KaydedilenlerDerginizi ekleyin

Dergiler / Türkiye Uzaktan Algılama Dergisi / 2026 / Volume: 8

Long-term spatio-temporal assessment of thermal comfort in Antalya (Türkiye) using the Universal Thermal Climate Index (UTCI)

Halil Burak Akdeniz(KONYA TEKNİK ÜNİVERSİTESİ)0000-0002-9504-051X
Ahmet Doğan Doğruluk(HATAY MUSTAFA KEMAL ÜNİVERSİTESİ, ANTAKYA MESLEK YÜKSEKOKULU)0000-0002-4318-8141
Ömer Acar(KAHRAMANMARAŞ SÜTÇÜ İMAM ÜNİVERSİTESİ, GÖKSUN MESLEK YÜKSEKOKULU)0000-0002-2382-8594
Sayfa
—
Yayın Tarihi
2026-10-05
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

These findings provide valuable scientific evidence for climate change adaptation, sustainable tourism management, public health planning, and the integration of thermal comfort into spatial planning practices.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Climate change and the increasing frequency of extreme heat events have intensified thermal stress, particularly in Mediterranean regions, posing significant challenges to human health, quality of life, and sustainable urban development.
📊
Temel Bulgular & Veri:Therefore, accurate assessment of outdoor thermal comfort has become increasingly important for supporting climate adaptation and planning strategies.
💡
Sonuç & Katkı:These findings provide valuable scientific evidence for climate change adaptation, sustainable tourism management, public health planning, and the integration of thermal comfort into spatial planning practices.
🔬Tür:Research Article
📍Kapsam:2000–2025 Verileri
⚙️Değişkenler:Bioclimatology · thermal comfort · universal thermal climate index (UTCI)

Abstract

Climate change and the increasing frequency of extreme heat events have intensified thermal stress, particularly in Mediterranean regions, posing significant challenges to human health, quality of life, and sustainable urban development. Therefore, accurate assessment of outdoor thermal comfort has become increasingly important for supporting climate adaptation and planning strategies. This study aims to investigate the long-term (2000–2025) spatio-temporal changes of thermal comfort in Antalya (Türkiye) using the Universal Thermal Climate Index (UTCI). In addition, the performance of different interpolation methods was compared using Leave-One-Out Cross-Validation to identify the most appropriate approach for UTCI mapping. Monthly mean air temperature, wind speed, and relative humidity data from 21 meteorological stations operated by the Turkish State Meteorological Service were used. As long-term mean radiant temperature observations were unavailable, this variable was derived from the ERA5-Land reanalysis dataset. UTCI values were calculated using the BioKlima 2.6 software package. UTCI surfaces were generated by interpolating station-based UTCI values, and Leave-One-Out Cross-Validation identified the Elevation Regression method as the most accurate spatial interpolation approach. The results reveal a pronounced seasonal cycle in thermal comfort across Antalya, strongly controlled by the elevation gradient extending from the Mediterranean coast to the Western Taurus Mountains. Six UTCI thermal stress classes were identified throughout the year. Spring and especially autumn were dominated by no thermal stress conditions, whereas cold stress prevailed over the high mountain ranges during winter. In contrast, moderate and strong heat stress became widespread along the coastal belt during summer, particularly in the central districts of Antalya and the coastal districts of Serik, Manavgat, and Kemer. These findings provide valuable scientific evidence for climate change adaptation, sustainable tourism management, public health planning, and the integration of thermal comfort into spatial planning practices.

🔖

Bu Makaleye Atıf Yap

Akdeniz, H. B., Doğruluk, A. D., Acar, Ö. (2026). Long-term spatio-temporal assessment of thermal comfort in Antalya (Türkiye) using the Universal Thermal Climate Index (UTCI). Türkiye Uzaktan Algılama Dergisi, Volume: 8. https://doi.org/10.51489/tuzal.2001975

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (62)

  1. Adıgüzel, F., & Doğan, M. (2020). Analysis of sufficiency and accessibility of active green areas in Cukurova. Kastamonu University Journal of Engineering and Sciences, 6(2), 95–106.
  2. Akdeniz, H. B. (2023). Spatio-temporal analysis of the effects of urban growth on urban heat island: Case of Konya, Turkiye. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLVIII-M-1-2023, 441–448. https://doi.org/10.5194/isprs-archives-XLVIII-M-1-2023-441-2023
  3. Akdeniz, H. B., Sağ, N. S., & İnam, Ş. (2023). Analysis of land use/land cover changes and prediction of future changes with land change modeler: Case of Belek, Turkey. Environmental Monitoring and Assessment, 195(1), 135. https://doi.org/10.1007/s10661-022-10746-w
  4. Barriopedro, D., Fischer, E. M., Luterbacher, J., Trigo, R. M., & García-Herrera, R. (2011). The hot summer of 2010: Redrawing the temperature record map of Europe. Science, 332(6026), 220–224. https://doi.org/10.1126/science.1201224
  5. Błażejczyk, K., Epstein, Y., Jendritzky, G., Staiger, H., & Tinz, B. (2012). Comparison of UTCI to selected thermal indices. International Journal of Biometeorology, 56(3), 515–535. https://doi.org/10.1007/s00484-011-0453-2
  6. Błażejczyk, K., Jendritzky, G., Bröde, P., Fiala, D., Havenith, G., Epstein, Y., Psikuta, A., & Kampmann, B. (2013). An introduction to the universal thermal climate index (UTCI). Geographia Polonica, 86(1), 5–10. https://doi.org/10.7163/gpol.2013.1
  7. Bröde, P., Fiala, D., Błażejczyk, K., Holmér, I., Jendritzky, G., Kampmann, B., Tinz, B., & Havenith, G. (2012). Deriving the operational procedure for the Universal Thermal Climate Index (UTCI). International Journal of Biometeorology, 56(3), 481–494. https://doi.org/10.1007/s00484-011-0454-1
  8. Bröde, P., Jendritzky, G., Fiala, D., & Havenith, G. (2010). The universal thermal climate index UTCI in operational use. In Proceedings of conference: Adapting to change: New thinking on comfort, Cumberland Lodge, Windsor, UK, 9–11 April 2010. Network for Comfort and Energy Use in Buildings.
  9. Coccolo, S., Kämpf, J., Scartezzini, J.-L., & Pearlmutter, D. (2016). Outdoor human comfort and thermal stress: A comprehensive review on models and standards. Urban Climate, 18, 33–57. https://doi.org/10.1016/j.uclim.2016.08.004
  10. Cressie, N. A. C. (1993). Statistics for spatial data. John Wiley & Sons. https://doi.org/10.1002/9781119115151
  11. Denizdurduran, M., & Kızılelma, Y. (2023). Maksimum ve minimum sıcaklıkların mevsimsel trendi: Orta Fırat bölümü [Seasonal trend of maximum and minimum temperatures: The Middle Firat section]. Social Science Development Journal, 8(40), 29–38. https://doi.org/10.31567/ssd.1052
  12. Di Napoli, C., Messeri, A., Novák, M., Rio, J., Wieczorek, J., Morabito, M., Silva, P., Crisci, A., & Pappenberger, F. (2021). The universal thermal climate index as an operational forecasting tool of human biometeorological conditions in Europe. In E. L. Krüger (Ed.), Applications of the universal thermal climate index UTCI in biometeorology: Latest developments and case studies (pp. 193–208). Springer International Publishing. https://doi.org/10.1007/978-3-030-76716-7_10
  13. Dobek, M., Wereski, S., & Krzyżewska, A. (2020). Bioclimatic conditions of Lublin based on the Universal Thermal Climate Index (UTCI). Miscellanea Geographica. Regional Studies on Development, 24(3), 118–127. https://doi.org/10.2478/mgrsd-2020-0025
  14. Doğruluk, A. D., Ekercin, S., & Varlık, A. (2024). Determining residential areas based on bioclimatic conditions in Kahramanmaraş, Türkiye. Afyon Kocatepe Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, 24(5), 1215–1224. https://doi.org/10.35414/akufemubid.1435627
  15. Doğruluk, A. D., Ekercin, S., & Varlık, A. (2026). Determination of suitable urban settlement areas based on multi-hazard susceptibility and bioclimatic comfort: A GIS–AHP approach for Kahramanmaraş, Türkiye. Turkish Journal of Remote Sensing, 8, 1925848. https://doi.org/10.51489/tuzal.1925848
  16. Fanger, P. O. (1970). Thermal comfort: analysis and applications in environmental engineering. Danish Technical Press.
  17. Fiala, D., Havenith, G., Bröde, P., Kampmann, B., & Jendritzky, G. (2012). UTCI-Fiala multi-node model of human heat transfer and temperature regulation. International Journal of Biometeorology, 56(3), 429–441. https://doi.org/10.1007/s00484-011-0424-7
  18. Fowler, H. J., Lenderink, G., Prein, A. F., Westra, S., Allan, R. P., Ban, N., Barbero, R., Berg, P., Blenkinsop, S., Do, H. X., Guerreiro, S., Haerter, J. O., Kendon, E. J., Lewis, E., Schaer, C., Sharma, A., Villarini, G., Wasko, C., & Zhang, X. (2021). Anthropogenic intensification of short-duration rainfall extremes. Nature Reviews Earth & Environment, 2(2), 107–122. https://doi.org/10.1038/s43017-020-00128-6
  19. Galanaki, E., Giannaros, C., Kotroni, V., Lagouvardos, K., & Papavasileiou, G. (2023). Spatio-temporal analysis of heatwaves characteristics in Greece from 1950 to 2020. Climate, 11(1), 5. https://doi.org/10.3390/cli11010005
  20. Ge, Q., Kong, Q., Xi, J., & Zheng, J. (2017). Application of UTCI in China from tourism perspective. Theoretical and Applied Climatology, 128(3), 551–561. https://doi.org/10.1007/s00704-016-1731-z
  21. Goovaerts, P. (1997). Geostatistics for Natural Resources Evaluation. Oxford University Press.
  22. Hejazizadeh, Z., Karbalaee, A., Hosseini, S. A., & Tabatabaei, S. A. (2019). Comparison of the holiday climate index (HCI) and the tourism climate index (TCI) in desert regions and Makran coasts of Iran. Arabian Journal of Geosciences, 12(24), 803. https://doi.org/10.1007/s12517-019-4997-5
  23. Hengl, T. (2009). A practical guide to geostatistical mapping. In: Extended edition of the EUR 22904 EN Scientific and Technical Research series report published by Office for Official Publications of the European Communities Luxembourg, 2nd edn, p. 293.
  24. Hiroki, R., Varquez, A. C. G., Khanh, D. N., Rynazal, R., Renard, F., Alonso, L., & Kanda, M. (2025). Long-term changes of Universal Thermal Climate Index (UTCI) estimated from weather stations and gradient-boosted decision trees throughout Japan. International Journal of Climatology, 45(8), e8843. https://doi.org/10.1002/joc.8843
  25. Hua, L., Zhang, H., Liu, X., Yang, X., Duan, H., & Wu, T. (2020). Climate comfort evaluation of national 5A touristattractions in the mainland of China based on universal thermal climate index. Advances in Meteorology, 2020(1), 4256164. https://doi.org/10.1155/2020/4256164
  26. IPCC. (2021). Climate change 2021: The physical science basis. Retrieved June 5, 2026, from https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_SummaryVolume.pdf
  27. IPCC. (2023). Summary for policymakers. In Core Writing Team, H. Lee, & J. Romero (Eds.), Climate change 2023: Synthesis report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 1–34). IPCC. https://doi.org/10.59327/IPCC/AR6-9789291691647.001
  28. Isinkaralar, O. (2023). Bioclimatic comfort in urban planning and modeling spatial change during 2020–2100 according to climate change scenarios in Kocaeli, Türkiye. International Journal of Environmental Science and Technology, 20(7), 7775–7786. https://doi.org/10.1007/s13762-023-04992-9
  29. Jendritzky, G., de Dear, R., & Havenith, G. (2012). UTCI—why another thermal index? International Journal of Biometeorology, 56(3), 421–428. https://doi.org/10.1007/s00484-011-0513-7
  30. Jendritzky, G., Havenith, G., Weihs, P., & Batchvarova, E. (2009). Towards a Universal Thermal Climate Index UTCI for assessing the thermal environment of the human being. Final Report COST Action, 730(10).
  31. Koppe, C., Kovats, S., Jendritzky, G., & Menne, B. (2004). Heat-waves: risks and responses (No. EUR/03/5036810). World Health Organization. Regional Office for Europe.
  32. Li, J., Niu, J., Mak, C. M., Huang, T., & Xie, Y. (2018). Assessment of outdoor thermal comfort in Hong Kong based on the individual desirability and acceptability of sun and wind conditions. Building and Environment, 145, 50–61. https://doi.org/10.1016/j.buildenv.2018.08.059
  33. Makhelouf, A. (2009). The effect of green spaces on urban climate and pollution. Iranian Journal of Environmental Health Science & Engineering, 6(1), 35–40.
  34. Mansuroğlu, S., Dağ, V., & Kalaycı Önaç, A. (2021). Attitudes of people toward climate change regarding the bioclimatic comfort level in tourism cities; evidence from Antalya, Turkey. Environmental Monitoring and Assessment, 193(7), 420. https://doi.org/10.1007/s10661-021-09205-9
  35. Meehl, G. A., & Tebaldi, C. (2004). More intense, more frequent, and longer lasting heat waves in the 21st century. Science, 305(5686), 994–997. https://doi.org/10.1126/science.1098704
  36. MGM. (2026). 2025 yılı Türkiye iklim değerlendirmesi. Retrieved June 15, 2026, from https://www.mgm.gov.tr/iklim/iklim-raporlari.aspx
  37. Mihăilă, D., Bistricean, P.-I., & 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(1-2), 601–622. https://doi.org/10.1007/s00704-018-2611-5
  38. MCT. (2025). Tourism statistics. Retrieved June 15, 2026, from https://yigm.ktb.gov.tr/TR-9851/turizm-istatistikleri.html
  39. Ncongwane, K. P., Botai, J. O., Sivakumar, V., & Botai, C. M. (2021). A literature review of the impacts of heat stress on human health across Africa. Sustainability, 13(9), 5312. https://doi.org/10.3390/su13095312
  40. Pantavou, K., Kotroni, V., Kyros, G., & Lagouvardos, K. (2024). Thermal bioclimate in Greece based on the Universal Thermal Climate Index (UTCI) and insights into 2021 and 2023 heatwaves. Theoretical and Applied Climatology, 155(7), 6661–6675. https://doi.org/10.1007/s00704-024-04989-5
  41. Pantavou, K., Kotroni, V., Lagouvardos, K., & Kyriakou, P. (2025). Future changes of bioclimate in Greece: Variations in thermal stress according to the Universal Thermal Climate Index (UTCI). Science of The Total Environment, 980, 179514. https://doi.org/10.1016/j.scitotenv.2025.179514
  42. Pantavou, K., Santamouris, M., Asimakopoulos, D., & Theoharatos, G. (2013). Evaluating the performance of bioclimatic indices on quantifying thermal sensation for pedestrians. Advances in Building Energy Research, 7(2), 170–185. https://doi.org/10.1080/17512549.2013.865557
  43. Pecelj, M. M., Lukić, M. Z., Filipović, D. J., Protić, B. M., & Bogdanović, U. M. (2020). Analysis of the Universal Thermal Climate Index during heat waves in Serbia. Natural Hazards and Earth System Sciences, 20(7), 2021–2036. https://doi.org/10.5194/nhess-20-2021-2020
  44. Potchter, O., Cohen, P., Lin, T.-P., & Matzarakis, A. (2018). Outdoor human thermal perception in various climates: A comprehensive review of approaches, methods and quantification. Science of The Total Environment, 631–632, 390–406. https://doi.org/10.1016/j.scitotenv.2018.02.276
  45. Roffe, S. J., van der Walt, A. J., & Fitchett, J. M. (2023). Spatiotemporal characteristics of human thermal comfort across southern Africa: An analysis of the Universal Thermal Climate Index for 1971–2021. International Journal of Climatology, 43(6), 2930–2952. https://doi.org/10.1002/joc.8009
  46. Sancar, M. C., & Güngör, Ş. (2022). Isı indeksi’ne göre Antalya ili biyoklimatik konfor özelliklerinin analizi. International Journal of Eurasia Social Sciences, 13(48), 710–723. https://doi.org/10.35826/ijoess.3166
  47. Seltenrich, N. (2015). Between extremes: Health effects of heat and cold. Environmental Health Perspectives, 123(11), A275–A279. https://doi.org/10.1289/ehp.123-A275
  48. Shepard, D. (1968). A two-dimensional interpolation function for irregularly-spaced data. In Proceedings of the 1968 23rd ACM national conference (pp. 517–524). Association for Computing Machinery. https://doi.org/10.1145/800186.810616
  49. Shukla, K. K., Attada, R., Kumar, A., Kunchala, R. K., & Sivareddy, S. (2022). Comprehensive analysis of thermal stress over northwest India: Climatology, trends and extremes. Urban Climate, 44, 101188. https://doi.org/10.1016/j.uclim.2022.101188
  50. Smith, E. T., & Sheridan, S. C. (2018). The characteristics of extreme cold events and cold air outbreaks in the eastern United States. International Journal of Climatology, 38(S1), e807–e820. https://doi.org/10.1002/joc.5408
  51. Spangler, K. R., Liang, S., & Wellenius, G. A. (2022). Wet-bulb globe temperature, universal thermal climate index, and other heat metrics for US Counties, 2000–2020. Scientific Data, 9(1), 326. https://doi.org/10.1038/s41597-022-01405-3
  52. Spronken-Smith, R. A., & Oke, T. R. (1998). The thermal regime of urban parks in two cities with different summer climates. International Journal of Remote Sensing, 19(11), 2085–2104. https://doi.org/10.1080/014311698214884
  53. TUIK. (2026). Nüfus istatistikleri portalı. Retrieved June 15, 2026, from https://www.tuik.gov.tr/
  54. van der Walt, A. J., & Fitchett, J. M. (2022). Extreme temperature events (ETEs) in South Africa: A review. South African Geographical Journal, 104(1), 70–88. https://doi.org/10.1080/03736245.2021.1907219
  55. Vinogradova, V. (2021). Using the Universal Thermal Climate Index (UTCI) for the assessment of bioclimatic conditions in Russia. International Journal of Biometeorology, 65(9), 1473–1483. https://doi.org/10.1007/s00484-020-01901-4
  56. WMO. (2019). The global climate in 2015–2019. Retrieved June 10, 2026, from https://library.wmo.int/idurl/4/56809
  57. WMO. (2021). State of the global climate 2020, WMO no. 1264. Retrieved June 10, 2026, from https://library.wmo.int/idurl/4/56247
  58. Wu, J., Liu, C., & Wang, H. (2022). Analysis of spatio-temporal patterns and related factors of thermal comfort in subtropical coastal cities based on local climate zones. Building and Environment, 207, 108568. https://doi.org/10.1016/j.buildenv.2021.108568
  59. Xu, Y., Tian, L., Cui, T., Zhang, J., Zhang, H., Wang, Y., & Wang, R. (2025). Spatiotemporal characteristics of Universal Thermal Climate Index during five-year return period extreme heat events in the Beijing–Tianjin–Hebei region. Atmospheric and Oceanic Science Letters, 18(3), 100612. https://doi.org/10.1016/j.aosl.2025.100612
  60. Zare, S., Hasheminejad, N., Shirvan, H. E., Hemmatjo, R., Sarebanzadeh, K., & Ahmadi, S. (2018). Comparing Universal Thermal Climate Index (UTCI) with selected thermal indices/environmental parameters during 12 months of the year. Weather and Climate Extremes, 19, 49–57. https://doi.org/10.1016/j.wace.2018.01.004
  61. Zeng, D., Wu, J., Mu, Y., Deng, M., Wei, Y., & Sun, W. (2020). Spatial-temporal pattern changes of UTCI in the China–Pakistan Economic Corridor in recent 40 years. Atmosphere, 11(8), 858. https://doi.org/10.3390/atmos11080858
  62. Zeydan, Ö., Zeydan, İ., & Gürbüz, A. (2025). Evaluating climate change effects on coastal tourism over the Black Sea region by using the summer simmer index. Sustainability, 17(4), 1490. https://doi.org/10.3390/su17041490