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  • 标题:Methods and Architectural Patterns of Storage, Analysis and Distribution of Spatio-temporal Data
  • 本地全文:下载
  • 作者:Stanislav A. Yamashkin ; Anatoliy A. Yamashkin ; Ekaterina O. Yamashkina
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2021
  • 卷号:12
  • 期号:8
  • DOI:10.14569/IJACSA.2021.0120867
  • 语种:English
  • 出版社:Science and Information Society (SAI)
  • 摘要:The work describes the key principles of the process of building digital spatial data infrastructures for effective decision-making in the management of natural systems and for the sustainable development of the regional economy. The following reference points are considered in detail: increasing the accuracy of the deep learning and neural networks algorithmic and software for the process of analyzing spatial data, developing storage systems for large spatio-temporal data by developing new physical and logical storage models, introducing effective geoportal technologies and developing new architectural patterns for presentation and further dissemination of spatio-temporal using modern web technologies. The plan for working out a scientific problem of development of methods and architectural patterns of storage, analysis and distribution of spatio-temporal data determined the structure of the article. The first section concretizes the criteria of efficiency of information processes in the digital spatial data infrastructure (SDI), the second section discusses algorithmic support of the process of analysis of spatial data, the third – integration of spatial data, and finally, the final section – implementation and project-oriented use of geoportal systems.
  • 关键词:Spatial data infrastructure; deep learning; neural networks; spatial data; geoportals
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