Analyzing the impacts of physical and morphological characteristics of built-ups on land surface temperature changes in semi-arid regions

Document Type : Original Article


1 Remote Sensing and GIS Center, University of Shahid Beheshti, Tehran, Iran

2 Department of Geography and Urban Planning, Faculty of Geography, University of Tehran, Tehran, Iran


Urbanization and urban growth have a significant impact on the natural and human environment as well as the climate at local and regional scales. For instance, the difference in the energy balance of the central and peripheral regions of cities stems from their physical characteristics and surface land cover. These characteristics in the temperate regions create the phenomenon of urban heat island, but they cause the phenomenon of the urban cold island in arid and semi-arid areas. The purpose of this study was to analyze the impacts of land-surface characteristics, land cover, built-up areas, and morphological characteristics on temperature changes in Zanjan city, Iran.
Material and methods:
The dataset used in this study included Landsat-5 TM sensor images in 2010 and 2011 as well as statistical information at the level of building blocks. The methodology used in this study was to investigate the effects of different land covers on surface temperature. Then, to demonstrate the effects of built-up areas on surface temperature, the IBI method and Otsu threshold were used. To investigate the effects of the configuration of built-up areas on land surface temperature variations, landscape metrics such as Landscape Division Index, Fractal Dimension Index, and Percent cover of class areas were used. Finally, urban morphology has been investigated using Plot size (PS).
Results and discussion:
The results of this research showed that among all seasons, the stronger cold island was detected in summer. Moreover, the results also showed that the cold island was much better presented in summer than other seasons. The scatter plots between the land surface temperature (LST) on one hand, and the built-up area as well as the vegetation land cover, on the other hand, illustrated indirect correlations where higher Pearson correlation coefficient was observed between LST and the built-up area (r = - 0.704). Among the landscape metrics, the highest positive correlation (r = 0.72) was observed between LST and the Landscape Division Index. Moreover, a high negative correlation was found between the characteristics of urban morphology or Plot size and the LST (r = - 0.73). The results of the Pearson correlation between land cover, configuration, and morphology characteristics and LST were quite significant (P≤0.01).
From this research, it can be concluded that the configuration and morphology characteristics can model surface temperature variations better than the land cover.