five

Landslide inventory and susceptibility maps – Dominica, 2025

收藏
NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://zenodo.org/record/15182980
下载链接
链接失效反馈
官方服务:
资源简介:
Science Case Name  Multihazards in the Caribbean SIDS Dataset Name/Title Landslide inventory and susceptibility maps – Dominica, 2025  Dataset Description Landslide inventory maps for tropical storm Erika (2015) and Hurricane Maria (2017)  Key Methodologies A large-scale landslide inventory was carried out by a team from the University of Twente, using five scenes of Pléiades satellite images with resolution of 0.5m, which were obtained in September 23 and October 5 2017, made available through UNITAR-UNOSAT. Apart from these also a series of Digital Globe Images were used that were collected for the Google Crisis Response through a KML layer. The images were visually interpreted by image interpretation experts, and landslides were mapped as polygons, separating scarp, transport and accumulation areas, and classifying the landslides in types. Earlier landslide inventories were generated in the framework of the CHARIM project (http://www.charim.net/sites/default/files/handbook/maps/DOMINICA/Landslide_susceptbility_report_Dominica.pdf  ) As the basis for the landslide susceptibility assessment a data layer was generated that represents homogeneous terrain units. Initially an attempt was made to generate these automatically , using the r.slopeunits application, which generates Terrain Units using a set of parameters from a Digital Elevation Model. To compute the susceptibility, we opted for a terrain unit partition and for the implementation of statistical models, in combination with expert-based mapping. These models, learn from past events (and specifically from past landslide occurrences) to find patterns with respect to a set of predisposing factors. On the basis of these patterns a prediction is then made on the expected unstable locations in the future. To assess the susceptibility, we used a statistical model known as binomial Generalized Linear Model or Logistic Regression.  Temporal Domain The maps are generated for the current situation (2025) Spatial Domain The maps cover  the country of Dominica Key indicators Landslide locations triggered by tropical storm Erika (2015) and Hurricane Maria (2017) Landslide susceptibility classes (Very low, Low, Moderate, High, Very high).   Data format GeoTIF Source data The maps were generated by the University of Twente  Accessibility Accesible, also via https://www.paratus-geonode.eu/catalogue/uuid/e648b7cd-234a-4608-9399-7be7fe863be4  Stakeholder Relevance Identifying area affected by landslide and expected unstable area for future planning of landuse and mitigation measures Limitations/Assumptions The maps does not provide information on the actual landslide runout, and focuses on the initiation zones, based on the Geomorphological units Additional Output/Information NA Contact Information University of Twente, Cees van Westen & Luigi Lombardo
创建时间:
2025-04-10
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作