Examining the impact of urban biophysical composition and neighboring environment on surface urban heat island effect

Due to atmospheric and surface modifications associated with urbanization, surface urban heat island (SUHI) effects have been considered essential in examining urban ecological environments. With remote sensing technologies, numerous land cover type related variables, including spectral indices and land cover fractions, have been applied to estimate land surface temperature (LST), thereby further examining SUHI. This study begins with the reexamination of the commonly used indicators of LST using Landsat Enhanced Thematic Mapper Plus (ETM+) and Landsat Thematic Mapper (TM) images which cover four counties of Wisconsin, United States. Origin of the large variation of LST found in urban areas is then investigated by discriminating soil and impervious surfaces. Except land cover types, neighboring environment is another key factor which may affect LST in urban areas. Thus, a neighboring effect considered method is proposed at the end of the study to better understand the relationship between impervious surfaces fraction (%ISA) and LST by taking the influence of neighboring environment into account. Results indicate that spectral indices have better performance in predicting LST than land cover fractions do within the study area. However, the result remains arguable due to the complexity and uncertainty of spectral mixture analysis. Impervious surfaces are found responsible for the large variation of LST in urban areas, which indicates that impervious surfaces should not be simply considered as a single land cover type has stable negative correlation with LST. Moreover, a better relationship is found between %ISA and LST when neighboring effect is considered, when compared to the traditional method which ignores the neighboring effect. (C) 2015 COSPAR. Published by Elsevier Ltd. All rights reserved.