Frontiers in Remote Sensing (Jun 2022)

Spatial Variability of In Situ Above-Water Reflectance in Coastal Dynamic Waters: Implications for Satellite Match-Up Analysis

  • Hussain J. Nasiha,
  • Ziwei Wang,
  • Fernanda Giannini,
  • Maycira Costa

DOI
https://doi.org/10.3389/frsen.2022.876748
Journal volume & issue
Vol. 3

Abstract

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The validation of ocean color satellite retrievals generally relies on analyzing match-ups between in situ measurements and satellite retrievals. These analyses focus on the quality of the satellite data, however, of the same importance is the quality of the in situ data. Here, we present the spatial variability of in situ above-water reflectance (Rrs(0+)) within the spatial resolution of different ocean color satellites—300, 900, 1500, and 3000 m spatial resolutions, mimicking Sentinel 3 OLCI and MODIS-Aqua satellites, and possible 3 × 3 and 5 × 5 windows. Radiometric data was acquired with autonomous radiometric sensors installed in the British Columbia Ferry Services Inc. vessel “Queen of Alberni” from May to September 2019, crossing the optically dynamic waters of the Strait of Georgia, Canada. The dataset followed optimal geometry of acquisition and processing, including corrections for skylight radiance signals, ship superstructure, the non-isotropic distribution of the water-leaving radiances, and quality control. A total of 33,073 spectra at full resolution, corresponding to 10 days, were considered for the analysis presented here. The results showed that, overall, the subpixel variability increased as the spatial resolution of the sensor or the window size increased, mainly in a linear fashion. Specifically, spatial variability of Rrs(0+) was the largest (∼18% and 68% for 900 and 3000 m pixel resolution, respectively) in Near Field Plume Interface waters, followed by in the Ocean Water Interface (∼28% and 35%, respectively), thus indicating spatial heterogeneity of interface waters. Further, we found that the estuarine waters showed higher subpixel Rrs(0+) variability (∼8% and 16% for 900 and 3000 m, respectively) compared with plume and oceanic waters. We showed that the high spatial variability in Rrs(0+) was primarily associated with the spatial dynamics of the optical water constituents, thus limiting the use of these datasets as Fiducial Reference Measurements and for validation of satellite-derived atmospherically corrected reflectance. We suggest that spatial variability of the in situ Rrs(0+) should also be considered in the selection criteria for good match-up data, especially for data acquired in coastal dynamic systems. As a result, it will advocate for the exclusion of interface or transition water pixel grids in order to avoid compromising the statistical result of satellite validation.

Keywords