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Spatio-Temporal Clustering of Sarawak Malaysia Total Protected Area Visitors

Author

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  • Abang Zainoren Abang Abdurahman

    (Faculty of Business Management, Universiti Teknologi MARA Cawangan Sarawak, Shah Alam 94300, Malaysia)

  • Syerina Azlin Md Nasir

    (Faculty of Mathematical and Computer Sciences, Universiti Teknologi MARA Cawangan Kelantan, Kota Bharu 18500, Malaysia)

  • Wan Fairos Wan Yaacob

    (Faculty of Mathematical and Computer Sciences, Universiti Teknologi MARA Cawangan Kelantan, Kota Bharu 18500, Malaysia)

  • Serah Jaya

    (Faculty of Business Management, Universiti Teknologi MARA Cawangan Sarawak, Shah Alam 94300, Malaysia)

  • Suhaili Mokhtar

    (Sarawak Forestry Corporation, Jalan Sungai Tapang, Kota Sentosa, Kuching 93250, Malaysia)

Abstract

Based on data of visitors to national parks, nature reserves and wildlife sanctuaries in Sarawak, this study’s objective is to use the spatial and temporal analysis to describe the underlying trend and temporal pattern of local and foreign visitors and ultimately infer the temporal distribution of visitors to 18 different TPAs. The second aim of the study is to cluster the visitors according to the location of TPAs using Wards hierarchical clustering method. By comparing average monthly visitors’ count, we observed that the average number of monthly visitors significantly reflects the distribution concentration of visitors based on the spatial map. Findings indicate that the monthly distributions of local and foreign visitors differ according to different TPAs. The spatial and temporal analysis found that local visitors’ arrival is high at the end of the year while foreign visitors showed significant arrival during the months of July, August and September. The Wards minimum variance method was able to cluster TPAs local and foreign visitors into very high, high, medium and low visitor area. This study provides 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 visitors’ experience. The findings of the study are also important to respective local authorities in providing information for planning and monitoring tourism in TPAs. Consecutively, this will ensure sustainability of TPAs resources while protecting their biodiversity.

Suggested Citation

  • Abang Zainoren Abang Abdurahman & Syerina Azlin Md Nasir & Wan Fairos Wan Yaacob & Serah Jaya & Suhaili Mokhtar, 2021. "Spatio-Temporal Clustering of Sarawak Malaysia Total Protected Area Visitors," Sustainability, MDPI, vol. 13(21), pages 1-19, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:11618-:d:661334
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    References listed on IDEAS

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    1. Michał Roman & Monika Roman & Piotr Prus & Małgorzata Szczepanek, 2020. "Tourism Competitiveness of Rural Areas: Evidence from a Region in Poland," Agriculture, MDPI, vol. 10(11), pages 1-19, November.
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    3. Michał Roman & Monika Roman & Arkadiusz Niedziółka, 2020. "Spatial Diversity of Tourism in the Countries of the European Union," Sustainability, MDPI, vol. 12(7), pages 1-16, March.
    4. Rosa Maria Fanelli & Luca Romagnoli, 2020. "Customer Satisfaction with Farmhouse Facilities and Its Implications for the Promotion of Agritourism Resources in Italian Municipalities," Sustainability, MDPI, vol. 12(5), pages 1-21, February.
    5. Pierpaolo D’Urso & Livia Giovanni & Marta Disegna & Riccardo Massari & Vincenzina Vitale, 2021. "A Tourist Segmentation Based on Motivation, Satisfaction and Prior Knowledge with a Socio-Economic Profiling: A Clustering Approach with Mixed Information," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 154(1), pages 335-360, February.
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    Cited by:

    1. Abang Zainoren Abang Abdurahman & Wan Fairos Wan Yaacob & Syerina Azlin Md Nasir & Serah Jaya & Suhaili Mokhtar, 2022. "Using Machine Learning to Predict Visitors to Totally Protected Areas in Sarawak, Malaysia," Sustainability, MDPI, vol. 14(5), pages 1-16, February.

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