초고속 GOCI-II 자료처리를 위한 해색 알고리즘 개발 환경

Abstract

Geostationary Ocean Color Imager&#8211 II (GOCI-II), the follow-up satellite sensor platform of GOCI, will be launched in Mar. 2019. For estimating ocean color information from this new sensor data, the dedicated ocean color algorithms will be newly developed. However, the existing ocean color algorithm development methodology without consideration for the high-speed data processing will not be employed because the amount of GOCI-II data will be significantly large and theirdata will have to be processed and distributed in real time. In this study, therefore, we designed the ocean color algorithm development environment (OCADE) to support high-performance computing and storage using the parallelism. Also, OCADE enables the source code projects for GOCI-II ocean color products to be automatically built and deployed. We expect that GOCI-II ocean color algorithm developers will easily create and manage their parallelized source code projects at any time and any place through the OCADE cloud service. Additionally, they will be able to validate the output and evaluate the processing performance under OCADE in real-time. We believe that OCADE will contribute to the field of massive satellite data processing.ll be newly developed. However, the existing ocean color algorithm development methodology without consideration for the high-speed data processing will not be employed because the amount of GOCI-II data will be significantly large and theirdata will have to be processed and distributed in real time. In this study, therefore, we designed the ocean color algorithm development environment (OCADE) to support high-performance computing and storage using the parallelism. Also, OCADE enables the source code projects for GOCI-II ocean color products to be automatically built and deployed. We expect that GOCI-II ocean color algorithm developers will easily create and manage their parallelized source code projects at any time and any place through the OCADE cloud service. Additionally, they will be able to validate the output and evaluate the processing performance under OCADE in real-time. We believe that OCADE will contribute to the field of massive satellite data processing.