Long-term and fine-scale satellite monitoring of the urban heat island effect by the fusion of multi-temporal and multi-sensor remote sensed data: A 26-year case study of the city of Wuhan in China

The trade-off between the temporal and spatial resolutions, and/or the influence of cloud cover, makes it difficult to obtain continuous fine-scale satellite data for surface urban heat island (SUHI) analysis. To relieve these difficulties, this study employs multi-temporal and multi-sensor fusion methods for a long-term and fine-scale summer SUHI analysis of the city of Wuhan in China. By integrating several series of satellite images, we generated 26-year (1988 to 2013) high spatial resolution (Landsat-like) summer land surface temperature (LST) data. This series of data was then used for a qualitative and quantitative analysis of the SUHI patterns, evolution characteristics, and mechanisms. This study not only provides a generalized research framework for the long-term and fine-scale analysis of the SUHI effect, but also reveals several findings about the heat distribution and SUHI characteristics in Wuhan. Firstly, our results show that the high temperature and sub-high temperature areas were continuously concentrated from rural to urban areas, but the high temperature area within the old city zones showed an obvious decreasing tendency. Secondly, a more important finding is that the SUHI intensity first increased and then decreased over the 26years. The maximum temperature difference between the city zone and the rural area was in 2003 (7.19K for the old city zone, and 4.65K for the area within the third ring road). Finally, we confirm that the relationships between heat distribution and land cover (especially vegetation and impervious surfaces) were interannually stable, and that the influences of industry, businesses, and residential districts on the SUHI effect were in descending order in Wuhan. •We solve the spatial–temporal discontinuity of remotely sensed LST data.•A long-term (26-years) and fine-scale summer LST data series has been generated.•This 26-year data is used for the analysis of the SUHI characteristic. The spatial–temporal relationships are investigated from a 3D perspective.