Evaluation of spatio-temporal variability in Land Surface Temperature: A case study of Zonguldak, Turkey

Sekertekin A., Kutoglu S. H., Kaya Ş.

ENVIRONMENTAL MONITORING AND ASSESSMENT, vol.188, no.1, 2016 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 188 Issue: 1
  • Publication Date: 2016
  • Doi Number: 10.1007/s10661-015-5032-2
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Keywords: Land Surface Temperature (LST), Landsat, Mono-window algorithm, Spatio-temporal variability, Zonguldak, URBAN HEAT ISLANDS, USE/LAND-COVER, IMPACTS, EMISSIVITY, URBANIZATION, ALGORITHM, SHANGHAI, ISTANBUL, IMAGE
  • Istanbul Technical University Affiliated: Yes


The aim of this study is to analyze spatiotemporal variability in Land Surface Temperature (LST) in and around the city of Zonguldak as a result of the growing urbanization and industrialization during the last decade. Three Landsat 5 data and one Landsat 8 data acquired on different dates were exploited in acquiring LST maps utilizing mono-window algorithm. The outcomes obtained from this study indicate that there exists a significant temperature rise in the region for the time period between 1986 and 2015. Some cross sections were selected in order to examine the relationship between the land use and LST changes in more detail. The mean LST difference between 1986 and 2015 in ERDEMIR iron and steel plant (6.8 degrees C), forestland (3 degrees C), city and town centers (4.2 degrees C), municipal rubbish tip (-3.9 degrees C), coal dump site (12.2 degrees C), and power plants' region (7 degrees C) were presented. In addition, the results indicated that the mean LST difference be-tween forestland and city centers was approximately 5 degrees C, and the difference between forestland and industrial enterprises was almost 8 degrees C for all years. Spatiotemporal variability in LST in Zonguldak was examined in that study and due to the increase in LST, policy makers and urban planners should consider LST and urban heat island parameters for sustainable development.