Quality monitoring of inland water bodies using Google Earth Engine

Regular quality monitoring of inland water bodies is vital for identifying the areas with deteriorating water quality. Satellite remote sensing has been used for obtaining long-term trends that require the processing of many images. The computational load of processing a large number of satellite imageries can be eased by utilizing the cloud computing capabilities of Google Earth Engine (GEE). The present study explores the possibility of using the GEE platform for mapping the Trophic State Index (TSI) of an inland water body. The bottom of atmosphere (BOA) reflectance retrieved by the SIAC algorithm (used in the GEE platform) is assessed for its accuracy. The algorithm could retrieve only BOA reflectance at bands B3 and B4 of Sentinel 2L1C (S2) with reasonable accuracy. The study has identified the Normalized Difference of B3 and B4 bands of S2 (i.e., ND34) as the tool for mapping TSI of a water body on GEE. TSI from six imageries of three lakes was estimated with a mean error ,17%. The capability of GEE as a rapid water quality monitoring tool is demonstrated by displaying the temporal and spatial variations of water quality across Vembanad Lake for the period 2016-2021.

Automated summary

Regular quality monitoring of inland water bodies is crucial for identifying areas where water quality is deteriorating. The cloud computing capabilities of Google Earth Engine (GEE) can help process a large number of satellite images, making it a valuable tool for obtaining long-term trends. This study demonstrates the potential of GEE for mapping the Trophic State Index (TSI) by assessing the accuracy of the SIAC algorithm in retrieving bottom of atmosphere (BOA) reflectance. The study identifies the Normalized Difference of B3 and B4 bands of Sentinel 2L1C (S2) as the tool for mapping TSI on GEE and showcases its capability as a rapid water quality monitoring tool.