Open Inventories of Rainfall-Triggered Landslides

IF 2.4 3区 地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY
Rachel (Soobitsky) Vershel, Jessica Sutton, Thomas Stanley, Pukar Amatya, Dalia Kirschbaum
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引用次数: 0

Abstract

Landslide inventories support both post-event response and predictive model evaluation, but it remains challenging to create public, current, comprehensive and accurate landslide inventories. In response to this need, thousands of rainfall-triggered landslides were mapped and organised within the National Aeronautics and Space Administration's Cooperative Open-Online Landslide Repository (COOLR), which contains over 11,000 landslide reports from the Global Landslide Catalogue. Recently, 22 inventories containing thousands of rainfall-triggered landslides have been added to COOLR, which was reorganised to better accommodate large landslide inventories. All the data are available on the ‘Landslide Viewer’ web application, which also shows referenced and imported landslide inventories from other researchers. The new inventories are each connected to a landslide-triggering rainfall event, and therefore their date of occurrence was usually known. Landslide events were found by searching through credible sources or due to an external request for support during a disaster response. In either case, high-resolution imagery was utilised to digitise the landslides in the region. The resulting data can be used for various purposes, such as model training and validation. To demonstrate their potential, satellite precipitation was analysed with reference to the new inventories. The precipitation analysis highlights the potential of daily satellite precipitation estimates in areas with limited ground precipitation observations. Some of the heavy precipitation events were underestimated, but many were captured and could inform future landslide hazard assessment.

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公开的降雨引发的山体滑坡清单
滑坡清单支持事后响应和预测模型评估,但创建公开、最新、全面和准确的滑坡清单仍然具有挑战性。为了应对这一需求,美国国家航空航天局(nasa)的合作开放在线滑坡库(COOLR)对数千个由降雨引发的滑坡进行了绘制和组织,该库包含了来自全球滑坡目录的1.1万多份滑坡报告。最近,COOLR新增了22个包含数千个降雨引发的山体滑坡的库存,并对其进行了重组,以更好地容纳大型山体滑坡库存。所有数据都可以在“滑坡查看器”网络应用程序上获得,该应用程序还显示了其他研究人员引用和导入的滑坡清单。新的清单每一个都与引发山体滑坡的降雨事件有关,因此它们的发生日期通常是已知的。滑坡事件是通过搜寻可靠来源或在灾害应对过程中由于外部请求支持而发现的。在这两种情况下,都利用高分辨率图像将该地区的山体滑坡数字化。结果数据可用于各种目的,例如模型训练和验证。为了证明它们的潜力,参照新的清单分析了卫星降水。降水分析强调了在地面降水观测有限的地区每日卫星降水估计的潜力。一些强降水事件被低估了,但许多事件被捕获,可以为未来的滑坡危害评估提供信息。
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来源期刊
Geoscience Data Journal
Geoscience Data Journal GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
5.90
自引率
9.40%
发文量
35
审稿时长
4 weeks
期刊介绍: Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered. An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices. Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.
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