Estimating the Chlorophyll-a in the Nha Trang Bay using Landsat-8 OLI data

Abstract

Abstract The pigment chlorophyll-a (Chl-a) is used to evaluate aquatic ecological health. Using remote sensing techniques to estimate this pigment and spatially mapping its distribution becomes essential for measuring and assessing water quality in coastal areas. Nha Trang Bay is famous not only for its scenery but also for its biodiversity values, especially the existence of coral reefs. In this study, Landsat-8 OLI was taken on June 3, 2015, and field measurements of Chl-a at 13 survey sites from June 6-8, 2015, were used to build a local algorithm to monitor the spatio-temporal distribution of Chl-a content in Nha Trang Bay. The ACOLITE processor was employed for the atmospheric modification of Landsat-8 OLI images to obtain atmospherically corrected surface reflectance products. Four types of simple regression models, including linear, exponential, logarithmic, and power models, were used to describe the relationship between the in-situ measurement of Chl-a and remote sensing reflectance of Landsat-8 OLI data. The results of correlation analysis have shown a statistically significant relationship between field measurement of Chl-a concentration and the remote sensing reflectance ratio of Landsat-8 band 3 versus band 2 using an exponential model with a coefficient of determination of 0.88 (p < 0.001) and root mean square error (RMSE) of 0.40 mg/m3. This empirical relationship was applied to map the spatial distribution of Chl-a concentration from 27 cloudless Landsat-8 OLI images from 2013 to 2021. The spatio-temporal distribution of Chl-a indicated that the Chl-a concentration in the Bay has a low value (less than 1 mg/m3). However, this concentration becomes high in the coastal areas (greater than 1 mg/m3) and the Cai and Tac rivers (greater than 2 mg/m3). It is also noted that the content of Chl-a in the rainy season is fairly higher than in the dry season, by an average of 0.68 mg/m3 and 0.53 mg/m3, respectively. This research highlights that Landsat-8 OLI data can be an effective and valuable tool in monitoring Chl-a for coastal areas.