A new method to quantify surface urban heat island intensity

Highlights: • Quantifying surface urban heat island intensity using the relationship between LST and Impervious Surface Areas. • The impervious surface areas was regionalized within the footprint of remote sensing observation using a Kernel Density Estimation method. • Linear functions of LST were well fitted using the regionalized impervious surface areas. • Slope of the linear function of LST was defined as the surface urban heat island intensity. Reliable quantification of urban heat island (UHI) can contribute to the effective evaluation of potential heat risk. Traditional methods for the quantification of UHI intensity (UHII) using pairs-measurements are sensitive to the choice of stations or grids. In order to get rid of the limitation of urban/rural divisions, this paper proposes a new approach to quantify surface UHII (SUHII) using the relationship between MODIS land surface temperature (LST) and impervious surface areas (ISA). Given the footprint of LST measurement, the ISA was regionalized to include the information of neighborhood pixels using a Kernel Density Estimation (KDE) method. Considering the footprint improves the LST-ISA relationship. The LST shows highly positive correlation with the KDE regionalized ISA (ISA_KDE). The linear functions of LST are well fitted by the ISA_KDE in both annual and daily scales for the city of Berlin. The slope of the linear function represents the increase in LST from the natural surface in rural regions to the impervious surface in urban regions, and is defined as SUHII in this study. The calculated SUHII show high values in summer and during the day than in winter and at night. The new method is also verified using finer resolution Landset data, and the results further prove its reliability.