Modelling inter-pixel spatial variation of surface urban heat island intensity

Context: Surface urban heat island intensity (SUHII) is a classical measure depicting urban heat island phenomenon via remotely sensed thermal infrared data. The most common approach is to compare urban and rural land surface temperatures (LST), which is not only sensitive to the selection of pixels/measurements representative of urban and rural areas, but also overlook the pixel-level intra-city SUHII variation and thermodynamics associated with heterogeneous urban landscape. Objectives: This study develops a new SUHIIen ^ , via pixel-based sharpening enhancement method to integrate a pixel’s LST magnitude that reflects a city’s overall thermal context with its local SUHII that takes the landscape variations and cognate thermal interactions with neighboring pixels into account. Methods: Using Guangzhou (south China) as a case study, SUHIIen ^ is constructed applying Moderate Resolution Imaging Spectroradiometer LST product for the summer season of 2015 through cloud-based Google Earth Engine platform. The effectiveness of SUHIIen ^ is tested by comparing SUHIIen ^ results (based on 3 × 3, 5 × 5 and 7 × 7 kernels) with the original LST, a two-dimensional Gaussian surface, and Gaussian density curve with stepwise increments of the thermal influence from neighboring pixels on the center pixels. Results: We found that (1) local SUHII variations are sensitive to the spatial composition of a center pixel’s land use type and that of its eight neighbors; (2) SUHIIen ^ makes more pronounced those spots that are not only heat per se (with higher original LST), but also receive additional heat load emitted from directly adjacent pixels due to land use homogeneity; (3) the effectiveness of SUHIIen ^ could be successfully verified. Conclusions: This new SUHI indicator accounts for inter-pixel spatial variation of UHI and highlights how neighboring pixels’ homogeneous/heterogeneous land use and associated thermal properties could affect center pixels’ thermal characteristics via either reinforcement or mitigation of heat load. It contributes to rigorous assessment of potential heat risks at micro-pixel scale and tailored design of mitigation strategies.