Abstract
Sea eutrophication is a natural process of water enrichment caused by increased nutrient loading that severely affects coastal ecosystems by decreasing water quality. The degree of eutrophication can be assessed by chlorophyll-a concentration. This study aims to develop a remote sensing method suitable for estimating chlorophyll-a concentrations in tropical coastal waters with abundant phytoplankton using Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra imagery and to improve the spatial resolution of MODIS/Terra-based estimation from 1 km to 100 m by geostatistics. A model based on the ratio of green and blue band reflectance (rGBr) is proposed considering the bio-optical property of chlorophyll-a. Tien Yen Bay in northern Vietnam, a typical phytoplankton-rich coastal area, was selected as a case study site. The superiority of rGBr over two existing representative models, based on the blue-green band ratio and the red-near infrared band ratio, was demonstrated by a high correlation of the estimated chlorophyll-a concentrations at 40 sites with values measured in situ. Ordinary kriging was then shown to be highly capable of predicting the concentration for regions of the image covered by clouds and, thus, without sea surface data. Resultant space-time maps of concentrations over a year clarified that Tien Yen Bay is characterized by natural eutrophic waters, because the average of chlorophyll-a concentrations exceeded 10 mg/m3 in the summer. The temporal changes of chlorophyll-a concentrations were consistent with average monthly air temperatures and precipitation. Consequently, a combination of rGBr and ordinary kriging can effectively monitor water quality in tropical shallow waters.
Highlights
Chlorophyll-a (Chl-a) concentration is an effective measure of the trophic state of sea and land waters, because it is related strongly to aquatic phytoplankton abundance and biomass
Despite the importance of Chl-a monitoring in such coastal areas by remote sensing, such applications have been limited, and the most suitable methods for estimating Chl-a concentrations from satellite imagery have not yet been identified. This lack of information is the result of several factors, including the difficulties associated with making atmospheric corrections and the influences of detritus and dissolved organic matter on water optical properties that may not co-vary with phytoplankton [21]
To improve the accuracy of Chl-a concentration estimates in phytoplankton-rich coastal waters using Moderate Resolution Imaging Spectroradiometer (MODIS) image data, the most representative sea-observation satellite imagery, we developed an algorithm that considers the bio-optical properties of coastal waters and adopted geostatistics as a post-processing technique for down-scaling spatial resolution
Summary
Chlorophyll-a (Chl-a) concentration is an effective measure of the trophic state of sea and land waters, because it is related strongly to aquatic phytoplankton abundance and biomass. Despite the importance of Chl-a monitoring in such coastal areas by remote sensing, such applications have been limited, and the most suitable methods for estimating Chl-a concentrations from satellite imagery have not yet been identified. This lack of information is the result of several factors, including the difficulties associated with making atmospheric corrections and the influences of detritus and dissolved organic matter on water optical properties that may not co-vary with phytoplankton [21]
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