Integrating susceptibility maps of multiple hazards and building exposure distribution: a case study of wildfires and floods for the province of Quang Nam, Vietnam

<p>Natural hazards have serious impacts worldwide on society, economy, and environment. In Vietnam, throughout the years, natural hazards have caused significant loss of lives as well as severe devastation to houses, crops, and transportation. This research presents a new approach to multi-haz...

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Main Authors: C. Luu, G. Forino, L. Yorke, H. Ha, Q. D. Bui, H. H. Tran, D. Q. Nguyen, H. C. Duong, M. Kervyn
Format: Article
Language:English
Published: Copernicus Publications 2024-12-01
Series:Natural Hazards and Earth System Sciences
Online Access:https://nhess.copernicus.org/articles/24/4385/2024/nhess-24-4385-2024.pdf
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author C. Luu
G. Forino
L. Yorke
H. Ha
Q. D. Bui
H. H. Tran
D. Q. Nguyen
H. C. Duong
M. Kervyn
author_facet C. Luu
G. Forino
L. Yorke
H. Ha
Q. D. Bui
H. H. Tran
D. Q. Nguyen
H. C. Duong
M. Kervyn
author_sort C. Luu
collection DOAJ
description <p>Natural hazards have serious impacts worldwide on society, economy, and environment. In Vietnam, throughout the years, natural hazards have caused significant loss of lives as well as severe devastation to houses, crops, and transportation. This research presents a new approach to multi-hazard (floods and wildfires) exposure estimates using machine learning models, Google Earth Engine, and spatial analysis tools for a typical case study in the province of Quang Nam in Central Vietnam. A geospatial database is built for multiple-hazard modeling, including an inventory of climate-related hazards (floods and wildfires), topography, geology, hydrology, climate features (temperature, rainfall, wind), land use, and building data for exposure assessment. The susceptibility of each hazard is first modeled and then integrated into a multi-hazard exposure matrix to demonstrate a hazard profiling approach to multi-hazard risk assessment. The results are explicitly illustrated for flood and wildfire hazards and the exposure of buildings. Susceptibility models using the random forest approach provide model accuracy of AUC (area under the receiver operating characteristic curve) <span class="inline-formula">=</span> 0.882 and 0.884 for floods and wildfires, respectively. The flood and wildfire hazards are combined within a semi-quantitative matrix to assess the building exposure to different hazards. Digital multi-hazard exposure maps of floods and wildfires aid the identification of areas exposed to climate-related hazards and the potential impacts of hazards. This approach can be used to inform communities and regulatory authorities on where to develop and implement long-term adaptation solutions.</p>
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spelling doaj-art-44792703c2bb4fb08e3bd2aba8dc03f52025-08-20T02:35:57ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812024-12-01244385440810.5194/nhess-24-4385-2024Integrating susceptibility maps of multiple hazards and building exposure distribution: a case study of wildfires and floods for the province of Quang Nam, VietnamC. Luu0G. Forino1L. Yorke2H. Ha3Q. D. Bui4H. H. Tran5D. Q. Nguyen6H. C. Duong7M. Kervyn8Faculty of Hydraulic Engineering, Hanoi University of Civil Engineering, Hanoi, 100000, VietnamSchool of Science, Engineering & Environment, University of Salford, Manchester, M5 4WT, UKSchool of Environmental and Natural Sciences, Bangor University, Bangor, Gwynedd, LL57 2DG, UKDepartment of Geodesy, Hanoi University of Civil Engineering, Hanoi, 100000, VietnamDepartment of Geodesy, Hanoi University of Civil Engineering, Hanoi, 100000, VietnamFaculty of Geomatics and Land Administration, Hanoi University of Mining and Geology, Hanoi, 100000, VietnamEnvironmental Chemistry and Ecotoxicology Lab, Phenikaa University, Hanoi, 12116, VietnamInstitute of Geodesy Engineering Technology, Hanoi University of Civil Engineering, Hanoi, 100000, VietnamDepartment of Geography, Vrije Universiteit Brussel, Brussels, 1050, Belgium<p>Natural hazards have serious impacts worldwide on society, economy, and environment. In Vietnam, throughout the years, natural hazards have caused significant loss of lives as well as severe devastation to houses, crops, and transportation. This research presents a new approach to multi-hazard (floods and wildfires) exposure estimates using machine learning models, Google Earth Engine, and spatial analysis tools for a typical case study in the province of Quang Nam in Central Vietnam. A geospatial database is built for multiple-hazard modeling, including an inventory of climate-related hazards (floods and wildfires), topography, geology, hydrology, climate features (temperature, rainfall, wind), land use, and building data for exposure assessment. The susceptibility of each hazard is first modeled and then integrated into a multi-hazard exposure matrix to demonstrate a hazard profiling approach to multi-hazard risk assessment. The results are explicitly illustrated for flood and wildfire hazards and the exposure of buildings. Susceptibility models using the random forest approach provide model accuracy of AUC (area under the receiver operating characteristic curve) <span class="inline-formula">=</span> 0.882 and 0.884 for floods and wildfires, respectively. The flood and wildfire hazards are combined within a semi-quantitative matrix to assess the building exposure to different hazards. Digital multi-hazard exposure maps of floods and wildfires aid the identification of areas exposed to climate-related hazards and the potential impacts of hazards. This approach can be used to inform communities and regulatory authorities on where to develop and implement long-term adaptation solutions.</p>https://nhess.copernicus.org/articles/24/4385/2024/nhess-24-4385-2024.pdf
spellingShingle C. Luu
G. Forino
L. Yorke
H. Ha
Q. D. Bui
H. H. Tran
D. Q. Nguyen
H. C. Duong
M. Kervyn
Integrating susceptibility maps of multiple hazards and building exposure distribution: a case study of wildfires and floods for the province of Quang Nam, Vietnam
Natural Hazards and Earth System Sciences
title Integrating susceptibility maps of multiple hazards and building exposure distribution: a case study of wildfires and floods for the province of Quang Nam, Vietnam
title_full Integrating susceptibility maps of multiple hazards and building exposure distribution: a case study of wildfires and floods for the province of Quang Nam, Vietnam
title_fullStr Integrating susceptibility maps of multiple hazards and building exposure distribution: a case study of wildfires and floods for the province of Quang Nam, Vietnam
title_full_unstemmed Integrating susceptibility maps of multiple hazards and building exposure distribution: a case study of wildfires and floods for the province of Quang Nam, Vietnam
title_short Integrating susceptibility maps of multiple hazards and building exposure distribution: a case study of wildfires and floods for the province of Quang Nam, Vietnam
title_sort integrating susceptibility maps of multiple hazards and building exposure distribution a case study of wildfires and floods for the province of quang nam vietnam
url https://nhess.copernicus.org/articles/24/4385/2024/nhess-24-4385-2024.pdf
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