用户名: 密码: 验证码:
长江三角洲自然灾害数据库建设与风险评估研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
目前,日益严重的灾害问题已经引起我国政府和学术界的高度关注。自然灾害风险评估是一项以预防为主、防患于末然的重要防灾减灾措施,是开展综合减灾和制定应急管理对策的基础和依据,是目前灾害研究领域的热点。在全球变暖与海平面上升的背景下,针对自然灾害发生频率和强度不断增高、灾害损失日益加剧这一趋势,选取我国长江三角洲地区(江苏、浙江、上海两省一市全境)为研究区,基于自然灾害研究的相关理论,消化吸收国内外研究的最新成果,建立自然灾害分类体系,采集相关灾害数据,构建自然灾害元数据标准和数据库,并应用情景分析的方法和GIS技术,开展了长江三角洲地区自然灾害风险评估研究,为政府部门构建区域风险管理体系,促进防灾减灾工作的开展提供了科学依据。主要研究结果如下:
     (1)以地球系统科学为基础,按圈层结构确定自然灾害性质并分类。在这一分类体系中,气象、水文、地质、生物四大类型分别对应地球表层系统结构中的大气圈、水圈、岩石圈和生物圈,有利于辨识和分析各致灾因子所处的孕灾环境,开展有针对性的脆弱性评价和风险分析。该分类体系是构建自然灾害元数据标准和长江三角洲自然灾害数据库的重要参照,既借鉴了国际现行的自然灾害分类方法,也兼顾了国内灾害研究和相关部门长期以来的分类习惯,具备良好的兼容性和可扩展性。
     (2)在通过报刊资料采集自然灾害历史数据时,应重点关注三个问题:文本语义理解和自然灾害数据的抽取;自然灾害事件的时空位置描述与匹配:自然灾害数据或文本信息的精度和可靠性评价。当数据预处理和收录工作完成以后,需要进行科学的数据编码,为每一条记录设置唯一的序列号作为标识。自然灾害类型编码可采用分类码+标识码的方法,自然灾害事件编码可采取自然灾害事件发生的具体日期+当日编号的格式。
     (3)通过分析元数据和元数据标准的定义、特征、分类以及作用,提出了自然灾害元数据标准的设计思路,并完成了自然灾害元数据标准的构建,可以为自然灾害数据管理和数据库开发提供服务,也为自然灾害数据共亨提供了支持。自然灾害元数据标准的编制,定义了自然灾害元数据的内容、结构和格式。具体标准涵盖六大实体、33个元素,另有36个子元素。对于每一个元数据元素,均有九个属性对其加以限制和说明。
     (4)在对国内外主要自然灾害数据库进行对比分析,总结国际先进经验以及我国现存问题的基础上,提出了长江三角洲自然灾害数据库的建设思路,主要包含建设原则、总体设计和软硬件环境三方面。完成了长江三角洲自然灾害数据库的结构设计,建立了数据概念模型,详细介绍了各数据表的结构及关系,并讨论了长江三角洲自然灾害数据库的管理和维护,主要包括用户管理、数据管理、数据库性能维护、数据库备份与恢复等。
     (5)对近60年长江三角洲地区自然灾害时空演变开展研究,分析其时空格局及特征,讨论了自然灾害发生次数年际和月际的变化,从省(直辖市)和县(市辖区)两级行政单元剖析了自然灾害发生次数的空间分布。结果显示:自然灾害高发区集中在长江三角洲地区沿海的各县(市辖区),就整个长江三角洲地区而言,中部和南部的自然灾害发生情况相较北部更为严重。在此基础上,建立了阶线性自回归预测模型,对长江三角洲地区自然灾害未来的变化趋势作了分析与预测。根据计算结果,长江三角洲地区未来至2020年,自然灾害的发生次数呈现上升趋势。2010年出现的高峰在2013年略有回落,但2013年以后则一直稳步升高。预计到2016年,自然灾害发生次数将重新回到2010年的水平。到2020年,将会出现新的历史峰值。
     (6)在重现期为10年的台风灾害情景下,各县(市辖区)的灾损率均较低,低脆弱性和中等脆弱性的地区面积相当,多数县(市辖区)属于低风险或较低风险。在重现期为50年的台风灾害情景下,低脆弱性和较低脆弱性的县(市辖区)只剩零星分布,大多数地区都达到中等或较高的脆弱性,低风险和较低风险地区面积大幅缩减,江苏和浙江都出现了许多中等风险或较高风险的县(市辖区)。在重现期为100年的台风灾害情景下,长江三角洲地区大部分县(市辖区)都呈现较高脆弱性或高脆弱性,中部几乎均为高风险或较高风险地区,北部有大量中等风险地区,南部风险相对较低。
     (7)在重现期为10年的洪水灾害情景下,连云港、盐城、扬州、上海、绍兴、丽水、台州等地区呈现高或较高脆弱性,常州、苏州等地区呈现总体偏低的脆弱性,长江三角洲中部地区风险较高,苏北地区、浙江中部和南部大片地区风险较低。在重现期为50年的洪水灾害情景下,较低脆弱性的地区仅余遂昌、溧阳两地,原有的低风险区面积缩减了约一半,高风险区向南北扩张,苏南、浙北地区的风险有所提升。在重现期为100年的洪水灾害情景下,长江三角洲地区出现比较极端的脆弱性分布,全境大多数地区都呈现高脆弱性,中部的高风险地区面积继续扩大,总体风险较低的地区仅剩浙西南以丽水地区为代表的少数区域。
     (8)在重现期为10年的暴雨灾害情景下,各县(市辖区)总体属于中低脆弱性,风险也较低。在重现期为50年的暴雨灾害情景下,长江三角洲地区脆弱性整体上升,绝大多数区域为中高脆弱性,较低脆弱性仅在浙江中部和东北部有零星分布,中等风险的区域面积扩张较多,低风险和较低低风险区域主要分布在江苏北部和浙江南部。在重现期为100年的暴雨灾害情景下,长江三角洲地区脆弱性继续攀升,大量出现高脆弱性区域,仅有少量中等脆弱性地区,原有的高风险区域向北发展较快,而浙江南部则拥有比较稳定的低风险和较低风险区域。
     (9)在重现期为10年的风暴潮灾害情景下,长江三角洲沿海地区总体呈现中等偏低的脆弱性,风险水平总体也不高。在重现期为50年的风暴潮灾害情景下,长江三角洲沿海多数地区处于中等脆弱性,脆弱性较高的区域有比较明显的增加,风险主要集中于中部沿海地带。在重现期为100年的风暴潮灾害情景下,长江三角洲沿海地区绝大多数县(市辖区)都呈现偏高的脆弱性,且处于中高风险水平,高风险区和较高风险区继续扩张,只有苏北和浙北沿海还有很少量的区域风险相对较低。
     (10)在重现期为10年的十早灾害情景下,整个长江三角洲地区未出现高脆弱性区域,少量低脆弱性区域主要出现在苏北、浙江中部和舟山地区,高风险区域主要集中在长江三角洲中部地区,风险最低的地区位于浙江南部。在重现期为50年的干旱灾害情景下,长江三角洲地区的中部和北部出现了一定数量的高脆弱性县(市辖区),较低脆弱性区域仅余浙江的东阳市和金华市辖区两处,中部的高风险区面积有所扩大。在重现期为100年的干旱灾害情景下,大多数县(市辖区)旱现出高脆弱性,已无脆弱性相对较低的地区和低风险区域,除浙江省西部和南部总体风险水平相对较低外,其余地区儿乎都处于中高风险水平。
Currently, the increasingly serious disasters have caused great concern of the Chinese government and academia. The natural disaster risk assessment is a prevention-oriented, proactive disaster prevention and mitigation measures. It is the basis and foundation to carry out a comprehensive disaster reduction and the development of emergency management countermeasures. It is also the focus of the field of disaster research. The frequency, intensity and loss of natural disasters are constantly increasing in the context of global warming and sea level rise. China's Yangtze River Delta region (the whole territory of Jiangsu, Zhejiang and Shanghai) is selected as the study region for research of natural disaster risk assessment. The research which is based on theory and the latest results in natural disasters apply scenario analysis and GIS. The paper discusses the establishment of natural disaster classification system, collecting relevant disaster data, construction of natural disaster metadata standard and database. It provides a scientific basis for government departments to build a regional risk management system and promote the work of disaster prevention and mitigation. The followings are main conclusions of the research
     1. Determine the properties and classification of natural disasters according to circle structure based on Earth System Science. In this classification system, four types of disasters which are meteorological disaster, hydrological disaster, geological disaster and biological disaster correspond to atmosphere, hydrosphere, lithosphere and biosphere in the earth surface system structure. The system is conducive to the identification and analysis for the environment of hazards and the development of targeted vulnerability assessment and risk analysis. The classification system which has a good compatibility and scalability is an important reference for construction of natural disaster metadata standard and the Yangtze River Delta natural disaster database. It with reference to the current international classification method of natural disaster, but also take into account the domestic disaster research and classification used by related departments for a long time.
     2. Collection of natural disaster history data in the newspapers should focus on three issues:the semantic understanding of text and natural disaster data extraction, description and matching on temporal and spatial position of natural disaster event, accuracy and reliability assessment of natural disaster data or text information. After data preprocessing and included work completed, each record need a scientific data coding as identifier by set a unique serial number. Natural disaster type encoding method can be used to identification code and classification codes, natural disaster event code can be used to the number and date.
     3. Develop design ideas of natural disasters metadata standards by analyzing definitions, characteristics, classification as well as the role of metadata and metadata standard. Completed the construction of natural disaster metadata standards, can provide services, data management, and database development for natural disasters and also provides support for data sharing of natural disasters. Preparation of the natural disaster metadata standards, defines the content, structure and format of the natural disasters metadata. Specific standard covers6entities,33elements, and another36sub-elements. Each metadata element has nine properties for restrictions and instructions.
     4. Comparative analysis on the domestic and foreign main natural disaster database, summarizing the advanced international experience and China's existing problems, puts forward the ideas of natural disasters in the Yangtze River Delta database, mainly includes three aspects which are the construction principle, the overall design and the environment of hardware and software. Completed the structural design of Yangtze Delta natural disasters database, established a conceptual data model and introduced the structure and relationship between data tables in detail. Finally, the paper discussed the management and maintenance of Yangtze River Delta natural disasters database, including user management, data management, database maintenance, database backup and recovery.
     5. Analyze spatial and temporal patterns and characteristics of space-time evolution of natural disasters for the past60years in the Yangtze River Delta region. Research of the annual and monthly changes of natural disasters from the provincial and county levels and analyze the number of natural disasters space distribution. The high incidence of natural disasters is concentrated in the coastal counties. More serious natural disasters of the central and southern parts of the Yangtze River Delta region compared to northern. Established two order linear regression prediction model to analyse and predict the future trend of natural disasters in the Yangtze River Delta region. The number of natural disasters in the Yangtze River Delta region is on the rise to2020according to the calculation results. Expected to2016, number of natural disasters will be back in2010. By2020, there will be a new historical peak.
     6. In a return period of10years typhoon disaster scenario, loss rates were low in counties, lower vulnerability and middle vulnerability regions have a considerable area. The majority of the counties belong to the low risk. In a return period of50years typhoon disaster scenario, most regions had a high vulnerability and the low vulnerability counties only scattered. Area of low risk regions is substantially reduced and Jiangsu and Zhejiang had many medium-risk or high-risk counties. In a return period of100years typhoon disaster scenario, Most of the Yangtze River Delta region counties show higher vulnerability or high vulnerability. The middle regions are almost all high-risk or high-risk areas. There are a large number of medium-risk areas in northern. Southern had a relatively low risk.
     7. Lianyungang, Yancheng, Yangzhou, Shanghai, Shaoxing, Lishui, Taizhou region presents high or higher vulnerability and Changzhou, Suzhou and other regions to render the overall low vulnerability in a return period of10years flood disaster scenario. The central region of Yangtze River Delta has a higher risk, a lower risk of large areas in Northern Jiangsu and central and southern of Zhejiang. The risk of southern Jiangsu, northern Zhejiang had improved in a return period of50years flood disaster scenario. Lower vulnerability areas are down to Suichang and Liyang. The low-risk area reduced by about half and high-risk areas expanse to the north and south. Majority of the Yangtze River Delta region presents high vulnerability in a return period of100years flood disaster scenario. High-risk areas of the Yangtze River in central region continues to expand, lower risk regions except for Lishui district in the southwestern Zhejiang is represented by a small area.
     8. In a return period of10years rainstorm disaster scenario, the counties in Yangtze River Delta region belong to the low vulnerability and lower risk. In a return period of50years rainstorm disaster scenario, the overall vulnerability of the Yangtze River Delta region is on the rise and the vast majority of regions have a high vulnerability. Lower vulnerability only sporadic distributed in central and northeastern Zhejiang province. The moderate risk regions increased more area. Low-risk regions are mainly distributed in the northern part of Jiangsu and southern part of Zhejiang. In a return period of100years rainstorm disaster scenario, the vulnerability of Yangtze River Delta region continues to rise. There are a large number of high vulnerability areas and only a small amount of medium vulnerability areas in Jiangsu and Zhejiang. The original high-risk region developed to north rapidly and southern Zhejiang has a relatively low risk and low risk region.
     9. In a return period of10years storm surge disaster scenario, coastal regions of Yangtze River Delta generally showed lower-middle vulnerability. The overall level of risk is not high. In a return period of50years storm surge disaster scenario, most coastal regions of Yangtze River Delta are in the middle vulnerability. High vulnerability areas have increased significantly and the risk is mainly concentrated in central coastal zone of Yangtze River Delta. In a return period of100years storm surge disaster scenario, vast majority of counties in the coastal regions of Yangtze River Delta presented high vulnerability and in a high-risk level. High-risk areas continue to expand and only the northern areas of Jiangsu and north along the coast of Zhejiang have a small amount of regions which showed a relatively low risk.
     10. In a return period of10years drought disaster scenario, Yangtze River Delta region as a whole does not appear high vulnerability areas. The small amount of low vulnerability areas occurred mainly in northern Jiangsu, central Zhejiang and Zhoushan districts. High-risk areas are mainly concentrated in the middle of Yangtze River Delta region. The lowest risk areas are located in southern Zhejiang. In a return period of50years drought disaster scenario, the central and northern parts of Yangtze River Delta region there had been a certain amount of high vulnerability counties. Lower vulnerability areas are only down in Dongyang City and Jinhua City. High-risk area has expanded in the middle of Yangtze River Delta region. In a return period of100years drought disaster scenario, majority of counties in Yangtze River Delta region show high vulnerability and there are no longer relatively low vulnerability areas and low-risk areas. In addition to the overall level of risk of the western and southern parts of Zhejiang province was relatively low, the rest of the regions are almost in the middle and high level of risk.
引文
1. ADPC/CDMC, IWDMC. The working drafts:a compendium of project reports (Applied Research Grants for Disaster Reduction) [R], The World Bank, Washington, DC USA,2004.
    2. ADRC (Asian Disaster Reduction Center). Good Practices:Total Disaster Risk Management [R].2005.
    3. Aleotti P, Baldelli P, Polloni G., et al. Hydro geological risk assessment of the Poriver basin(Italy),landslides in research, theory and practice[R]:13-18,Thomas Telford, London.2000.
    4. Arnold M, Chen R S, Deichmann U, et al. Natural Disaster Hotspots Case Studies, Washington DC [R]. Hazard Management Unit, World Bank,2006,1-181.
    5. Artessa S, Herbert H E. A Landslide Risk Rating System for Baguio,Philippines[J]. Engineering Geology,2007,91:85-99.
    6. Asia Pacific Network Project:An assessment of the socio-economic impacts of floods under climate change conditions in large coastal cites in South and South-east Asia [R]. Starting date: September,2004.
    7. Asian Disaster Reduction Center. Natural Disaster Data Book 2003:An Analytical overview[R]. Kobe:ADRC,2004.
    8. Asian Disaster Reduction Center. Data book on Asian natural disasters in the 20th Century[R]. Kobe:ADRC,2000.
    9. Bai S B, Wang J, Lv G N. GIS-Based and Data-Driven Bivariate Landslide-Susceptibility Mapping in the Three Gorges Area, China [J]. Pedosphere,2009,19(1):14-20.
    10. Batuk F, Sengezer B, Emem O. The New Zoning Approach for Earthquake Risk Assessment [A]. In:Geo-information for Disaster Management, Part 17. Springer Belin Heidelberg,2005, 1225-1237.
    11. Benouar D, Mimi A. Improving emergency management in Algeria [C]. Global Alliance International Workshop on Disaster Reduction:2001,18-22.
    12. Bocchiola D, Medagliani M, Rosso R. Regional snow depth frequency curves for avalanche hazard mapping in central Italian Alps [J]. Cold Regions Science and Technology,2006, 46(3):204-221.
    13. Brown L. Modelling future landscape change on coastal floodplains using a rule-based GIS [J]. Environmental Modelling & Software,2006,21(10):1479-1490.
    14. Cardona O D, Ordaz M G, Yamin L E, et al. Earthquake loss assessment for integrated disaster risk management [J]. J Earthq Eng,2003, (12):48-59.
    15. Cardoso R M R, Waters H R. Calculation of finite time ruin probabilities for some risk models [J]. Insurance:Mathematics and Economics,2005,37(2):197-215.
    16. Date C J.An Introduction to Database Systems (8th Edition)[M].USA:Addison-Wesley,2003.
    17. Cutter S L. Emricli C T and Webbe J J et al. Social Vulnerability to Climate Variability Hazards:A Review of the Literature[R]. Columbia:University of South Carolina,2009.
    18. David L, Olson, Wu D S. Natural Disaster Risk Management [J]. Enterprise Risk Management Models:2010,57-69.
    19. DFID. Reducing the Risk of Disasters-Helping to Achieve Sustainable Poverty Reduction in a Vulnerable World [R]. A DFID policy paper.2006.
    20. DHA U N. Internationally agreed glossary of basic terms related to disaster management [R]. UN DHA (United Nations Department of Humanitarian Affairs), Geneva,1992.
    21. Dilley M, Chen R S, Deichmann U. Natural Disaster Hotspots:A Global Risk Analysis, Washington DC[R]. Hazard Management Unit, World Bank,2005,1-132.
    22. EERI. Guidelines for Developing an Earthquake Scenario [R]. Report of Endowment Fund of the Earthquake Engineering Research Institute and FEMA.2006.
    23. FEMA. Handbook for the Seismic Evaluation of Existing Buildings [R]. Federal Emergency Management Agency. Washington D.C.1998.
    24. Frazier T G, Wood N, Yarnal B. Stakeholder perspectives on land-use strategies for adapting to climate-change-enhanced coastal hazards:Sarasota, Florida[J].Applied Geography,2010, 30:506-517.
    25. Freeman P K, Martin L A, Linneroot-Bayer J et al. Disaster risk management:national systems fur the comprehensive management of disaster risk financial strategies for natural disaster reconstruction [R]. Inter-American Development Bank, Washington, DC USA,2005.
    26. Garatwa W, Bollin GDC. Disaster Risk Management [R]. OK KOPIE GmbH,65719.
    27. Glade T. Vulnerability assessment in landslide risk analysis[J]. Die Erde,2003, 134(2):123-146.
    28. Government of Alberta. Metadata resources guide[R].2004.
    29. Graham M, Nixon R, Burrell L J, et al. Low rates of cutaneous adverse reactions to alcohol-based hand hygiene solution during prolonged use in a large teaching hospital [J], Antimicrobial agents and chemotherapy,2005,49(10):4404-4405.
    30. Granger K J. Lifelines and the AGSO Cities Project [J]. Australian Journal of Emergency Management,1997,12(1):16-18.
    31. Grunthal G., Thieken A H, Schwarz J et al. Comparative risk assessment for the city of Cologne, Germany:Storms, foods, earthquakes. Natural Hazards [J],2006,38 (1/2):21-44.
    32. Guha-Sapir D, Below R. The Quality and accuracy of disaster data:A comparative analysis of 3 global data sets[R]. Brussels:CRED:2002,3-18.
    33. Hall J W, Dawson R J. A methodology for national-scale flood risk assessment [J]. Water & Maritime Engineering,2003,156 (3):235-247.
    34. Helm P. Integrated risk management for natural and technological disasters[J], Tepra,1996, 15(1):4-13.
    35. Hori T, Zhang J, Tatano H, Okada N, Likebuchi S. Micro-zonation-based Flood Risk Assessment in Urbanized Floodplain [C]. Second Annual IIASA-DPRI Meeting Integrated Disaster Risk Management Megacity Vulnerability and Resilience. Laxenburg, Austria:2002, 29-31.
    36. Hubbert G D, McInnes K L. A Storm Surge Inundation Model for Coastal Planning and Impact studies[J], Journal of Coastal Research,1999,15:168-185.
    37. IADB-ECLAC-IDEA. Indicators of Disaster Risk and Risk Management [R]. Program for Latin America and the Caribbean:2005,1-47.
    38. ICTP. Workshop on the Physics of Tsunami, Hazard Assessment Methods and Disaster Risk Management [EB/OL]. Miramare-Trieste, Italy, May,14-18.2007.
    39. IHDP. Integrated risk governance project science plan[R]. IHDP, Germany,Bonn.2010.
    40. IIASA-DPRI. Meeting Integrated Disaster Risk Management Megacity Vulnerability and Resilience [R], Laxenburg, Austria,2002.
    41. ISDR. Comparative Analysis of Disaster Databases [R]. United Nations Publication.2002.
    42. ITC. Multi-hazard Risk Assessment [R]. Bangkok,2009,253-265.
    43. Jelesnianski C P, Chen J, Shaffer W A. SLOSH:Sea, Lake, and Overland Surges from Hurricanes[R]. NOAA Technical Report NWS 48, United States Department of Commerce, NOAA, NWS, Silver Springs, MD.71pp.1992.
    44. Jones R, Boer R. Assessing current climate risks Adaptation Policy Framework:A Guide for Policies to Facilitate Adaptation to Climate Change [R]. UNDP, in review, see http://www. undp. org/cc/apf-outline.html.2003.
    45. Kaplan S, Garrick B J. On the quantitative definition of risk [J]. Risk Analysis,1981, 1(1):11-27.
    46. Karen O, Jon B, Indra D S, et al. Hurricane Katrina Reveals Challenges to Human Security-Hurricane Katrina Reinforced Many Key Lessons about the Nature of Environmental Change [R]. AVISO.2005.
    47. Karimi I, Eyke H. Risk assessment system of natural hazards:a new approach based on fuzzy probability[J]. Fuzzy sets and systems,2007,158:987-999.
    48. Granger K, Jones T, Leiba M. Community risk in Cairns:a multi-hazard risk assessmentfJ]. Australian Journal of Emergency Management 1999, (4):29-30.
    49. Kron. Flood Risk Zoning and Loss Accumulation Analysis for Germany[A]. In:Proc. Of the International Conference on Flood Estimation, Mar.6-8, Berne, Switzerland,2002,549-558.
    50. Kwan M P, Jiyeong L. Emergency Response After 9/11:the Potential of Real-time 3D GIS for Quick Emergency Response in Micro-spatial Environments[J]. Computers, Environment and Urban Systems,2005,29:93-113.
    51. Lateltin O, Haemmig C, Raetzo H, et al. Landslide Risk Management in Switzerland[J]. Landslides,2005,2(4):313-320.
    52. Lisa K F, Russell W J, David N S. Community Vulnerability Assessment Tool Methodology [J].Natural Hazards Rev.2002,3(4):163-176.
    53.Lopez-Baldovin M J, Gutierrez-Martin C, Berbel J. Multicriteria and Multiperiod Programming for Scenario Analysis in Guadalquivir River Irrigated Farming [J]. Journal of the Operational Research Society,2006,57(5):499-509.
    54. Lorenzoni I, Pidgeon N F, Connor R E. Dangerous climate change:the role for risk research[J]. Risk Analysis,2005,25(6):1387-1398.
    55. Alexander M. Aging, Bioavailability, and Overestimation of Risk from Environmental Pollutants [J]. Environ. Sci. Technol.2000,34 (20):4259-1265.
    56. Martha E. Williams. New database products-science, technology and medicine[J]. Online Information Review,1999,23(1):19-34.
    57. Mcinnes K L, Walsh K J E, Hubbert G D, et al. Impact of Sea-level Rise and Storm Surges on a Coastal Community [J]. Natural Hazards,2003,30:187-207.
    58. Merz B, Thieken A H. Flood risk curve and uncertainty bounds[J]. Natural Hazards,2009, 51:437-458.
    59. Michael-leiba M. Quantitative landslides risk assessment of Cairns, Australia [R].LandsIides in research, theory and practice:1059-1064. Thomas Telford London.2000.
    60. Mike L, Steve R. The Survivor's Guide to 2001:Data Management & Storage Technology [R].2000.
    61. Mileti D S. Natural Hazards and Disasters-Disasters by Design a Reassessment of Natural Hazards in the United States[M]. Washington D C:Joseph Henry Press.1999.
    62. Su M D, Kang J L, Chang L F, Albert C. A grid-based GIS approach to regional flood damage assessment [J].Journal of marine science and technology,2005,113(3):184-192.
    63. Morrow, B.H. Identifying and Mapping Community Vulnerability[J].Disasters.1999, 23(1):11-18.
    64. Mwenelupembe J, Mylius H. Geological Hazards and Anthropogenic Impacts on the Environment in Malawi:Lesson From A Case Study of Debris Flows in Zomba [A]. In:The East African Great Lakes:Limnology, Palaeolimnology and Biodiversity [M]. Springer Netherlands,2004,557-573.
    65. Ngo, E. B. When Disasters and Age Collide:Reviewing Vulnerability of the Elderly [J]. Natural Hazards Review,2001,2(2):80-89.
    66. Pearce. An integrated approach for community hazard, impact, risk and vulnerability analysis: HIRV [R]. Laurence Dominique Renee.2000.
    67. Peduzzi P, Dao H, Herold C. Mapping Disastrous Natural Hazards Using Global Datasets[J]. Natural Hazards,2005,35:265-289.
    68. Perry R. Emergency Operations Centres in an Era of Terrorism [J]. Journal of Contingencies and Crisis Management,2003,11(4):151-159.
    69. Picarelli L,Olivares L,Avolio B. Zoning for flowslide and debris flow in pyroclastic soils of Campania Region based on "infinite slope"analysis[J].Engineering Geology,2008, 102:132-141.
    70. Poortinga W, Pidgeon N F. Exploring the dimensionality of trust in risk regulation[1]. Risk Analysis,2003,23(5):961-972.
    71. ProVention Consortium. Global Risk Identification Programme [EB/OL]. From the World Wide Web:http://www.proventionconsortium.Org/.2007.
    72. Provincial Emergency Program (PEP). Emergency Preparedness Information [EB/OL]. http://www.pep.bc.ca/index.html.2009.
    73. Pusch C. Preventable Losses:Saving Lives and Property Through Hazard Risk Management[R]. Working Paper Series of the World Bank.2004.
    74. Rajib S, Kenji O. A User's Guide:Sustainable community based disaster management (CBDM) practices in Asia [R]. UNCRD Disaster Management Planning Hyogo Office, Kobe, Japan, 2004.
    75. Ramon C, Joan M V. Rockfall susceptibility zoning at a large scale:From geomorphological inventory to preliminary land use planning[J]. Engineering Geology,2008,102:142-151.
    76. Renn O, Sellke P. Risk, society and policy making:risk governance in a complex world[J]. International Journal of Performability Engineering,2011,7(4):341-158.
    77. Schmidt-Thome P. The spatial effects and management of natural and technological hazards in Europe [J]. Luxembourg:European Spatial Planning and Observation Network (ESPON) Project.2003,1(1):1-89.
    78. Schneider R O. Hazard mitigation and sustainable community development [J]. Disaster Prevention and Management.2002,11(2):141-147.
    79. Schneiderbauer S, Ehrlich D. Risk, hazard and people's vulnerability to natural hazards-a review of definition, concept and data [R]. Reported No. EUR21410 EN, European Commission.2004.
    80. Shi P J, Du J, Ji M X. Urban Risk Assessment Research of Major Natural Disasters in China [J]. Advances in Earth Science,2006,21(2):170-177.
    81.Shrestha B K. Building a Disaster Resistant Community-A Case for Lalitpur Sub-metropolitan City [R]. Nepal. International Symposium on Earthquake Safer World in the 21st Century. Kobe, Japan:2002,1-15.
    82. Sinnakaudan S, Ghani A. Flood Risk Mapping for Pari River Incorporating Sediment Transport [J]. Environmental Modelling & Software.2003,18:119-130.
    83. Stefan G, Mark F, Johannes L. Methodology for an Integrated Risk Assessment of spatially relevant hazards [J]. Journal of environmental planning and management.2006,149(1):1-19.
    84. Steve R, Richard P. Use of LDAP to partially implement the OGIS discovery service [J]. International Journal of Geographical Information Science.2001,15 (5):391-413.
    85. Sujit, Lee R. A Nontraditional Methodology for Flood Stage-damagecalculation [M].Water Resources Bulletin,1988,110-135.
    86. Sunil S, Mukesh M, Vijay K, Yahiko K. Recent Advance and Research Problems in Data Warehousing[J].Lecture Notes in Computer Science,1999,1552:81-92.
    87. Susan H C, Philip S P, Roger A P, et al. Preliminary evaluation of the fire-related debris flows on storm KING mountain [R]. Glenwood.1995.
    88. Downing T. Reducing hazard vulnerability:towards a common approach between disaster risk reduction and climate adaptation [J]. Disasters.2006,30(1):39-48.
    89. Terry P, Lichtenstein P, Feychting M, et al. Fatty fish consumption and risk of prostate cancer [J]. The Lancet,2001,357(9270):1764-1766.
    90. Tiedemann H. Disaster Prevention and Mitigation:Some Prerequisites [J]. Disaster Prevention and Management.1992, 1(1):6-10.
    91. Tiedemann H. Earthquake and Volcanic Eruptions:A Handbook on Risk Assessment [M]. Swiss Re, Zurich,951pp.1992.
    92. Rashed T, Weeks J. Assessing vulnerability to earthquake hazards through spatial multicriteria analysis of urban areas [J]. International Journal of Geographical Information Science.2003,17(6):547-576.
    93. UNDP-BURMA. Glossary of disaster risk reduction [M], United Nations Development Programme.2008.
    94. UNDP/CRED. An Analytical Review of Selected Data Sets on Natural Disasters and Impacts [R]. United Nations Publication.2006.
    95. UN/ISDR. Living with Risk:A Global Review of Disaster Reduction Initiatives 2004 Version[M], United Nations publication.2004.
    96. United Nations Development Programme (UNDP). A Global Report Reducing Disaster Risk: A Challenge for Development[R]. New York:UNDP,2004,1-144.
    97.United Nation, Draft programme outcome document. Building the resilience of nations and communities to disasters:Hyogo framework for action 2005-2015 [R].World Conference on Disaster Reduction, Kobo, Hyogo, Japan,2005.
    98. Knijff J M, Younis J.Deroo A P J. LISFLOOD:a GIS-based distributed model for river basin scale water balance and flood simulation[J]. International Journal of Geographical Information Science,2010,24(2):189-212.
    99. Weichselgartner J, Kasperson R. Barriers in the science-policy-practic interface:toward a knowledge-action-system in global environmental change research[J]. Global Environmental Change,2010,20(2):266-277.
    100. Velasquez A, Rosales C, Ramirez F. Comparative Analysis of Disaster Databases:Final report submitted to working group 3:risk, vulnerability and impact assessment[R]. ISDR/UNDP:LaRED-OSSO,2002,1-82.
    101. WCDR. Disaster reduction technology list on implementation strategies:a contribution from Japan [R]. Kobe, Hyogo Japan,2005.
    102. WGIII T, Metz B. Climate change 2001:Mitigation [R]. Contribution of Working Group III to the Third Assessment Report of the Intergovernmental Panel of Climate Change (IPCC). 2001.
    103. Yan J P. Natural disaster risk assessment:Models, working procedure and integration with GIS [C]. Proceedings of the 2nd World Conference on Disaster Reduction, Kobe, Japan, January,2005,18-22.
    104. Zerger A. Examining GIS decision utility for natural hazard risk modeling[J]. Environmental Modelling and Software,2002,17:287-294.
    105. Zhang J, Shan W. Early Warning and Prevention of Geo-Hazards in China [A]. In:Landslides, Part Ⅳ. Springer Belin Heidelberg,2005,285-289.
    106.白景昌.基十遥感与地理信息系统的洪灾风险区划研究[D].中国科学院遥感应用研究所.2004.
    107.布里林格,片山恒雄.[黄玮琼等译].地震危险性评定与地震区划[M].北京:地震出版社.1988.
    108.常捷.地震元数据标准及管理构建研究[D].南京理工大学.2010.
    109.陈德清,杨存建,黄诗峰.应用GIS方法反演洪水最大淹没水深的空间分布研究[J].灾害学, 2002.17(2):1-6.
    110.陈洪富HAZ-China地震灾害损失评估系统设计及初步实现[D].中国地震局工程力学研究所.2012.
    111.陈喆民,王晓锋.海洋核心元数据标准初探[J].现代计算机,2007.(6):120-122.
    112.丁一汇,张建云等.暴雨洪涝[M].北京:气象出版社.2009.
    113.丁志雄.基于RS与GIS的洪涝灾害损失评估技术方法研究[D].中国科学院上海冶金研究所.2000.
    114.樊隽轩,迟昭利,陈峰等.元数据标准及其在古生物数据库中的应用[J].地层学杂志,2009.33(4):391-397.
    115.冯利华.热带气旋的风险评估[J].海洋通报,1999.18(2):40-43.
    116.冯项云,肖珑,廖三三等.国外常用元数据标准比较研究[J].大学图书馆学报,2001.19(4):15-21.
    117.葛全胜,邹铭,郑景云等.中国自然灾害风险综合评估初步研究[M].北京:科学出版社.2008.
    118.国家发展和改革委员会.长江三角洲地区区域规划[R].2010.
    119.国家质量技术监督局.中国地震动参数区划图[M].北京:中国标准出版社.2001.
    120.韩丽蓉,倪三川,李积花.西宁瓦窑沟流域地质灾害信息数据库的建立方法[J].青海大学学报(自然科学版),2005.23(6):22-25.
    121.黄崇福.自然灾害风险评价理论与实践[M].北京:科学出版社.2005.
    122.黄崇福.自然灾害风险分析的基本原理[J].自然灾害学报,1999.8(2):21-30.
    123.黄崇福,张俊香,陈志芬等.自然灾害风险区划图的一个潜在发展方向[J].自然灾害学报,2004.13(2):9-15.
    124.黄蕙,基于情景的台风灾害风险评估研究——以上海市杨浦区富禄里居委地区为例[D].上海师范大学.2009.
    125.黄声.上海市综合减灾管理体制研究——以上海市民防办公室承担减灾职能为例[D].华东师范大学.2005.
    126.蒋庆丰,游珍.基于GIS的南通市自然灾害风险区划[J].灾害学,2006.20(2):110-114.
    127.江苏省地方志编纂委员会.江苏省志地理志建制志[M].南京:江苏古籍出版社.1999.
    128.江苏省人民政府.江苏省国民经济和社会发展第十二个五年规划纲要(2011-2015年)[R].2011.
    129.李刚,许倩英,刘惠瑾.城市抗震防灾规划元数据标准研究——基础设施元数据模型[C]. 城市规划和科学发展——2009中国城市规划年会论文集:2009.4318-4325.
    130.李军,周成虎.地球空间数据元数据标准初探[J].地理科学进展,1998.17(4):55-63.
    131.李世元,简季,吴章生等.广元市地质环境管理数据库系统设计[J].地质灾害与环境保护,2012.23(3):36-42.
    132.李卫江,温家洪.基于Web文本的灾害信息挖掘研究进展[J].灾害学,2010.25(2):119-123.
    133.李文峰,刘雪涛,贾月琴.基于元数据标准的标准资源库建设研究[J].中国标准化,2007.(4):24-25.
    134.李谢辉,工磊,谢灵芝等.渭河下游河流沿线区域洪水灾害风险评价[J].地理科学,2009.29(5):33-39.
    135.李月臣,赵纯勇,刘春霞等.重庆市地质灾害数据库设计与建设[J].中国地质灾害与防治学报,2007.18(1):115-119.
    136.刘昌森,姚保华,章振铨等.上海自然灾害史[M].上海:同济大学出版社.2010.
    137.刘东琴.地理实休数据库构建研究[D].山东科技大学.2010.
    138.刘君德.中国政区地理[M].北京:科学出版社,1999.
    139.刘少军,张京红,蔡大鑫等.台风过程引发洪涝灾害的风险评估—以海南岛为例[J].自然灾害学报,2010.19(3):146-150.
    140.刘希林.区域泥石流风险评价研究[J].自然灾害学报,2000.9(1):54-61.
    141.刘耀龙.多尺度自然灾害情景风险评估与区划——以浙江省温州市为例[D].华东师范大学.2011.
    142.刘耀龙,陈振楼,工军等.经常性暴雨内涝区域房屋财(资)产脆弱性研究——以温州市为例[J].灾害学,2011.26(2):66-71.
    143.刘耀龙,许世远,王军等.国内外灾害数据信息共享现状研究[J].灾害学,2008.23(3):109-113.
    144.罗元华.泥石流堆积数值模拟及泥石流灾害风险评估方法研究[D].中国地质大学.1998.
    145.马宗晋,杨华庭,高建国等.我国自然灾害的经济特征与社会发展[J].科技导报,1994.(7):61-64.
    146.毛松柏.现代城市应急管理机制的思考[J].中山大学学报论丛,2006.26(1):130-134.
    147.孟宪学.中国农业科技数据库系统建设研究[D].中国农业科学院研究生院.2002.
    148.彭颖霞,何贞铭,古辽芳等.基于GIS的省级地质灾害数据库设计与实现[J].测绘与空间地理信息,2011.34(3):157-161.
    149.权瑞松.典型沿海城市暴雨内涝灾害风险评估研究[D].华东师范大学.2012.
    150.上海市人民政府.上海市国民经济和社会发展第十二个五年规划纲要(2011-2015年)[R].2011.
    151.上海通志编纂委员会.上海通志[M].上海:上海人民出版社.2005.
    152.石勇.灾害情景下城市脆弱性评估研究——以上海市为例[D].华东师范大学.2010.
    153.石勇,石纯,孙阿丽.中国南方城市居民建筑物洪灾脆弱性研究[J].人民长江,2009.40(5):19-22.
    154.石勇,许世远,石纯等.洪水灾害脆弱性研究进展[J].地理科学进展,2009.28(1):41-46.
    155.史培军.中国自然灾害系统地图集[M].北京:科学出版社.2003.
    156.司瑞洁,温家洪,尹占娥等.EM-DAT灾难数据库概述及其应用研究[J].科技导报,2007.25(6):60-67.
    157.孙阿丽.基于情景模拟的城市暴雨内涝风险评估[D].华东师范大学.2011.
    158.谭丽荣.中国沿海地区风暴潮灾害综合脆弱性评估[D].华东师范大学.2012.
    159.唐川,朱静.基于GIS的山洪灾害风险区划[J].地理学报,2005.60(1):87-94.
    160.滕五晓.城市灾害应急预案基本要素探讨[J].城市发展研究,2006.13(1):11-17.
    161.王建鹏,薛春芳,解以扬等.基于内涝模型的西安市区强降水内涝成因分析[J].气象科技,2008.36(6):772-775.
    162.王静爱,史培军,朱骊等.中国自然灾害数据库的建立与应用[J].北京师范大学学报:自然科学版,1995.31(1):121-126.
    163.工绍玉,冯百狭.城市灾害应急与管理[M].重庆:重庆出版社.2005.
    164.王新.都柏林核心集综述[J].情报理论与实践,2000.(5):389-391.
    165.温克刚.中国气象灾害大典(江苏卷)[M].北京:气象出版社.2006.
    166.温克刚.中国气象灾害大典(上海卷)[M].北京:气象出版社.2006.
    167.温克刚.中国气象灾害大典(浙江卷)[M].北京:气象出版社.2006.
    168.吴亚玲,吴佳银,曾峰.深圳市气象灾情信息数据库的设计与应用[J].广东气象,2010.32(3):66-68.
    169.夏富强,康相武,吴绍洪等.黄河下游不同洪水情景决溢风险评价[J].地理研究,2008.27(1):229-239.
    170.谢翠娜.上海沿海地区台风风暴潮灾害情景模拟及风险评估[D].华东师范大学.2010.
    171.徐建华.现代地理学中的数学方法[M].北京:高等教育出版社.2002.
    172.许世远,王军,石纯等.沿海城市自然灾害风险研究[J].地理学报,2006.61(2):127-138.
    173.许武成,马劲松,杨霞.洪水等级的三种划分方法[J].东北水利水电,2003.21(12):20-22.
    174.徐霞,王静爱,王文宇.自然灾害案例数据库的建立与应用—以中国1998年洪水灾害案例数据库为例[J].北京师范大学学报(自然科学版),2000.26(4):274-280.
    175.杨桂山.中国沿海风暴潮灾害的历史变化及未来趋向[J].自然灾害学报,2000.9(3):23-30.
    176.叶明武.沿海台风风暴潮灾害复合情景模拟与应急避难研究——以上海为例[D].华东师范大学.2011.
    177.叶欣梁.旅游地自然灾害风险管理框架研究——以九寨沟为例[D].上海师范大学.2011.
    178.殷杰.中国沿海台风风暴潮灾害风险评估研究[D].华东师范大学.2011.
    179.尹占娥.城市自然灾害风险评估与实证研究[D].华东师范大学.2009.
    180.尹占娥,许世远,殷杰等.基于小尺度的城市暴雨内涝灾害情景模拟与风险评估[J].地理学报,2010.65(5):553-562.
    181.张爱,邢立强.元数据的应用及其标准化[J].世界标准化与质量管理,2005.(10):52-53.
    182.张博.基于ArcGIS的府谷县地质灾害数据库建立及易发区评价研究[D].长安大学.2009.
    183.张会,张继权,韩俊山.基于GIS技术的洪涝灾害风险评估与区划划研究——以辽河中下游地区为例[J].自然灾害学报,2005.14(6):141-146.
    184.张俊香,黄崇福.自然灾害软风险区划图模式研究[J].自然灾害学报,2005.14(6):20-25.
    185.张立宪,甘淑,刘水等.基于Geodatabase的滑坡地质灾害数据库设计[J].科学技术与工程,2010.10(34):8503-8506.
    186. 张行南,安如,张文婷.上海市洪涝淹没风险图研究[J].河海大学学报(自然科学版),2005.33(3):251-254.
    187.张业成.中国自然灾害综合风险预测与分区减灾对策[J].地质灾害与环境保护,1998.9(1):1-5.
    188.张英华.美国联邦地理数据委员会FGDC编制的标准[J].测绘标准化,2004.(1):47-48.
    189.赵慧勤.网络信息资源组织Dublin Core无数据[J].情报科学,2001.19(4):439-442.
    190.赵林,武建军.灾害风险防范数据库的设计与开发[J].自然灾害学报,2008.17(1):44-48.
    191.浙江省人民政府.浙江省国民经济和社会发展第十二个五年规划纲要(2011-2015年)[R].2011.
    192.浙江省水利河口研究院,浙江广川工程咨询有限公司.浙江省水土保持生态修复规划报告(2006-2010年)[R].2006.
    193.周寅康.自然灾害风险评价初步研究[J].自然灾害学报,1995.4(1):6-11.
    194.赵庆良.沿海山地丘陵型城市洪灾风险评估与区划研究——以温州龙湾区为例[D].华东师范大学.2009.
    195.赵思键,黄崇福.情景驱动的淮河流域水稻灾害流域水稻洪涝灾害风险评价[C].中国灾害防御协会风险分析专业委员会第四届年会论文集,中国,长春.2010.392-399.
    196.中国国家标准化管理委员会.《热带气旋等级国家标准》(GB 19201-2006)[S].2006.
    197.中国科学院计算机网络信息中心,科学数据库中心.中国科学院科学数据库核心元数据标准[S].2004.
    198.中华人民共和国水利部.《水文情报预报规范》(SL250-2000)[S].2000.
    199.朱传华,胡光道.基于Geodatabase的滑坡灾害空间数据库设计[J].灾害学,2010.25(2):54-57.
    200.朱静.城市山洪灾害风险评价—以云南省文山县城为例[J].地理研究,2010.29(4):655-664.
    201. DesInventar数据库http://online.desinventar.org.
    202.地球系统科学数据共享平台http://www.geodata.cn/Portal/aboutWebsite/connectus.jsp
    203.紧急灾难数据库http://www.emdat.be.
    204.幕尼黑再保险公司数据库http://www.natcat.org.
    205.气象科学数据共享中心http://cdc.cma.gov.cn/home.do
    206.瑞士再保险公司数据库http://www.swissre.com.
    207.中国农业部信息中心http://202.127.42.157/moazzys/zaiqing.aspx

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700