Landslide Databases as Tools for Integrated Assessment of Landslide Risk

This doctoral thesis presents a novel approach to landslide risk assessment that explores the various dimensions of landslide risk in an integrated perspective. The research approach introduced here is tailored for use with landslide databases and Geographic Information Systems (GIS). A landslide su...

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Tác giả chính: Klose, Martin
Định dạng: Sách
Ngôn ngữ:English
Được phát hành: Springer 2015
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Truy cập trực tuyến:https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/59274
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spelling oai:scholar.dlu.edu.vn:DLU123456789-592742023-11-11T06:34:38Z Landslide Databases as Tools for Integrated Assessment of Landslide Risk Klose, Martin Prevention Data processing Landslides Landslide hazard analysis Risk assessment This doctoral thesis presents a novel approach to landslide risk assessment that explores the various dimensions of landslide risk in an integrated perspective. The research approach introduced here is tailored for use with landslide databases and Geographic Information Systems (GIS). A landslide susceptibility model is at the heart of this new approach, enabling to identify and delineate areas at risk of landslides and to assess infrastructure exposure. Landslide risk is a pressing societal issue that is still poorly understood. Temporal landslide hazard is derived from landslide frequency statistics and a hydrological simulation approach to estimate triggering thresholds. These methods are integrated into a powerful toolset for cost modeling that uses historical data to compile, model, and extrapolate damage costs on different spatial scales over time. The combination of this toolset with techniques to analyze fiscal cost impacts supports integrated risk assessment by quantifying the economic relevance of landslide losses. 2015-12-02T02:15:39Z 2015-12-02T02:15:39Z 2015 Book 978-3-319-20403-1 978-3-319-20402-4 https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/59274 en application/pdf Springer
institution Thư viện Trường Đại học Đà Lạt
collection Thư viện số
language English
topic Prevention
Data processing
Landslides
Landslide hazard analysis
Risk assessment
spellingShingle Prevention
Data processing
Landslides
Landslide hazard analysis
Risk assessment
Klose, Martin
Landslide Databases as Tools for Integrated Assessment of Landslide Risk
description This doctoral thesis presents a novel approach to landslide risk assessment that explores the various dimensions of landslide risk in an integrated perspective. The research approach introduced here is tailored for use with landslide databases and Geographic Information Systems (GIS). A landslide susceptibility model is at the heart of this new approach, enabling to identify and delineate areas at risk of landslides and to assess infrastructure exposure. Landslide risk is a pressing societal issue that is still poorly understood. Temporal landslide hazard is derived from landslide frequency statistics and a hydrological simulation approach to estimate triggering thresholds. These methods are integrated into a powerful toolset for cost modeling that uses historical data to compile, model, and extrapolate damage costs on different spatial scales over time. The combination of this toolset with techniques to analyze fiscal cost impacts supports integrated risk assessment by quantifying the economic relevance of landslide losses.
format Book
author Klose, Martin
author_facet Klose, Martin
author_sort Klose, Martin
title Landslide Databases as Tools for Integrated Assessment of Landslide Risk
title_short Landslide Databases as Tools for Integrated Assessment of Landslide Risk
title_full Landslide Databases as Tools for Integrated Assessment of Landslide Risk
title_fullStr Landslide Databases as Tools for Integrated Assessment of Landslide Risk
title_full_unstemmed Landslide Databases as Tools for Integrated Assessment of Landslide Risk
title_sort landslide databases as tools for integrated assessment of landslide risk
publisher Springer
publishDate 2015
url https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/59274
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