UCLA

The application of remotely sensed data to water quality monitoring is an active area of research nowadays, as GIS and remote sensing can reduce the cost and enlarge the scale of ground observation. However, a major challenge is the calibration of satellite-derived data with in situ data, which are sometimes difficult and expensive to acquire compared with remote sensing data. This study aims to investigate the effectiveness of Sentinel-2 for estimating coastal water quality in the Santa Monica Bay (SMB), California. Surface reflectance values are obtained from the Copernicus Sentinel-2 and remote sensing derived turbidity values are calculated by ACOLITE. In situ total suspended solids (TSS), absorbance, light transmission, and fecal indicator bacteria (FIB) have been tested to compare with the satellite data. The results of regression analysis demonstrate that remote sensing can offer preliminary qualitative estimates of coastal water quality in the SMB area.