Abstract
Monitoring surface water bodies accurately is one of the most crucial applications of remote sensing. It is a global challenge in the times of climate change, since surface water is the most important component of the hydrological cycle. Modified Normalized Difference Water Index (MNDWI) method based on spectral index is calculated from the Green and Shortwave-Infrared (SWIR) bands, for monitoring surface water. This index helps to map surface water accurately based on the threshold using Otsu method for achieving higher level of accuracy. Earth observing satellite by ESA, Sentinel-2 provides multispectral images at a fine spatial and spectral resolution. This dataset has high potentiality for significantly mapping regional surface water, due to its frequent revisiting capabilities and spectral capabilities. Google Earth Engine (GEE) platform can be used for processing the huge datasets easily in the most efficient way for fast computation, storing and displaying the huge datasets. A pilot study has been carried out in Northwest part of India to demonstrate the effectiveness of mapping mean surface water for the temporal window June 2016 to March 2020 from Sentinel-2 using GEE so as to understand the patterns of surface water inundation at a regional scale.
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