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Impervious surface areas (ISAs) and vegetation are two major urban land cover types. Estimating the spatial distribution of ISA and vegetation is critical for analyzing urban landscape patterns and their impact on the thermal environment. In this paper, linear spectral mixture analysis (LSMA) is used to extract their respective subpixel land cover composition from bitemporal Landsat images and the accuracy of the fractional covers is assessed with a subpixel confusion matrix at the category level and the map level by comparing with the reference data from high-resolution images. The percent ISA was divided into discrete categories representing different urban development density areas. Mean land surface temperature (LST) is calculated for each ISA category to analyze the thermal characteristics of different levels of development in the urban area of Fuzhou, China. ISA and vegetation variations are also quantified between different ISA categories and different dates. The contribution index is also calculated based on each ISA category to analyze the impact of different landscape patterns on the urban thermal environment. The results show that ISA category is an important determinant of the urban thermal environment. Furthermore, seasonal variations significantly impact the strength of this relationship. In the study area, the contribution indices were highest in the 90%-100% ISA category in summer 2013 and early spring 2001. The analytical methodologies used in this study can help to quantify urban thermal environmental functions under conditions of urban expansion and explore the climate adaptation potential of cities. Index Terms-Contribution index (CI), fractional vegetation cover (FVC), land surface temperature (LST), linear spectral unmixing, percent impervious surface area (ISA), subpixel confusion matrix, urban heat island (UHI). I. INTRODUCTION T HE change from nonurban land cover (pervious surfaces such as grass, forest, water body, crop field, etc.

12The urban heat island effect describes the phenomenon of increased surface temperatures 13 in urban environments compared to their surroundings. China. The objective of this study was to estimate the anthropogenic heat discharge in the 20 form of sensible heat flux in complex urban environments. In order to increase the accuracy 21 of the anthropogenic heat flux analysis, sub-pixel fractional vegetation cover was calculated 22by linear spectral unmixing. The result was then used to estimate latent heat flux in urban 23 areas and to separate anthropogenic heat discharge from heat radiation due to insolation. 24Spatial and temporal distributions of anthropogenic heat flux were analysed as a function of 25 land cover type, percent impervious surface area and fractional vegetation cover. The 26 accuracy of heat fluxes was assessed using the ratios of H, LE and G to R n , which were 27 compared to the results from other studies. It is apparent that the contribution of 28 anthropogenic heat is smaller in suburban areas, and larger in high density urban areas. 29However, seasonal disparities of anthropogenic heat discharge are small, and the variance of 30 anthropogenic heat discharge is influenced by urban expansion, land cover change and 31 increasing energy consumption. The results suggest that anthropogenic heat release probably 32 plays a significant role in the urban heat island effect, and must be considered in urban 33 climate change adaptation strategies. Remote sensing can play a role in mapping the spatial 34 and temporal patterns of urban heat islands and can differentiate the anthropogenic from the 35 solar radiative fluxes. The findings presented here have important implications for urban 36 development planning. 37 38