Design on Marine Pollution Monitoring System Using Multiple Remote Sensing Data

Abstract

An automatic production and sharing of marine pollution information (MPI) is necessary to detect and combat an oil-spill accident from aerial surveillance. KIOST has established a Kubernetes-based container infrastructure environment consisting of data acquisition, MPI detection and prediction. The automatic production module of MPI is applicable to satellite (SAR and optical) and aircraft-based sensors and a camerabased module supports floating hazardous substances detection. In the DB, domestic and foreign numerical models (sea water flow, wind, and wave), real-time observation data (Korea Meteorological Administration, Korea Hydrographic and Oceanographic Agency, National Institute of Fisheries Science), ship location information, and oil-spill prediction result can be automatically collected and linked. The final MPIs confirmed through the comprehensive evaluation process for the extracted MOI candidate group is connected to the Korea Coast Guard's pollution prevention support system (POSEIDON) and users can use it on-site.