地理空间分析综合应用

基于GeoKSCloud的地震影响场分析云服务研究——以福建省为例

展开
  • 1. 福州大学福建省空间信息工程研究中心 空间数据挖掘与信息共享教育部重点实验室, 福州 350002;
    2. 福建地震灾害预防中心, 福州 350003
巫建伟(1984-),男,福建永春人,博士生,研究方向主要为空间数据挖掘与地理知识工程。E-mail:wujw.dm@gmail.com

收稿日期: 2013-02-22

  修回日期: 2013-06-25

  网络出版日期: 2013-09-29

基金资助

国家科技支撑计划项目(2013BAH28F00、2009BAK55B00);福建省科技计划项目(2010I0008、2010HZ0004-1);欧盟第七框架国际合作项目(FP7-2009-People-IRSES,No.247608)

Cloud Service for Seismic Influence Field Analysis Based on GeoKSCloud: A Case Study in Fujian Province

Expand
  • 1. Spatial Information Research Center of Fujian, Fuzhou University, Key Lab of Spatial Data Mining & Information Sharing of Ministry of Education, Fuzhou 350002, China;
    2. Earthquake Disaster Prevention Center of Fujian Province, Fuzhou 350003, China

Received date: 2013-02-22

  Revised date: 2013-06-25

  Online published: 2013-09-29

摘要

地震发生后处于不同地震烈度区域的地物受灾程度不同。快速准确地获取地震影响或波及范围内地震烈度空间分布,是震后应急救援的重要依据和主要参数。依托云计算技术,以云服务方式构建地震烈度速报系统,提供可扩展、可配置、开放透明的地震影响场分析应用服务,将是我国烈度速报系统研究开发与应用中的一项新技术和发展趋势。本文依托研究小组自主研发的地理知识云服务系统GeoKSCloud,以福建省为研究区域,在提出适用于福建省地震烈度衰减关系与地震动峰值加速度场地校正方法的基础上,开展了地震影响场分析云服务系统的设计与实现工作,分析了地震影响场分析云服务的运行机制和服务组合工作流;实现了地震烈度衰减关系计算方法、场地放大因子校正方法、网格点场地类别属性获取、网格点沿地震衰减长短轴方向的坐标变换等相关原子服务的云服务封装,以及支撑数据云存储、网络地理信息系统的云服务门户的开发与集成;最后,以1604年发生在泉州近海7.5级大地震为震例,在云服务门户进行了全省范围内所有等间距网格点地震峰值加速度(基岩PGA和地表PGA)的计算、插值,并进行计算结果与实际调查数据的对比分析。结果表明,因充分考虑了具体场地的放大效应,构建的地震影响场分析云服务,不仅较传统单凭地震烈度衰减关系确定地震动峰值加速度方法更加精细化,而且提供的服务与传统的网络服务相比具有可扩展、可配置、开放透明等明显优势,可为我国烈度速报系统研究与应用提供一个共性技术与支撑服务平台,创新地震烈度速报的运营模式。

本文引用格式

巫建伟, 陈崇成, 吴小竹, 林剑峰, 黄昭, 张锦福, 郑师春, 张颖 . 基于GeoKSCloud的地震影响场分析云服务研究——以福建省为例[J]. 地球信息科学学报, 2013 , 15(5) : 695 -704 . DOI: 10.3724/SP.J.1047.2013.00695

Abstract

After the occurrence of an earthquake, different surface features at different seismic intensity areas are exposed to individual degrees of damage. The quick obtainment of accurate seismic intensities and their spatial distribution is an important basis and parameter for the post-earthquake emergency rescue. To construct seismic intensity rapid reporting system as a cloud service applying cloud computing technology and provide scalable, configurable, transparent seismic influence field analysis application service, will be a new technology and trend for the development of seismic intensity rapid reporting systems. Based on a geographical knowledge cloud service system, namely GeoKSCloud, which is developed innovatively and independently by our research team, this paper carried out the design and implementation of a cloud service system for seismic influence field analysis. By taking Fujian Province as the study area, seismic intensity attenuation relationship and peak ground motion acceleration site correction method suitable for Fujian area are firstly analyzed, and then the working mechanism and workflow-based service composition of their cloud service are proposed. To implement the cloud service, related atomic services are realized, service-oriented packaged and published on GeoKSCloud system (such as seismic intensity attenuation calculation service, PGA site correction service, seismic site property obtaining service for grid points, service for coordinate transformation along the seismic attenuation axis direction for grid points, et al.), data services for supporting spatial datasets are published as well, and also a Web GIS based cloud service portal are developed and integrated with GeoKSCloud. Finally, an analysis case of seismic influence field analysis is carried out on the constructed cloud portal, with the offshore 7.5 earthquake occurred in Quanzhou area in 1604 as the real case. The peak motion accelerations (including bedrock PGA and ground PGA) for all equally spaced grid points within Fujian Province are calculated via the cloud service proposed. Based on the PGA values of the grid points, the spatial distribution of PGA values covered Fujian Province was also interpolated and further comparative analyzed with the actual survey data. The results show that, the seismic influence field analysis cloud service presented in this paper, which has taken account of the site-specific amplification effecting, can provide more precise seismic influence spatial distribution than the traditional method which consider only the seismic intensity attenuation relationship. The cloud service system with distinct advantage features of cloud service, such as scalable, configurable and transparent, would provide a common technology and a support service platform for intensity rapid reporting system research and application, and also give an innovative operation pattern for public service of seismic intensity rapid reporting.

参考文献

[1] 康兰池,金星.四川地区地震动峰值衰减规律研究[J].地震学报,2009,31(4):34-45.

[2] 吴微微,杨建思,李谊瑞,等.WebGIS在防震减灾工作中的应用与发展趋势[J].国际地震动态,2009(3):20-27.

[3] Wald D J, Quitoriano V, Heaton T H, et al. TriNet "Shake- Maps": Rapid generation of peak ground motion and intensity maps for earthquakes in southern California[J]. Earthquake Spectra, 1999,15(3):537-555.

[4] Sokolov V, Furumura T, Wenzel F. On the use of JMA intensity in earthquake early warning systems[J]. Bulletin of Earthquake Engineering, 2010,8(4):767-786.

[5] Wang D, Xie L. Attenuation of peak ground accelerations from the great Wenchuan earthquake[J]. Earthquake Engineering and Engineering Vibration, 2009,8(2):179-188.

[6] 郝敏,谢礼立.集集地震等震线和PGA、PGV等值线关系 的研究[J].地震工程与工程震动,2006, 26(1):243-248.

[7] 地震预警与烈度速报系统的研究与示范应用[EB/OL]. http://www.cea.gov.cn/manage/html/8a8587881632fa 5c0116674a018300cf/_content/12_10/13/1350116975085. html, 2012.

[8] Asanovic K, Bodik R, Demmel J, et al. A view of the parallel computing landscape[J]. Communications of the ACM,2009,52(10):56-67.

[9] Buyya R, Yeo C S, Venugopal S, et al. Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility[J]. Future Generation computer systems, 2009,25(6):599-616.

[10] Wu L, Kumar Garg S, Buyya R. SLA-based admission control for a Software-as-a-Service provider in Cloud computing environments[J]. Journal of Computer and System Sciences, 2012,78(5):1280-1299.

[11] 姜立新,帅向华,聂高众,等.地震应急联动信息服务技术平台设计探讨[J].震灾防御技术,2011,6(2):156-163.

[12] 姜立新,帅向华,聂高众,等.地震应急指挥协同技术平台设计研究[J].震灾防御技术,2012,7(3):294-302.

[13] Alazawi Z, Altowaijri S, Mehmood R, et al. Intelligent disaster management system based on cloud-enabled vehicular networks[C]. The 11th International Conference on ITS Telecommunications (ITST); St. Petersburg: IEEE; 23-25 Aug, 2011,361-368.

[14] Kelly S M, Mazyck C A. Cloud Computing in Support of Synchronized Disaster Response Operations[D]. Monterey, Califonia: Naval Postgraduate School, 2010.

[15] Velev D, Member, ACSIT, et al. A Feasibility Analysis of Emergency Management with Cloud Computing Integration[J]. International Journal of Innovation, Management and Technology, 2012,3(2):188-193.

[16] Mitchell B. Cloud Computing and Earthquake Preparation [EB/OL].http://compnetworking.about.com/b/2011/03/11/cloud-computing-and-earthquake-preparation.htm, 2013.

[17] Dignan L. Tokyo earthquake, tsunami puts data centers, cloud services at risk[EB/OL]. http://www.zdnet.com/blog/btl/tokyo-earthquake-tsunami-puts-data-centers- cloud-services-at-risk/45955, 2013.

[18] Pierce M, Ma Y, Fox G, et al. Using Service-Based GIS to Support Earthquake Research and Disaster Response[J]. Computing in Science & Engineering, 2012,14(5):21-30.

[19] 胡聿贤,张敏政.缺乏强震观测资料地区地震动参数的估 算方法[J].地震工程与工程振动,1984,4(1):1-11.

[20] 勒超宇,廖旭,黄河,等.基于美国NGA项目的长周期地震动衰减关系研究[J].东北地震研究,2009,26(1):20-24.

[21] 雷建成,高孟潭,俞言祥.四川及邻区地震动衰减关系[J]. 地震学报,2007,29(5):500-511.

[22] 李英民,蔡辉腾,韩军.重庆及邻近地区地震烈度衰减关系研究[J].防灾及减灾工程学报,2007,27(1):17-22.

[23] 林金瑛,王善雄,林锦华.华南沿海地区地震烈度衰减关系[J].海峡地震,2005,3(1):1-9.

[24] 汪素云,俞言祥,高阿甲,等.中国分区地震动衰减关系的确定[J].中国地震,2000,16(2):99-106.

[25] 谢礼立,周雍年,胡成祥,等.地震动反应谱的长周期特性 [J].地震工程与工程振动,1990,10(1):1-20.

[26] 于海英,王栋,杨永强,等.汶川8.0 级地震强震动特征初步分析[J].震灾防御技术,2008,3(4):321-336.

[27] 俞言祥,汪素云.青藏高原东北地区水平向基岩加速度峰值与反应谱衰减关系[J].地震学报,2004,26(6):591-600.

[28] 俞言祥,汪素云.中国东部和西部地区水平向基岩加速度反应谱衰减关系[J].震灾防御技术,2006,1(3):206-217.

[29] 周雍年,周正华,于海英.设计反应谱长周期区段的研究 [J].地震工程与工程振动,2004,24(2):15-18.

[30] Akojwar M R A, Kothari M R V, Kahate M S A, et al. Software as a service with cloud computing[J]. IJECCE, 2012,3(1):149-155.

[31] 左惠强,谢礼立.设定地震影响场的GIS模拟[J].地震学 报,1999,21(4):427-432.

[32] 聂树明.基于GIS的地震影响场设计与应用[J].应用基础与工程科学学报,2008,16(4):546-555.

[33] 陈崇成,林剑峰,吴小竹,等.基于NoSQL的海量空间数据云存储与服务技术[J].地球信息科学学报,2013,15(2): 166-174.

[34] 国家地震局地球物理研究所,国家地震局地质研究所,福建省地震局,等.福建省惠安山前核电厂厂址地震详细调查及其安全性评价报告[R].1994.

文章导航

/