Water quality monitoring in coastal areas is challenging due to cost and time constraints. Identifying and selecting sampling sites accurately and effectively is crucial for efficient monitoring. The need for efficient monitoring of marine waters has led to exploring the use of remote sensing as one helpful alternative. Remote sensing is practical in several applications based on pattern recognition and information processing of large terrestrial and aquatic surface areas. Collected information is processed with various image processing techniques to identify objects such as microorganisms. Fecal coliforms are microorganisms that are indicators of sanitary quality and are present in human and animal wastes discharged into water bodies reaching coastal regions. The present study estimated the presence of fecal coliforms as an indicator of contamination in coastal marine waters. Satellite data from two sensors, Landsat 7 ETM+ and Landsat 8 OLI, were used to evaluate the reflectance of fecal coliforms in marine waters. Then, statistical analysis and four regression models were tested to establish a functional correlation between the spectral bands and historical in situ fecal coliform measurement. In this research, satellite imagery in the vicinity of Pucusana Bay helped estimate the concentration of fecal coliforms in marine waters. As a result, a significant relationship was found between the shortwave infrared band splitting (SWIR 2) with the blue band and fecal coliforms presence. The relationship was used to estimate coliform concentration from the reflectance of the aquatic surface in Pucusana Bay. Finally, spatial distribution maps of fecal coliform concentrations were generated to compare the increase of these microorganisms over different years in the area. The methodology and results can be calibrated to other water body locations where fecal coliform is a concern.
Y-A Palma-Gongora et al 2022 IOP Conf. Ser.: Earth Environ. Sci. 1077 012005. https://doi.org/10.1088/1755-1315/1077/1/012005
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.
IOP Conf. Series: Earth and Environmental Science