Modeling of urban geological attributes based on conditional simulation: A case study of Guang'an City.

ZHOU Fang; LI Minghui; HUANG Congjun; LIU Yujie; ZHANG Jianlong; WANG Baodi; HAO Ming; WU Zhe

doi:10.19826/j.cnki.1009-3850.2022.06002

2023 Vol. 43, No. 4

Article Contents

Article navigation > Sedimentary Geology and Tethyan Geology > 2023 > 43(4): 844-855

Next Article Previous Article

ZHOU Fang, LI Minghui, HUANG Congjun, LIU Yujie, ZHANG Jianlong, WANG Baodi, HAO Ming, WU Zhe. 2023. Modeling of urban geological attributes based on conditional simulation: A case study of Guang'an City.. Sedimentary Geology and Tethyan Geology, 43(4): 844-855. doi: 10.19826/j.cnki.1009-3850.2022.06002

Citation:

ZHOU Fang, LI Minghui, HUANG Congjun, LIU Yujie, ZHANG Jianlong, WANG Baodi, HAO Ming, WU Zhe. 2023. Modeling of urban geological attributes based on conditional simulation: A case study of Guang'an City.. Sedimentary Geology and Tethyan Geology, 43(4): 844-855. doi: 10.19826/j.cnki.1009-3850.2022.06002

Modeling of urban geological attributes based on conditional simulation: A case study of Guang'an City.

1.
Chengdu Center, China Geological Survey(Geosciences Innovation Center of Southwest China), Chengdu 610218, China
2.
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China
3.
Research Center of Applied Geology , China Geological Survey, Chengdu 610036, China

More Information

Corresponding author: LI Minghui, Lmh680408@163.com

Received Date: 30 August 2021

Revised Date: 06 June 2022

Accepted Date: 20 June 2022

Publish Date: 31 December 2023

Abstract

Abstract

Urban Geological Modeling (UGM) is a crucial approach for implementing visualization of the underground space and recognizing the complex geological conditions of a city, and it is the top priority task of urban geological survey. Previous UGM studies, assuming homogeneous geological characteristics, have resulted in deviated modeling results and applications. In the case of Guang'an city, a conditional simulation interpolation method is used to establish an attributes distribution model with rock samples as the modeling unit. Combined with field surveys, data collection (topographic, boreholes, profile diagrams, stratigraphic columns, etc.) and data analysis, this methodology is capable of presenting the geological discreteness and heterogeneity of the study area. In this paper, the structure, lithology and attributes distribution model were constructed for the study area. Meanwhile, a rating of tunnel country rock was done using Analytic Hierarchy Process (AHP) as a development method. The results indicate that there are four geotechnical zones in the southwest, west, middle and south of the modeling area with significant zonation characteristics. And the ratings of tunnel country rock demonstrate favorable features for utilization by means of tunnel excavation method from deep to shallow, which provides three-dimensional reference for the planning and utilization of urban underground space in Guang'an city. Additionally, future research directions of UGM are being discussed.
- urban geology /
- geological modeling /
- conditional simulation /
- engineering geology /
- underground space

FullText(HTML)

References

[1]	Chen Z L, Chen J Y, Liu H, et al. , 2018. Present status and development trends of underground space in chinese cities: evaluation and analysis[J]. Tunnelling and Underground Space Technology, 71: 253-270. doi: 10.1016/j.tust.2017.08.027 CrossRef Google Scholar
[2]	Doyle M R, 2016. From hydro/geology to the streetscape: evaluating urban underground resource potential[J]. Tunnelling and Underground Space Technology, 55: 83-95. doi: 10.1016/j.tust.2016.01.021 CrossRef Google Scholar
[3]	He H H, He J, Xiao J Z, et al. , 2020. 3D geological modeling and engineering properties of shallow superficial deposits: A case study in Beijing, China[J]. Tunnelling and Underground Space Technology, 100: 1-17. Google Scholar
[4]	Hou W S, Yang L, Deng D C, et al. , 2016. Assessing quality of urban underground spaces by coupling 3D geological models: The case study of Foshan city, South China[J]. Computers & Geosciences, 89: 1-11. Google Scholar
[5]	Lapenna V, Chambers J, Shi B, et al. , 2020. Preface to the special issue on “Frontiers and applications of geological engineering and geophysical monitoring technologies in urban areas”[J]. Engineering Geology, 268: 1-2. Google Scholar
[6]	Paradigm, 2018. GOCAD Operation Manual[S]. Google Scholar
[7]	Price S J, Terrington R L, Busby J, et al. , 2018. 3D ground-use optimisation for sustainable urban development planning: A case-study from Earls Court, London, UK[J]. Tunnelling and Underground Space Technology, 81: 144-164. doi: 10.1016/j.tust.2018.06.025 CrossRef Google Scholar
[8]	Šipetić N, Kuzmić P, 2016. Design the future urban plan of the underground construction from the aspect of geological and geotechnical features of belgrade's inner city area[J]. Procedia Engineering, 165: 641-648. doi: 10.1016/j.proeng.2016.11.761 CrossRef Google Scholar
[9]	Zhu H H, Huang X B, Li X J, et al. , 2016. Evaluation of urban underground space resources using digitalization technologies[J]. Underground Space, 1（2）: 124-136. doi: 10.1016/j.undsp.2016.08.002 CrossRef Google Scholar
[10]	丁俊, 倪军师, 魏伦武, 等, 2005. 西南地区城市环境地质调查工作的思考. 沉积与特提斯地质, 25（4）: 108 − 110 Google Scholar Ding J, Ni J S, Wei L W, et al., 2005. Reflections on the urban environmental geological survey in southwest China[J]. Sedimentary Geology and Tethyan Geology, 25（4）: 108 − 110. Google Scholar
[11]	方寅琛, 龚日祥, 李三凤, 等, 2017. 基于三维地质模型的地下空间开发适宜性评价——以嘉兴城市地质调查工作为例[J]. 上海国土资源, 38（2）: 43 − 45. Google Scholar Fang Y C, Gong R X, Li S F, et al., 2017. Suitability evaluation of underground space development based on a three-dimensional geological model, using the Jiaxing urban geological survey as an example[J]. Geotechnical Investigation&Surveying（9）: 5 − 10. Google Scholar
[12]	胡先莉, 2007. 序贯条件模拟方法研究及应用[D]. 成都: 成都理工大学. Google Scholar Hu X L, 2007. Research and application of sequentially conditional simulation methods[D]. Chengdu: Chengdu University of Technology. Google Scholar
[13]	李佳伟, 2019. 三维城市空间一体化集成建模技术研究[D]. 成都: 成都理工大学. Google Scholar Li J W, 2019. Research on urban space unified 3D modeling technology[D]. Chengdu: Chengdu University of Technology. Google Scholar
[14]	李鹏岳, 韩浩东, 王东辉, 等, 2021. 城市地下空间资源开发和利用适宜性评价现状及发展趋势[J]. 沉积与特提斯地质, 41（1）: 121-128 Google Scholar Li P Y, Han H D, Wang D H, et al. , 2021. Current situation and development trends of suitability evaluation of urban underground space resources[J]. Sedimentary Geology and Tethyan Geology, 41（1）: 121-128. Google Scholar
[15]	廖建三, 彭卫平, 林本海, 2006. 影响广州市浅层地下空间开发利用的地质因素分析及分区评价[J]. 岩石力学与工程学报, 25（S2）: 3357-3362 Google Scholar Liao J S, Peng W P, Lin B H, 2006. Analysis and partition evaluation of geological factors affecting space development and utilization of shallow underground in Guangzhou city[J]. Chinese Journal of Rock Mechanics and Engineering, 25（S2）: 3357-3362. Google Scholar
[16]	林良俊, 李亚民, 葛伟亚, 等, 2017. 中国城市地质调查总体构想与关键理论技术[J]. 中国地质, 44（6）: 1086-1101 Google Scholar Lin L J, Li Y M, Ge W Y, et al. , 2017. General ideas for urban geological survey in China and key theory and techniques[J]. China Geology, 44（6）: 1086-1101. Google Scholar
[17]	彭芳乐, 乔永康, 程光华, 等, 2019. 我国城市地下空间规划现状、问题与对策[J]. 地学前缘, 26（3）: 57-68 doi: 10.13745/j.esf.sf.2019.5.23 CrossRef Google Scholar Peng F L, Qiao Y K, Cheng G H, et al. , 2019. Current situation and existing problems of and coping strategies for urban underground space planning in China[J]. Earth Science Frontiers, 26（3）: 57-68. doi: 10.13745/j.esf.sf.2019.5.23 CrossRef Google Scholar
[18]	屈红刚, 潘懋, 刘学清, 等, 2015. 城市三维地质建模及其在城镇化建设中的应用[J]. 地质通报, 34（7）: 1350-1358 doi: 10.3969/j.issn.1671-2552.2015.07.013 CrossRef Google Scholar Qu H G, Pan M, Liu X Q, et al. , 2015. Urban 3-D geological modeling and its application to urbanization[J]. Geological Bulletin of China, 34（7）: 1350-1358. doi: 10.3969/j.issn.1671-2552.2015.07.013 CrossRef Google Scholar
[19]	阮明, 钱婷, 2020. 城市地下空间三维可视化平台研究[J]. 地理空间信息, 18（4）: 34-37 Google Scholar Ruan M, Qian T, 2020. Research on 3D visualization platform for urban underground space[J]. Geospatial Information, 18（4）: 34-37. Google Scholar
[20]	谭飞, 汪君, 焦玉勇, 等, 2021. 城市地下空间适宜性评价研究国内外现状及趋势[J]. 地球科学, 46（5）: 1896-1908 Google Scholar Tan F, Wang J, Jiao Y Y, et al. , 2021. Current situation and development of urban underground space suitability evaluation[J]. Earth Science, 46（5）: 1896-1908. Google Scholar
[21]	王波, 2013. 城市地下空间开发利用问题的探索和实践[D]. 北京: 中国地质大学（北京）. Google Scholar Wang B, 2013. Exploration and practice of the development and utilization of urban underground space[D]. Beijing: China University of Geosciences（Beijing）. Google Scholar
[22]	王磊, 王运生, 陈云, 等, 2013. 基于GIS的四川广安区地质灾害危险性评价[J]. 中国地质灾害与防治学报, 24（1）: 98-117 Google Scholar Wang L, Wang Y S, Chen Y, et al. , 2013. Geological hazard assessment based on GIS in Guang’an, Sichuan province[J]. The Chinese Journal of Geological Hazard and Control, 24（1）: 98-117. Google Scholar
[23]	魏小佳, 付博, 邓雪莉, 等, 2017. 广安市区城市总体规划用地地质灾害危险性评价[J]. 长春工程学院学报（自然科学版）, 18（2）: 110 − 116. Google Scholar Wei X J, Fu B, Deng X L, et al., 2017. The risk evalution on geological hazards assessment in Guang'an urban overall plan areas[J]. J. Changchun Inst. Tech. （Nat. Sci. Edi.）, 18（2）: 110 − 116. Google Scholar
[24]	邢红星, 琚太忠, 林建阳, 1997. 普通克里格法在矿产储量计算中的应用[J]. 地质与勘探, 33（4）: 46-51 Google Scholar Xin H X, Ju T Z, Lin J Y, 1997. The ordinary kring's application to mineral calculation of reserves[J]. Geology and Prospecting, 33（4）: 46-51. Google Scholar
[25]	熊晶璇, 倪军师, 张成江, 等, 2006. 城市地质环境风险性分区评价GIS软件的设计与实现[J].沉积与特提斯地质, 26（2）: 106 − 109 Google Scholar Xiong J X, Ni J S, Zhang C J, et al., 2006. The design and implementation of the GIS software for risk assessment of urban geo-environments[J]. Sedimentary Geology and Tethyan Geology, 26（2）: 106 − 109. Google Scholar
[26]	赵彦锋, 孙志英, 陈杰, 2010. Kriging插值和序贯高斯条件模拟算法的对比分析[J]. 地球信息科学学报, 12（6）: 767-776 Google Scholar Zhao Y F, Sun Z Y, Chen J, 2010. Analysis and comparison in arithmetic for kriging interpolation and sequentialgaussian conditional simulation[J]. Journal Of Geo-Information Science, 12（6）: 767-776. Google Scholar