Abstract:
Total suspended matters (TSM) play a significant role in water quality assessment and resource management of coastal waters as it has a direct influence on many aquatic p...View moreMetadata
Abstract:
Total suspended matters (TSM) play a significant role in water quality assessment and resource management of coastal waters as it has a direct influence on many aquatic processes. This paper discovers dynamic spatial-temporal TSM patterns in coastal waters by using the self-organizing map (SOM), an unsupervised machine learning method on the 19 years Moderate-resolution Imaging Spectroradiometer (MODIS) 250 m imagery data. The paper found that the SOM of 2 × 3 grid is suitable to the Yellow River estuary, which shows six different patterns from winter to summer. Characteristics and factors affect the variability of the identified TSM patterns were also discussed. This study also demonstrated a general approach to apply SOM to identify TSM patterns in coastal waters.
Date of Conference: 26 September 2020 - 02 October 2020
Date Added to IEEE Xplore: 17 February 2021
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