Visual Perception of Environmental Elements Analysis in Historical District Based on Eye-Tracking and Semi-Structured Interview: A Case Study in Xining, Taishan
The style and overall urban texture of historic districts embody rich social and cultural values. Therefore, how to make relevant environmental elements effectively perceived visually has become the key to protecting and displaying historic streets. Based on this, the non-subjective eye movement data and subjective impression of the subject were collected through an eye-tracking experiment and semi-structured interview. ErgoLAB was used to generate eye-tracking metrics and heat maps based on eye movement data, and ROST-CM6 software was used to generate word frequency and emotional degree data for interview text. Through comparative analysis, it is found that the subjective and objective evaluation indexes of the subjects tend to be consistent in general, but the visual behavior characteristics of different environmental elements’ types are different. The greater the variety of elements involved in visual perception, the longer the time required for participants to identify the relevant elements. The extent of element distribution also influenced differences in visual perception. Additionally, visual perceptions from partial elevation views and overall human perspective angles were largely similar, with distinctive elements attracting more interest. This study has an exploratory nature, and its findings contribute to the preservation and enhancement of the visual quality of historic districts.
Authors
- X. H. Wu (ORCID: https://orcid.org/0009-0004-5327-6323)
- F F Chen
- Ziang Li (ORCID: https://orcid.org/0000-0002-5203-5630)
- Xing Jiang (ORCID: https://orcid.org/0009-0009-8036-7710)
- Zonghan Chen
Institutions
- Guangzhou University (CN)
Publication Details
- Journal
- Buildings
- Published
- 2025-05-05
- DOI
- https://doi.org/10.3390/buildings15091554
- Citations
- 4
- Primary Topic
- Color perception and design
- Type
- article
- Field-Weighted Citation Impact
- 9.75
Funders
- Guangzhou University