留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

大数据时代地质灾害数据管理及应用模式探讨

刘军旗 刘强 刘千慧 张夏林 林晨 周鑫 李国策

刘军旗, 刘强, 刘千慧, 张夏林, 林晨, 周鑫, 李国策. 大数据时代地质灾害数据管理及应用模式探讨[J]. 地质科技通报, 2021, 40(6): 276-282, 292. doi: 10.19509/j.cnki.dzkq.2021.0627
引用本文: 刘军旗, 刘强, 刘千慧, 张夏林, 林晨, 周鑫, 李国策. 大数据时代地质灾害数据管理及应用模式探讨[J]. 地质科技通报, 2021, 40(6): 276-282, 292. doi: 10.19509/j.cnki.dzkq.2021.0627
Liu Junqi, Liu Qiang, Liu Qianhui, Zhang Xialin, Lin Chen, Zhou Xin, Li Guoce. Discussion of geological hazard data management and application model in big data era[J]. Bulletin of Geological Science and Technology, 2021, 40(6): 276-282, 292. doi: 10.19509/j.cnki.dzkq.2021.0627
Citation: Liu Junqi, Liu Qiang, Liu Qianhui, Zhang Xialin, Lin Chen, Zhou Xin, Li Guoce. Discussion of geological hazard data management and application model in big data era[J]. Bulletin of Geological Science and Technology, 2021, 40(6): 276-282, 292. doi: 10.19509/j.cnki.dzkq.2021.0627

大数据时代地质灾害数据管理及应用模式探讨

doi: 10.19509/j.cnki.dzkq.2021.0627
基金项目: 

国家自然科学基金项目 41572336

水利部重点项目"基于大数据的三峡工程湖北库区移民安置区地质安全智能管控关键技术研究 

详细信息
    作者简介:

    刘军旗(1971-), 男, 副研究员, 主要从事地质灾害大数据技术研究工作。E-mail: liujqg@126.com

  • 中图分类号: X43

Discussion of geological hazard data management and application model in big data era

  • 摘要: 地质灾害数据是一种多源异构数据,是典型的大数据。关系型数据库是目前地质灾害数据的主流管理方法。在地质灾害数据中,非结构化数据占有很大的比例。由于关系模型难以有效地管理非结构化数据,因而关系型数据库对地质灾害数据的管理效果并不理想。这种弱点,在大数据时代将会被进一步放大,并对地质数据挖掘和大数据分析造成一定的影响。针对大数据时代地质灾害数据的管理模式,从泛结构化地质数据管理、应用模型和分布式异构系统的集成等方面进行了探讨。认为地质灾害数据的有效管理应该把文件系统、关系型数据库和NoSQL结合起来,并提出了一种基于双C模型和中间件结合的泛结构化地质数据管理与应用模式。这种模式已应用在多个工程中,取得了良好的效果。

     

  • 图 1  泛结构化地质大数据管理模式

    Figure 1.  Pan-structured geological big data management mode

    图 2  三维地表通过水平面投影得到平面图(AC实例)

    Figure 2.  A plan obtained by horizontal projection from three-dimensional surface: An instance of AC

    图 3  地质数据处理的双C模型

    Figure 3.  Double C model for geological data processing

    图 4  地质大数据管理及应用集成方案

    Figure 4.  Geological big data management and application integration scheme

    表  1  钻孔孔径记录表结构示例

    Table  1.   Structure of borehole aperture record table

    序号 字段名称 字段编号 字段类型 字段长度 小数位
    1 工程名称 GCEABA 字符型 20
    2 勘察阶段 GCJBA 字符型 14
    3 钻孔编号 GCJCBN 字符型 10
    4 孔径序号 IOTXH 字符型 2
    5 钻孔直径/mm SWNCALZ 数值型 4 0
    6 终止深度/m MDBWAC 数值型 6 2
    注:表中的字段编号是对应字段的标准识别码
    下载: 导出CSV
  • [1] 吴润泽, 程温鸣, 刘军旗, 等. 三峡库区地质灾害防治信息系统及预警指挥系统数据管理模式探讨[J]. 中国地质灾害与防治学报, 2018, 29(5): 102-107. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDH201805017.htm

    Wu R Z, Chen W M, Liu J Q, et al. Discussion on the data management mode of geologic disaster prevention and control information system and early warning command system in the Three Gorges Reservoir Area[J]. The Chinese Journal of Geological Hazard and Control, 2018, 29(5): 102-107(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDH201805017.htm
    [2] Viktor M-S, Kenneth C. Big data: A revolution that will transform how we live, work, and think[M]. Eamon Dolan: Houghton Mifflin Harcourt, 2013.
    [3] Li D R. Towards geo-spatial information science in big data Era[J]. Acta Geodetica et Cartographica Sinica, 2016, 45(4): 379-384. http://en.cnki.com.cn/Article_en/CJFDTOTAL-CHXB201604002.htm
    [4] He F H, Gu L J, Wang T, et al. The synthetic geo-ecological environmental evaluation of a coastal coal-mining city using spatiotemporal big data: A case study in Longkou, China[J]. Journal of Cleaner Production, 2017, 142(2): 854-866.
    [5] 刘军旗, 黄长青, 吴冲龙, 等. 工程地质信息处理技术与方法概论[M]. 武汉: 中国地质大学出版社, 2015.

    Liu J Q, Huang C Q, Wu C L, et al. Introduction to engineering geology information processing technology and method[M]. Wuhan: China University of Geosciences Press, 2015(in Chinese).
    [6] Baars H, Kemper H G. Management support with structured and unstructured data: An integrated business intelligence framework[J]. Information Systems Management, 2008, 25(2): 132-148. doi: 10.1080/10580530801941058
    [7] 陈金水, 王崟. 非结构化数据存储管理的实用化方法[J]. 计算机与现代化, 2006(8): 25-28. doi: 10.3969/j.issn.1006-2475.2006.08.008

    Chen J S, Wang Y. A method for unstructured data storage management[J]. Computer and Modernization, 2006(8): 25-28(in Chinese with English abstract). doi: 10.3969/j.issn.1006-2475.2006.08.008
    [8] Carver T, Berriman M, Tivey A, et al. Artemis and ACT: Viewing, annotating and comparing sequences stored in a relational database[J]. Bioinformatics, 2008, 24(23): 2672-2676. doi: 10.1093/bioinformatics/btn529
    [9] Sacco G M, Nigrelli G, Bosio A, et al. Dynamic taxonomies applied to a web- based relational database for geo-hydrological risk mitigation[J]. Computers & Geosciences, 2012, 39: 182-187. http://www.onacademic.com/detail/journal_1000035031235010_465a.html
    [10] Chang F, Dean J, Ghemawat S, et al. Big table: A distributed storage system for structured data[J]. Acm Transactions on Computer Systems, 2008, 26(2): 205-218. http://web.stanford.edu/class/cs240/old/sp2014/readings/bigtable-osdi06.pdf
    [11] 吴广君, 王树鹏, 陈明, 等. 海量结构化数据存储检索系统[J]. 计算机研究与发展, 2012, 49(增刊1): 1-5. https://www.cnki.com.cn/Article/CJFDTOTAL-JFYZ2012S1004.htm

    Wu G J, Wang S P, Chen M, et al, Massive structured data oriented storageand retrieve system[J]. Journal of Computer Research and Development, 2012, 49(S1): 1-5(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-JFYZ2012S1004.htm
    [12] Dean J, Ghemawat S. Mapreduce: Simplified data processing on large clusters[J]. Communications of the Acm, 2008, 51(1): 107-113. doi: 10.1145/1327452.1327492
    [13] McKenna A, Hanna M, Banks E, et al. The genome analysis toolkit: A map reduce framework for analyzing next-generation DNA sequencing data[J]. Genome Research, 2010, 20(9): 1297-1303. doi: 10.1101/gr.107524.110
    [14] 郎波, 张博宇. 面向大数据的非结构化数据管理平台关键技术[J]. 信息技术与标准化, 2013, 434(10): 53-56. doi: 10.3969/j.issn.1671-539X.2013.10.013

    Lang B, Zhang B Y. Key techniques for building big-data-oriented unstructured data management platform[J]. Information Technology and Standardization, 2013, 434(10): 53-56(in Chinese with English abstract). doi: 10.3969/j.issn.1671-539X.2013.10.013
    [15] O'Driscoll A, Daugelaite J, Sleator R D. "Big data", Hadoop and cloud computing in genomics[J]. Journal of Biomedical Informatics, 2013, 46(5): 774-781. doi: 10.1016/j.jbi.2013.07.001
    [16] 张丰. 面向网格的海量时空数据访问、集成与互操作研究[D]. 杭州: 浙江大学, 2007.

    Zhang F. Research on massivespatio-temporal data access, integration and interoperation for grid[D]. Hangzhou: Zhejiang University, 2007(in Chinese with English abstract).
    [17] Amorim R C, Castro J A, Silva J R, et al. A comparison of research data management platforms: architecture, flexible metadata and interoperability[J]. Universal Access in the Information Society, 2017, 16(4): 851-862. doi: 10.1007/s10209-016-0475-y
    [18] Heinzelman W B, Murphy A L, Carvalho H S, et al. Middleware to support sensor network applications[J]. Ieee Network, 2004, 18(1): 6-14. doi: 10.1109/MNET.2004.1265828
    [19] 罗颖. 针对面向多源异构数据的数据集成中间件的设计与开发[J]. 网络安全技术与应用, 2019(6): 55-57. doi: 10.3969/j.issn.1009-6833.2019.06.032

    Luo Y. Design and development of data integration middleware for multi-source heterogeneous data[J]. Network Security Technology and Application, 2019, (6): 55-57(in Chinese with English abstract). doi: 10.3969/j.issn.1009-6833.2019.06.032
    [20] George G, Haas M, Pentland A. Big data and management[J]. Academy of Management Journal, 2014, 57(2): 321-326. doi: 10.5465/amj.2014.4002
    [21] Cattell R. Scalable SQL and NoSQL data stores[J]. Sigmod Record, 2010, 39(4): 12-27. http://www.researchgate.net/profile/Rick_Cattell/publication/220415613_Scalable_SQL_and_NoSQL_data_stores/links/568a189608ae1e63f1fabc20.pdf
    [22] Leavitt N. Will NoSQL databases live up to their promise?[J]. Computer, 2010, 43(2): 12-14. doi: 10.1109/MC.2010.58
    [23] 申德荣, 于戈, 王习特, 等. 支持大数据管理的NoSQL系统研究综述[J]. 软件学报, 2013, 24(8): 1786-1803. https://www.cnki.com.cn/Article/CJFDTOTAL-RJXB201308008.htm

    Shen D R, Yu G, Wang X T, et al. Survey on NoSQL for management of big data[J]. Journal of Software, 2013, 24(8): 1786-1803(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-RJXB201308008.htm
    [24] Liu J Q, Mao X P, Wu C L, et al. Study on a computing technique suitable for true 3D modeling of complex geologic bodies[J]. Journal Geological Society of India, 2013, 82: 570-574. doi: 10.1007/s12594-013-0189-1
    [25] 刘军旗. 工程地质数据处理方法探讨: 以水利枢纽工程为例[J]. 工程地质学报, 2014, 22(5): 989-996. https://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ201405035.htm

    Liu J Q. Engineering geological data processing method withwater conservancy hub project, as example[J]. Journal of Engineering Geology, 2014, 22(5): 989-996(in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ201405035.htm
    [26] Keim D A, Panse C, Sips M, et al. Pixel based visual data mining of geo-spatial data[J]. Computers & Graphics-UK, 2004, 28(3): 327-344. http://pdfs.semanticscholar.org/f1c5/589138d0b96923417e9be5b5eba0447db4dd.pdf
    [27] 吴冲龙, 刘刚, 周琦, 等. 地质科学大数据统合应用的基本问题[J]. 地质科技通报, 2020, 39(4): 1-11. doi: 10.19509/j.cnki.dzkq.2020.0401

    Wu C L, Liu G, Zhou Q, et al. Fundamental problems of integrated application of big data in geoscience[J]. Bulletin of Geological Science and Technology, 2020, 39(4): 1-11(in Chinese with English abstract). doi: 10.19509/j.cnki.dzkq.2020.0401
    [28] Fan J Q, Han F, Liu H. Challenges of big data analysis[J]. National Science Review, 2014, 1(2): 293-314. doi: 10.1093/nsr/nwt032
    [29] 田宜平, 刘维安, 张夏林. 基于等角度变比例投影的矿体轮廓线自动匹配方法研究[J]. 地质科技通报, 2020, 39(1): 175-180. doi: 10.19509/j.cnki.dzkq.2020.0119

    Tian Y P, Liu W A, Zhang X L. Automatic matching of ore body contour line based on equal-angle and variable proportion projection[J]. Bulletin of Geological Science and Technology, 2020, 39(1): 175-180(in Chinese with English abstract). doi: 10.19509/j.cnki.dzkq.2020.0119
    [30] Noor A, Shukri M. Java based distributed multimedia data streaming with object request broker[D]. Kuala Lumpur, Malaysia: IEEE International Symposium on Information Technology, 2008.
  • 加载中
图(4) / 表(1)
计量
  • 文章访问数:  1095
  • PDF下载量:  274
  • 被引次数: 0
出版历程
  • 收稿日期:  2020-09-17

目录

    /

    返回文章
    返回