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Response of Urban Park Visitor Behavior to Water Quality in Beijing

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Spatial Data and Intelligence (SpatialDI 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13614))

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Abstract

Based on the big data of remote sensing observation and mobile phone signaling, we put forward two quantitative indices that objectively characterize visitor visiting behavior—Park Visiting Hours (PVH) and the probability of visitor attendance (PVA). We hope to answer whether the water quality of urban landscape water will affect PVH and how different it will be for various groups. The findings are as follows: (1) Sensory Pollution Index (SPI) has a very significant negative correlation with HPV. The conclusion that the deterioration of water quality will shorten PVH is statistically significant. However, water quality is not the main factor affecting that. (2) Visitor visits decrease with the deterioration of water quality, and this trend is more evident with the extension of PVH. (3) There are significant differences in PVH between various groups when the water quality is excellent or poor. Generally speaking, when the water quality is good, the younger visitors will have a higher PVH, while when the water quality is poor, the more youthful visitors will have a lower PVH.

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Notes

  1. 1.

    “t” means the time within the range of [8:00, 21:00].

    “p” means the probability of tourists in the parks.

  2. 2.

    *** Significant at 1% level.

    ** Significant at 5% level.

    * Significant at 10% level.

  3. 3.

    POP, the number of people in the park.

    EPT, time to enter the park.

    MON, male or not.

    DON, workdays or not.

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Author information

Authors and Affiliations

  1. Faculty of Geographic Science, Beijing Normal University, Beijing, 100875, China

    Wen Jiang, Yuan Zhang, Jiaxin Wu & Xiang Li

  2. School of National Safety and Emergency Management, Beijing Normal University, Beijing, 100875, China

    Wen Jiang & Yaobin Meng

Authors
  1. Wen Jiang
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  2. Yaobin Meng
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  3. Yuan Zhang
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  4. Jiaxin Wu
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  5. Xiang Li
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Corresponding author

Correspondence to Yaobin Meng .

Editor information

Editors and Affiliations

  1. Peking University, Wuhan, China

    Huayi Wu

  2. Peking University, Beijing, China

    Yu Liu

  3. Harbin Institute of Technology, Harbin, China

    Jianzhong Li

  4. Department of Computer Science and Information, Renmin University of China, Beijing, China

    Xiaofeng Meng

  5. China University of Geosciences (Wuhan), Wuhan, China

    Qingfeng Guan

  6. Southern University of Science and Technology, Shenzhen, China

    Xuan Song

  7. Jiangxi University of Finance and Economics, Nanchang, China

    Guoqiong Liao

  8. Department of Computer Science and Technology, Tsinghua University, Beijing, China

    Guoliang Li

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Jiang, W., Meng, Y., Zhang, Y., Wu, J., Li, X. (2022). Response of Urban Park Visitor Behavior to Water Quality in Beijing. In: Wu, H., et al. Spatial Data and Intelligence. SpatialDI 2022. Lecture Notes in Computer Science, vol 13614. Springer, Cham. https://doi.org/10.1007/978-3-031-24521-3_17

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  • DOI: https://doi.org/10.1007/978-3-031-24521-3_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-24520-6

  • Online ISBN: 978-3-031-24521-3

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