Land surface temperature shaped by urban fractions in megacity region

• Published in: Theoretical and applied climatology 2017-02, Vol.127 (3-4), p.965-975
• Main Authors: Zhang, Xiaoxuan, Hu, Yonghong, Jia, Gensuo, Hou, Meiting, Fan, Yanguo, Sun, Zhongchang, Zhu, Yuxiang
• Format: Article
• Language: English
• Subjects: Agricultural land; Analysis; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Atmospheric Sciences; Buildings; Case studies; Climatology; Earth and Environmental Science; Earth Sciences; High rise buildings; Land surface temperature; Land use planning; Landsat; Landsat satellites; Megacities; Natural vegetation; Original Paper; Remote sensing; Studies; Temperature; Urban areas; Urban climatology; Urban heat islands; Urban sprawl; Urbanization; Vegetation; Waste Water Technology; Water Management; Water Pollution Control
• ISSN: 0177-798X; 1434-4483
• DOI: 10.1007/s00704-015-1683-8

Large areas of cropland and natural vegetation have been replaced by impervious surfaces during the recent rapid urbanization in China, which has resulted in intensified urban heat island effects and modified local or regional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-km 2 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.