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Data Fusion for Increasing Monitoring Capabilities of Sentinel Optical Data in Marine Environment

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Marine monitoring constitutes one of the main thematic areas of the Sentinel mission. The Sentinel 3 OLCI (S3) sensor provides satellite data for services relevant to the ocean and land.… Click to show full abstract

Marine monitoring constitutes one of the main thematic areas of the Sentinel mission. The Sentinel 3 OLCI (S3) sensor provides satellite data for services relevant to the ocean and land. While the spatial resolution of S3 images (300 m) is suitable for most marine applications, there are some applications such as floating debris detection, suspended mater estimation, etc., that require higher resolution. To fulfill this requirement this study applies an unmixing-based data fusion technique on S3 and BRDF-corrected Sentinel 2 (S2) images and evaluates the fused data by calculating the correlation coefficient and the spectral angle distance (SAD) indexes. Then, it explores the increased monitoring capabilities of the fused image by applying improved chlorophyll-a (Chl-a) and total suspended matter (TSM) algorithms, developed for satellite data. The fused image presents spectral similarity to S3 data and spatial similarity to S2 image. Consequently, the products provided by the fused image have much better resolution than those of S3 image, which enables detailed estimations of Chl-a and TSM concentrations. However, the dynamic nature of the marine environment that results in the formation of time-varying patterns at sea surface, in relation to the time lag between S2 and S3 image acquisitions may locally affect the accuracy of the products in the neighborhood of these patterns. This study exploits the effective elimination of directional reflectance effects in S2 ocean images, interprets the fused image and the generated ocean products, and points out the constraints regarding the synergy of Sentinel optical data for ocean areas.

Keywords: data fusion; fused image; monitoring capabilities; image; marine

Journal Title: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Year Published: 2020

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