Development of GOCI-II Toolbox for SNAP

Title
Development of GOCI-II Toolbox for SNAP
Author(s)
Heo, Jae Moo; Han, Hee Jeong; Yang, Hyun; Kwak, Sunghee; Lee, Taekyung
KIOST Author(s)
Heo, Jae Moo(허재무)Yang, Hyun(양현)
Publication Year
2020-05-07
Abstract
GOCI-II (Geostationary Ocean Color Imager II), the successor of GOCI, will be launched in February 2020. And a ground system for GOCI-II has been developed since 2015. Also, new tools should be developed for the scientific analysis and exploitation of GOCI-II data. GDPS (GOCI Data Processing System), a data analysis tool for existing GOCI, has some problems. It only works on Windows and a great deal of effort is required to develop and improve functions for analysis and processing for GOCI data. To solve these problems, we are developing a GOCI-II Toolbox (GTBX) based on SNAP (SeNtinel Application Platform) which is a widely used software platform and an evolution of ESA BEAM/NEST architecture inheriting all current NEST functionality. GOCI Level-1B and Level-2 file format are binary and HDF-EOS5, respectively. And GOCI-II Level-1B and Level-2 file format is NetCDF. The GTBX provides the visualization and analysis of GOCI/GOCI-II data, as well as GOCI-II Level-2 processor for ocean color products including atmospheric correction and application products of ocean, atmosphere and land. Furthermore, the GTBX extends SNAP product library to display the Thematic Realtime Environmental Distributed Data Services (THREDDS) catalogs of GOCI/GOCI-II data and provides remote access to partial data using the Open-Source Project for a Network Data Access Protocol (OPeNDAP). In terms of the GOCI-II Level-2 processor, algorithms are implemented in Python and C/C ++ and each algorithm application is distributed as a Docker image. So, it can be run in any environment that support the Docker (e.g., Windows, Linux and Mac OS). In addition, we introduce parallel processing methods suitable for each application. In computing environments that support the Open Multi-Processing, Open Computing Language (OpenCL) and Compute Unified Device Architecture (CUDA) libraries, users of GOCI-II data take advantage of the powerful computing resources of multi-core CPU and GPU, and it is possible to process large-scale data at very high speed. The GTBX work seamlessly with the generic functions of SNAP. By utilizing various visualization and analysis functions of SNAP and adding functions of easy access and powerful processing for GOCI/GOCI-II data, it is expected that the rich utilization of GOCI-II data will be possible.
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/37701
Bibliographic Citation
The EGU General Assembly 2020, 2020
Publisher
EGU
Type
Conference
Language
English
Publisher
EGU
Related Researcher
Files in This Item:
There are no files associated with this item.

qrcode

Items in ScienceWatch@KIOST are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse