Standardized Analysis Ready (STAR) data cube for high-resolution Flood
  mapping using Sentinel-1 data
Surajit Ghosh Arpan Dawn Sneha Kour Susmita Ghosh
Floods are one of the most common disasters globally. Flood affects humans in
many ways. Therefore, rapid assessment is needed to assess the effect of floods
and to take early action to support the vulnerable community in time.
Sentinel-1 is one such Earth Observation (EO) mission widely used for mapping
the flooding conditions at a 10m scale. However, various preprocessing steps
are involved before analyses of the Sentinel-1 data. Researchers sometimes
avoid a few necessary corrections since it is time-consuming and complex.
Standardization of the Sentinel-1 data is the need of the hour, specifically
for supporting researchers to use the Standardized Analysis-Ready (STAR) data
cube without experiencing the complexity of the Sentinel-1 data processing. In
the present study, we proposed a workflow to use STAR in Google Earth Engine
(GEE) environment. The Nigeria Flood of 2022 has been used as a case study for
assessing the model performance.