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Modeling Spatial and Temporal Change of National Park Visits Using Social Media Data: The Case of Beydağları Coastal National Park

Yıl 2021, Cilt: 23 Sayı: 2, 386 - 398, 16.08.2021
https://doi.org/10.24011/barofd.910977

Öz

Today, national parks have become popular tourism destinations for nature-based tourism and recreation activities, with the increasing use of visitors. Real-time data on the behavior and preferences of visitors are needed for nature-based tourism research and the management of national parks. Obtaining visitor data through surveys are very expensive and time consuming. In this context, geotagged social media data can be a potential data source for collecting visitor data and gaining strong insights into visitor patterns in protected areas. In this study, the potential for the use of geotagged photographs has been investigated in order to analyze temporal and spatial behavior patterns of visitors to Beydağları Coastal National Park. The results of the study revealed that Flickr data provides a useful resource for evaluating the characteristics of national parks, analyzing their temporal and spatial aspects, and offers new opportunities for future research.

Kaynakça

  • 1. Arkema, K. K., Fisher, D. M., Wyatt, K., Wood, S. A., Payne, H. J. (2021). Advancing Sustainable Development and Protected Area Management with Social Media-Based Tourism Data. Sustainability, 13(5), 2427.
  • 2. Arslan, E. S., Örücü, Ö. K. (2020). Kültürel ekosistem hizmetlerinin sosyal medya fotoğrafları kullanılarak modellenmesi: Eskişehir örneği. Türkiye Ormancılık Dergisi, 21(1), 94-105.
  • 3. Balmford, A., Beresford, J., Green, J., Naidoo, R., Walpole, M., Manica, A. (2009). A global perspective on trends in nature-based tourism. PLoS Biol, 7(6), e1000144.
  • 4. Barros, C., Moya-Gómez, B., & García-Palomares, J. C. (2019). Identifying temporal patterns of visitors to national parks through geotagged photographs. Sustainability, 11(24), 6983.
  • 5. Barros, C., Moya-Gómez, B., Gutiérrez, J. (2020). Using geotagged photographs and GPS tracks from social networks to analyse visitor behaviour in national parks. Current Issues in Tourism, 23(10), 1291-1310.g
  • 6. Cessford, G., Muhar, A. (2003). Monitoring options for visitor numbers in national parks and natural areas. Journal for nature conservation, 11(4), 240-250.
  • 7. Di Minin, E., Tenkanen, H., Toivonen, T. (2015). Prospects and challenges for social media data in conservation science. Frontiers in Environmental Science, 3, 63.
  • 8. Gülçin, D. (2020). Kültürel ekosistem hizmetlerinin sosyal medya verileri kullanılarak haritalanması: Datça yarımadası örneği. Türkiye Ormancılık Dergisi, 21(4), 407-416.
  • 9. Kovacs-Györi, A., Ristea, A., Kolcsar, R., Resch, B., Crivellari, A., Blaschke, T. (2018). Beyond spatial proximity—classifying parks and their visitors in London based on spatiotemporal and sentiment analysis of Twitter data. ISPRS International Journal of Geo-Information, 7(9), 378.
  • 10. Heikinheimo, V., Minin, E. D., Tenkanen, H., Hausmann, A., Erkkonen, J., Toivonen, T. (2017). User-generated geographic information for visitor monitoring in a national park: A comparison of social media data and visitor survey. ISPRS International Journal of Geo-Information, 6(3), 85.
  • 11. Levin, N., Lechner, A. M., Brown, G. (2017). An evaluation of crowdsourced information for assessing the visitation and perceived importance of protected areas. Applied geography, 79, 115-126.
  • 12. Manning, R. E. (2002). How much is too much? Carrying capacity of national parks and protected areas. In Monitoring and management of visitor flows in recreational and protected areas. conference proceedings (pp. 306-313).
  • 13. Schägner, J. P., Maes, J., Brander, L., Paracchini, M. L., Hartje, V., Dubois, G. (2017). Monitoring recreation across European nature areas: A geo-database of visitor counts, a review of literature and a call for a visitor counting reporting standard. Journal of outdoor recreation and tourism, 18, 44-55.
  • 14. Shoval, N., Ahas, R. (2016). The use of tracking technologies in tourism research: the first decade. Tourism Geographies, 18(5), 587-606.
  • 15. Sessions, C., Wood, S. A., Rabotyagov, S., Fisher, D. M. (2016). Measuring recreational visitation at US National Parks with crowd-sourced photographs. Journal of environmental management, 183, 703-711.
  • 16. Ullah, H., Wan, W., Ali Haidery, S., Khan, N. U., Ebrahimpour, Z., Luo, T. (2019). Analyzing the spatiotemporal patterns in green spaces for urban studies using location-based social media data. ISPRS International Journal of Geo-Information, 8(11), 506.
  • 17. Walden-Schreiner, C., Rossi, S. D., Barros, A., Pickering, C., Leung, Y. F. (2018). Using crowd-sourced photos to assess seasonal patterns of visitor use in mountain-protected areas. Ambio, 47(7), 781-793.
  • 18. Xie, Z., Yan, J. (2008). Kernel density estimation of traffic accidents in a network space. Computers, environment and urban systems, 32(5), 396-406.
  • 19. URL-1: http://beydaglari.tabiat.gov.tr/, (15.03.2021).
  • 20. URL-2: https://www.flickr.com/, (18.03.2021).
  • 21. URL-3: https://www.python.org, (18.03.2021).

Sosyal Medya Verileri Kullanılarak Milli Park Ziyaretlerinin Mekânsal ve Zamansal Değişiminin Modellenmesi: Beydağları Sahil Milli Parkı Örneği

Yıl 2021, Cilt: 23 Sayı: 2, 386 - 398, 16.08.2021
https://doi.org/10.24011/barofd.910977

Öz

Günümüzde milli parklar, ziyaretçi kullanımının artmasıyla birlikte doğa temelli turizm ve rekreasyon faaliyetleri açısından popüler turizm destinasyonları haline gelmiştir. Doğa temelli turizm araştırmaları ve milli parkların yönetimi için ziyaretçilerin davranışları ve tercihleri hakkında gerçek zamanlı verilere ihtiyaç duyulmaktadır. Ziyaretçi verilerini anketler yoluyla elde etmek çok pahalı ve zaman alıcıdır. Bu bağlamda coğrafi etiketli sosyal medya verileri ziyaretçi verilerini toplamak, korunan alanlardaki ziyaret modellerine ilişkin güçlü içgörüler elde etmek için potansiyel bir veri kaynağı olabilir. Bu çalışmada, Beydağları Sahil Milli Parkı’na gelen ziyaretçilerin zamansal ve mekânsal davranış modellerini analiz etmek amacıyla coğrafi etiketli fotoğrafların kullanım potansiyeli araştırılmıştır. Çalışmanın sonuçları, Flickr verilerinin milli parkların özelliklerini değerlendirmek, zamansal ve mekânsal yönlerini analiz etmek için yararlı bir kaynak oluşturduğunu ve gelecekteki araştırmalar için yeni fırsatlar sunduğunu ortaya koymuştur.

Kaynakça

  • 1. Arkema, K. K., Fisher, D. M., Wyatt, K., Wood, S. A., Payne, H. J. (2021). Advancing Sustainable Development and Protected Area Management with Social Media-Based Tourism Data. Sustainability, 13(5), 2427.
  • 2. Arslan, E. S., Örücü, Ö. K. (2020). Kültürel ekosistem hizmetlerinin sosyal medya fotoğrafları kullanılarak modellenmesi: Eskişehir örneği. Türkiye Ormancılık Dergisi, 21(1), 94-105.
  • 3. Balmford, A., Beresford, J., Green, J., Naidoo, R., Walpole, M., Manica, A. (2009). A global perspective on trends in nature-based tourism. PLoS Biol, 7(6), e1000144.
  • 4. Barros, C., Moya-Gómez, B., & García-Palomares, J. C. (2019). Identifying temporal patterns of visitors to national parks through geotagged photographs. Sustainability, 11(24), 6983.
  • 5. Barros, C., Moya-Gómez, B., Gutiérrez, J. (2020). Using geotagged photographs and GPS tracks from social networks to analyse visitor behaviour in national parks. Current Issues in Tourism, 23(10), 1291-1310.g
  • 6. Cessford, G., Muhar, A. (2003). Monitoring options for visitor numbers in national parks and natural areas. Journal for nature conservation, 11(4), 240-250.
  • 7. Di Minin, E., Tenkanen, H., Toivonen, T. (2015). Prospects and challenges for social media data in conservation science. Frontiers in Environmental Science, 3, 63.
  • 8. Gülçin, D. (2020). Kültürel ekosistem hizmetlerinin sosyal medya verileri kullanılarak haritalanması: Datça yarımadası örneği. Türkiye Ormancılık Dergisi, 21(4), 407-416.
  • 9. Kovacs-Györi, A., Ristea, A., Kolcsar, R., Resch, B., Crivellari, A., Blaschke, T. (2018). Beyond spatial proximity—classifying parks and their visitors in London based on spatiotemporal and sentiment analysis of Twitter data. ISPRS International Journal of Geo-Information, 7(9), 378.
  • 10. Heikinheimo, V., Minin, E. D., Tenkanen, H., Hausmann, A., Erkkonen, J., Toivonen, T. (2017). User-generated geographic information for visitor monitoring in a national park: A comparison of social media data and visitor survey. ISPRS International Journal of Geo-Information, 6(3), 85.
  • 11. Levin, N., Lechner, A. M., Brown, G. (2017). An evaluation of crowdsourced information for assessing the visitation and perceived importance of protected areas. Applied geography, 79, 115-126.
  • 12. Manning, R. E. (2002). How much is too much? Carrying capacity of national parks and protected areas. In Monitoring and management of visitor flows in recreational and protected areas. conference proceedings (pp. 306-313).
  • 13. Schägner, J. P., Maes, J., Brander, L., Paracchini, M. L., Hartje, V., Dubois, G. (2017). Monitoring recreation across European nature areas: A geo-database of visitor counts, a review of literature and a call for a visitor counting reporting standard. Journal of outdoor recreation and tourism, 18, 44-55.
  • 14. Shoval, N., Ahas, R. (2016). The use of tracking technologies in tourism research: the first decade. Tourism Geographies, 18(5), 587-606.
  • 15. Sessions, C., Wood, S. A., Rabotyagov, S., Fisher, D. M. (2016). Measuring recreational visitation at US National Parks with crowd-sourced photographs. Journal of environmental management, 183, 703-711.
  • 16. Ullah, H., Wan, W., Ali Haidery, S., Khan, N. U., Ebrahimpour, Z., Luo, T. (2019). Analyzing the spatiotemporal patterns in green spaces for urban studies using location-based social media data. ISPRS International Journal of Geo-Information, 8(11), 506.
  • 17. Walden-Schreiner, C., Rossi, S. D., Barros, A., Pickering, C., Leung, Y. F. (2018). Using crowd-sourced photos to assess seasonal patterns of visitor use in mountain-protected areas. Ambio, 47(7), 781-793.
  • 18. Xie, Z., Yan, J. (2008). Kernel density estimation of traffic accidents in a network space. Computers, environment and urban systems, 32(5), 396-406.
  • 19. URL-1: http://beydaglari.tabiat.gov.tr/, (15.03.2021).
  • 20. URL-2: https://www.flickr.com/, (18.03.2021).
  • 21. URL-3: https://www.python.org, (18.03.2021).
Toplam 21 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Çevresel Olarak Sürdürülebilir Mühendislik
Bölüm Sustainable Design, Landscape Planning and Architecture
Yazarlar

Ahmet Uslu 0000-0001-8745-423X

Yayımlanma Tarihi 16 Ağustos 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 23 Sayı: 2

Kaynak Göster

APA Uslu, A. (2021). Sosyal Medya Verileri Kullanılarak Milli Park Ziyaretlerinin Mekânsal ve Zamansal Değişiminin Modellenmesi: Beydağları Sahil Milli Parkı Örneği. Bartın Orman Fakültesi Dergisi, 23(2), 386-398. https://doi.org/10.24011/barofd.910977


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