A New High-Resolution Remote Sensing Monitoring Method for Nutrients in Coastal Waters.
IEEE Trans. Geosci. Remote. Sens.(2023)
Abstract
Mariculture is an important offshore economic activity, and excessive farming can lead to the deterioration of sea ecology. The concentration of nutrients [mainly dissolved inorganic nitrogen (DIN) and orthophosphate-phosphorous (PO4)] is the main factor characterizing the health condition of farmed seas. Conventional field monitoring methods are spatiotemporally limited, and remote sensing technology has the advantages of high spatial coverage and long time series monitoring. Thus, the Sentinel-3 reflectance data and the in situ measured data for the offshore waters of Wenzhou were matched simultaneously. Then, the matched dataset between the Sentinel-2 band and the in situ measured data were obtained through spectral correspondence conversion between Sentinel-2 and Sentinel-3, and a machine learning algorithm was used to build the inversion model with an independent validation process. The correlations between the concentration of nutrients, area of rafts, and precipitation were assessed, and a strong positive correlation was found between the concentration of nutrients and the area of rafts, and a weak negative correlation was found between the former and precipitation.
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Key words
Environmental monitoring of nori culture,Gaussian regression machine algorithm,nutrients,remote sensing monitoring,support vector machine (SVM)
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