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Research on Block Storage and Analysis Model for Belt and Road Initiative Ecological Carrying Capacity Evaluation System

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Data Science (ICPCSEE 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1258))

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Abstract

Assessment and analysis of ecological carrying capacity are significant issues in regional sustainable development. Large-scale ecological carrying capacity research consume a lot of time and labor costs. In this paper, considering redundant storage, on-demand computing, and multi-scale representation, a block storage and analysis model (BSAM) is proposed to make computation faster. Taking “The Belt and Road Initiative” as an example, the ecological carrying capacity evaluation system (ECCES) was developed. The results show that the problems of low calculation efficiency and high time cost were effectively solved with improved data storage, analysis, and expression approaches used by the ECCES. And the calculation speed is improved with the BSAM. Moreover, in the BSAM, the complexity of the original data is under a more significant impact on computing speed. In contrast, the complexity of an algorithm has a smaller influence on computing speed. Furthermore, the early warning push function and automated report function can generate the ecological carrying capacity states or changes automatically, which can improve the real-time, usability, and convenience of the ecological carrying capacity assessment.

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References

  1. Arrow, K., et al.: Economic growth, carrying capacity, and the environment. Ecol. Econ. 15(2), 91–95 (1995)

    Article  Google Scholar 

  2. Rees, W.E.: Ecological footprints and appropriated carrying capacity: what urban economics leaves out. Environ. Urban. 4(2), 121–130 (1992)

    Article  Google Scholar 

  3. Feng, Z., et al.: Research on the carrying capacity of resources and environment in the past 100 years: from theory to practic. Resour. Sci. 39(03), 379–395 (2017). (in Chinese)

    Google Scholar 

  4. Yan, H., et al.: Status of land use intensity in China and its impacts on land carrying capacity. J. Geog. Sci. 27(4), 387–402 (2017). https://doi.org/10.1007/s11442-017-1383-7

    Article  Google Scholar 

  5. Du, W., et al.: Evaluation methods and research trends of ecological carrying capacity. J. Resour. Ecol. 9(02), 115–124 (2018). (in Chinese)

    Google Scholar 

  6. Rönnbäck, P., et al.: Ecosystem goods and services from Swedish coastal habitats: identification, valuation, and implications of ecosystem shifts. AMBIO J. Hum. Environ. 36(7), 534–544 (2007)

    Article  Google Scholar 

  7. Ouyang, Z., et al.: Improvements in ecosystem services from investments in natural capital. Science 352(6292), 1455–1459 (2016)

    Article  Google Scholar 

  8. Cuadra, M., Björklund, J.: Assessment of economic and ecological carrying capacity of agricultural crops in Nicaragua. Ecol. Ind. 7(1), 133–149 (2007)

    Article  Google Scholar 

  9. Byron, C., et al.: Calculating ecological carrying capacity of shellfish aquaculture using mass-balance modeling: Narragansett Bay, Rhode Island. Ecol. Modell. 222(10), 1743–1755 (2011)

    Article  Google Scholar 

  10. Xin, Z., Xu, Z.: Analysis of water resources carrying capacity of the “Belt and Road” initiative countries based on virtual water theory. J. Resour. Ecol. 10(6), 574–583 (2019)

    Google Scholar 

  11. Teo, H.C., et al.: Environmental impacts of infrastructure development under the belt and road initiative. Environments 6(6), 72 (2019)

    Article  Google Scholar 

  12. Sun, P., Liu, S.: Large scale eco-hydrological model and its integration with GIS. Acta Ecol. Sin. 23(10), 2115–2124 (2003)

    Google Scholar 

  13. Wang, Y., Huang, M.: Research on hierarchical inter-connectivity among multi-scale representations from GIS feature. J. Hunan Univ. Sci. Technol. (Nat. Sci. Edn.) 1, 20 (2006)

    Google Scholar 

  14. Hu, Y., et al.: Design and implementation of agricultural product quality and safety traceability system based on grid management. Chin. Eng. Sci. 20(02), 63–71 (2018). (in Chinese)

    Article  Google Scholar 

  15. Wulder, M.: Optical remote-sensing techniques for the assessment of forest inventory and biophysical parameters. Prog. Phys. Geogr. 22(4), 449–476 (1998)

    Article  Google Scholar 

  16. Cheng, C., et al.: Research on remote sensing image subdivision pyramid. Geogr. Geo Inf. Sci. 26(1), 19–23 (2010)

    Google Scholar 

  17. Li, L., et al.: An algorithm for fast topological consistent simplification of face features. J. Comput. Inf. Syst. 9, 791–803 (2013)

    Google Scholar 

  18. Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. In: Proceedings of Sixth Symposium on Operating System Design and Implementation (OSD 2004) (2004)

    Google Scholar 

  19. Gorelick, N., et al.: Google earth engine: planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202, 18–27 (2017)

    Article  Google Scholar 

  20. Hu, Y., Dong, Y.: An automatic approach for land-change detection and land updates based on integrated NDVI timing analysis and the CVAPS method with GEE support. ISPRS J. Photogramm. Remote Sens. 146, 347–359 (2018)

    Article  Google Scholar 

  21. Shi, Y., et al.: Research progress and prospect on urban comprehensive carrying capacity. Geogr. Res. 32(1), 133–145 (2013)

    Google Scholar 

  22. Kang, P., Xu, L.: The urban ecological regulation based on ecological carrying capacity. Procedia Environ. Sci. 2, 1692–1700 (2010)

    Article  Google Scholar 

  23. Dong, Y., et al.: Analysis of spatiotemporal changes of grassland carrying capacity in Mongolian Plateau based on supply-consumption relationship. J. Nat. Resour. 34(05), 1093–1107 (2019). (in Chinese)

    Google Scholar 

  24. Jie, F., Kan, Z., Wang, Y.: Basic points and progress in technical methods of early-warning of the national resource and environmental carrying capacity. Progress Geogr. 36(3), 266–276 (2017)

    Article  Google Scholar 

  25. Xu, W., et al.: Evaluation methods and case study of regional ecological carrying capacity for early-warning. Progress Geogr. 36(3), 306–312 (2017)

    Article  Google Scholar 

  26. Du, W.: Research on Ecological Carrying Capacity Based on Supply and Consumption. Changan University (2018)

    Google Scholar 

  27. Mcdaniel, K., Haas, R.: Assessing mesquite-grass vegetation condition from landsat. Photogramm. Eng. Remote Sens. 48, 441–450 (1982)

    Google Scholar 

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Authors and Affiliations

  1. School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan, 030024, China

    Lihu Pan & Yunkai Li

  2. Institute of Geographic Science and Natural Resource Research, Chinese Academy of Science, Beijing, 100101, China

    Lihu Pan, Yunkai Li, Yu Dong & Huimin Yan

  3. Jilin Provincial Department of Natural Resources, Changchun, 130000, China

    Yu Dong

Authors
  1. Lihu Pan
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  2. Yunkai Li
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  3. Yu Dong
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  4. Huimin Yan
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Corresponding author

Correspondence to Lihu Pan .

Editor information

Editors and Affiliations

  1. North University of China, Taiyuan, China

    Pinle Qin

  2. Harbin Institute of Technology, Harbin, China

    Hongzhi Wang

  3. Harbin University of Science and Technology, Harbin, China

    Guanglu Sun

  4. National Academy of Guo Ding Institute of Data Science, Beijing, China

    Zeguang Lu

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Pan, L., Li, Y., Dong, Y., Yan, H. (2020). Research on Block Storage and Analysis Model for Belt and Road Initiative Ecological Carrying Capacity Evaluation System. In: Qin, P., Wang, H., Sun, G., Lu, Z. (eds) Data Science. ICPCSEE 2020. Communications in Computer and Information Science, vol 1258. Springer, Singapore. https://doi.org/10.1007/978-981-15-7984-4_26

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  • DOI: https://doi.org/10.1007/978-981-15-7984-4_26

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-7983-7

  • Online ISBN: 978-981-15-7984-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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