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International Journal of Disaster Risk Science 2020年第3期11卷 316-332页

作者： Caroline Michellier Patrick Pigeon André Paillet Théodore Trefon Olivier Dewitte Francois Kervyn natural hazards Service Royal Museum for Central Africa3080 TervurenBelgium EDYTEM Laboratory Universite de Savoie-Mont-Blanc73376 Le Bourget du lacFrance Geodynamics and Mineral Resources Service Royal Museum for Central Africa3080 TervurenBelgium

Based on a literature review and two case studies,this article presents the difficulties inherent in the main disaster risk reduction conceptual *** method used to highlight such evidence is to compare two programs on disaster risk reduction with mainstream conceptual *** authors participated in these programs,which were confronted with the need to integrate contributions and insights from both earth and social *** analysis found that the existing main conceptual models were unable to do justice to disaster risk reduction *** finding encouraged us to critique these *** effort led us to present possible solutions to compensate for the shortcomings of current models while taking into account the contextualization and dynamics of phenomena,as well as grappling with the more explicit integration of hazards and hazard risk into model design.

关键词： Central Africa Conceptual models Disaster risk reduction natural hazards Northern French Alps

Social Vulnerability to natural hazards in Brazil

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International Journal of Disaster Risk Science 2016年第2期7卷 111-122页

作者： Beatriz Maria de Loyola Hummell Susan L.Cutter Christopher T.Emrich American Red Cross Southwest Washington ChapterHumanitarian Services hazards & Vulnerability Research Institute Department of Geography University of South Carolina

Although social vulnerability has recently gained attention in academic studies, Brazil lacks frameworks and indicators to assess it for the entire *** vulnerability highlights differences in the human capacity to prepare for, respond to, and recover from disasters. It varies over space and time, and among and between social groups, largely due to differences in socioeconomic and demographic characteristics. This article provides a social vulnerability index(SoVI~) replication study for Brazil and shows how SoVI~concepts and indicators were adapted to the country. SoVI~Brazil follows the place-based framework adopted in the Social Vulnerability Index initially developed for the United States. Using a principal component analysis(PCA), 45city-level indicators were reduced to 10 factors that explain about 67 % of the variance in the data. Clearly identified spatial patterns showed a concentration of the most socially vulnerable cities in the North and Northeast regions of Brazil, as well as the social vulnerability of metropolitan areas and state capitals in the South and Southeast *** least vulnerable cities are mainly concentrated in the inland regions of the Southeast. Although different factors contribute to the social vulnerability in each city, the overall results confirm the social and economic disparities among Brazilian’s regions and reflect a differential vulnerability to natural hazards at local to regional scales.

关键词： Brazil natural hazards Social vulnerability Social vulnerability index(SoVI)

Is multi-hazard mapping effective in assessing natural hazards and integrated watershed management?

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Geoscience Frontiers 2020年第4期11卷 1203-1217页

作者： Hamid Reza Pourghasemi Amiya Gayen Mohsen Edalat Mehrdad Zarafshar John P.Tiefenbacher Department of natural Resources and Environmental Engineering College of AgricultureShiraz University71441-65186ShirazIran Department of Geography Ballygunge Science CollegeUniversity of CalcuttaKolkataWest Bengal700019India Crop Production and Plant Breeding Department School of AgricultureShiraz University71441-65186ShirazIran natural Resources Department Fars Agricultural and Natural Resources Research and Education CenterAREEOShirazFarsIran Department of Geography Texas State UniversitySan MarcosTX78666USA

natural hazards are often studied in ***,there is a great need to examine hazards holistically to better manage the complex of threats found in any *** regions of the world have complex hazard landscapes wherein risk from individual and/or multiple extreme events is *** parts of Iran experience a complex array of natural hazards-floods,earthquakes,landslides,forest fires,subsidence,and *** effectiveness of risk mitigation is in part a function of whether the complex of hazards can be collectively considered,visualized,and *** study develops and tests individual and collective multihazard risk maps for floods,landslides,and forest fires to visualize the spatial distribution of risk in Fars Province,southern *** do this,two well-known machine-learning algorithms-SVM and MARS-are used to predict the distribution of these *** floods,landslides,and forest fires were surveyed and *** locations of occurrence of these events(individually and collectively) were randomly separated into training(70%) and testing(30%) data *** conditioning factors(for floods,landslides,and forest fires) employed to model the risk distributions are aspect,elevation,drainage density,distance from faults,geology,LULC,profile curvature,annual mean rainfall,plan curvature,distance from man-made residential structures,distance from nearest river,distance from nearest road,slope gradient,soil types,mean annual temperature,and *** outputs of the two models were assessed using receiver-operating-characteristic(ROC) curves,true-skill statistics(TSS),and the correlation and deviance values from each models for each *** areas-under-the-curves(AUC) for the MARS model prediction were 76.0%,91.2%,and 90.1% for floods,landslides,and forest fires,***,the AUCs for the SVM model were 75.5%,89.0%,and 91.5%.The TSS reveals that the MARS model was better able to predict landslide risk,but was less able to

关键词： Multi-hazard risk mapping Considering flood Landside and forest fire jointly Machine-learning algorithms

Scientific challenges of research on natural hazards and disaster risk

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Geography and Sustainability 2021年第3期2卷 216-223页

作者： Peng Cui Jianbing Peng Peijun Shi Huiming Tang Chaojun Ouyang Qiang Zou Lianyou Liu Changdong Li Yu Lei Key Laboratory of Mountain hazards and Surface Process/Institute of Mountain hazards and Environment Chinese Academy of SciencesChengdu 610041China China-Pakistan Joint Research Center on Earth Sciences CAS-HECIslamabad 45320Pakistan Department of Geological Engineering Chang’an UniversityXi’an 710054China State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal UniversityBeijing 100875China Faculty of Engineering China University of GeosciencesWuhan 430074China

As a discipline,the science of natural hazards and disaster risk aims to explain the spatial-temporal pattern,process and mechanism,emergency response and risk mitigation of natural hazards,which requires a multidisci-plinary and interdisciplinary *** the support of natural Science Finance of China(NSFC)and Chinese Academy of Sciences(CAS),in-depth research and systematic analysis on natural hazards and disaster risk were *** this paper,the state of the art in research on natural hazards is summarized from seven aspects:formation process,mechanism and dynamic of natural hazards,disaster risk assessment,forecast,monitoring and early warning,disaster mitigation,emergency treatment and rescue,risk management and post-disaster *** trends within the natural hazards and disaster risk as a discipline were identified,along with existing shortcomings and significant gaps that need to be *** paper highlighted:1)the scientific challenges including the frontier scientific issues and technological gaps on natural hazards and disaster risk dis-cipline from 2025 to 2035 in China,and 2)the proposal to develop a systemic and holistic natural hazards and disaster risk discipline.

关键词： natural hazards Disaster risk Discipline Progress Challenge Development goals

Assessment of Regional Vulnerability to natural hazards in China Using a DEA Model

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International Journal of Disaster Risk Science 2011年第2期2卷 41-48页

作者： Jianyi Huang Yi Liu Li Ma Institute of Geographic Sciences and natural Resource Research Key Laboratory of Regional Sustainable Development ModelingChinese Academy of SciencesBeijing 100101China Graduate School of the Chinese Academy of Sciences Beijing 100049China

This paper presents a new method for quantifying regional vulnerability to natural hazards in China. In recent decades, the study of vulnerability has gained a position of centrality in natural hazards research. How to quantitatively assess vulnerability has raised much interest in academia. Researchers have proposed a variety of methods for quantitative assessment. But these methods are very sensitive to weights set for subindices. As a result, analytic results are often less convincing. A model based on data envelopment analysis(DEA) is used for the assessment of regional vulnerability to natural hazards in an attempt to improve existing analytical methods. Using a regional natural disaster system framework, this article constructs an input-output DEA model for the assessment of regional vulnerability, and takes China’s mainland as a case study area. The result shows that the overall level of vulnerability to natural hazards in China's Mainland is high. The geographical pattern is that vulnerability is highest in western China, followed by diminishing vulnerability in central China, and lowest vulnerability levels in eastern China. There is a negative correlation between the level of regional vulnerability and level of regional economic development. Generally speaking, the more economically developed a region, the lower its regional vulnerability.

关键词： mainland disaster gained

Mapping Global Mortality and Affected Population Risks for Multiple natural hazards

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International Journal of Disaster Risk Science 2016年第1期7卷 54-62页

作者： Peijun Shi Xu Yang Wei Xu Jing'ai Wang State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Key Laboratory of Environmental Change and natural Disasters of Ministry of Education Beijing Normal University Academy of Disaster Reduction and Emergency Management Ministry of Civil Affairs and Ministry of Education Key Laboratory of Regional Geography Beijing Normal University

Substantial reduction in both mortality from and the number of people affected by natural hazards by2030 are two principal targets that can be measured to assess global progress toward meeting the goals of the Sendai Framework for Disaster Risk Reduction 2015–2030(SFDRR). Based on existing research of expected annual multi-hazard intensity(Mh) of 11 hazards at the 0.5° 9 0.5° grid scale in the World Atlas of natural Disaster Risk, including earthquake, volcanic eruption,landslide, flood, storm surge, tropical cyclone, sand and dust storm, drought, heat wave, cold wave, and wildfire, a vulnerability model involving Mhand GDP per capita was developed to estimate the mortality level and scale of affected populations in 2005–2015 and 2020–2030. Global mortality and affected population risks were then mapped at the 0.5° 9 0.5° grid scale and the mortality and affected population rates were ranked at the national scale. The results show that most countries can achieve the target of reducing the mortality and affected population *** with increasing rates such as Bangladesh and Madagascar, where the coping capacity for natural hazard risks cannot keep pace with the increase of Mhand the growth of exposure, should be the ‘‘hotspots' ' of concern in global disaster risk reduction. The method proposed to quantitatively calculate the mortality and affected population risks can provide scientific and technical support for assessing global and national/regional progress in achieving the outcome and goal of the SFDRR.

关键词：影响人口全球规模多危险死亡仙台框架

A typhoon-induced storm surge numerical model with GPU acceleration based on an unstructured spherical centroidal Voronoi tessellation grid

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Acta Oceanologica Sinica 2024年第3期43卷 40-47页

作者： Yuanyong Gao Fujiang Yu Cifu Fu Jianxi Dong Qiuxing Liu National Marine Environmental Forecasting Center Beijing 100081China Key Laboratory of Marine hazards Forecasting Ministry of Natural ResourcesBeijing 100081China

Storm surge is often the marine disaster that poses the greatest threat to life and property in coastal *** and timely issuance of storm surge warnings to take appropriate countermeasures is an important means to reduce storm surge-related *** surge numerical models are important for storm surge *** further improve the performance of the storm surge forecast models,we developed a numerical storm surge forecast model based on an unstructured spherical centroidal Voronoi tessellation(SCVT)*** model is based on shallow water equations in vector-invariant form,and is discretized by Arakawa C *** SCVT grid can not only better describe the coastline information but also avoid rigid transitions,and it has a better global consistency by generating high-resolution grids in the key areas through transition *** addition,the simulation speed of the model is accelerated by using the openACC-based GPU acceleration technology to meet the timeliness requirements of operational ensemble *** only takes 37 s to simulate a day in the coastal waters of *** newly developed storm surge model was applied to simulate typhoon-induced storm surges in the coastal waters of *** hindcast experiments on the selected representative typhoon-induced storm surge processes indicate that the model can reasonably simulate the distribution characteristics of storm *** simulated maximum storm surges and their occurrence times are consistent with the observed data at the representative tide gauge stations,and the mean absolute errors are 3.5 cm and 0.6 h respectively,showing high accuracy and application prospects.

关键词： typhoon-induced storm surge numerical model GPU acceleration unstructured grid spherical centroidal Voronoi tessellation(SCVT)

Exploring deep learning for landslide mapping:A comprehensive review

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China Geology 2024年第2期7卷 330-350页

作者： Zhi-qiang Yang Wen-wen Qi Chong Xu Xiao-yi Shao College of Surveying and Geo-Informatics Tongji UniversityShanghai 200092China National Institute of natural hazards Ministry of Emergency ManagementBeijing 100085China Key Laboratory of Compound and Chained natural hazards Dynamics Ministry of Emergency Management of ChinaBeijing 100085China

A detailed and accurate inventory map of landslides is crucial for quantitative hazard assessment and land *** methods relying on change detection and object-oriented approaches have been criticized for their dependence on expert knowledge and subjective *** advancements in highresolution satellite imagery,coupled with the rapid development of artificial intelligence,particularly datadriven deep learning algorithms(DL)such as convolutional neural networks(CNN),have provided rich feature indicators for landslide mapping,overcoming previous *** this review paper,77representative DL-based landslide detection methods applied in various environments over the past seven years were *** study analyzed the structures of different DL networks,discussed five main application scenarios,and assessed both the advancements and limitations of DL in geological hazard *** results indicated that the increasing number of articles per year reflects growing interest in landslide mapping by artificial intelligence,with U-Net-based structures gaining prominence due to their flexibility in feature extraction and ***,we explored the hindrances of DL in landslide hazard research based on the above research *** such as black-box operations and sample dependence persist,warranting further theoretical research and future application of DL in landslide detection.

关键词： Landslide Mapping Quantitative hazard assessment Deep learning Artificial intelligence Neural network Big data Geological hazard survery engineering

Preliminary geological interpretation of long-wavelength magnetic anomalies over China and surrounding regions

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Earth and Planetary Physics 2024年第3期8卷 445-458页

作者： Jie Wang YanYan Yang ZhiMa Zeren Jian Wang Xin Wang YuXin Luo XuHui Shen National Institute of natural hazards Ministry of Emergency Management of ChinaBeijing 100085China Key Laboratory of Compound and Chained natural hazards Dynamics Ministry of Emergency Management of ChinaBeijing 100085China School of Emergency Management Science and Engineering University of Chinese Academy of SciencesBeijing 100049China National Space Science Center Chinese Academy of SciencesBeijing 100190China

Long-wavelength(>500 km)magnetic anomalies originating in the lithosphere were first found in satellite magnetic *** to the striking magnetic anomalies around the world,the long-wavelength magnetic anomalies in China and surrounding regions are relatively *** research on each of these anomalies has been quite inadequate;their geological origins remain unclear,in particular their connection to tectonic activity in the Chinese and surrounding *** focus on six magnetic high anomalies over the(1)Tarim Basin,(2)Sichuan Basin(3)Great Xing’an Range,(4)Barmer Basin,(5)Central Myanmar Basin,and(6)Sunda and Banda Arcs,and a striking magnetic low anomaly along the southern part of the Himalayan-Tibetan *** have analyzed their geological origins by reviewing related research and by detailed comparison with geological *** tectonic backgrounds for these anomalies belong to two cases:either ancient basin basement,or subduction-collision ***,the geological origins of large-scale regional magnetic anomalies are always subject to dispute,mainly because of limited surface exposure of sources,later tectonic destruction,and superposition of multi-phase events.

关键词： long-wavelength magnetic anomaly lithospheric magnetic anomaly lithospheric magnetic field model satellite magnetic survey CSES

Mapping lineaments using Landsat 8 OLI and SRTM data;a case study of the eastern part of the Ouarzazate Basin,Morocco

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Journal of Mountain Science 2024年第3期21卷 987-1003页

作者： MOUJANE Said ALGOUTI Ahmed ALGOUTI Abdellah FARAH Abdelouahed ABOULFARAJ Abdelfatah NAFOURI Imane Geoscience Geotourism natural hazards and Remote Sensing Laboratory(2GRNT) Department of GeologyFaculty of Sciences SemlaliaUniversity of Cadi AyyadBP 239040000MarrakechMorocco

The integration of remote sensing and geographic information system(GIS)was employed in this study to delineate the structural lineaments within the eastern section of the Ouarzazate Basin,situated between the southern front of the Central High Atlas and the northern slopes of the Eastern Anti-Atlas(also known as the Saghro Massif).To achieve this objective,Landsat 8 Operational Land Imager(OLI)and Shuttle Radar Topography Mission(SRTM)data were *** Component Analysis(PCA)was computed and a directional filter was applied to the first PCA and the panchromatic band(B8).Additionally,shading was applied to the SRTM data in four directions;N0°,N45°,N90°,N135°.After removing of the non-geological linear structures,the results obtained,using the automatic extraction method,allowed us to produce a synthetic map that included 1251 lineaments with an average length of 1331 m and was dominated by NE-SW,ENE-WSW and E-W directions,***,the high lineament density is clearly noted in the Anti-Atlas(Saghro Massif)and at the level of the northern part,extending from the Ait Ibrirne to Arg-Ali Oubourk *** lineament density can always be found around the major faults affecting this *** data collected during the field investigations and from geological maps show that the major direction of the faults and structural accidents range mostly between N45°,N70°and N75°.The correlation of remote sensing results with those collected in the field shows a similarity and coincidence with each *** these results,it is possible to consider the automatic extraction method as a supplementary kind that can serve classical geology by quickly enriching it with additional *** shown in this work,this method provides more information when applied in arid areas where the fields are well outcropped.

关键词： Remote sensing GIS Landsat 8 OLI SRTM Ouarzazate Basin Central High Atlas