IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2023i5p3843-d1075975.html
   My bibliography  Save this article

Research on Spatio-Temporal Characteristics of Tourists’ Landscape Perception and Emotional Experience by Using Photo Data Mining

Author

Listed:
  • Junxia Yan

    (College of Geographical Sciences, Hebei Normal University, Shijiazhuang 050024, China
    Department of Geography, Handan College, Handan 056005, China)

  • Jiaheng Yue

    (Institute of Geological Survey, China University of Geosciences, Wuhan 430074, China)

  • Jianfeng Zhang

    (Department of Geography, Handan College, Handan 056005, China)

  • Peng Qin

    (College of Resources and Environment, Qingdao Agricultural University, Qingdao 266109, China)

Abstract

Mountainous scenic spots are important tourism resources, and the study of tourists’ landscape perception and emotional preference when visiting them is beneficial to the management of scenic spots in order to improve the service quality and promote the protection, development, and utilization of scenic resources. In this paper, we use the location photo data of tourists at Huangshan Mountain to extract the visual semantic information of location photos, calculate the photo sentiment value, and mine the landscape perception and sentiment preference features of tourists using DeepSentiBank image recognition model and photo visual semantic quantification method. The results show the following: (1) Huangshan tourists mainly focus on nine types of photos, with the most attention paid to the category of mountain rock landscapes and the least attention paid to the category of animal landscapes. (2) In terms of spatial distribution, the landscape types of tourist photos show the spatial characteristics of “concentrated into a belt”, “significant nucleus”, and “fragmented distribution”. The spatial variation of the emotional value of tourists’ photos is significant, and the high values are mainly distributed at the entrances and exits, interchanges, and famous attractions. (3) On a temporal scale, the type of perception of the Huangshan location photograph landscape shows a significant imbalance. The emotional values of tourists’ photos vary significantly, with a “slowly sloping straight line” type of emotional change on the seasonal scale, a “W” type of emotional change on the monthly scale, an “N” type of emotional change on the weekly scale, and an “M” type of emotional change on the hourly scale. This study attempts to explore the landscape perceptions and emotional preferences of tourists in mountainous scenic areas with new data and methods, aiming to promote the sustainable and high-quality development of mountainous scenic areas.

Suggested Citation

  • Junxia Yan & Jiaheng Yue & Jianfeng Zhang & Peng Qin, 2023. "Research on Spatio-Temporal Characteristics of Tourists’ Landscape Perception and Emotional Experience by Using Photo Data Mining," IJERPH, MDPI, vol. 20(5), pages 1-18, February.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:5:p:3843-:d:1075975
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/5/3843/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/20/5/3843/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Parvaneh Sobhani & Hadi Veisi & Hassan Esmaeilzadeh & Seyed Mohammad Moein Sadeghi & Marina Viorela Marcu & Isabelle D. Wolf, 2022. "Tracing the Impact Pathways of COVID-19 on Tourism and Developing Strategies for Resilience and Adaptation in Iran," Sustainability, MDPI, vol. 14(9), pages 1-21, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hossein Komasi & Sarfaraz Hashemkhani Zolfani & Olegas Prentkovskis & Paulius Skačkauskas, 2022. "Urban Competitiveness: Identification and Analysis of Sustainable Key Drivers (A Case Study in Iran)," Sustainability, MDPI, vol. 14(13), pages 1-22, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:20:y:2023:i:5:p:3843-:d:1075975. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.