Evaluation of Chlorophyll-a Estimation Approaches Using Iterative Stepwise Elimination Partial Least Squares (ISE-PLS) Regression and Several Traditional Algorithms from Field Hyperspectral Measurements in the Seto Inland Sea, Japan.

Harmful algal blooms (HABs) occur frequently in the Seto Inland Sea, bringing significant economic and environmental losses for the area, which is well known as one of the world's most productive fisheries. Our objective was to develop a quantitative model using in situ hyperspectral measurements in the Seto Inland Sea to estimate chlorophyll a (Chl-a) concentration, which is a significant parameter for detecting HABs. We obtained spectra and Chl-a data at six stations from 12 ship-based surveys between December 2015 and September 2017. In this study, we used an iterative stepwise elimination partial least squares (ISE-PLS) regression method along with several empirical and semi-analytical methods such as ocean chlorophyll, three-band model, and two-band model algorithms to retrieve Chl-a. Our results showed that ISE-PLS using both the water-leaving reflectance (RL) and the first derivative reflectance (FDR) had a better predictive ability with higher coefficient of determination (R²), lower root mean squared error (RMSE), and higher residual predictive deviation (RPD) values (R² = 0.77, RMSE = 1.47 and RPD = 2.1 for RL; R² = 0.78, RMSE = 1.45 and RPD = 2.13 for FDR). However, in this study the ocean chlorophyll (OC) algorithms had poor predictive ability and the three-band and two-band model algorithms did not perform well in areas with lower Chl-a concentrations. These results support ISE-PLS as a potential coastal water quality assessment method using hyperspectral measurements.

Chlorophyll and suspended sediment mapping to the Caribbean Sea from rivers in the capital city of the Dominican Republic using ALOS AVNIR-2 data.

This study aims to study the distribution of contaminants in rivers that flow into the Caribbean Sea using chlorophyll-a (Chl-a) and suspended sediment (SS) as markers and ALOS AVNIR-2 satellite sensor data. The Haina River (HN) and Ozama and Isabela Rivers (OZ-IS) that flow through the city of Santo Domingo, the capital of the Dominican Republic, were chosen. First, in situ spectral reflectance/Chl-a and SS datasets obtained from these rivers were acquired in March 2011 (case A: with no rain influence) and June 2011 (case B: with rain influence), and the estimation algorithm of Chl-a and SS using AVNIR-2 data was developed from the datasets. Moreover, the developed algorithm was applied to AVNIR-2 data in November 2010 for case A and August 2010 for case B. Results revealed that for Chl-a and SS estimations under cases A and B conditions, the reflectance ratio of AVNIR-2 band 4 and band 3 (AV4/AV3) and the reflectance of AVNIR-2 band 4 (AV4) were effective. The Chl-a and SS mapping results obtained using AVNIR-2 data corresponded with the field survey results. Finally, an outline of the distribution of contaminants at the mouth of the river that flows into the Caribbean Sea was obtained for both rivers in cases A and B.