Modelling Inter-pixel Spatial Variation of Surface Urban Heat Island Intensity

Abstract

Context Surface urban heat island intensity (SUHII) is a classical measure, which is sensitive to the selection of pixels/measurements representative of urban and rural areas, and overlooks pixel-level SUHII variation and thermodynamics of heterogeneous urban landscape. Accounting inter-pixel landscape heterogeneity in SUHII would capture inter-pixel thermodynamics and reveal complicated micro-thermal situations, contribute to assessment of potential heat risks at micro-pixel scale. Objectives This study develops [[EQUATION]] using pixel-based sharpening enhancement method. It integrates a pixel’s LST magnitude that reflects a city’s thermal context with local SUHII considering landscape variations and cognate thermal interactions of neighboring pixels. Methods [[EQUATION]] is constructed using MODIS LST product for Guangzhou (south China) in the summer season of 2015 through cloud-based GEE platform. Its effectiveness is tested using a bivariate choropleth map and Gaussian density curve with stepwise increments of the thermal influence from neighboring pixels. Results We found that (1) local SUHII variations are sensitive to the spatial configuration of a center pixel’s land use and that of its neighbors; (2) [[EQUATION]] makes more pronounced those spots that are heat per se (with higher original LST), but also receive additional heat load from adjacent pixels due to land-use homogeneity; (3) the effectiveness of [[EQUATION]] could be demonstrated by Gaussian density curve. Conclusions This paper proposed a new SHUII indicator, [[EQUATION]] , which models inter-pixel spatial variation of SHUI and highlights how neighboring pixels’ homogenous/heterogeneous land-use and associated thermal properties could affect center pixels’ thermal characteristics via either reinforcement or mitigation of heat load.

Inversion of land surface temperature by remote sensing technology: a case study of Shapingba District in Chongqing

“…At the same time, the surface temperature information is also the main basis for the evaluation and discrimination of heat island effect, which has broad application prospects in the field of national economy. Since the end of 1970s, scholars at home and abroad have carried out a large number of studies using thermal infrared remote sensing to obtain land surface temperature quickly and accurately [5,6] . Theoretically, thermal infrared remote sensing can accurately provide high spatial resolution surface emissivity and temperature information.…”