Identification of Floating Green Tide in High-Turbidity Water from Sentinel-2 MSI Images Employing NDVI and CIE Hue Angle Thresholds

Remote sensing technology is widely used to obtain information on floating green tides, and thresholding methods based on indices such as the normalized difference vegetation index (NDVI) and the floating algae index (FAI) play an important role in such studies. However, as the methods are influenced by many factors, the threshold values vary greatly; in particular, the error of data extraction clearly increases in situations of high-turbidity water (HTW) (NDVI > 0). In this study, high spatial resolution, multispectral images from the Sentinel-2 MSI mission were used as the data source. It was found that the International Commission on Illumination (CIE) hue angle calculated using remotely sensed equivalent multispectral reflectance data and the RGB method is extremely effective in distinguishing floating green tides from areas of HTW. Statistical analysis of Sentinel-2 MSI images showed that the threshold value of the hue angle that can effectively eliminate the effect of HTW is 218.94°. A test demonstration of the method for identifying the floating green tide in HTW in a Sentinel-2 MSI image was carried out using the identified threshold values of NDVI > 0 and CIE hue angle < 218.94°. The demonstration showed that the method effectively eliminates misidentification caused by HTW pixels (NDVI > 0), resulting in better consistency of the identification of the floating green tide and its distribution in the true color image. The method enables rapid and accurate extraction of information on floating green tide in HTW, and offers a new solution for the monitoring and tracking of green tides in coastal areas.

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Publication Details

Journal
Journal of Marine Science and Engineering
Published
2024-09-13
DOI
https://doi.org/10.3390/jmse12091640
Citations
5
Primary Topic
Marine and coastal ecosystems
Type
article
Field-Weighted Citation Impact
2.40
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article

Identification of Floating Green Tide in High-Turbidity Water from Sentinel-2 MSI Images Employing NDVI and CIE Hue Angle Thresholds

Xiang Wang, Lin Wang, Jie Han, Yanlong Chen et al.
5 citations
Journal of Marine Science and Engineering
Marine and coastal ecosystems
2.40
article

Identification of Floating Green Tide in High-Turbidity Water from Sentinel-2 MSI Images Employing NDVI and CIE Hue Angle Thresholds

Xiang Wang, Lin Wang, Jie Han, Yanlong Chen, Qinghui Meng, Bingqiang Wang, Xinxin Wang
article en
5 citations

Abstract

Remote sensing technology is widely used to obtain information on floating green tides, and thresholding methods based on indices such as the normalized difference vegetation index (NDVI) and the floating algae index (FAI) play an important role in such studies. However, as the methods are influenced by many factors, the threshold values vary greatly; in particular, the error of data extraction clearly increases in situations of high-turbidity water (HTW) (NDVI > 0). In this study, high spatial resolution, multispectral images from the Sentinel-2 MSI mission were used as the data source. It was found that the International Commission on Illumination (CIE) hue angle calculated using remotely sensed equivalent multispectral reflectance data and the RGB method is extremely effective in distinguishing floating green tides from areas of HTW. Statistical analysis of Sentinel-2 MSI images showed that the threshold value of the hue angle that can effectively eliminate the effect of HTW is 218.94°. A test demonstration of the method for identifying the floating green tide in HTW in a Sentinel-2 MSI image was carried out using the identified threshold values of NDVI > 0 and CIE hue angle < 218.94°. The demonstration showed that the method effectively eliminates misidentification caused by HTW pixels (NDVI > 0), resulting in better consistency of the identification of the floating green tide and its distribution in the true color image. The method enables rapid and accurate extraction of information on floating green tide in HTW, and offers a new solution for the monitoring and tracking of green tides in coastal areas.

Journal of Marine Science and EngineeringVol. 12(9)
Cangzhou Normal University (CN), China National Environmental Monitoring Center (CN), National Marine Environmental Monitoring Center
Life below water
Openalex Percentile: Top 12%
Marine and coastal ecosystems
2.40
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