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1.
In the context of disaster risk management and in particular for improving preparedness and mitigation of potential impacts, information on socioeconomic characteristics including aspects of situation-specific human exposure and vulnerability is considered vital. This paper provides an overview on available multi-level geospatial information and modeling approaches from global to local scales that could serve as inventory for people involved in disaster-related areas. Concepts and applications related to the human exposure and social vulnerability domains are addressed by illustrating the varying dimensions and contextual implications. Datasets and methods are highlighted that can be applied to assess earthquake-related population exposure, ranging from global and continental-scale population grids (with a focus on recent developments for Europe) to high-resolution functional urban system models and space–time variation aspects. In a further step, the paper elaborates on the integration of social structure on regional scale and the development of aggregative social and economic vulnerability indicators which would eventually enable the differentiation of situation-specific risk patterns. The presented studies cover social vulnerability mapping for selected US federal states in the New Madrid seismic zone as well as the advancement of social vulnerability analysis through integration of additional economic features in the index construction by means of a case study for Turkey’s provinces.  相似文献   

2.
Geospatial technologies and digital data have developed and disseminated rapidly in conjunction with increasing computing efficiency and Internet availability. The ability to store and transmit large datasets has encouraged the development of national infrastructure datasets in geospatial formats. National datasets are used by numerous agencies for analysis and modeling purposes because these datasets are standardized and considered to be of acceptable accuracy for national scale applications. At Oak Ridge National Laboratory a population model has been developed that incorporates national schools data as one of the model inputs. This paper evaluates spatial and attribute inaccuracies present within two national school datasets, Tele Atlas North America and National Center of Education Statistics (NCES). Schools are an important component of the population model, because they are spatially dense clusters of vulnerable populations. It is therefore essential to validate the quality of school input data. Schools were also chosen since a validated schools dataset was produced in geospatial format for Philadelphia County; thereby enabling a comparison between a local dataset and the national datasets. Analyses found the national datasets are not standardized and incomplete, containing 76 to 90 percent of existing schools. The temporal accuracy of updating annual enrollment values resulted in 89 percent inaccuracy for 2003. Spatial rectification was required for 87 percent of NCES points, of which 58 percent of the errors were attributed to the geocoding process. Lastly, it was found that by combining the two national datasets, the resultant dataset provided a more useful and accurate solution.  相似文献   

3.
Interoperability is becoming essential for the today’s geographic information systems. Geographic information is usually available as datasets stored in databases and accessible via GIS. However, these information sources are increasingly heterogeneous and show differences in data formats, database schema and object concepts. To satisfy the increased demand for the use and sharing of geographic data in common applications, considering the heterogeneity and the methods to support interoperability are required by the GIS community. The implementation of Spatial Data Infrastructure (SDI) such as the European INSPIRE (Infrastructure for Spatial Information in the European Community) enables accessibility and the sharing of geographic data and interoperability among the systems. In addition to this, traditional GIS systems perform spatial queries using a keyword-based method. However, this approach remains incapable of fully expressing the users' needs due to a lack of geographic concepts (semantics) in the dataset. Different terms may refer to similar concepts, while the same terms may refer to different concepts. This causes semantic heterogeneity in the dataset. In this context, the most promising approach is the implementation of geospatial semantics by means of ontology in the geospatial dataset to overcome this kind of ambiguity. The aim of this research is to investigate the implementation of INSPIRE as a SDI standard and the use of Semantic Technology to empower the traditional GIS approach. In this regard, a public transportation geoportal has been developed for the experimental investigation which uses a revised sample transportation data complaint with the INSPIRE Transport Network Data Theme and a developed Transportation Ontology Domain, including concepts, relationships and individuals to provide a semantic spatial search.  相似文献   

4.
Floods and associated landslides account for the largest number of natural disasters and affect more people than any other type of natural disaster. With the availability of satellite rainfall analyses at fine time and space resolution, it has also become possible to mitigate such hazards on a near-global basis. In this article, a framework to detect floods and landslides related to heavy rain events in near-real-time is proposed. Key components of the framework are: a fine resolution precipitation acquisition system; a comprehensive land surface database; a hydrological modeling component; and landslide and debris flow model components. A key precipitation input dataset for the integrated applications is the NASA TRMM-based multi-satellite precipitation estimates. This dataset provides near real-time precipitation at a spatial-temporal resolution of 3 h and 0.25° × 0.25°. In combination with global land surface datasets it is now possible to expand regional hazard modeling components into a global identification/monitoring system for flood/landslide disaster preparedness and mitigation.  相似文献   

5.
Attaining fire-adapted human communities has become a key focus of collaborative planning on landscapes across the western United States and elsewhere. The coupling of fire simulation with GIS has expanded the analytical base to support such planning efforts, particularly through the “fireshed” concept that identifies areas where wildfires could ignite and reach a human community. Previous research has identified mismatches in scale between localized community wildfire planning and the broader fireshed considering patterns of wildfire activity across landscapes. Here we expand upon this work by investigating the degree to which alternative geospatial characterizations of human communities could influence assessment of community exposure and characterization of the fireshed. We use three methods of mapping human communities (point, raster, and polygon) and develop three fireshed metrics (size, number of fires reaching houses, and number of houses exposed), and apply this analytical framework on a 2.3 million ha case study landscape encompassing the Sierra National Forest in California, USA. We simulated fire occurrence and growth using FSim for 10,000 iterations (fire seasons) at 180-m resolution. The simulation resulted in 3.9 large fires per million ha per year, with a mean size of 3432 ha. Results exhibit similarities and differences in how exposure is quantified, specifically indicating that polygons representing recognized community boundaries led to the lowest exposure levels. These results highlight how choice of the mapping approach could lead to misestimating the scope of the problem or targeting mitigation efforts in the wrong areas, and underscore the importance of clarity and spatial fidelity in geospatial data representing communities at risk.  相似文献   

6.
Spatially enabled bushfire recovery   总被引：1，自引：0，他引：1  
Over the last decade growth in spatial information use for disaster management has been considerable. Maps and spatial data are now recognized as critical elements in each of the four phases of disaster management: mitigation, preparedness, response, and recovery. The use of spatial information to support the phases of mitigation, preparedness and response to bushfires is widely understood. Less attention, however, has been given to the role of spatial information in the recovery. Moreover, the application of the spatially enabled society concept to bushfire recovery has not been explored. This paper explores the role that spatial information plays and could play in the recovery phase of a bushfire disaster. The bushfires in Victoria, Australia that took place during February 2009 are used as the primary case study. It is found that: Spatial information for recovery requires a pre-existing infrastructure; Spatial capacity must be developed across agencies dealing with recovery; Spatially enabled address and parcel information are the key dataset required to support all recovery tasks; Spatial integration of bushfire datasets (spread and intensity) require linking with planning regimes, and Spatial information that is volunteered could be incorporated into recovery activities.  相似文献   

7.

Disaster mitigation as a pre-disaster measure within the scope of disaster risk management is significant in the sense of reducing the adverse effects of earthquakes in the context of earthquake-sensitive risk planning. In the urban planning context, the existence of numerous decision makers and alternatives, which are depending on many criteria, makes decision-making process difficult. This difficulty was overcomed through geographical information systems (GIS). In the context of GIS-based multicriteria decision-making (MCDM) analysis, we used analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) to determine earthquake-risky areas in Yalova City Center. First, AHP analysis related to geological and superstructure/infrastructure criteria was conducted and two separate AHP maps were obtained. Then, we conducted TOPSIS analysis to consider both criteria in the sense of earthquake risk-sensitive planning. Then, overall earthquake risk map obtained which could be used as an input for disaster mitigation processes.

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8.
The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related losses.In this study,we applied two novel deep learning algorithms,the recurrent neural network(RNN)and convolutional neural network(CNN),for national-scale landslide susceptibility mapping of Iran.We prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors(altitude,slope degree,profile curvature,distance to river,aspect,plan curvature,distance to road,distance to fault,rainfall,geology and land-sue)to construct a geospatial database and divided the data into the training and the testing dataset.We then developed RNN and CNN algorithms to generate landslide susceptibility maps of Iran using the training dataset.We calculated the receiver operating characteristic(ROC)curve and used the area under the curve(AUC)for the quantitative evaluation of the landslide susceptibility maps using the testing dataset.Better performance in both the training and testing phases was provided by the RNN algorithm(AUC=0.88)than by the CNN algorithm(AUC=0.85).Finally,we calculated areas of susceptibility for each province and found that 6%and 14%of the land area of Iran is very highly and highly susceptible to future landslide events,respectively,with the highest susceptibility in Chaharmahal and Bakhtiari Province(33.8%).About 31%of cities of Iran are located in areas with high and very high landslide susceptibility.The results of the present study will be useful for the development of landslide hazard mitigation strategies.  相似文献   

9.
Typhoon disaster in China: prediction,prevention, and mitigation   总被引：4，自引：1，他引：3  
Typhoon-induced disaster is one of the most important factors influencing the economic development and more than 250 million in China. In view of the existing state of typhoon disaster prediction, prevention, and mitigation, this paper proposes a new probability model, Multivariate Compound Extreme Value Distribution (MCEVD), to predict typhoon-induced extreme disaster events. This model establishes prevention criteria for coastal areas, offshore structures, and estuarine cities, and provides an appropriate mitigation scheme for disaster risk management and decision-making.  相似文献   

10.
The paper examined the concept of development in line with the role of geospatial technology applications in governance and geospatial management in Nigeria. It also evaluates the previous efforts made by successive governments in managing governance process through geospatial technology initiatives using Lagos State as a proof-of-concept. It empirically demonstrates the role of monitoring spatial development initiatives using Landsat multi-dates satellite images 1985, 1990, 1995, 2000, 5005, 2010 and 2016 and Geographic Information System technique. The paper then identified, mapped and examined the settlement growth of Lagos using Ikorodu Division as an empirical proof-of-concept. The study reveals a geometric increase in uncoordinated human activities resulting from sporadic spatial development (builtup area) from 27.67 sq km (7.7%) in 1985–313.02 sq km (87.3%) spatial coverage in 2016. Based on the regression line, the study reveals a strong correlation between increasing settlement development and time. Low level of community involvement and lack of sense of ownership of development project initiatives in developing a local “vision” and strategy are identified as a problem. The paper re-emphasized that sustaining democratic processes as well as the fight against poverty will be won or lost mostly in the rural and less in the urban areas. The rural area is home to about 70% of the world’s poor due to lack or inadequate government services and basic amenities. The study suggest that making the future better for the yet unborn requires appreciable fundamental dataset, technologies, human resources and reliable government structures.  相似文献   

11.
Gridded population distribution data are finding increasing use in a wide range of fields, including resource allocation, disease burden estimation and climate change impact assessment. Land cover information can be used in combination with detailed settlement extents to redistribute aggregated census counts to improve the accuracy of national-scale gridded population data. In East Africa, such analyses have been done using regional land cover data, thus restricting application of the approach to this region. If gridded population data are to be improved across Africa, an alternative, consistent and comparable source of land cover data is required. Here these analyses were repeated for Kenya using four continent-wide land cover datasets combined with detailed settlement extents and accuracies were assessed against detailed census data. The aim was to identify the large area land cover dataset that, combined with detailed settlement extents, produce the most accurate population distribution data. The effectiveness of the population distribution modelling procedures in the absence of high resolution census data was evaluated, as was the extrapolation ability of population densities between different regions. Results showed that the use of the GlobCover dataset refined with detailed settlement extents provided significantly more accurate gridded population data compared to the use of refined AVHRR-derived, MODIS-derived and GLC2000 land cover datasets. This study supports the hypothesis that land cover information is important for improving population distribution model accuracies, particularly in countries where only coarse resolution census data are available. Obtaining high resolution census data must however remain the priority. With its higher spatial resolution and its more recent data acquisition, the GlobCover dataset was found as the most valuable resource to use in combination with detailed settlement extents for the production of gridded population datasets across large areas.  相似文献   

12.
Flood hazards are the most destructive among all natural disasters and are a constant threat to human’s life and property. Effective disaster risk reduction strategies can be improved by geospatial approach in the way of producing information and knowledge that are useful to plan truly effective actions for the protection from floods. This research aims to develop a quantified predictive model of flood susceptibility in the Ghatal and Tamluk subdivision of Medinipur district of West Bengal, India, by means of empirically selected and weighted spatial predictors of flood. The weighted prediction model is used to quantify the spatial associations between individual geospatial factors within the flood inundated study area. Yule’s coefficient and distance distribution analysis are used to assign weights to individual geo-factors, and finally weighted spatial predictors are integrated to a multi-class index overlay analysis to derive the spatially explicit predictive model of flood susceptibility. The resultant susceptibility model reveals that approximately 32.35 and 52.99% of the total study areas (3261.45 km2) are under the category of high-to-moderate flood susceptible zone. Quantitative results of this study could be integrated into the policy process in the formulation of local and national government plans for the future flood mitigation management and also to develop appropriate infrastructure in order to protect the lives and properties of the common people of the Medinipur district.  相似文献   

13.
Wang  Qian  Zhang  Qi-peng  Liu  Yang-yang  Tong  Lin-jing  Zhang  Yan-zhen  Li  Xiao-yu  Li  Jian-long 《Natural Hazards》2020,100(1):3-15

Natural disaster vulnerability can intuitively reflect the susceptibility of an area to environmental changes. Better understanding the spatial distribution of natural disaster vulnerability is a critical process for taking effective adaptation and management. Although significant achievements have been made in disaster vulnerability, few studies are known about natural disaster vulnerability at the national scale, especially from the typical natural disaster events in China. In this study, with normalizing selected indicators and calculating vulnerability index, we analyzed the spatial distribution of natural disasters vulnerability during 2010–2017 using the geospatial techniques. The results showed that natural disaster vulnerability has certain spatial differences, but different natural disaster can occur in the same area during the study period. Drought disaster can occur in all regions of China, especially in Inner Mongolia. Flood disaster is mainly concentrated in the middle and lower reaches of the Yangtze River and the Yellow River Basin. The wind and storm disaster is chiefly in the northern regions in China. The freezing disaster is widely distributed in China. Furthermore, the regions with low vulnerability were primarily distributed in the eastern coastal region, indicating that the rapid development of economy and technology can resist or mitigate natural disaster to a certain extent. This study offers a solution to study natural disasters and provides scientific basis for disaster prevention and mitigation actions.

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14.
This article explores whether past exposure to debris flow disasters with a human dimension (e.g. caused in part by deforestation) results in adaptive hazard mitigation and improved environmental and resource management practices in affected areas. When guiding hazard mitigation practice, the ‘adaptive hazard mitigation’ approach views mitigation as a multi-dimensional experiment, with the associated need for post-experiment monitoring, evaluation, learning and adjustment, and attention paid to multiple scales (Bogardi 2004). This article explores how the concept of ‘adaptive hazard mitigation’ has emerged, linking this ‘adaptive management’ used increasingly in resource and environmental management. Two case studies of disasters linked to human-induced environmental change are examined, and the mitigation responses of local communities, NGOs and Government agencies are documented. Data sources include secondary data (journal articles, web-based disaster reports and grey literature) on each disaster, key informant interviews (n = 8) and direct observation over the 2005–2006 period of post-disaster mitigation actions implemented after each disaster. The research indicates that in both case studies, a limited range of hazard mitigation actions was employed, including both structural and non-structural approaches. However, the research also found that causal factors involving human-induced environmental change (e.g. deforestation) were not addressed, and overall, the hazard mitigation strategies adopted lacked monitoring, learning and adjustment. In both case studies, responses to disaster were judged to be examples of ‘trial and error’ adaptation, rather than either ‘passive’ or ‘active’ adaptation.
Brent DobersteinEmail:
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15.
Haque  C. Emdad 《Natural Hazards》2003,29(3):465-483
The regions of East and South Asia, and the Pacific Islands are among the most-hazardprone areas in the world. Because of this, during the last century, most of the humancasualties of `natural-triggered' disasters have taken place in this region. This circumstance therefore has become a major global humanitarian concern. Another major concern, specifically for the donor agencies, is the damage sustained by infrastructure resulting from environmental disasters. These recurrent loses take away a significant proportion of the cumulative economic gains accrued from development investments over many years.Stepwise multiple regression results substantiated the fact that many of the socio-economic and demographic variables significantly influence disaster-related deaths and injuries in this part of the world. A comparative temporal analysis has shown that, over the past two decades, demographic variables have become prominent predictors of disaster-loss in South, Southeast and East Asian and the Pacific states.Many countries of the region are lagging behind in understanding and recognizing thebroader scope of disaster mitigation and management. Emerging needs and awarenessamong the decision-makers and the general public, however, have prompted institutionsin many countries to initiate a critical review of the prevailing approaches. Thecountry-specific disaster-management capacities and needs in the region vary widely.There are many differences in historical courses, institutional and administrative settings, sociocultural characteristics, as well as political and economic systems. Development of a common institutional framework for the region, therefore, seems unfeasible. Based upon a regional review, it has become clear that the research calls for improving the understanding of the significance of disaster mitigation and management in light of sustainable development and the emerging global issues. In addition, aspects of human resource development to enhance institutional mitigation and response capacities are emphasized.  相似文献   

16.
Transboundary hazard risk reflects how different societies interact with disaster in a shared landscape. In the Gobi desert of northern China and southern Mongolia recurring drought, extreme cold, wind and dust storms are the dominant hazards yet disasters vary significantly in the two countries. Research examined national approaches to environmental engagement and livelihoods in the desert through an assessment of disaster risk in two Gobi communities; farmers in Gansu Province, China, and herders in Dundgov and Omnogov Provinces, Mongolia. Exposure and resilience was evaluated and work examined how risk factors are shaped by policy, economics, culture and social memory. Comparison between two state systems reveals how disaster risk and vulnerability are shaped as much by human action as by the physical climatic event. China stressed government-led disaster management whilst Mongolia emphasised adaptation to hazards. Integrating multiple divisions within a hazard zone is essential to address risk reduction; without this disaster mitigation remains state-specific and lacks applicability to a wider area or global context.  相似文献   

17.
强震区城市地质灾害风险管理的研究内容与方法探讨   总被引：3，自引：0，他引：3  
地质灾害风险管理是一种寻求更加合理有效的地质灾害减灾防灾的理念和模式。随着山区城市化进程的加快,经济和人口在城市的相对聚集,加之强烈地震活动,使得山区城市面临风险不断地提高。研究强震城市风险管理,已成为当前城市防灾减灾工作的一项重大课题。本文概述了国内外研究进展,提出该研究方向的主要研究内容和研究方法。未来研究内容应该包括（1）强震区城市地质灾害风险结构与风险量化分析,（2）城市地震地质灾害风险判据研究与风险准则建立,（3）强震区城市地质灾害管制的途径和方法研究,（4）强震区城市地质灾害管制的效能监控机制研究,（5）强震区城市地质灾害风险管制的模式与规范体系研究。  相似文献   

18.
A significant proportion of the urban areas in Turkey is subject to high seismic risk. An important step for seismic risk mitigation is to define the hazard and damage after an earthquake. This paper proposes an integrated seismic hazard assessment and disaster management processes for Turkey. The proposed methodology utilizes information technologies in its seismic assessment component that provides fast results for assessment. First, image process methodology by using satellite images was implemented in the seismic assessment process for fast evaluation right after an earthquake. Second, the seismic assessment process was integrated with disaster management process. As a result, through integrated seismic hazard evaluation and disaster management procedure, an effective, fast and dependable estimation of loss for Turkey was planned.  相似文献   

19.
Integrated risk assessment of multi-hazards in China   总被引：1，自引：0，他引：1  
Maps of population exposure, vulnerability and risk to natural hazards are useful tools for designing and implementing disaster risk mitigation programs in China. The ranking of provinces by relative risk to natural hazards would provide a metric for prioritizing risk management strategies. Using provinces as our study unit, from the perspectives of hazard exposure, susceptibility, coping capacity and adaptive capacity, this study first constructed China’s disaster risk index for five types of major natural hazards: earthquakes, floods, droughts, low temperatures/snow and gale/hail. Then, the relative risk level at the provincial scale in China was assessed. Finally, the hotspots with the highest hazard exposure, vulnerability and risk were identified. The results showed that high exposure was a significant risk driver in China, whereas high vulnerability, especially social vulnerability, amplified the risk levels. Similar to the population exposure to disasters, the relative risk levels in the southwestern, central and northeastern regions of China were significantly higher than those in the eastern, northern and western regions. The high-risk regions or hotspots of multi-hazards were concentrated in southern China (less-developed regions), while the low-risk regions were mainly distributed in the eastern coastal areas (well-developed regions). Furthermore, a nonlinear relationship existed between the disaster risk level and poverty incidence as well as per capita GDP, demonstrating that disaster losses in middle-income areas are likely to increase if economic policies are not modified to account for the rising disaster risk. These findings further indicated that research on disaster risk should focus not only on hazards and exposure but also on the vulnerability to natural disasters. Thus, reducing vulnerability and population exposure to natural hazards would be an effective measure in mitigating the disaster risk at hotspots in China.  相似文献   

20.
Mapping Disastrous Natural Hazards Using Global Datasets   总被引：3，自引：0，他引：3  
The increased interest for categorising countries at risk calls for an improved methodology allowing comparison of natural hazard impacts at a global level. A disaster is the intersection between a hazardous event, the elements at risk (population, infrastructures) and their vulnerability. In order to associate reported impacts with affected elements and socio-economic or geophysical contextual parameters, geographical location and extent of hazards is needed. The scope of this paper is to present improved automated procedures for a rapid mapping of large disastrous hazard events (floods, earthquakes, cyclones and volcanoes) using Geographical Information Systems (GIS) and available global datasets. Up to 82% of the events and 88% of the reported victims could be geo-referenced and the results highlight both the potentialities and limitations of the methods applied.  相似文献   

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