Remote Sens. 2010, 2(3), 794-818; https://doi.org/10.3390/rs2030794
Introduction and Assessment of Measures for Quantitative Model-Data Comparison Using Satellite Images
1
Department of Mathematics and Statistics, Dalhousie University, Halifax B3H 3J5, NS, Canada
2
Department of Oceanography, Dalhousie University, Halifax B3H 4J1, NS, Canada
*
Author to whom correspondence should be addressed.
Received: 13 January 2010 / Revised: 5 February 2010 / Accepted: 5 March 2010 / Published: 19 March 2010
Abstract
Satellite observations of the oceans have great potential to improve the quality and predictive power of numerical ocean models and are frequently used in model skill assessment as well as data assimilation. In this study we introduce and compare various measures for the quantitative comparison of satellite images and model output that have not been used in this context before. We devised a series of test to compare their performance, including their sensitivity to noise and missing values, which are ubiquitous in satellite images. Our results show that two of our adapted measures, the Adapted Gray Block distance and the entropic distance D2, perform better than the commonly used root mean square error and image correlation. View Full-TextKeywords:
image comparison; model data comparison; similarity measures; data assimilation; skill assessment; ocean model
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Mattern, J.P.; Fennel, K.; Dowd, M. Introduction and Assessment of Measures for Quantitative Model-Data Comparison Using Satellite Images. Remote Sens. 2010, 2, 794-818.
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