WaterMasks integrates an unsupervised local thresholding approach to estimate water extent of an area relying on a single Sentinel-2 radiometrically corrected image. This module detects automatically thresholds on the Short-Wave Infrared (SWIR) band and on a Modified-Normalized Difference Vegetation Index (MNDVI), derived from radiometrically-corrected Sentinel-2 data. Then, it combines them in a meaningful way based on a knowledge base coming out of an iterative trial and error process. Classes of interest concern water and non-water areas. The inundation map generated by the WaterMask module can be used as input in the HydroMap one. 

Relevant material/sources

Kordelas, G.A.; Manakos, I.; Aragonés, D.; Díaz-Delgado, R.; Bustamante, J. Fast and Automatic Data-Driven Thresholding for Inundation Mapping with Sentinel-2 Data. Remote Sens. 2018, 10, 910.

Developed by

Name: Georgios Kordelas, Ioannis Manakos, Marios Bakratsas, Kalliroi Marini, Georgios Chantziaras (Contact: imanakos - at -

Organization: Centre for Research and Technology Hellas (CERTH) | Information Technologies Institute (ITI) (

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