A sub-pixel analysis of urbanization effect on land surface temperature and its interplay with impervious surface and vegetation coverage in Indianapolis, United States

This study developed an analytical procedure based upon a spectral unmixing model for characterizing and quantifying urban andscape changes in Indianapolis, Indiana, the United States, and for examining the environmental impact of such changes on land urface temperatures (LST). Three dates of Landsat TM/ETM+ images, acquired in 1991, 1995, and 2000, respectively, were tilized to document the historical morphological changes in impervious surface and vegetation coverage and to analyze the elationship between these changes and those occurred in LST. Three fraction endmembers, i.e., impervious surface, green egetation, and shade, were derived with an unconstrained least-squares solution. A hybrid classification procedure, which ombined maximum-likelihood and decision-tree algorithms, was developed to classify the fraction images into land use and land over classes. Correlation analyses were conducted to investigate the changing relationships of LST with impervious surface and egetation coverage. Results indicate that multi-temporal fraction images were effective for quantifying the dynamics of urban orphology and for deriving a reliable measurement of environmental variables such as vegetation abundance and impervious urface coverage. Urbanization created an evolved inverse relationship between impervious and vegetation coverage, and brought bout new LST patterns because of LST’s correlations with both impervious and vegetation coverage. Further researches should be irected to refine spectral mixture modeling by stratification, and by the use of multiple endmembers and hyperspectral imagery. 2007 Elsevier B.V. All rights reserved. www.elsevier.com/locate/jag International Journal of Applied Earth Observation and Geoinformation 10 (2008) 68–83