This repo contains the OMBRIA dataset as described in the journal "OmbriaNet—Supervised Flood Mapping via Convolutional Neural Networks Using Multitemporal Sentinel-1 and Sentinel-2 Data Fusion" (https://ieeexplore.ieee.org/abstract/document/9723593).
It is a Sentinel-1 and Sentinel-2 imagery dataset constructed for benchmarking the OmbriaNet deep learning CNN architecture. OmbriaNet was designed for adressing the flood mapping problem. Each satellite module contains three folders:
- The folder named BEFORE contains image of a region taken before a selected flood event
- The folder named AFTER contains image of the same region taken after the flood event
- The folder named MASK contains a binary ground truth image of the region as produced by the EMS Rapid mapping.
This work was funded by the Hellenic Foundation for Research and Innovation (HFRI) and the General Secretariat for Research and Technology (GSRT) under grant agreement No. 1725 (V4-ICARUS)