Temperature-Humidity Index described by fractal Higuchi Dimension affects tourism activity in the urban environment of Focşani City (Romania)

  • Ana-Maria Ciobotaru
  • Ion Andronache
  • Nilanjan Dey
  • Martina Petralli
  • Mohammad Reza Mansouri Daneshvar
  • Qianfeng Wang
  • Marko Radulovic
  • Radu-Daniel Pintilii
Original Paper


The bioclimatic analysis in the context of urban environment and tourism activity is relatively new in Romania and highly important for the development of tourism. In the present study, the evidence of increasing air temperature by the Temperature-Humidity Index (THI) was conducted in the Focşani City, Romania, within the period of 17 years (2001–2017). Bioclimatic conditions were defined for this area by the relationship between air temperature, relative humidity, and THI. Tourism activities, such as nights spent in the city and arrivals of tourists in accommodations, were associated with the THI for the periods 2001–2016. As the THI values increased, higher tourist activity was recorded as measured by the overnight stays and arrivals in accommodations. The results of the bioclimatological analysis further revealed a high discomfort by the low winter temperatures and the high summer heat. The highest THI value, recorded in this period, was 38.5 °C in August 2017, while the lowest was − 6.8 °C, in January 2013. The bioclimatic comfort positively correlated with an increase in the number of arrivals and nights spent, in summer and in early autumn. In this paper, the analysis of THI in Focşani City (Romania) was used as a research example, to show that analysis of extreme temperatures can improve the future characterization of climatic events, its variability, and spatial pattern. Higuchi Dimension (D H ) was used for additional assessment of THI, in order to better define its annual and monthly THI complexity. The innovative results consist of using the D H to determine the degree of complexity of THI oscillations and their impact on tourism activity. This study reports tools that efficiently define periods when conditions are usually unfavorable for tourism. This information facilitates the decision to increase the tourist offer for this period and thus may help decision-makers in the management of regional tourism. This can be the basis for future studies on the prevention of negative effects caused by the extreme weather conditions.


Bioclimatic analysis Temperature-Humidity Index Tourism activity 



We would like to thank Bahram Saghafian from the Soil Conservation and Watershed Management Research Institute, Iran, Hasan Tatli from Çanakkale Onsekiz Mart University, Department of Geography, Turkey, for advices and great comments, and Gerard van der Schrier from ECA&D for help and the quick response to our requests.

Funding information

This work was supported by a grant from the Romanian National Authority for Scientific Research and Innovation, CNCS-UEFISCDI, project number PN-II-RU-TE-2014-4-0835 and by a grant from the University of Bucharest—“Spatial projection of the human pressure on forest ecosystems in Romania” (UB/1365).


  1. Agayev TD, Gorchiyev AA (1989) Negative factors in the use of the bioclimatic resources of the Apsheron Peninsula. Sov Geogr 30(7):539–546Google Scholar
  2. Bleta A, Nastos PT, Matzarakis A (2014) Assessment of bioclimatic conditions on Crete Island, Greece. Reg Environ Chang 14(5):1967–1981. CrossRefGoogle Scholar
  3. Bodri L (1994) Fractal analysis of climatic data: mean annual temperature records in Hungary. Theor Appl Climatol 49(1):53–57. CrossRefGoogle Scholar
  4. Çalışkan O, Çiçek I, Matzarakis A (2012) The climate and bioclimate of Bursa (Turkey) from the perspective of tourism. Theor Appl Climatol 107(3–4):417–425. Google Scholar
  5. Coyt GG, Diosdado AM, Lopez JAB, Correa JLD, Brown FA (2013) Higuchi’s method applied to the detection of periodic components in time series and its application to seismograms. Revista Mexicana de Física 59(1):1–6Google Scholar
  6. Daneshvar MRM, Bagherzadeh A, Tavousi T (2013) Assessment of bioclimatic comfort conditions based on Physiologically Equivalent Temperature (PET) using the RayMan Model in Iran. Central Eur J Geosci 5(1):53–60. Google Scholar
  7. Davidson J (1937) Bioclimatic zones of Australia. Nature 140:265–266. CrossRefGoogle Scholar
  8. Dimadama Z, Chantzi G (2014) A new era for tourism in the Black Sea area. Int J Cult Digit Tour 1(2):23–29Google Scholar
  9. Drăghici CC (2012) Touristic activities and integrated development in the influence areas of Râmnicu Vâlcea city. Universitara Publisher, Bucharest (in Romanian)Google Scholar
  10. ECA&D (2017) European Climate Assessment & Dataset. Accessed 10 Jan 2018
  11. Fraga H, Malheiro AC, Moutinho-Pereira J, Jones GV, Alves F, Pinto JG, Santos JA (2014) Very high resolution bioclimatic zoning of Portuguese wine regions: present and future scenarios. Reg Environ Chang 14(1):295–306. CrossRefGoogle Scholar
  12. Garzón-Machado V, Otto R, Aguilar MJD (2014) Bioclimatic and vegetation mapping of a topographically complex oceanic island applying different interpolation techniques. Int J Biometeorol 58(5):887–899. Google Scholar
  13. Guzmán-Vargas L, Ramírez-Rojas A, Hernández-Pérez R, Angulo-Brown F (2009) Correlations and variability in electrical signals related to earthquake activity. Physica A Stat Mech Appl 388(19):4218–4228. CrossRefGoogle Scholar
  14. Haylock MR, Hofstra N, Tank AMGK, Klok EJ, Jones PD, New M (2008) A European daily high-resolution gridded dataset of surface temperature and precipitation for 1950–2006. J Geophys Res-Atmos 113(D20).
  15. Higuchi T (1988) Approach to in irregular time-series on the basis of the fractal theory. Physica D Nonlinear Phenom 31(2):277–283. CrossRefGoogle Scholar
  16. Hjalager AM (2010) A review of innovation research in tourism. Tour Manag 31(1):1–12. CrossRefGoogle Scholar
  17. Jolly WM, Nemani R, Running SW (2005) A generalized, bioclimatic index to predict foliar phenology in response to climate. Glob Chang Biol 11(4):619–632. CrossRefGoogle Scholar
  18. Kôvári I, Zimányi K (2011) Safety and security in the age of global tourism (the changing role and conception of safety and security in tourism). Res Agric Appl Econ 59–61Google Scholar
  19. Kyle WJ (1994) The human bioclimate of Hong Kong. In Brazdil R, Kolář M (ed) Proceedings of the Contemporary Climatology Conference, Brno, pp 345–350Google Scholar
  20. Letunov PA, Ivanova YN, Rozov NN, Fridland VM, Shashko DI, Shuvalov SA (1960) A soils and bioclimatic regionalization of the USSR. Sov Geogr 1(8):32–55. CrossRefGoogle Scholar
  21. Lin TP, Matzarakis A (2008) Tourism climate and thermal comfort in sun moon Lake, Taiwan. Int J Biometeorol 52(4):281–290. CrossRefGoogle Scholar
  22. Marakova V, Dyr T, Wolak-Tuzimek A (2016) Factors of tourism’s competitiveness in the European Union countries. E M Ekonomie a Manag 19(3):92–109. CrossRefGoogle Scholar
  23. Matzarakis A (2006) Weather-and climate-related information for tourism. Tour Hosp Plann Dev 3(2):99–115. CrossRefGoogle Scholar
  24. Matzarakis A (2007) Assessment method for climate and tourism based on daily data. In: Matzarakis A, de Freitas CR, Scott D (eds) Developments in tourism climatology. German Meteorological Society, Freiburg, pp 52–58Google Scholar
  25. Matzarakis A, Hämmerle M, Koch E, Rudel E (2012) The climate tourism potential of Alpine destinations using the example of Sonnblick, Rauris and Salzburg. Theor Appl Climatol 110(4):645–658. CrossRefGoogle Scholar
  26. Matzarakis A, Rammelberg J, Junk J (2013) Assessment of thermal bioclimate and tourism climate potential for central Europe—the example of Luxembourg. Theor Appl Climatol 114(1–2):193–202. CrossRefGoogle Scholar
  27. Moral FJ, Rebollo FJ, Paniagua LL, García A (2014) Climatic spatial variability in Extremadura (Spain) based on viticultural bioclimatic indices. Int J Biometeorol 58(10):2139–2152. CrossRefGoogle Scholar
  28. NIS (2017) National Institute of Statistics, Statistics research Tourism. Accessed 20 Apr 2017
  29. NNDC CDO (2018) NNDC Climate Data Online. Accessed 10 Jan 2018
  30. Oliveira S, Andrade H (2007) An initial assessment of the bioclimatic comfort in an outdoor public space in Lisbon. Int J Biometeorol 52(1):69–84. CrossRefGoogle Scholar
  31. Pantavou K, Santamouris M, Asimakopoulos D, Theoharatos G (2013) Evaluating the performance of bioclimatic indices on quantifying thermal sensation for pedestrians. Adv Build Energy Res 7(2):170–185. CrossRefGoogle Scholar
  32. Park S, Tuller SE, Jo M (2014) Application of Universal Thermal Climate Index (UTCI) for microclimatic analysis in urban thermal environments. Landsc Urban Plan 125:146–155. CrossRefGoogle Scholar
  33. Petralli M, Brandani G, Napoli M, Messeri A, Massetti L (2015) Thermal comfort and green areas in Florence. Ital J Agrometeorol-Rivista Italiana di Agrometeorologia 20(2):39–48Google Scholar
  34. Rutty M, Scott D (2015) Bioclimatic comfort and the thermal perceptions and preferences of beach tourists. Int J Biometeorol 59(1):37–45. CrossRefGoogle Scholar
  35. Salata F, Golasi I, Proietti R, Vollaro AD (2017) Implications of climate and outdoor thermal comfort on tourism: the case of Italy. Int J Biometeorol 61(12):2229–2244. CrossRefGoogle Scholar
  36. Sandu I, Pescaru VI, Poiana I (2008) Clima Romaniei. Academia Romania Publishing House, BucharestGoogle Scholar
  37. Schneider T (2001) Analysis of incomplete climate data: estimation of mean values and covariance matrices and imputation of missing values. J Clim 14(5):853–871.<0853:AOICDE>2.0.CO;2 CrossRefGoogle Scholar
  38. Shitzer A (2008) Assessment of the effects of environmental radiation on wind chill equivalent temperatures. Eur J Appl Physiol 104(2):215–220. CrossRefGoogle Scholar
  39. Shiue I, Matzarakis A (2011) Estimation of the tourism climate in the Hunter Region, Australia, in the early twenty-first century. Int J Biometeorol 55(4):565–574. CrossRefGoogle Scholar
  40. Sormunen H, Virtanen R, Luoto M (2011) Inclusion of local environmental conditions alters high-latitude vegetation change predictions based on bioclimatic models. Polar Biol 34(6):883–897. CrossRefGoogle Scholar
  41. Steadman RG (1979) The assessment of sultriness. 1. Temperature-humidity index based on human physiology and clothing science. J Appl Meteorol 18(7):861–873. CrossRefGoogle Scholar
  42. Surdu O, Tuta LA, Surdu TV, Surdu M, Mihailov CI (2015) Sustainable development of balneotherapy/thermalisme in Romania. J Environ Prot Ecol 16(4):1440–1446Google Scholar
  43. Surugiu C, Surugiu MR (2012) The assessment of climate change impact on the Romanian seaside tourism. Ekonomska Istrazivanja-Economic Research 25(4):959–972. CrossRefGoogle Scholar
  44. Tank AMGK, Kӧnnen GP (2003) Trends in indices of daily temperature and precipitation extremes in Europe, 1946–99. J Clim 16(22):3665–3680.<3665:TIIODT>2.0.CO;2 CrossRefGoogle Scholar
  45. Turcu D, Weisz J (2008) The economy of tourism. Eurostampa Publisher, TimişoaraGoogle Scholar
  46. WTTC (2017) World Travel & Tourism Council. London, United Kingdom. Accessed 25 Jun 2017
  47. Zaninović K, Matzarakis A (2009) The bioclimatological leaflet as a means conveying climatological information to tourists and the tourism industry. Int J Biometeorol 53(4):369–374. CrossRefGoogle Scholar
  48. Zbuchea A, Radu O (2009) Mountain tourism in Romania and its attractiveness on students. J Tour Chall Trends 2(1):43–64Google Scholar
  49. Žliobaitė I, Hollmén J, Junninen H (2014) Regression models tolerant to massively missing data: a case study in solar-radiation nowcasting. Atmos Meas Techn 7(12):4387–4399. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2018

Authors and Affiliations

  • Ana-Maria Ciobotaru
    • 1
    • 2
    • 3
  • Ion Andronache
    • 1
    • 2
  • Nilanjan Dey
    • 4
  • Martina Petralli
    • 5
    • 6
  • Mohammad Reza Mansouri Daneshvar
    • 7
  • Qianfeng Wang
    • 8
    • 9
    • 10
  • Marko Radulovic
    • 11
  • Radu-Daniel Pintilii
    • 1
    • 2
    • 3
  1. 1.Research Center for Integrated Analysis and Territorial ManagementUniversity of BucharestBucharestRomania
  2. 2.Research Institute of the University of Bucharest (ICUB)BucharestRomania
  3. 3.Faculty of GeographyUniversity of BucharestBucharestRomania
  4. 4.Department of Information TechnologyTechno India College of TechnologyKolkataIndia
  5. 5.Centre of BioclimatologyUniversity of FlorenceFlorenceItaly
  6. 6.Department of Agrifood Production and Environmental Sciences, DISPAAUniversity of FlorenceFlorenceItaly
  7. 7.Department of Geography and Natural HazardsResearch Institute of Shakhes PajouhIsfahanIran
  8. 8.College of Environment and ResourcesFuzhou UniversityFuzhouChina
  9. 9.Key Lab of Spatial Data Mining & Information SharingMinistry of Education of ChinaFuzhouChina
  10. 10.Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster ProtectionFuzhouChina
  11. 11.Institute for Oncology and Radiology, Laboratory of Cancer Cell BiologyBelgradeSerbia

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