Assessing COVID-19 lockdown effects on coastal water quality in a strongly impacted tourist destination using Sentinel-2 multispectral data

Abstract

Remote sensing data from satellite platforms were the only available source of information for environmental studies during the COVID-19 lockdown in many regions of the world. We analyzed the spatial variability of representative water indices derived from the Sentinel-2 sensor across six coastal land cover classes along a tourist destination on the North Pacific coast of Mexico. A comparative assessment was conducted between the 2020 lockdown period and the same holiday season in 2019, 2020, and 2022, evaluating the spatial distribution of water indices per coastal class. Principal coordinate analysis of organic content matter (CDOM), Chlorophyll-a (CHLA), and total suspended matter (TSMC2 and TSM_Clear) indices demonstrated clear distinctions in water quality among pre-pandemic (2019), pandemic (2020), and post-pandemic (2021−2022) periods. Canonical analysis of principal coordinates during the lockdown year revealed two key patterns: (1) sewage and harbor areas displayed a significant decrease in CHLA levels alongside elevated TSMC2, while (2) mangrove forest exhibited markedly reduced CDOM in post-pandemic years. Distance-based redundancy analysis further showed interannual variability across coastal zones, while the pandemic year (2020) was particularly distinguished by diminished CDOM in tourist and industrial areas. The high-resolution (10 m/pixel) and revisit time (5 days) of Sentinel-2 data was invaluable for monitoring water quality dynamics during the COVID-19 lockdown.