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  • 标题:Quality assessment of urban areas based on neural network modeling and GIS
  • 本地全文:下载
  • 作者:Olga Popova ; Julia Glebova ; Andrey Pustovgar
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2018
  • 卷号:33
  • 页码:1-8
  • DOI:10.1051/e3sconf/20183302032
  • 出版社:EDP Sciences
  • 摘要:In this article the authors carry out the research of the urban development areas structure and propose the system of its characteristics on the basis of sector affiliation of the municipal economy. The authors have developed an algorithm for quality assessment of urban development areas. The results of the research are presented on the example of several central quarters of Arkhangelsk city. The city’s residential development was formed in the periods from 1900-1950, 1950-1980 and from 2002 to date. It is currently presented by low-rise wooden, homestead type residential houses and barracks-type houses; mid-rise and high-rise brick and panel buildings of typical development, buildings of large-panel housing construction. Structural SOM-analysis compiled separate quarters of Arkhangelsk into 5 groups with a high level of characteristic similarity: "Commercial", "Prospective complex development", "Sustainable development", "Perspective renovation of residential development", "Investment-unattractive". Typical development strategies for each group of quarters are determined. Most developed areas characterized by upward height. The development strategies for depressed areas is in a high-rise building, which show the economic, social and environmental benefits of upward growth of the city. Using GIS allows to visually reflect the state and assess the quality of the urban development area by the aggregate of all parameters, and also to assess the quality of the quarters for each sector.
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