Automatic detection of ship tracks in ATSR-2 satellite imagery E. Campmany1,*, R. G. Grainger1, S. M. Dean1,**, and A. M. Sayer1 1Atmospheric, Oceanic and Planetary Physics, University of Oxford, Oxford OX1 3PU, UK *now at: NASA Goddard Institute for Space Studies, New York, USA **now at: National Institute of Water and Atmospheric Research Ltd, Wellington, New Zealand
Abstract. Ships modify cloud microphysics by adding cloud condensation nuclei (CCN) to
a developing or existing cloud. These create lines of larger reflectance in
cloud fields that are observed in satellite imagery. An algorithm has been
developed to automate the detection of ship tracks in Along Track Scanning
Radiometer 2 (ATSR-2) imagery. The scheme has been integrated into the Global
Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) processing chain.
The algorithm firstly identifies intensity ridgelets in clouds which have the
potential to be part of a ship track. This identification is done by
comparing each pixel with its surrounding ones. If the intensity of three
adjacent pixels is greater than the intensity of their neighbours, then it is
classified as a ridgelet. These ridgelets are then connected together,
according to a set of connectivity rules, to form tracks which are classed as
ship tracks if they are long enough. The algorithm has been applied to two
years of ATSR-2 data. Ship tracks are most frequently seen off the west coast
of California, and the Atlantic coast of both West Africa and South-Western
Europe. The global distribution of ship tracks shows strong seasonality,
little inter-annual variability and a similar spatial pattern to the
distribution of ship emissions.
Citation: Campmany, E., Grainger, R. G., Dean, S. M., and Sayer, A. M.: Automatic detection of ship tracks in ATSR-2 satellite imagery, Atmos. Chem. Phys., 9, 1899-1905, doi:10.5194/acp-9-1899-2009, 2009.