Recently, I posted an analysis of the Orbital Insight’s Global Water Reserves product, in which they use deep learning to automatically detect global surface water on a weekly to bi-weekly basis using Landsat images. In this post, I want to draw attention to work done by the European Commission’s Joint Research Centre (JRC) in which they used Google Earth Engine‘s extensive Landsat archive to derive global surface water occurrence map, along with probability and seasonality measures. They have used Landsat 5, 7, and 8 for this study.
This work by JRC is of a much more scientific nature than Orbital Insight’s global water mapping, giving the capability of study and analysis of river dynamics and morphology also. The study also reports some validation statistics.
Other research groups are also working on similar solutions; see, for example, this news report about Amy Hudson at the University of Maryland trying to use GEE in a similar manner to analyse global surface water dynamics using Landsat.