An application of VNREDSat-1/NAOMI for Chlorophyll-a estimation

Abstract

Monitoring chlorophyll-a (Chl-a) concentrations using remote sensing techniques has been extensively studied across diverse marine and coastal environments. However, the optical complexity and dynamic nature of aquatic environments present significant challenges for such studies. This research aims to develop and evaluate two empirical models, a standard model (STD) and a calibration model (CAL), for estimating Chl-a content using VNREDSat-1 and Sentinel-2B images in the coastal estuary of Thua Thien Hue province, Vietnam. We used 29 paired datasets, comprising radiometric measurements and in-situ Chl-a samples, with 70 % for model development and 30 % for validation. The results indicate that the CAL model, which utilises spectral bands from the NAOMI sensor (VNREDSat-1) and MSI sensors (Sentinel-2B), estimates Chl-a concentration more effectively than the STD models, achieving R² values ​​of 0.79 and 0.76, respectively. Furthermore, the RMSE, Bias, and MAE values of the CAL models are significantly lower than those of the STD models. Spatial analysis reveals that higher Chl-a concentrations are predominantly distributed  in nearshore and shallow waters, whereas lower concentrations are observed in offshore and deeper waters. However, the study has several limitations, including a small sample size, challenges associated with atmospheric correction of VNREDSat-1 imagery, and difficulties in synchronising imagery with in-situ data. Further research is recommended to assess the potential of VNREDSat-1 data for water-quality monitoring in other coastal and estuarine environments in Vietnam.