A global analysis of the timing of changes in water extents using Google Earth Engine and Landsat Time Series.

Coastal and inland surface water resources are affected by complex and overlapping processes such as climate change, droughts, flooding, river damming, coastal expansion, dredging, river meander migration, and so on. The use of satellite-acquired imagery, combined with recent advances in cloud computing, is enabling the monitoring on a global scale of areas where water limits have advanced or receded (Donchyts et al., 2016; Donchyts et al., 2022; Pekel et al., 2016). However, previous studies have not estimated an important aspect: the precise timing at which changes in water extents happened. Here we present preliminary results of an analysis using 38 years of Landsat time series and the cloud platform Google Earth Engine (GEE) in which we monitor areas where water has advanced and receded and the year that this change happened. The developed algorithm detects only permanent changes in water features and thus avoids seasonal or higher-frequency fluctuations caused by short-lived events. The method employs a two-step algorithm. The first step detects areas of permanent change using the Modified Normalized Different Water Index (mNDWI), which effectively detects water and non-water features. In the areas of detected permanent change, the second step uses a Green-Red Normalized Different Water Index (GR_NDWI), which has a smoother value transition from water to land, to identify the year that the change happened. The thresholds of mNDWI and GR_NDWI used to determine if a pixel is water or not were estimated using the Otsu method. Furthermore, an additional novel algorithm was developed to fill in cloud holes in the time series, allowing the monitoring of cloudy regions, such as the Amazon Basin. The final product will be a World Map of the year that the water advanced or receded. A preliminary result for the American continent (excluding Canada) can be visualized in this app: https://gustavoonagel.users.earthengine.app/view/americawaterdetection . The product will be available in a public GEE dataset, for open access use by researchers, governments, and private companies working on oceans, rivers and water lakes, helping to improve water management on a global scale. Donchyts, G., Baart, F., Winsemius, H., Gorelick, N., Kwadijk, J., & van de Giesen, N. (2016). Earth's surface water change over the past 30 years. Nature Climate Change, 6(9), 810-813. https://doi.org/10.1038/nclimate3111Donchyts, G., Winsemius, H., Baart, F., Dahm, R., Schellekens, J., Gorelick, N., Iceland, C., & Schmeier, S. (2022). High-resolution surface water dynamics in Earth’s small and medium-sized reservoirs. Scientific Reports, 12(1), 13776. https://doi.org/10.1038/s41598-022-17074-6Pekel, J.-F., Cottam, A., Gorelick, N., & Belward, A. S. (2016). High-resolution mapping of global surface water and its long-term changes. Nature, 540(7633), 418-422. https://doi.org/10.1038/nature20584

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