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The Relation between Green Visual Index and Visual Comfort in Qingdao Coastal Streets

Author(s): ORCID
ORCID
ORCID






Medium: journal article
Language(s): English
Published in: Buildings, , n. 2, v. 13
Page(s): 457
DOI: 10.3390/buildings13020457
Abstract:

The public’s mental health is obviously impacted by the perception of green quantity in urban streets. As one of the important urban spatial indicators, the Green View Index (GVI) reflects the green quantity of streets, which is helpful in revealing the level of street vegetation from the perspective of pedestrians. The GVI can improve the attraction and the visual experience in urban streets. Taking Qingdao Coastal Streets as an example, the study used OpenStreetMap, Baidu Street View (BSV) image, DeepLabV3+ semantic segmentation, and the SD method to obtain the GVI and Visual Comfort (VICO), and the correlation and influence mechanisms were discussed. The result showed that the greening landscape of the overall Qingdao Coastal Streets was of high quality, and the historic district was the most outstanding. The greening quality was a little low in the transitional district and the western modern district, which should be improved. In addition, the relationship between GVI and VICO showed a strong positive correlation. The spatial distribution of the VICO was more consistent with the GVI. The street VICO was affected by the GVI, plant richness, the street scale, and landscape diversity. Moreover, with the increase of the GVI, the increase trend of the VICO instead gradually decreased. The contribution of this study was not only accurately diagnosing the problems of street greening quality, shedding light on the relationship between GVI and VICO, but also providing theoretical support for urban greening planning and management, especially for healthy street design.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10712342
  • Published on:
    21/03/2023
  • Last updated on:
    10/05/2023
 
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