Improved Accuracy of Chlorophyll-a Concentration Estimates from MODIS Imagery Using a Two-Band Ratio Algorithm and Geostatistics: As Applied to the Monitoring of Eutrophication Processes over Tien Yen Bay (Northern Vietnam)

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/m 3 in the summer. The temporal changes of chlorophyll-a concentrations were consistent with average monthly air

Selecting the Best Band Ratio to Estimate Chlorophyll-a Concentration in a Tropical Freshwater Lake Using Sentinel 2A Images from a Case Study of Lake Ba Be (Northern Vietnam)

“…Among the many band-reflectance ratio algorithms that have been proposed for Chla estimation in lake waters, algorithms based on spectral band ratios are the more preferred because they help reduce the irradiance, atmospheric and air-water surface effects on reflectance [14,34]. Three commonly-used algorithms are based on the ratios of: (1) reflectances within the first peak of strong absorption at the blue region between 440 and 510 nm, to reflectances at the minimum absorption at the green region between 550 and 555 nm [35,36]; (2) reflectances at the minimum absorption at the NIR region between 685 and 710 nm, to reflectances at the second peak of absorption at the red region between 670 and 675 nm [16,18]; and (3) reflectances at the minimum absorption at the green region between 550 and 555 nm, to reflectances at the second peak absorption at the red region between 670 and 675 nm [33,37]. In addition to two-band ratio algorithms, three-band ratio algorithms also have been widely used to estimate Chla in turbid productive waters using two reflectances in the NIR region (720 and 750 nm) and one at near-670 nm [38], particularly when based on MERIS data using the ratio of the two NIR bands at 708 nm and 748 nm [17].…”

“…As previously mentioned, a wide range of band ratios has been developed for retrieving Chla [16][17][18][34][35][36][37][38]. The successful selection of these ratios depends largely on the biogeochemical characteristics of the water body, clearly shown by the water reflectance spectrum.…”

Spectral Feature Selection Optimization for Water Quality Estimation

“…Analytical-based methods analyze the physical interconnections among absorption, scattering coefficients, and water parameters at different wavelengths of spectral bands, based on the radiative transfer equation [3,[15][16][17]. By contrast, empirical-based methods address the link between spectral bands of satellite images and measured water parameters of interest [12,13,[18][19][20]. Recently, a neural network was also applied to define the various eutrophic levels and estimate the water quality parameters [21,22].…”

Remote Sensing of Chlorophyll‐A in Case II Waters: A Novel Approach With Improved Accuracy Over Widely Implemented Turbid Water Indices

“…Notwithstanding the uncertainty in remote retrieval of IOPs, researchers made relentless efforts to estimate CHL using band‐ratio algorithms in quadratic forms, which depends on the primary and secondary absorption peaks at 443 and 665 nm, respectively (Blondeau‐Patissier et al, ; Ha et al, ; Lee et al, ). Secondarily, reflectance peak at 700 nm removes the effect of particulate and dissolved organic/inorganic matter (see Gitelson, , for further understanding).…”