Back to Search Start Over

Performance Metrics for the Assessment of Satellite Data Products: An Ocean Color Case Study

Authors :
Bridget N Seegers
Richard P Stumpf
Blake A Schaeffer
Keith A Loftin
P Jeremy Werdell
Source :
Optics Express. 26(6)
Publication Year :
2018
Publisher :
United States: NASA Center for Aerospace Information (CASI), 2018.

Abstract

Performance 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 multimetric and user-dependent approach that can be applied within science, modeling, and resource management communities.

Details

Language :
English
ISSN :
10944087
Volume :
26
Issue :
6
Database :
NASA Technical Reports
Journal :
Optics Express
Notes :
389018.02.10.03.68, , 80NSSC22M0001, , 80NSSC21D0002
Publication Type :
Report
Accession number :
edsnas.20220004406
Document Type :
Report
Full Text :
https://doi.org/10.1364/OE.26.007404