve a classification problem: given a collection of spatial variables, and their combination associated with landslide presence or absence, a model should be trained, tested to reproduce the target outcome, and eventually applied to unseen data.

中文翻译：

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山体滑坡易发性分区的基准数据集和工作流


山体滑坡易感性显示了特定地理区域内发生山体滑坡的空间可能性，是减轻全球山体滑坡影响的相关工具。因此，它是无数科学研究的主题。有许多方法可以生成敏感性图，其中大多数都属于统计或机器学习的定义。这些模型试图解决分类问题：给定一组空间变量，以及它们与山体滑坡存在或不存在相关的组合，应该训练、测试模型以重现目标结果，并最终应用于看不见的数据。