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Performance Metrics for the Assessment of Satellite Data Products: An Ocean Color Case StudyPerformance assessment of ocean color satellite data has generally relied on statistical metrics chosen for their common usage and the rationale for selecting certain metrics is infrequently explained. Commonly reported statistics based on mean squared errors, such as the coefficient of determination (r2), root mean square error, and regression slopes, are most appropriate for Gaussian distributions without outliers and, therefore, are often not ideal for ocean color algorithm performance assessment, which is often limited by sample availability. In contrast, metrics based on simple deviations, such as bias and mean absolute error, as well as pair-wise comparisons, often provide more robust and straightforward quantities for evaluating ocean color algorithms with non-Gaussian distributions and outliers. This study uses a SeaWiFS chlorophyll-a validation data set to demonstrate a framework for satellite data product assessment and recommends a multi-metric and user-dependent approach that can be applied within science, modeling, and resource management communities.
Document ID
Document Type
Accepted Manuscript (Version with final changes)
External Source(s)
Seegers, Bridget N. (Universities Space Research Association (USRA) Columbia, MD, United States)
Richard P. Stumpf, (National Ocean Service Silver Spring, MD, United States)
Schaeffer, Blake A. (Environmental Protection Agency Durham, NC, United States)
Loftin, Keith A. (Geological Survey Lawrence, KS, United States)
Werdell, P. Jeremy (NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
June 4, 2018
Publication Date
March 14, 2018
Publication Information
Publication: Optics Express
Volume: 26
Issue: 6
Subject Category
Earth Resources and Remote Sensing
Report/Patent Number
Funding Number(s)
Distribution Limits
Use by or on behalf of the US Gov. Permitted.

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