Detecting harmful algal blooms using Geostationary Ocean Color Imager (GOCI) data in Bohai Sea, China

Mingzhu Xu; Zhiqiang Gao; Chaoshun Liu

doi:10.1117/12.2184249

4 September 2015 Detecting harmful algal blooms using Geostationary Ocean Color Imager (GOCI) data in Bohai Sea, China

Mingzhu Xu, Zhiqiang Gao, Chaoshun Liu

Proceedings Volume 9610, Remote Sensing and Modeling of Ecosystems for Sustainability XII; 96100U (2015) https://doi.org/10.1117/12.2184249
Event: SPIE Optical Engineering + Applications, 2015, San Diego, California, United States

Abstract

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.

Citation Download Citation

Mingzhu Xu, Zhiqiang Gao, and Chaoshun Liu "Detecting harmful algal blooms using Geostationary Ocean Color Imager (GOCI) data in Bohai Sea, China", Proc. SPIE 9610, Remote Sensing and Modeling of Ecosystems for Sustainability XII, 96100U (4 September 2015); https://doi.org/10.1117/12.2184249

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KEYWORDS

Magnetic resonance imaging

Remote sensing

Imaging systems

MODIS

Ocean optics

Clouds

Reflectivity

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