Bohai Sea is a semi-enclosed inland sea with serious environmental problems. Harmful algal blooms (HABs) in Bohai Sea happen almost every year covering a large area for a long duration. Real time detection of the HABs can significantly reduce economic loss and assure human safety. Remote sensing technology can monitor the sea surface over a large area and detect HABs. Geo-stationary Ocean Color Imager (GOCI) is the world's first geostationary ocean color imager with high spatial and temporal resolution for monitoring the Bohai Sea. Rapid scanning of the GOCI allows enough cloud-free observations to accumulate for detection of HABs. Many approaches exist for detecting the HABs with GOCI data, but the approaches are rarely validated.. In this paper, an Aureococcus anophagefferens bloom that happened in Qinhuangdao is used to evaluate several HAB detecting approaches: abnormal chlorophyll concentration, red tide index (RI) and MODIS red tide index (MRI). Validations with field observations showed that the HAB was best detected with MRI, second with chlorophyll concentration abnormity and worst with RI. These results show that the MRI best detects the Aureococcus anophagefferens algae.
To improve the access efficiency of geoscience data, efficient data model and storage solutions should be used. Geoscience data is usually classified by format or coordinate system in existing storage solutions. When data is large, it is not conducive to search the geographic features. In this study, a geographical information integration system of Shandong province, China was developed based on the technology of ArcGIS Engine, .NET, and SQL Server. It uses Geodatabase spatial data model and ArcSDE to organize and store spatial and attribute data and establishes geoscience database of Shangdong. Seven function modules were designed: map browse, database and subject management, layer control, map query, spatial analysis and map symbolization. The system’s characteristics of can be browsed and managed by geoscience subjects make the system convenient for geographic researchers and decision-making departments to use the data.