It is essential for the planning and management of fishery resources that accurate and high-resolution marine environmental data in the sea area of low-density sea surface measurement devices. Hence， the sea environmental data measured by satellite remote sensing and marine buoys are merged to improve the resolution of sea environmental data at a large scale by the successive correction method （SCM）. The South China Sea surface temperature （SST） data collected from January 2009 to December 2010 are taken as a sample. The SCM algorithm is more versatile with fast calculation speed. The iterative smoothness of the correction can be improved， compared with the traditional optimal interpolation （OI） method.