GOCI-II Toolbox Is Developed Based On SNAP (Sentinel Application Platform) To Process and Analysis Geostationary Ocean Color Sensor Data

Abstract

Geostationary Ocean Color Imager-II (GOCI-II), which will be launched in early 2020, has high temporal and spatial resolution to monitor oceanographic phenomena occurred by various biogeochemical and/or physical interactions. The data amount of GOCI-II has increased hugely but its timeliness requirement is very short like near real-time. We have been developing new ground segment (G2GS) and user support plug-in called GOCI-II Toolbox (GTBX). G2GS is composed of Algorithm Development Environment (ADE), System Operation Environment (SOE), Data Service Environment (DSE) for the researcher/engineer to develop new algorithm for GOCI/GOCI-II, for system operator in Korea Ocean Satellite Center (KOSC), for data user to ask the GOCI/GOCI-II data, respectively. To get high performance in GOCI/GOCI-II Level 2 data processing, we have to adopted parallel and distributed processing techniques using heterogeneous computing system (Multi-core CPU, GPU) on linux machines. GPU version of data processing, for example, showed the performance improvements 40 times better than a sequential version and nearly twice as high as a CPU version in parallel processing of GOCI atmospheric correction algorithm. The GTBX is developed for easy searching and easy accessing the GOCI/GOCI-II data based on SNAP (Sentinel Application Platform). It has three functions Access the GOCI/GOCI-II data remotely, Translate geostationary observed satellite da