Abstract India had announced the longest ever lockdown from 25 March 2020 to 14 April 2020 amid COVID-19 pandemic. It was reported that the water quality of the Ganga River has improved as compared to regular during this country-wide lockdown. In the present study, an attempt has been made to study the change in water quality of the river in terms of turbidity purely through remote sensing data, in the absence of ground observations, especially during this time period. The change in spectral reflectance of water along the river in the visible region has been analyzed using the Sentinel-2 multispectral remote sensing data at Haridwar, Kanpur, Prayagraj, and Varanasi stretches of the river. In the present study, it was found that the red and NIR bands are most sensitive, and can be used to estimate the turbidity. Further, the temporal variation in turbidity was also analyzed through normalized difference turbidity index at each location. It was observed that the turbidity in the river has reduced drastically at each stretch of the river. The study elicited that the remote sensing approach can be used to make qualitative estimates on turbidity, even in the absence of field observations.

中文翻译：

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使用 Sentinel-2 卫星数据在与 COVID-19 相关的锁定期间沿恒河的浊度变化

摘要 印度在 COVID-19 大流行期间宣布了有史以来最长的封锁，从 2020 年 3 月 25 日到 2020 年 4 月 14 日。据报道，在此次全国封锁期间，恒河的水质较正常情况有所改善。在目前的研究中，在没有地面观测的情况下，特别是在这段时间里，已经尝试纯粹通过遥感数据来研究河流水质在浊度方面的变化。已使用位于 Haridwar、Kanpur、Prayagraj 和 Varanasi 河段的 Sentinel-2 多光谱遥感数据分析了可见区域沿河水的光谱反射率变化。在本研究中，发现红色和 NIR 波段最为敏感，可用于估计浊度。更多，还通过每个位置的归一化差浊度指数分析了浊度的时间变化。据观察，河流的浑浊度在河流的每一段都急剧下降。该研究表明，即使在没有实地观察的情况下，遥感方法也可用于对浊度进行定性估计。