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Constructing a complete landslide inventory dataset for the 2018 monsoon disaster in Kerala, India, for land use change analysis

机译:在印度喀拉拉邦的2018年季风灾难构建完整的滑坡库存数据集,用于土地利用变更分析

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Event-based landslide inventories are important for analyzing the relationship between the intensity of the trigger (e.g., rainfall, earthquake) and the density of the landslides in a particular area as a basis for the estimation of the landslide probability and the conversion of susceptibility maps into hazard maps required for risk assessment. They are also crucial for the establishment of local rainfall thresholds that are the basis of early warning systems and for evaluating which land use and land cover changes are related to landslide occurrence. The completeness and accuracy of event-based landslide inventories are crucial aspects to derive reliable results or the above types of analyses. In this study, we generated a relatively complete landslide inventory for the 2018 monsoon landslide event in the state of Kerala, India, based on two inventories that were generated using different methods: one based on an object-based image analysis (OBIA) and the other on field surveys of damaging landslides. We used a collaborative mapping approach based on the visual interpretation of pre- and post-event high-resolution satellite images (HRSIs) available from Google Earth, adjusted the two inventories, and digitized landslides that were missed in the two inventories. The reconstructed landslide inventory database contains 4728 landslides consisting of 2477 landslides mapped by the OBIA method, 973 landslides mapped by field survey, 422 landslides mapped both by OBIA and field methods, and an additional 856 landslides mapped using the visual image (Google Earth) interpretation. The dataset is available at https://doi.org/10.17026/dans-x6c-y7x2 (van Westen, 2020). Also, the location of the landslides was adjusted, based on the image interpretation, and the initiation points were used to evaluate the land use and land cover changes as a causal factor for the 2018 monsoon landslides. A total of 45 % of the landslides that damaged buildings occurred due to cut-slope failures, while 34 % of those having an impact on roads were due to road cut-slope failures. The resulting landslide inventory is made available for further studies.
机译:基于事件的滑坡库存用于分析触发的强度(例如,降水,地震)并且在特定的区域中的滑坡的密度作为滑坡概率的估计和磁敏度测绘图的转换的基础之间的关系很重要进入风险地图需要进行风险评估。他们还建立当地的降雨阈值是预警系统的基础上的,并评估其土地利用和土地覆盖变化与滑坡的发生至关重要。完整性和基于事件的滑坡库存的准确性是至关重要的方面推导可靠的结果或上述类型的分析。在这项研究中,我们产生了在喀拉拉邦,印度国家2018年雨季山体滑坡事件一个比较完整的滑坡库存的基础上,采用不同的方法生成两个库存:根据基于对象的图像分析(OBIA)和一个破坏山体滑坡等在实地调查。我们采用了前置和后置事件的高分辨率卫星图像(HRSIs),可从谷歌地球的视觉诠释调整两个库存,以及数字化的山体滑坡错过了两个库存是协作映射方法。重建的滑坡编目数据库包含4728个滑坡包括由OBIA方法映射2477次塌方,973个滑坡映射通过实地调查,422个山体滑坡由OBIA和现场方法映射两种,和一个额外的856个滑坡使用可视化图像映射(谷歌地球)解释。该数据集可在https://doi.org/10.17026/dans-x6c-y7x2(面包车韦斯滕,2020年)。此外,山体滑坡的位置进行了调整,基于图像解释和起始点来评价土地利用和土地覆盖变化为2018年的季风滑坡的致病因素。共有的是损坏的建筑滑坡的45%发生因切口斜率故障,而那些具有在道路上的冲击的34%是由于道路切口斜率故障。产生的滑坡库存为进一步的研究提供。

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