City Street Scent Landscape Drawing

Digital Media Representation Art for Olfactory Perception

DOI

10.2991/978-94-6463-046-6_41How to use a DOI?

Keywords

Urban Street; Odor Tracking; Odor Landscape; Big Data Search; Urban Environment Design

Abstract

The street is the most intuitive space for people to perceive the city, and street odor is also an important way to measure the quality of street space. Nevertheless, due to insufficient means of quantitative odor analysis, the urban odor landscape has not yet attracted sufficient attention from the urban research community. This article attempts to use big data search and information retrieval technology, combine the street odor tracking experiment with the semantic analysis of social media data, classify the typical street odors in Shanghai, analyze the odor distribution characteristics of typical characteristic streets, use GIS geographic information system, adopt the multidisciplinary technical means to draw the odor map of typical characteristic streets, and verify the reliability of the odor landscape map by social data and its semantic analysis. The reliability of the odor landscape map is verified by social data and semantic analysis. On the basis of the results, we analyze the influence of street odor levels and odor landscape on the characteristics of the streets, focusing on Wukang Road. Finally, we discuss the potential application of odorscape research in urban environment design in the context of the research results.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yiqi Li
PY  - 2022
DA  - 2022/12/17
TI  - City Street Scent Landscape Drawing
BT  - Proceedings of the 2022 2nd International Conference on Computer Technology and Media Convergence Design (CTMCD 2022)
PB  - Atlantis Press
SP  - 342
EP  - 351
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-046-6_41
DO  - 10.2991/978-94-6463-046-6_41
ID  - Li2022
ER  -