High-precision extraction of nearshore green tides using satellite remote sensing data of the Yellow Sea, China

ABSTRACT

Since 2007, a massive floating green tide has occurred repeatedly in the Yellow Sea. The work involved in monitoring and clearing such a phenomenon requires highly precise spatial information. Satellite remote sensing data can provide such detail but they can be limited by long revisit periods and small-scale observational coverage. Therefore, in operational monitoring of green tides, Moderate Resolution Imaging Spectroradiometer (MODIS) data have an important role because of their short revisit period (twice daily) and large-scale observational coverage (viewing swath width: 2330 km). However, errors exist in MODIS-derived areal detection of green tides because its coarse spatial resolution (250–1000 m) can lead to mixed-pixel problems (i.e. in many cases, the limit of spatial resolution results in single pixels covering multiple ground objects). In this study, a method for spectral unmixing was developed for remote green tide detection. This method is based on mathematical morphology, and it integrates both the spatial and spectral characteristics of the image in the process of endmember extraction. Experiments using simulated and actual MODIS images were undertaken to illustrate the advantages of the proposed method. Compared with traditional linear unmixing methods, the abundance and area of green tides extracted by the proposed method were closer to the ‘real’ condition. The average relative deviation of green tide area decreased from 84.0% to 21.0%. The results illustrate that the proposed method is able to work efficiently and that it can provide improved information on green tide abundance and area.

Acknowledgements

We thank the data providers. HJ-1 CCD satellite data were provided by the China Centre for Resources Satellite Data and Application (http://www.cresda.com/n16/n92006/index.html). MODIS data were provided by the NASA Goddard Space Flight Centre (http://oceancolor.gsfc.nasa.gov). We also thank the anonymous reviewers for constructive comments to the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Science Foundation of China [41506203], [41476159]; the Cooperation Project of FIO and KOIST under contract [GY2014T03]; the Special Fund in the Public Interest under contract [2013418025-2]; the Team Research Progress of Dragon 3 Coastal Zones Project [10470].