Intelligent geological mapping technology and its applications based on the multivariate knowledge and mapping model

HUANG Hui; LU Yanming; LI Yangchun; ZHANG Wenhua; ZHANG Dake; ZHAO Youzhi; LI Chao; CHEN Yuanyuan

2021 Vol. 40, No. 6

Article Contents

Article navigation > Geological Bulletin of China > 2021 > 40(6): 978-987

Next Article Previous Article

HUANG Hui, LU Yanming, LI Yangchun, ZHANG Wenhua, ZHANG Dake, ZHAO Youzhi, LI Chao, CHEN Yuanyuan. Intelligent geological mapping technology and its applications based on the multivariate knowledge and mapping model[J]. Geological Bulletin of China, 2021, 40(6): 978-987.

Citation:

HUANG Hui, LU Yanming, LI Yangchun, ZHANG Wenhua, ZHANG Dake, ZHAO Youzhi, LI Chao, CHEN Yuanyuan. Intelligent geological mapping technology and its applications based on the multivariate knowledge and mapping model[J]. Geological Bulletin of China, 2021, 40(6): 978-987.

Intelligent geological mapping technology and its applications based on the multivariate knowledge and mapping model

1.
Geophysical Survey Center, China Geological Survey, Langfang 065000, Hebei, China
2.
Development and Research Center, China Geological Survey, Beijing 100037, China
3.
Institute of Regional Geological and Mineral Survey of Hebei, Langfang 065000, Hebei, China

More Information

Corresponding author: LU Yanming, yanming-lu-163@163.com

Received Date: 01 March 2019

Revised Date: 29 March 2020

Publish Date: 15 June 2021

Abstract

Abstract

In China, 1:250 000-1:50 000 regional geological survey has accumulated a large amount of database and formed a rich geological map with corresponding scale.How to make full use of these data and maps to compile small scale geological maps, and systematically reflect the latest geological survey results, brings a severe challenge to geological cartographers.Based on the big data, the geological map models are constructed through the multi-knowledge of geology, cartography and database, which can realize the intelligent recognition of geological phenomena such as stratum, magmatic rock, geological structure and their complex relations by computer, which can effectively replace the decision-making of geological cartographers on the synthesis and plotting of complicated geological map elements.Finally, the geological map spatial database is formed through the linkage of map elements and attributes.Focusing on knowledge extraction and map compilation model construction, this paper explores the technology of intelligent geological map compilation, and analyzes and verifies it through the 1∶500 000 intelligent geological map compilation practice in the eastern part of Qinghai Province.The mapping knowledge and model meet the requirements of intelligent geological mapping.The technology of intelligent geological mapping can greatly improve the efficiency and quality of geological map reduction from medium-large scale to small scale.
- multivariate geological knowledge /
- geological mapping model /
- geological body generalization /
- artificial intelligence /
- unification of database and maps

FullText(HTML)

References

[1]	乔秀夫, 丁孝忠. 区域地质调查与编图综合研究——写在新编《中国地质图集》出版之际[J]. 地质通报, 2003, 22(10): 769-774. doi: 10.3969/j.issn.1671-2552.2003.10.004 CrossRef Google Scholar
[2]	王家耀. 空间数据自动综合研究进展及趋势分析[J]. 测绘科学技术学报, 2008, 25(1): 1-8. Google Scholar
[3]	武芳, 巩现勇, 杜佳威. 地图制图综合回顾与前望[J]. 测绘学报, 2017, 46(10): 1645-1664. doi: 10.11947/j.AGCS.2017.20170287 CrossRef Google Scholar
[4]	李仰春, 王永志, 陈圆圆, 等. 智绘地质——新一代智能化地质编图模式及应用[J]. 地质通报, 2020, 39(6): 861-870. Google Scholar
[5]	何文娜, 朱长青, 李仰春, 等. 智能地质体综合技术在地质图缩编中的应用[J]. 地质通报, 2020, 39(6): 871-879. Google Scholar
[6]	何文娜, 朱长青, 王永志, 等. 智绘地质——一种基于MapGIS的地质编图智能化系统[J]. 地球物理学进展, 2019, 34(5): 2030-2036. Google Scholar
[7]	Tomlin C D. GIS and Cartographic modeling[M]. California: Esri Press, 2012. Google Scholar
[8]	BGS. DiGMapGB digital geological maps of Great Britain Datasets[EB/OL]. [2018-10-24](2019-08-01). http://www.bgs.ac.uk/products/digitalmaps/DiGMapGBMaps.html, 2019. Google Scholar
[9]	OneGeology. Portal[EB/OL]. [2018-10-24](2019-08-01). http://www.onegeology.org/portal/home.html, 2019. Google Scholar
[10]	Smirnoff A, Huot-Vezina G, Paradis S J, et al. Generalizing geological maps with the GeoScaler software: The case study approach[J]. Computers & Geosciences, 2012, (40): 66-86. Google Scholar
[11]	李廷栋. 当前国际地质编图的一些动态[J]. 地质论评, 2013, 2: 208, 216. Google Scholar
[12]	叶天竺, 黄崇轲, 邓志奇. 1: 250万中华人民共和国数字地质图空间数据库[J]. 中国地质, 2017, 44(S1): 19-24. Google Scholar
[13]	庞健峰, 丁孝忠, 韩坤英, 等. 1: 100万中华人民共和国数字地质图空间数据库[J]. 中国地质, 2017, 44(S1): 8-18. Google Scholar
[14]	中国地质调查局基础调查部. 中国小比例尺地质图概况[J]. 中国地质, 2018, 45(2): 423. Google Scholar
[15]	任纪舜, 牛宝贵, 王军, 等. 1: 500万国际亚洲地质图[J]. 地球学报, 2013, 34(1): 24-30. Google Scholar
[16]	于萍萍, 陈建平, 柴福山, 等. 基于地质大数据理念的模型驱动矿产资源定量预测[J], 地质通报, 2015, 34(7): 1333-1343. doi: 10.3969/j.issn.1671-2552.2015.07.011 CrossRef Google Scholar
[17]	Charlie F. Modeling active database-driven cartography within GIS databases[C]//The 21st International Cartographic Conference of the International Cartographic Association. Durban, South Africa, 2003. Google Scholar
[18]	Buckly A, Frye C, Buttenfield B. An Information Model for Maps: Towards Cartographic Production from GIS Databases[EB/OL]. [2018-10-24](2019-08-01). http://icaci.org/files/documents/ICC-proceedings/ICC2005/htm/pdf/oral/TEMA1/SESSION1/AILEEN%20BUCKLEY.pdf, 2019. Google Scholar
[19]	陈刚, 姚仲友, 王天刚, 等. 大洋洲地区系列地质图件编制[J]. 地质通报, 2014, 33(2/3): 159-163. Google Scholar
[20]	王家耀, 钱海忠. 制图综合知识及其应用[J]. 武汉大学学报(信息科学版), 2006, 5: 382-386, 439. Google Scholar
[21]	王家耀, 孙群, 王光霞, 等. 地图学原理与方法[M]. 北京: 科学出版社, 2014. Google Scholar
[22]	van Gasselt S, Nass A. Planetary mapping——The data model's perspective and GIS framework[J]. Planetary and Space Science, 2010, (59): 12. Google Scholar
[23]	陈军, 王东华, 商瑶玲, 等. 国家1: 50 000数据库更新工程总体设计研究与技术创新[J]. 测绘学报, 2010, 39(1): 7-10. Google Scholar
[24]	王杨刚, 郝丽荣, 黄辉, 等. 基于空间数据和专家知识驱动的地质编图技术研究与应用[J]. 地质通报, 2019, 38(12): 2067-2076. Google Scholar
[25]	赵鹏大. 地质大数据特点及其合理开发利用[J], 地学前缘, 2019, 26(4): 1-5. Google Scholar
[26]	黄崇轲, 李浩川. 中华人民共和国1: 50万数字地质图和空间元数据[J]. 中国地质, 2001, 28(2): 43-48. doi: 10.3969/j.issn.1000-3657.2001.02.008 CrossRef Google Scholar
[27]	王家耀, 孙力楠, 成毅. 创新思维改变地图学[J]. 地理空间信息, 2011, 9(2): 1-5. doi: 10.3969/j.issn.1672-4623.2011.02.001 CrossRef Google Scholar
[28]	罗建民, 张旗. 大数据开创地学研究新途径: 查明相关关系, 增强研究可行性[J]地学前缘, 2019, 26(4): 6-12. Google Scholar
[29]	王家耀, 邹建华. 地图制图数据处理的模型方法[M]. 北京: 解放军出版社, 1992. Google Scholar
[30]	王家耀. 地图学与地理信息工程研究[M]. 北京: 科学出版社, 2005. Google Scholar
[31]	王光霞. 数字环境下制图综合概念和方法的拓展[J]. 测绘学院学报, 2005, 9: 207-211. doi: 10.3969/j.issn.1673-6338.2005.03.017 CrossRef Google Scholar
[32]	邬宽廉, 左群超, 邬可筠. 建立地质图数据库的地质年代代码问题[J]. 地质通报, 2008, 27(7): 1103-1106. doi: 10.3969/j.issn.1671-2552.2008.07.025 CrossRef Google Scholar
①	DD2006-06. 中国地质调查局地质调查技术标准[S]. 中国地质调查局, 2006. Google Scholar
②	黄辉, 路彦明, 张大可, 等. 基础地质图更新编制技术研究与数据库建设报告. 廊坊: (原)武警黄金地质研究所, 2015-2017. Google Scholar
③	黄辉, 路彦明, 张文华, 等. 基础地质数据更新技术流程方案. 廊坊: (原)武警黄金地质研究所, 2015-2017. Google Scholar
④	张克信, 朱云海, 樊光明. 1: 25万临夏市幅(I48C001001)区域地质调查报告(修测). 武汉: 中国地质大学(武汉)地质调查研究院, 2006. Google Scholar