[HTML][HTML] Chlorophyll algorithms for ocean color sensors-OC4, OC5 & OC6

JE O'Reilly, PJ Werdell - Remote sensing of environment, 2019 - Elsevier
A high degree of consistency and comparability among chlorophyll algorithms is necessary
to meet the goals of merging data from concurrent overlapping ocean color missions for …

Remote sensing of chlorophyll a concentration in turbid coastal waters based on a global optical water classification system

TW Cui, J Zhang, K Wang, JW Wei, B Mu, Y Ma… - ISPRS Journal of …, 2020 - Elsevier
Accurate chlorophyll a concentration (Chla) retrieval in coastal waters from ocean color
remote sensing faces challenges due to the significant optical complexity compared to clear …

[HTML][HTML] Impact of El Niño variability on oceanic phytoplankton

MF Racault, S Sathyendranath, RJW Brewin… - Frontiers in Marine …, 2017 - frontiersin.org
Oceanic phytoplankton respond rapidly to a complex spectrum of climate-driven
perturbations, confounding attempts to isolate the principal causes of observed changes. A …

A global study of NDVI difference among moderate-resolution satellite sensors

X Fan, Y Liu - ISPRS Journal of Photogrammetry and Remote …, 2016 - Elsevier
Moderate-resolution sensors, including AVHRR (Advanced Very High Resolution
Radiometer), MODIS (MODerate-resolution Imaging Spectroradiometer) and VIIRS (Visible …

Warming of the Indian Ocean and its impact on temporal and spatial dynamics of primary production

P Dalpadado, KR Arrigo, GL van Dijken… - Progress in …, 2021 - Elsevier
Abstract The Indian Ocean, the third largest among the world's oceans, is experiencing
unprecedented changes in sea surface temperature (SST). We present temporal and spatial …

[HTML][HTML] Applications of DINEOF to satellite-derived chlorophyll-a from a productive coastal region

A Hilborn, M Costa - Remote Sensing, 2018 - mdpi.com
A major limitation for remote sensing analyses of oceanographic variables is loss of spatial
data. The Data INterpolating Empirical Orthogonal Functions (DINEOF) method has …

[HTML][HTML] Coupling ecological concepts with an ocean-colour model: Phytoplankton size structure

X Sun, RJW Brewin, S Sathyendranath… - Remote Sensing of …, 2023 - Elsevier
Phytoplankton play a central role in the planetary cycling of important elements and
compounds. Understanding how phytoplankton are responding to climate change is …

Long‐Term Trends in Phytoplankton Chlorophyll a and Size Structure in the Benguela Upwelling System

T Lamont, RG Barlow… - Journal of Geophysical …, 2019 - Wiley Online Library
Abstract The Benguela Upwelling System (BUS) is among the most productive ecosystems
globally, supporting numerous fisheries and ecosystem services in Southern Africa. Sea …

Modelling size-fractionated primary production in the Atlantic Ocean from remote sensing

RJW Brewin, GH Tilstone, T Jackson, T Cain… - Progress in …, 2017 - Elsevier
Marine primary production influences the transfer of carbon dioxide between the ocean and
atmosphere, and the availability of energy for the pelagic food web. Both the rate and the …

Causes of the regional variability in observed sea level, sea surface temperature and ocean colour over the period 1993–2011

B Meyssignac, CG Piecuch, CJ Merchant… - Integrative Study of the …, 2017 - Springer
We analyse the regional variability in observed sea surface height (SSH), sea surface
temperature (SST) and ocean colour (OC) from the ESA Climate Change Initiative datasets …