Theoretical and Applied Climatology

, Volume 130, Issue 3–4, pp 807–816 | Cite as

Trends of urban surface temperature and heat island characteristics in the Mediterranean

  • Nikolaos Benas
  • Nektarios Chrysoulakis
  • Constantinos Cartalis
Original Paper


Urban air temperature studies usually focus on the urban canopy heat island phenomenon, whereby the city center experiences higher near surface air temperatures compared to its surrounding non-urban areas. The Land Surface Temperature (LST) is used instead of urban air temperature to identify the Surface Urban Heat Island (SUHI). In this study, the nighttime LST and SUHI characteristics and trends in the seventeen largest Mediterranean cities were investigated, by analyzing satellite observations for the period 2001–2012. SUHI averages and trends were based on an innovative approach of comparing urban pixels to randomly selected non-urban pixels, which carries the potential to better standardize satellite-derived SUHI estimations. A positive trend for both LST and SUHI for the majority of the examined cities was documented. Furthermore, a 0.1 °C decade−1 increase in urban LST corresponded to an increase in SUHI by about 0.04 °C decade−1. A longitudinal differentiation was found in the urban LST trends, with higher positive values appearing in the eastern Mediterranean. Examination of urban infrastructure and development factors during the same period revealed correlations with SUHI trends, which can be used to explain differences among cities. However, the majority of the cities examined show considerably increased trends in terms of the enhancement of SUHI. These findings are considered important so as to promote sustainable urbanization, as well as to support the development of heat island adaptation and mitigation plans in the Mediterranean.


Land Surface Temperature Sampling Zone Anthropogenic Heat Local Solar Time Surface Urban Heat Island 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was performed in the framework of the PEFYKA project within the KRIPIS Action of the GSRT. The project is funded by Greece and the European Regional Development Fund of the European Union under the NSRF and the O.P. Competitiveness and Entrepreneurship. The MODIS MOD11A2 product files were obtained from the NASA Land Processes Distributed Active Archive Center ( mod11a2). The GlobCOVER V2.3 product files were obtained from the ESA Data User Element web page (


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Copyright information

© Springer-Verlag Wien 2016

Authors and Affiliations

  • Nikolaos Benas
    • 1
  • Nektarios Chrysoulakis
    • 1
  • Constantinos Cartalis
    • 2
  1. 1.Foundation for Research and Technology Hellas (FORTH)Institute of Applied and Computational MathematicsHeraklionGreece
  2. 2.Department of Environmental PhysicsNational and Kapodistrian University of AthensAthensGreece

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