Automatic cloud-shadow removal from flood/standing water maps using MSG/SEVIRI imagery

Abstract

Cloud shadows are a major problem in the detection of flood/standing water using satellite data. Because cloud shadows and flood/standing water have similar spectral characteristics, the traditional means of detection based on spectral properties may fail to distinguish them from each other accurately. Because clouds cast shadows over land, this phenomenon can be analysed using the geometric correlations between clouds and cloud shadows; thus, this method might detect cloud shadows. Based on this concept, geometric relationships were established between clouds and their shadows using satellite data and satellite-solar geometries. Furthermore, an iterative method combining geometric and spectral properties was developed to automatically remove cloud shadows from flood/standing water in satellite maps. This method was applied and tested using MSG/SEVIRI (Meteosat Second Generation/Spinning Enhanced Visible and Infrared Imager) data and continues to show promising and consistent results.

Acknowledgements

This study was supported by the National Oceanic and Atmospheric Administration (NOAA) GOES-R Program. The article contents are solely the opinions of the authors and do not constitute a statement of policy, decision, or position on behalf of NOAA or the US Government.