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Identifying Temporal Patterns of Visitors to National Parks through Geotagged Photographs

Author

Listed:
  • Carolina Barros

    (Transport, Infrastructure, and Territory–This, Geography Department, Universidad Complutense de Madrid, 28040 Madrid, Spain)

  • Borja Moya-Gómez

    (Transport, Infrastructure, and Territory–This, Geography Department, Universidad Complutense de Madrid, 28040 Madrid, Spain)

  • Juan Carlos García-Palomares

    (Transport, Infrastructure, and Territory–This, Geography Department, Universidad Complutense de Madrid, 28040 Madrid, Spain)

Abstract

Visitor data is essential for decision-making, policy formulation, and monitoring of protected areas. In this context, the data on the temporal distribution of visitors is essential to characterize influx and seasonality, and even to measure the carrying capacity of a site. However, obtaining information from visitors often involves high costs and long production times. Moreover, traditional visitor data has a limited level of detail. New sources of data can provide valuable information regarding the timing of visits. In this study, we tested the use of geotagged data to infer the temporal distribution of visitors to 15 Spanish national parks, and we identified temporal patterns of the visits at three levels: monthly, weekly, and daily. By comparing official monthly visitor counts and geotagged photographs from Flickr, we observed that the number of monthly users who upload photos significantly reflects the number of monthly visitors. Furthermore, the weekly and daily distributions of the Flickr data provided additional information that could contribute to identifying the periods of highest visitor pressure, design measures to manage the concentration of visitors, and improve the overall visitor experience. The results obtained indicate the potential of new data sources for visitor monitoring in protected areas and to open opportunities for future research. Moreover, monitoring tourism in protected areas is crucial to ensure the sustainability of their resources and to protect their biodiversity.

Suggested Citation

  • Carolina Barros & Borja Moya-Gómez & Juan Carlos García-Palomares, 2019. "Identifying Temporal Patterns of Visitors to National Parks through Geotagged Photographs," Sustainability, MDPI, vol. 11(24), pages 1-16, December.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:24:p:6983-:d:295212
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    References listed on IDEAS

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    1. Ballantyne, Roy & Packer, Jan & Falk, John, 2011. "Visitors’ learning for environmental sustainability: Testing short- and long-term impacts of wildlife tourism experiences using structural equation modelling," Tourism Management, Elsevier, vol. 32(6), pages 1243-1252.
    2. Orellana, Daniel & Bregt, Arnold K. & Ligtenberg, Arend & Wachowicz, Monica, 2012. "Exploring visitor movement patterns in natural recreational areas," Tourism Management, Elsevier, vol. 33(3), pages 672-682.
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    Cited by:

    1. Papafitsoros, Kostas & Adam, Lukáš & Schofield, Gail, 2023. "A social media-based framework for quantifying temporal changes to wildlife viewing intensity," Ecological Modelling, Elsevier, vol. 476(C).
    2. Zhi Yue & Jon Bryan Burley & Zhouxiao Cui & Houping Lei & Jing Zhou, 2021. "Visitor Capacity Considering Social Distancing in Urban Parks with Agent-Based Modeling," IJERPH, MDPI, vol. 18(13), pages 1-24, June.
    3. Veronica Alampi Sottini & Elena Barbierato & Iacopo Bernetti & Irene Capecchi, 2021. "Impact of Climate Change on Wine Tourism: An Approach through Social Media Data," Sustainability, MDPI, vol. 13(13), pages 1-18, July.

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