Over the past few days, there has been a lot of media coverage on the flooding in northern Italy. According to REUTERS NEWS, around 36,000 people have been forced to leave their homes, and many of those who remained in flooded areas were left without electricity. Some 10,000 of those were able to go home. Agriculture has been hit hard in the area.
Understanding Flooding and its Consequences
Floods happen when soil and vegetation cannot absorb water from a downpour or when a river outbursts its banks, and the water spills onto the floodplain; the inadequate drainage in some urban areas is also a major cause of flooding, causing widespread community disruption, displacement, economic loss, property damage (e.g., infrastructure, houses, commercial assets, agricultural properties, or historical and cultural heritage sites), deaths, injuries as well as profound emotional suffering.
It is necessary to continuously increase society’s resilience to climate change and disasters by producing new knowledge and understanding the nature of these events in order to create the right disaster risk reduction and mitigation strategies. Monitoring is vital in flood disaster management’s pre-flooding, flooding and post-flooding stages. The status evaluation and decision-making require timely monitoring to assess the impact of flooding and its effects and dictate the critical interventions necessary for mitigating the impact of flooding on people, infrastructure, and the environment.
Space for Flood Prediction, Monitoring, and Management
Advanced technologies have been developed to aid flood disaster prediction, monitoring and management, such as geographic information systems-GIS, remote sensing and hydrologic models.
SAR (Synthetic Aperture Radar)) data from Sentinel-1 are key assets for generating flooding maps for areas affected by these types of events and at this scale of catastrophic magnitude. At groundstation.space, we applied the Threshold method using Sentinel-1 images to determine the affected zone by the flooding in northern Italy.
The Threshold method is the most widely adopted approach used for flood mapping. It is less complex, making it suitable for large SAR image scenes. The images utilised in this example were Sentinel-1 SAR Vertically transmitted Vertically received (VV) Polarization data, with dates between April 28, 2023, and May 22, 2023.
The methodology process flow (see diagram) used to obtain the results displayed in the lower images (i.e., coloured polygons) includes the following steps: i. Radiometric Calibration  to calibrate radar reflectivity to the backscattering coefficient (physical units), which is mainly performed to compare the SAR images of different acquisition dates; ii. Speckle Filter to remove speckle noise from the dataset; iii. Binarisation to obtain the threshold values; and iv. Terrain correction to convert Sentinel-1 GRD (Ground Range Detected) from ellipsoid projection data to a map coordinate system and to rectify the distortions like foreshortening, layover, or shadowing effects.
The following images show us the affected zone during pre-flood (image 1) and post-flood (image 2):
Finally, we export the polygons obtained from the .kml file and thus overlap on Google Earth data.
Satellite data processing and interpretation prove to be a fast and reliable method to create awareness and preparedness for flood events covering large areas, which further contributes to significantly reducing the adverse impacts of these disasters on people and settlements.
The Threshold method, a widely adopted approach in flood mapping, utilizes SAR images and is particularly suitable for large-scale scenes. By calibrating radar reflectivity, applying speckle filters, binarizing the data, and implementing terrain correction, accurate flood maps can be obtained. This method was employed to assess the extent of the flooding in northern Italy during May 2023, using Sentinel-1 SAR VV Polarization data.
However, it is important to note that alternative methods and resources are available for flood mapping. One such method is the Rapid Mapping module of the Copernicus Emergency Management Service (CEMS), which has the capacity to produce detailed delineation maps for flooded areas. This service, based on CEMS data, combines information from specific dates, such as May 18 and May 20, to visualize the extent of the flooded areas. The inclusion of this information highlights the availability of multiple approaches and tools for flood mapping and analysis (see Rapid Mapping Activation Viewer (copernicus.eu))
This article is part of our series on SAR Remote Sensing Applications.