Quantifying Spatial-Temporal Pattern of Urban Heat Island in Beijing: An Improved Assessment Using Land Surface Temperature (LST) Time Series Observations From LANDSAT, MODIS, and Chinese New Satellite GaoFen-1

The purpose of this study is to comprehensively quantify the spatial-temporal patterns of surface urban heat island (SUHI) by investigating the relationship between Land surface temperature (LST) and the land-cover types and associated landscape components in the case of Beijing, China. The spatial and temporal adaptive reflectance fusion model (STARFM) developed by Gao et al. was employed to create the high spatial resolution LST time series, using LST data from the MODIS/Terra and LANDSAT 8 over the period from May to November in 2013. This paper also investigated the application of the Chinese new high spatial resolution satellite GaoFen-1 in urban thermal environments studies which were insufficiently studied previously. The impacts of four landscape metrics (LSMs) on urban LST were investigated on the basis of two scenes of GaoFen images acquired in 2013 summer (June 19 and August 10). Results showed that SUHI effect was prevalent in Beijing from May to October. The intensity of SUHI magnitude was found accentuated mainly in the summer months (July and August), indicating that the trend of surface UHI effect is inconsistent with that of canopylayer UHI effect. No obvious linear relationships were observed between subplot LST and impervious surfaces LSMs. However, four impervious surfaces LSMs were correlated well with the temporal dynamics of LST. We also found the configurational patterns of green space could put substantial influences as strong as corresponding compositional patterns and the lower vegetation coverage in downtown could better account for the urban LST.