Abstract
Large areas of cropland and natural vegetation have been replaced by impervious surfaces during the recent rapid urbanization in China, which has resulted in intensified urban heat island effects and modified local or regional warming trends. However, it is unclear how urban expansion contributes to local temperature change. In this study, we investigated the relationship between land surface temperature (LST) change and the increase of urban land signals. The megacity of Tianjin was chosen for the case study because it is representative of the urbanization process in northern China. A combined analysis of LST and urban land information was conducted based on an urban–rural transect derived from Landsat 8 Thermal Infrared Sensor (TIRS), Terra Moderate Resolution Imaging Spectrometer (MODIS), and QuickBird images. The results indicated that the density of urban land signals has intensified within a 1-km2 grid in the urban center with an impervious land fraction >60 %. However, the construction on urban land is quite different with low-/mid-rise buildings outnumbering high-rise buildings in the urban–rural transect. Based on a statistical moving window analysis, positive correlation (R 2 > 0.9) is found between LST and urban land signals. Surface temperature change (ΔLST) increases by 0.062 °C, which was probably caused by the 1 % increase of urbanized land (ΔIF) in this case region.
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Acknowledgments
This work is supported by CAS Strategic Research Program (XDA05090203), National Natural Science Foundation of China (41405064, 41201044), “One-Three-Five” Strategic Planning by the Institute of Remote Sensing and Digital Earth, CAS (Y4SG0500CX), and China Meteorological Administration Special Public Welfare Research Fund (GYHY201406020). We thank the Institute of Remote Sensing and Digital Earth (RADI) for providing Landsat 8 (http://ids.ceode.ac.cn/query.html) and QuickBird images (http://cs.rsgs.ac.cn/cs_en/cshome.asp).
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Zhang, X., Hu, Y., Jia, G. et al. Land surface temperature shaped by urban fractions in megacity region. Theor Appl Climatol 127, 965–975 (2017). https://doi.org/10.1007/s00704-015-1683-8
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DOI: https://doi.org/10.1007/s00704-015-1683-8