An image analysis procedure based on a two dimensional Gaussian fitting is\npresented and applied to satellite maps describing the surface urban heat island (SUHI).\nThe application of this fitting technique allows us to parameterize the SUHI pattern in\norder to better understand its intensity trend and also to perform quantitative comparisons\namong different images in time and space. The proposed procedure is computationally\nrapid and stable, executing an initial guess parameter estimation by a multiple regression\nbefore the iterative nonlinear fitting. The Gaussian fit was applied to both low and high\nresolution images (1 km and 30 m pixel size) and the results of the SUHI parameterization\nshown. As expected, a reduction of the correlation coefficient between the map values and\nthe Gaussian surface was observed for the image with the higher spatial resolution due to\nthe greater variability of the SUHI values. Since the fitting procedure provides a smoothed\nGaussian surface, it has better performance when applied to low resolution images, even if\nthe reliability of the SUHI pattern representation can be preserved also for high resolution\nimages.
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