بررسی رابطه اقلیم با روند گردشگری در نیمه شمال شرقی ایران
محورهای موضوعی : علوم جغرافیا (کلیه گرایشها)عبدالمطلب کریم زاده 1 , رحیم بردی آنامراد نژاد 2 , الهه مرادی 3
1 - دانشگاه مازندران
2 - دانشگاه مازندران
3 - دانشگاه آزاد اسلامی واحد یاسوج
کلید واژه: تورسیم, اقلیم, شاخص TCI, شمال¬شرق ایران,
چکیده مقاله :
اين پژوهش با هدف بررسی رابطة شرايط اقليمی و نيز تاثير اقليم بر توسعه و روند گردشگري در نیمه ی شرقی شمال ایران انجام شده است. در اين پژوهش از شاخص اقليم گردش (TCI) و 7 متغیر اقلیمی برای محاسبه مقادیر شاخص های اصلی و فرعی TCI استفاده شده است. این داده های اقلیمی برای یک دوره 20 ساله از 1990 تا 2011 مربوط به ایستگاه سینوپتیک استان خراسان رضوی، شمالی و جنوبی از طریق پایگاه اینترنتی سازمان هواشناسی کشور دریافت شد. به منظور پهنه بندي شرايط اقليم گردشگري نیمه ی شمال شرقی ایران از تبديل اطلاعات نقطه اي ايستگاه ها به اطلاعات سطحي، از نرم افزار GIS بهره گرفته شد. شرايط اقليم توريستي شمال شرق ایران در مقياس ماهانه با استفاده از شاخص اقليم توريستي مورد بررسي قرار گرفت. نتايج حاصله براي هر ماه به صورت مجزا در یافته های پژوهش آورده شده است. نتایج پژوهش نشان داد، كه شاخص TCI در مناطق مختلف منطقه مورد مطالعه داراي تنوع زيادي است. به طوري كه با توجه به ويژگي سالانه شاخص(TCI) در سطح استانها ماه هاي مي، ژوئن، جولاي، آگوست و سپتامبر (ارديبهشت، خرداد، تير، مرداد و شهريور) داراي بهترين شرايط از نظر آسايش اقليمي گردشگران مي باشد و ماه هاي ژانويه، فوريه، نوامبر و مارس (آذر، دي، بهمن و اسفند) داراي بدترين شرايط از اين نظر مي باشند. بررسي و مقايسة نتايج به دست آمده از شاخص TCI براي مناطق مختلف استان، حاكي از همخواني و تناسب نتايج پژوهش با واقعيت هاي اقليمي اين مناطق دارد.
The aim of this study was to investigate the relationship between climatic conditions and the effect of climate on the development and trend of tourism in the eastern half of northern Iran. In this study, circulation climate index (TCI) and 7 climatic variables have been used to calculate the values of major and minor TCI indices. These climatic data for a period of 20 years from 1990 to 2011 related to the synoptic station of Khorasan Razavi province, north and south were received through the website of the Meteorological Organization. In order to zoning the tourism climate conditions of the northeastern half of Iran from the conversion of station point information to surface information, GIS software was used. The tourist climate conditions of Northeast Iran were studied on a monthly basis using the tourist climate index. The results for each month are presented separately in the research findings. The results showed that the TCI index in different regions of the study area has a great variety. According to the annual characteristics of the index (TCI) in the provinces, May, June, July, August and September (May, June, July, August and September) have the best conditions in terms of climatic comfort of tourists and the month January, February, November and March (December, January, February and March) have the worst conditions in this regard. The study and comparison of the results obtained from the TCI index for different regions of the province indicate the concordance and appropriateness of the research results with the climatic realities of these regions.
• Adiguzel, F., Bozdogan Sert, E., Dinc, Y., Cetin, M., Gungor, S., Yuka, P., Sertkaya Dogan, O., Kaya, E., Karakaya, K. and Vural, E., 2021. Determining the relationships between climatic elements and thermal comfort and tourism activities using the tourism climate index for urban planning: a case study of Izmir Province. Theoretical and Applied Climatology, pp.1-16.
• Bouras, E.H., Jarlan, L., Er-Raki, S., Balaghi, R., Amazirh, A., Richard, B. and Khabba, S., 2021. Cereal yield forecasting with satellite drought-based indices, weather data and regional climate indices using machine learning in Morocco. Remote Sensing, 13(16), p.3101.
• Bouras, E.H., Jarlan, L., Er-Raki, S., Balaghi, R., Amazirh, A., Richard, B. and Khabba, S., 2021. Cereal yield forecasting with satellite drought-based indices, weather data and regional climate indices using machine learning in Morocco. Remote Sensing, 13(16), p.3101.
• Carrillo, J., González, A., Pérez, J.C., Expósito, F.J. and Díaz, J.P., 2022. Projected impacts of climate change on tourism in the Canary Islands. Regional Environmental Change, 22(2), pp.1-13.
• Day, J., Chin, N., Sydnor, S., Widhalm, M., Shah, K.U. and Dorworth, L., 2021. Implications of climate change for tourism and outdoor recreation: an Indiana, USA, case study. Climatic Change, 169(3), pp.1-21.
• Demiroglu, O.C., Saygili-Araci, F.S., Pacal, A., Hall, C.M. and Kurnaz, M.L., 2020. Future Holiday Climate Index (HCI) performance of urban and beach destinations in the Mediterranean. Atmosphere, 11(9), p.911.
• Gao, C., Liu, J., Zhang, S., Zhu, H. and Zhang, X., 2022. The Coastal Tourism Climate Index (CTCI): Development, Validation, and Application for Chinese Coastal Cities. Sustainability, 14(3), p.1425.
• García-León, D., Contreras, S. and Hunink, J., 2019. Comparison of meteorological and satellite-based drought indices as yield predictors of Spanish cereals. Agricultural Water Management, 213, pp.388-396.
• Howard, S.J., Cerar, D., Anderson, M.J., Albarrag, A., Fisher, M.C., Pasqualotto, A.C., Laverdiere, M., Arendrup, M.C., Perlin, D.S. and Denning, D.W., 2009. Frequency and evolution of azole resistance in Aspergillus fumigatus associated with treatment failure. Emerging infectious diseases, 15(7), p.1068.
• Krebs, L.K., 2019. ASSESSING CLIMATE CHANGE, Ecotourism and Small Communities. Northeastern Geographer, 11.
• Lee, J.H., Ramirez, J.A., Kim, T.W. and Julien, P.Y., 2019. Variability, teleconnection, and predictability of Korean precipitation in relation to large scale climate indices. Journal of Hydrology, 568, pp.12-25.
• Ma, S., Craig, C.A., Feng, S. and Liu, C., 2021. Climate resources at United States National Parks: A tourism climate index approach. Tourism Recreation Research, pp.1-15.
• Matthews, L., Scott, D. and Andrey, J., 2021. Development of a data-driven weather index for beach parks tourism. International journal of biometeorology, 65(5), pp.749-762.
• Mihăilă, D., Bistricean, P.I. and Briciu, A.E., 2019. Assessment of the climate potential for tourism. Case study: the North-East Development Region of Romania. Theoretical and applied climatology, 137(1), pp.601-622.
• Miró Pérez, J.J. and Olcina, J., 2020. Cambio climático y confort térmico. Efectos en el turismo de la Comunidad Valenciana.
• Noome, K. and Fitchett, J.M., 2019. An assessment of the climatic suitability of Afriski Mountain Resort for outdoor tourism using the Tourism Climate Index (TCI). Journal of Mountain Science, 16(11), pp.2453-2469.
• Qiang, M., 2020. Does climate drive tourism seasonality in cultural destinations? A comparative study. Current Issues in Tourism, 23(22), pp.2756-2761.
• Rasilla, D.F., 2021. Impact of Climate Variability on Climate Beach-Based Tourism Aptitude: A Case Study in the Atlantic Coast of SW Europe. Atmosphere, 12(10), p.1328.
• Roshani, A., Parak, F. and Esmaili, H., 2021. Trend analysis of climate change compound indices in Iran. Journal of Water and Climate Change, 12(3), pp.801-816.
• Rutty, M., Scott, D., Matthews, L., Burrowes, R., Trotman, A., Mahon, R. and Charles, A., 2020. An inter-comparison of the holiday climate index (HCI: Beach) and the tourism climate index (TCI) to explain Canadian tourism arrivals to the Caribbean. Atmosphere, 11(4), p.412.
• Scott, D. and McBoyle, G., 2001, December. Using a ‘tourism climate index’to examine the implications of climate change for climate as a tourism resource. In First International Workshop on Climate, Tourism and Recreation (pp. 69-88). Porto Carras: International Society of Biometeorology.
• Yañez, C.C., Hopkins, F.M. and Porter, W.C., 2020. Projected impacts of climate change on tourism in the Coachella Valley, California. Climatic Change, 162(2), pp.707-721.
• Yin, G., Zhang, H. and Zhang, L., 2021, July. A New Comprehensive Drought Index Based on Response Adjustment for Vegetation Types. In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS (pp. 8636-8639). IEEE.
• Yu, D.D., Rutty, M., Scott, D. and Li, S., 2021. A comparison of the holiday climate index: beach and the tourism climate index across coastal destinations in China. International Journal of Biometeorology, 65(5), pp.741-748.
• Yushina, Y. and Yegemberdiyeva, K., 2019. Assessment of tourism and recreational potential of climatic resources of the Akmola region (Kazakhstan). International Multidisciplinary Scientific GeoConference: SGEM, 19(5.3), pp.69-75.
• Zhong, L., Yu, H. and Zeng, Y., 2019. Impact of climate change on Tibet tourism based on tourism climate index. Journal of Geographical Sciences, 29(12), pp.2085-2100.