Author: Elizabeth C Atwood,  EO Scientist (PML - Plymouth Marine Laboratory)

Designation: 

Description:
Water quality (WQ) algorithms often separate marine and freshwater systems, introducing artificial boundaries to the ocean-inland water continuum. Building upon Ocean Colour- (OC) and Lakes-Climate Change Initiative (CCI) work, we propose an improved tool to assess source-to-sea linkages. Both OC-CCI and Lakes-CCI use fuzzy clustering methods to: 1) generate optical water type (OWT) classes (clusters) representing spectrally distinct waters occurring over the space/time period analysed, 2) assign pixels a membership value for each OWT class, and 3) seamlessly blend optimal in-water algorithms across the region. This allows flexible representation of water province transition zones than classic hard clustering techniques. Improvements deal with (a) expanded spectral band-sets from sensors such as Sentinel-3 OLCI, and (b) increased spatial resolution, down to 10m Sentinel-2 MSI data. Fuzzy clustering OWT time series allow unique insight into optical regime changes within a lagoon or estuary, independent of WQ algorithm performance. Results for one project site will be discussed, as well as benefits and challenges in OWT cluster optimization when moving to cross-regional analysis. Work is part of EC Horizon 2020 CERTO (Copernicus Evolution: Research for harmonised Transitional water Observation), focusing on knowledge gaps in transitional water remote sensing and harmonizing EO-derived WQ products from EU Copernicus services. Study sites are: Plymouth Sound, UK; Tagus Estuary, PT; Elbe Estuary, DE; Venice Lagoon, IT; Curonian Lagoon, LI; Danube Razelm-Sinoe Lagoon System, RO.

Category: Scientific Program Abstract > Special Sessions > SS64 Addressing challenges in monitoring water quality using Earth Observation (EO) in transitional waters