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Algorithms 2015, 8(2), 82-91; doi:10.3390/a8020082

A Stable Gaussian Fitting Procedure for the Parameterization of Remote Sensed Thermal Images

1
Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, via Eudossiana 18, 00184 Roma, Italy
2
Department of Engineering, University of Perugia, via G. Duranti 93, 06125 Perugia, Italy
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Stefano Mariani
Received: 7 January 2015 / Revised: 12 March 2015 / Accepted: 25 March 2015 / Published: 27 March 2015
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Abstract

An image analysis procedure based on a two dimensional Gaussian fitting is presented and applied to satellite maps describing the surface urban heat island (SUHI). The application of this fitting technique allows us to parameterize the SUHI pattern in order to better understand its intensity trend and also to perform quantitative comparisons among different images in time and space. The proposed procedure is computationally rapid and stable, executing an initial guess parameter estimation by a multiple regression before the iterative nonlinear fitting. The Gaussian fit was applied to both low and high resolution images (1 km and 30 m pixel size) and the results of the SUHI parameterization shown. As expected, a reduction of the correlation coefficient between the map values and the Gaussian surface was observed for the image with the higher spatial resolution due to the greater variability of the SUHI values. Since the fitting procedure provides a smoothed Gaussian surface, it has better performance when applied to low resolution images, even if the reliability of the SUHI pattern representation can be preserved also for high resolution images. View Full-Text
Keywords: Gaussian fit; regression; least-square; satellite image parameterization; urban heat island Gaussian fit; regression; least-square; satellite image parameterization; urban heat island
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Anniballe, R.; Bonafoni, S. A Stable Gaussian Fitting Procedure for the Parameterization of Remote Sensed Thermal Images. Algorithms 2015, 8, 82-91.

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