Near-real time remote-sensing processing systems

Chlorophyll Animation

Figure 1: Chlorophyll distribution for the summer of 2005 as captured by MODIS-Aqua and processed in near-real time (Shutler et al 2005).

We have designed and implemented many automated near-real time processing systems for orbiting sensors including MODIS-Aqua, MODIS-Terra, AVHRR, SeaWiFS and MERIS. These data support research cruises within the laboratory and those of our national and international partners, as well as providing suitable data for water quality monitoring, algorithm development and time-series analyses.

These systems also provide platforms for the development of further products and algorithms. For example we have recently developed a phytoplankton classifier for water quality monitoring (Shutler et al 2005) and techniques to allow the near-real time generation of primary productivity maps (Smyth et al 2005).

The main research staff involved with the development of these systems are Peter Miller, Tim Smyth, Jamie Shutler and Mike Grant. Organisations that have benefited from the generated data include The National Southampton Oceanography Centre, the Marine Biological Association, Proudman Oceanographic Laboratory and the Royal Navy. These data have been exploited in many different projects and research contracts with financial support from NERC, DEFRA, BNSC and the EU.

Try our MultiView portal allowing access to global near-real time ocean colour data from multiple orbiting sensors.


Recent publications

Miller, P.I., J. D. Shutler, G. F. Moore, and S. B. Groom, (2006) SeaWiFS discrimination of harmful algal bloom evolution, International Journal of Remote Sensing, 27 (11), 2287-2301.

Smyth, T. J., G. H. Tilstone and S. B. Groom (2005) Integration of radiative transfer into satellite models of ocean primary production, Journal of Geophysical Research, 110, C10014, doi. 10.1029/2004JC002784

Shutler, J.D., T. J. Smyth, P. E. Land and S. B. Groom (2005) A near-real time MODIS data processing system, International Journal of Remote Sensing , 25(5), 1049-1055.

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