Mapping of large-scale flooding in Thessaly region using Sentinel data

Floods are considering as one of the most common natural disasters, affecting seriously both natural and man-made environment. Remote sensing has proved to be an effective solution for post-disaster mapping and monitoring, facilitating the proper management of such crises. In this framework, the current research focuses on the post-disaster mapping of the flooded areas in the wider region of Thessaly using multispectral and radar data of Sentinel-1 and Sentinel-2 missions respectively. On September 5-7, 2023 Thessaly region was hit by a devastating medicane (Storm Daniel), where almost 3.7 billions m3 of rain inundated the region causing widespread flooding, loss of life, infrastructure damages, etc. The main objective of the research is to assess two different approaches, i.e. a manually one and a more automated one performed using GEE, to map the flood extent in Thessaly. Beyond this differentiation, Sentinel data were processed with several methodologies ranging from simple digitization and thresholding to the calculation of Modified Normalized Difference Water Index (MNDWI) and random forest classification. The flooded areas emerged from the processing of each approach were integrated in a GIS environment in order to be compared with the estimated flood extent obtained from the Copernicus EMS Rapid Mapping Service.