Précédent|Prochain

Digital twin human geographic environment

  • role： First author第一作者
  • Affiliation：

    School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China

  • Email：huilin@cuhk.edu.hk
  • Introduction：林珲，研究方向为虚拟地理环境、空间综合人文与社会科学、多云多雨遥感。E-mail： huilin@cuhk.edu.hk
LIN Hui1,  
  • role： Corresponding author通信作者
  • Affiliation：

    Department of Information and Communication, Academy of Army Armored Forces, Beijing 100072, China

  • Email：xublmail@126.com
  • Introduction：徐丙立，研究方向为虚拟地理环境、地理协同。E-mail： xublmail@126.com
XU Bingli2*,  
  • Affiliation：

    School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China

XIAO Xin1,  
  • Affiliation：

    Department of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen 518055, China

CHEN Yuting3

résumé

The human geographic environment is a comprehensive environment formed by the interaction of human activities and the geographic environment, which is complex and highly vulnerable. Introducing the digital twin method to build a new framework of research on human geography issues has great disciplinary importance and application value because this framework has the characteristics of driving the virtual according to the real, controlling the real according to the virtual, and the coordinated evolution of the virtual and the real. It also helps avoid disturbing the real environment, explores complex problems in depth, and optimizes the control scheme of real geographical problems. Based on the review of relative research in China and abroad, a conceptual model of the digital twin human geographic environment is proposed, and its systematic connotation is elaborated. The major components of this system include the real human geographic environment, the virtual human geographic environment, and the information interaction between them. Through the digital twin construction and simulation of the geographic environment, human activities as well as human-nature interaction, the virtual and real synergy, complementary advantages, and coevolution between the virtual and the real environment can be realized. Furthermore, a technical framework with bilateral technology roadmap for the implementation of digital twin human geographic environments is proposed. One route is to complete the comprehensive perception and twin reproduction of the real human geographic environment through digital accurate mapping to the virtual geography environment, and the other route is to achieve intelligent feedback of the virtual human geographic environment and its manipulation on the real human geographic environment through multichannel virtual-real interaction. On the basis of the above, a hierarchical construction scheme of the digital twin human geographic environment platform, which covers five sub platforms, namely, collaborative monitoring and environmental awareness platform, multimodal full-scale database, intelligent modeling and simulation technology integration, high-performance spatiotemporal computing engine, and cross-domain knowledge application for decision making is designed. Supported by the Nanchang Subcenter of the UNESCO International Natural and Cultural Heritage Space Technology Center, the digital twin of Jiangxi Bailudong Academy, the education base of Chinese Confucian culture, is taken as a typical case to demonstrate the construction method, main function, and result form of the digital twin human geographic environment. The conclusions are drawn from three perspectives: (1) The digital twin human geographic environment should be taken as a creative method for the exploratory learning of human geography. (2) The digital twin human geographic environment is currently the best way to build a geographic metaverse with human activities. (3) The virtual geographic environment can provide theoretical basis for the construction of the digital twin human geographic environment. Lastly, the purpose of this paper is to throw bricks and spark jade to arouse scholars’ thinking on the research of coupling digital twins and human geographic environment, and to promote the sustainable development of human geography jointly.

mots-clés

remote sensing;Digital twins;Human geographic environment;virtual geographic environments;collaboration between the real and the virtual;Bailudong Academy

References

  1. 1.
    Bainbridge W S. 2007. The scientific research potential of virtual worlds. Science, 317(5837): 472-476
  2. 2.
    Batty M. 2018. Digital twins. Environment and Planning B: Urban Analytics and City Science, 45(5): 817-820
  3. 3.
    Bauer P, Stevens B and Hazeleger W. 2021. A digital twin of earth for the green transition. Nature Climate Change, 11(2): 80-83
  4. 4.
    Baumgartner C. 2022. The world's first digital cell twin in cancer electrophysiology: a digital revolution in cancer research?. Journal of Experimental and Clinical Cancer Research, 41(1): 298
  5. 5.
    Bol P K, Xia C J and Wang H S. 2018. The digital humanities and a cyberinfrastructure for China studies. Library Journal, 37(11): 18-25
  6. 6.
    Cai Z R, Fang C Y, Zhang Q and Chen F L. 2021. Joint development of cultural heritage protection and tourism: the case of mount lushan cultural landscape heritage site. Heritage Science, 9(1): 86
  7. 7.
    Chen J, Liu J J and Tian H B. 2022. Basic directions and technological path for building 3D realistic geospatial scene in China. Geomatics and Information Science of Wuhan University, 47(10): 1568-1575
  8. 8.
    Fan C, Zhang C, Yahja A and Mostafavi A. 2021. Disaster city digital twin: a vision for integrating artificial and human intelligence for disaster management. International Journal of Information Management, 56: 102049
  9. 9.
    Fan Z L, Chen C C and Huang H Y. 2022. Immersive cultural heritage digital documentation and information service for historical figure metaverse: a case of Zhu Xi, Song Dynasty, China. Heritage Science, 10(1): 148
  10. 10.
    Gan H X and Wu H N. 2022. Study on the construction of the digital twin Pearl River Basin. China Flood and Drought Management, 32(2): 36-39
  11. 11.
    Grieves M. 2014. Digital Twin: Manufacturing Excellence Through Virtual Factory Replication. [2022-11-30].
  12. 12.
    Guo J J, Bilal M, Qiu Y Y, Qian C, Xu X L and Raymond Choo K K. 2022. Survey on digital twins for internet of vehicles: fundamentals, challenges, and opportunities. Digital Communications and Networks, In Press
  13. 13.
    Hollenbeck D and Chen Y Q. 2022. A digital twin framework for environmental sensing with suas. Journal of Intelligent and Robotic Systems, 105(1): 1
  14. 14.
    Hribernik K, Cabri G, Mandreoli F and Mentzas G. 2021. Autonomous, context-aware, adaptive digital twins—state of the art and roadmap. Computers in Industry, 133: 103508
  15. 15.
    Huang W H, Zhang Y J and Zeng W. 2022. Development and application of digital twin technology for integrated regional energy systems in smart cities. Sustainable Computing: Informatics and Systems, 36: 100781
  16. 16.
    Huang Y, Yu S, Luo B, Li R B, Li C W and Huang W. 2022. Development of the digital twin Changjiang River with the pilot system of joint and intelligent regulation of water projects for flood management. Journal of Hydraulic Engineering, 53(3): 253-269
  17. 17.
    Johnston R. 2024. geography. [2022-11-30].
  18. 18.
    Knowles A. 2014. The contested nature of historical GIS. International Journal of Geographical Information Science, 28(1): 206-211
  19. 19.
    Kwan M P. 2021. The stationarity bias in research on the environmental determinants of health. Health and Place, 70: 102609
  20. 20.
    Laubenbacher R, Sluka J P and Glazier J A. 2021. Using digital twins in viral infection. Science, 371(6534): 1105-1106
  21. 21.
    Li D R, Yu W B and Shao Z F. 2021. Smart city based on digital twins. Computational Urban Science, 1(1): 4
  22. 22.
    Li S C, Zhang W B, Chen L Y, Liang Z, Zhang Y J and Wang Z. 2022. Digital twin space and its applications: concurrent discussion on the space reconstruction of geographical research. Acta Geographica Sinica, 77(3): 507-517
  23. 23.
    Li W X and Kou H Z. 2022. Thoughts on the construction of digital twin Yellow River in the new stage. China Flood and Drought Management, 32(2): 27-31
  24. 24.
    Li X M, Luo J, Li Y L, Wang W X, Hong W Y, Liu M W, Li X Y and Lv Z H. 2022. Application of effective water-energy management based on digital twins technology in sustainable cities construction. Sustainable Cities and Society, 87: 104241
  25. 25.
    Lin H and Xu B L. 2007. Some thoughts on virtual geographic environments. Geography and Geo-Information Science, 23(2): 1-7
  26. 26.
    Lin H, Zhang J, Yang P and Liu J. 2006. Development on spatially integrated humanities and social science. Geo-Information Science, 8(2): 30-37
  27. 27.
    Liu W and Ye Y. 2017. Exploring technical system and theoretical structure of digital humanities. Journal of Library Science in China, 43(5): 32-41
  28. 28.
    Liu Y, Liu X, Gao S, Gong L, Kang C G, Zhi Y, Chi G H and Shi L. 2015. Social sensing: a new approach to understanding our socioeconomic environments. Annals of the Association of American Geographers, 105(3): 512-530
  29. 29.
    Lü G N, Zhou C H, Lin H, Chen M, Yue S S and Wen Y N. 2021. Development overview and some thoughts on geographic synthesis. Chinese Science Bulletin, 66(20): 2542-2554
  30. 30.
    Ma S Y, Ding W, Liu Y, Ren S and Yang H D. 2022. Digital twin and big data-driven sustainable smart manufacturing based on information management systems for energy-intensive industries. Applied Energy, 326: 119986
  31. 31.
    Mamgain G. 2022. What Is Human Geography? Meaning, Definition, Nature, Source. [2022-11-30].
  32. 32.
    Qin K, Lin H, Hu D, Xu G, Zhang X X, Lu B B and Ye X Y. 2020. A review of spatially integrated humanities and social sciences. Journal of Geo-Information Science, 22(5): 912-928
  33. 33.
    Tao F, Cheng J F, Qi Q L, Zhang M, Zhang H and Sui F. 2018. Digital twin-driven product design, manufacturing and service with big data. The International Journal of Advanced Manufacturing Technology, 94(9/12): 3563-3576
  34. 34.
    Tao F, Zhang H, Liu A and Nee A Y C. 2019. Digital twin in industry: state-of-the-art. IEEE Transactions on Industrial Informatics, 15(4): 2405-2415
  35. 35.
    Tuegel E J, Ingraffea A R, Eason T G and Spottswood S M. 2011. Reengineering aircraft structural life prediction using a digital twin. International Journal of Aerospace Engineering, 2011: 154798
  36. 36.
    VanDerHorn E and Mahadevan S. 2021. Digital twin: generalization, characterization and implementation. Decision Support Systems, 145: 113524
  37. 37.
    Van Dinter R, Tekinerdogan B and Catal C. 2022. Predictive maintenance using digital twins: a systematic literature review. Information and Software Technology, 151: 107008
  38. 38.
    Verdouw C, Tekinerdogan B, Beulens A and Wolfert S. 2021. Digital twins in smart farming. Agricultural Systems, 189: 103046
  39. 39.
    Voosen P. 2020. Europe builds 'digital twin' of Earth to hone climate forecasts. Science, 370(6512): 16-17
  40. 40.
    Wang J. 2010. On the practicality of humane social sciences research. Educational Research, 31(4): 25-29
  41. 41.
    Wang W X, Guo H, Li X M, Tang S J, Xia J Z and Lv Z H. 2022. Deep learning for assessment of environmental satisfaction using BIM big data in energy efficient building digital twins. Sustainable Energy Technologies and Assessments, 50: 101897
  42. 42.
    Wei S L. 2021. Is human digital twin possible?. Computer Methods and Programs in Biomedicine Update, 1: 100014
  43. 43.
    Xiao X, Fang C Y and Lin H. 2020. Characterizing tourism destination image using photos’ visual content. ISPRS International Journal of Geo-information, 9(12): 730
  44. 44.
    Xiao X, Fang C Y, Lin H and Chen J F. 2022. A framework for quantitative analysis and differentiated marketing of tourism destination image based on visual content of photos. Tourism Management, 93: 104585
  45. 45.
    Yang J N, Langley R S and Andrade L. 2022. Digital twins for design in the presence of uncertainties. Mechanical Systems and Signal Processing, 179: 109338
  46. 46.
    Yano K, Nakaya T, Isoda Y, Takase Y, Kawasumi T, Matsuoka K, Seto T, Kawahara D, Tsukamoto A, Inoue M and Kirimura T. 2008. Virtual Kyoto: 4DGIS comprising spatial and temporal dimensions. Chigaku Zasshi (jounal of Geography), 117(2): 464-478
  47. 47.
    Ye Y T, Jiang Y Z, Liang L L, Zhao H L, Gu J J, Dong J P, Cao Y and Duan H. 2022. Digital twin watershed: new infrastructure and new paradigm of future watershed governance and management. Advances in Water Science, 33(5): 683-704
  48. 48.
    Zhang J. 2020. Zhu Xi of Yang Zi River Right Track Test. Nanchang: Jiangxi Normal University
  49. 49.
    Zhu Q, Zhang L G, Ding Y L, Hu H, Ge X M, Liu M W and Wang W. 2022. From real 3D modeling to digital twin modeling. Acta Geodaetica et Cartographica Sinica, 51(6): 1040-1049

Lire l'article complet

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website