Evaluation of Public Space in Traditional Villages Based on Eye Tracking Technology

References

• Abusaada, H., and A. Elshater. 2021. “Revealing Distinguishing Factors Between Space and Place in Urban Design Literature.” Journal of Urban Design 26 (3): 319–340. https://doi.org/10.1080/13574809.2020.1832887.
   Web of Science ®Google Scholar
• Antúnez, L., L. Machín, G. Ares, and S. R. Jaeger. 2019. “Visual Attention to Rate-All-That-Apply (RATA) Questions: A Case Study with Apple Images as Food Stimuli.” Food Quality and Preference 72:136–142. https://doi.org/10.1016/j.foodqual.2018.10.007.
   Web of Science ®Google Scholar
• Behe, B. K., M. Bae, P. T. Huddleston, and L. Sage. 2015. “The Effect of Involvement on Visual Attention and Product Choice.” Journal of Retailing and Consumer Services 24:10–21. https://doi.org/10.1016/j.jretconser.2015.01.002.
   Web of Science ®Google Scholar
• Berni, A., S. Altavilla, L. Ruiz-Pastor, C. Nezzi, and Y. Borgianni 2022. An Eye-Tracking Study to Identify the Most Observed Features in a Physical Prototype of a Tiny House. Proceedings of the Design Society; Volume 2, Page 841–850; ISSN 2732-527X. https://doi.org/10.1017/pds.2022.86.
   Google Scholar
• Blascheck, T., K. Kurzhals, M. Raschke, M. Burch, D. Weiskopf, and T. Ertl. 2017. “Visualization of Eye Tracking Data: A Taxonomy and Survey.” Computer Graphics Forum 36 (8): 260–284. https://doi.org/10.1111/cgf.13079.
   Web of Science ®Google Scholar
• Bojko, A. 2009. “Informative or Misleading? Heatmaps Deconstructed.” In Human-Computer Interaction. New Trends. HCI 2009. Lecture Notes in Computer Science, J. A. Jackoedited by, 30–39. Berlin: SpringerVol. 5610. https://doi.org/10.1007/978-3-642-02574-7_4.
   Google Scholar
• Carrasco, M. 2011. “Visual Attention: The Past 25 Years.” Vision Research 51 (13): 1484–1525. https://doi.org/10.1016/j.visres.2011.04.012.
   PubMed Web of Science ®Google Scholar
• Chen, X. H., and Q. Q. Chen. 2019. “Review of the Studies on Public Space of China’s Traditional Villages.” Journal of Anhui Agricultural University (Social Sciences Edition) 28 (6): 25–32+58. In Chinese. https://doi.org/10.19747/j.cnki.1009-2463.2019.06.005.
   Google Scholar
• Cho, H. 2016. “A Study on the Comparison of the Visual Attention Characteristics on the Facade Image of a Detached House Due to the Features on Windows.” Journal of Asian Architecture and Building Engineering 15 (2): 209–214. https://doi.org/10.3130/jaabe.15.209.
   Web of Science ®Google Scholar
• de la Fuente Suárez, L. A. 2020. “Subjective Experience and Visual Attention to a Historic Building: A Real-World Eye-Tracking Study.” Frontiers of Architectural Research 9 (4): 774–804. https://doi.org/10.1016/j.foar.2020.07.006.
   Web of Science ®Google Scholar
• De Lucio, J. V., M. Mohamadian, J. P. Ruiz, J. Banayas, and F. G. Bernaldez. 1996. “Visual Landscape Exploration as Revealed by Eye Movement Tracking.” Landscape and Urban Planning 34 (2): 135–142. https://search.ebscohost.com/login.aspx?direct=true&db=edscal&AN=edscal.5977991&lang=zh-cn&site=eds-live.
   Web of Science ®Google Scholar
• De Smet, B., L. Lempereur, Z. Sharafi, Y.-G. Guéhéneuc, G. Antoniol, and N. Habra. 2014. “Taupe: Visualizing and Analyzing Eye-Tracking Data.” Science of Computer Programming 79:260–278. https://doi.org/10.1016/j.scico.2012.01.004.
   Web of Science ®Google Scholar
• Dong, W., L. Zheng, B. Liu, and L. Meng. 2018. “Using Eye Tracking to Explore Differences in Map-Based Spatial Ability Between Geographers and Non-Geographers.” Canadian Historical Review 7 (9). https://doi.org/10.3390/ijgi7090337.
   Google Scholar
• Dupont, L., M. Antrop, and V. Van Eetvelde. 2014. “Eye-Tracking Analysis in Landscape Perception Research: Influence of Photograph Properties and Landscape Characteristics.” Landscape Research 39 (4): 417–432. https://doi.org/10.1080/01426397.2013.773966.
   Web of Science ®Google Scholar
• Franěk, M., J. Petružálek, and D. Šefara. 2019. Eye Movements in Viewing Urban Images and Natural Images in Diverse Vegetation Periods. Vol. 46. Urban Forestry & Urban Greening. https://doi.org/10.1016/j.ufug.2019.126477.
   Google Scholar
• Gou, A. P., and J. B. Wang. 2011. “SD Method Based Street Space Vitality Evaluation.” Planners 27 (10): 102–106. In Chinese. https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFD2011&filename=GHSI201110021&uniplatform=NZKPT&v=8U7C_UJ-MQowLnmEyjksmjFvS2ScfybACp_T_moTXr1RedUIeeA8sxrTDqN7Maro.
   Google Scholar
• Gruden, C., I. Ištoka Otković, and M. Šraml. 2021. “Pedestrian Safety at Roundabouts: Their Crossing and Glance Behavior in the Interaction with Vehicular Traffic.” Accident Analysis and Prevention 159. https://doi.org/10.1016/j.aap.2021.106290.
   Web of Science ®Google Scholar
• Hamedani, Z., E. Solgi, T. Hine, and H. Skates. 2020. “Revealing the Relationships Between Luminous Environment Characteristics and Physiological, Ocular and Performance Measures: An Experimental Study.” Building & Environment 172. https://doi.org/10.1016/j.buildenv.2020.106702.
   PubMed Web of Science ®Google Scholar
• Hessels, R. S., C. Kemner, C. van den Boomen, and I. T. C. Hooge. 2016. “The Area-Of-Interest Problem in Eyetracking Research: A Noise-Robust Solution for Face and Sparse Stimuli.” Behavior Research Methods 48 (4): 1694–1712. https://doi.org/10.3758/s13428-015-0676-y.
   PubMed Web of Science ®Google Scholar
• Hollander, J. B., A. Purdy, A. Wiley, V. Foster, R. J. Jacob, H. A. Taylor, and T. T. Brunyé. 2018. “Seeing the City: Using Eye-Tracking Technology to Explore Cognitive Responses to the Built Environment.” Journal of Urbanism: International Research on Placemaking and Urban Sustainability 12 (2): 156–171. https://doi.org/10.1080/17549175.2018.1531908.
   Google Scholar
• Holmqvist, K., S. L. Örbom, I. T. C. Hooge, D. C. Niehorster, R. G. Alexander, R. Andersson, J. S. Benjamins, et al. 2022. “Eye Tracking: Empirical Foundations for a Minimal Reporting Guideline.” Behavior Research Methods 55 (1): 364–416. https://doi.org/10.3758/s13428-021-01762-8.
   PubMed Web of Science ®Google Scholar
• Khachatryan, H., A. Rihn, G. Hansen, and T. Clem. 2020. “Landscape Aesthetics and Maintenance Perceptions: Assessing the Relationship Between Homeowners’ Visual Attention and Landscape Care Knowledge.” Land Use Policy 95. https://doi.org/10.1016/j.landusepol.2020.104645.
   Web of Science ®Google Scholar
• Lei, Q., C. Yuan, and S. S. Y. Lau. 2021. “A Quantitative Study for Indoor Workplace Biophilic Design to Improve Health and Productivity Performance.” Journal of Cleaner Production 324:324. https://doi.org/10.1016/j.jclepro.2021.129168.
   Web of Science ®Google Scholar
• Li, X., Y. Li, Y. P. Ren, and A. Lusk. 2020. “Research on the Urban Spatial Visual Quality Based on Subjective Evaluation Method and Eye Tracking Analysis.” In Chinese Architectural Journal S2:190–196. https://kns.cnki.net/kcms/detail/detail.aspx?FileName=JZXB2020S2032&DbName=CJFQ2020.
   Google Scholar
• Lisińska-Kuśnierz, M., and M. Krupa. 2020. “Suitability of Eye Tracking in Assessing the Visual Perception of Architecture—A Case Study Concerning Selected Projects Located in Cologne.” Buildings 10 (2): 20. https://doi.org/10.3390/buildings10020020.
   Web of Science ®Google Scholar
• Li, Z., X. Sun, S. Zhao, and H. Zuo. 2021. “Integrating Eye-Movement Analysis and the Semantic Differential Method to Analyze the Visual Effect of a Traditional Commercial Block in Hefei, China.” Frontiers of Architectural Research 10 (2): 317–331. https://doi.org/10.1016/j.foar.2021.01.002.
   Web of Science ®Google Scholar
• Liu, Y., M. Hu, and B. Zhao. 2019. Audio-Visual Interactive Evaluation of the Forest Landscape Based on Eye-Tracking Experiments. Vol. 46. Urban Forestry & Urban Greening. https://doi.org/10.1016/j.ufug.2019.126476.
   Google Scholar
• Liu, C., J. Kang, and H. Xie. 2020. “Effect of Sound on Visual Attention in Large Railway Stations: A Case Study of St. Pancras Railway Station in London.” Building & Environment 185. https://doi.org/10.1016/j.buildenv.2020.107177.
   Web of Science ®Google Scholar
• Liu, L., H. Qu, Y. Ma, K. Wang, and H. Qu. 2022. “Restorative Benefits of Urban Green Space: Physiological, Psychological Restoration and Eye Movement Analysis.” Journal of Environmental Management 301. https://doi.org/10.1016/j.jenvman.2021.113930.
   Web of Science ®Google Scholar
• Liu, J., Y. Zhang, and Q. Zhao. 2019. “Adaptive ViBe Algorithm Based on Pearson Correlation Coefficient. 2019 Chinese Automation Congress (CAC.” Chinese Automation Congress (CAC) 2019: 4885–4889. https://doi.org/10.1109/CAC48633.2019.8997209.
   Google Scholar
• Li, N., S. Zhang, L. Xia, and Y. Wu. 2022. “Investigating the Visual Behavior Characteristics of Architectural Heritage Using Eye-Tracking.” Buildings 12 (7). https://doi.org/10.3390/buildings12071058.
   Web of Science ®Google Scholar
• Ministry of Housing and Urban-Rural Development and Other Departments on the Announcement of the Sixth Batch of the List of Villages Included in the List of Chinese Traditional Villages Notice, 2023. https://www.mohurd.gov.cn/gongkai/zhengce/zhengcefilelib/202303/20230320_770845.html. (Accessed May 15, 2023).
   Google Scholar
• Ponce, H. R., R. E. Mayer, M. S. Loyola, M. J. López, and E. E. Méndez. 2018. “When Two Computer-Supported Learning Strategies are Better Than One: An Eye-Tracking Study.” Computers & Education 125:376–388. https://doi.org/10.1016/j.compedu.2018.06.024.
   Web of Science ®Google Scholar
• Qi, L., W. Liang, and M. Xi. 2019. “The Public Space Pattern Research of Guangfu Traditional Villages Based on Spatial Syntax: A Case Study of Huangpu Village in Guangzhou City, China.” IOP Conference Series: Earth and Environmental Science 267 (6): 062033. ISSN 1755-1307 1755-1315. https://doi.org/10.1088/1755-1315/267/6/062033.
   Google Scholar
• Weiyi, C., L. Zao, X. Xuan, L. Qingtao, L. Shi, X. Sun, K. Zhu, and Y. Shi. 2022. “Influence of Hospital Outdoor Rest Space on the Eye Movement Measures and Self-Rating Restoration of Staff Frontiers in Public Health.” Frontiers in Public Health 10. https://doi.org/10.3389/fpubh.2022.855857.
   Web of Science ®Google Scholar
• Xu, D. W., and Y. J. Li. 2014. “Experts and Public Aesthetic Differences Based on SD-SBE Method.” In Chinese Chinese Landscape Architecture 7:52–56. https://kns.cnki.net/kcms/detail/detail.aspx?FileName=ZGYL201407014&DbName=CJFQ2014.
   Google Scholar
• Zhang, H. L., J. Chen, and C. S. Zhou. 2017. “Research Review and Prospects of Traditional Villages in China.” City Planning Review 41 (4): 74–80. In Chinese. https://doi.org/10.11819/cpr20170413a.
   Google Scholar
• Zhang, Y. J., Y. Hong, and L. Lin. 2022. “Study on Influencing Factors of Public Space Vitality of Mountainous Traditional Villages in Southern Zhejiang.” Development of Small Cities And Towns 40 (10): 84–92. In Chinese. https://doi.org/10.3969/j.issn.1009-1483.2022.10.011.
   Google Scholar
• Zhang, L. M., R. X. Zhang, T. S. Jeng, and Z. Y. Zeng. 2019. “Cityscape Protection Using VR and Eye Tracking Technology.” Journal of Visual Communication and Image Representation 64:102639. https://doi.org/10.1016/j.jvcir.2019.102639.
   Web of Science ®Google Scholar
• Zhang, H. R., D. Y. Zhang, and W. S. Li. 2023. “Research on the Public Space Potential Evaluation and Improvement Countermeasures of Linggong Village Based on Convex Space Model.” Development of Small Cities & Towns 41 (4): 67–74+94. In Chinese. https://doi.org/10.3969/j.issn.1009-1483.2023.04.010.
   Google Scholar
• Zhuang, W. M. 1996. “SD Method Related to Evaluation of Architectural Space Objectives.” Journal of Tsinghua University (Science and technology) 4:42–47. In Chinese. https://doi.org/10.3969/j.issn.10091483.2022.10.011.
   Google Scholar