Flood mapping with openEO

interTwin

Preface

This is a thematic module example that supports the development of digital twins within the interTwin project.

On this page we showcase openEOs standardization of remote sensing and Earth observation operations. We do this by translating the flood mapping algorithm as presented in Bauer-Marschallinger et al. (2022), and part of the GloFAS Global Flood Monitoring to the openEO syntax of the Python Client. This algorithm employs Sentinel-1 backscattered microwaves, so-called “sigma nought” or \(\sigma^0\), to detect flooding. In this exercise we will replicate the case study of the above mentioned paper, the February 2018 flooding of the Greek region of Thessaly.

Source: Copernicus Emergency Management Service

Bauer-Marschallinger, Bernhard, Senmao Cao, Mark Edwin Tupas, Florian Roth, Claudio Navacchi, Thomas Melzer, Vahid Freeman, and Wolfgang Wagner. 2022. “Satellite-Based Flood Mapping Through Bayesian Inference from a Sentinel-1 SAR Datacube.” Remote Sensing 14 (15): 3673. https://doi.org/10.3390/rs14153673.