2024 IEEE GRSS Data Fusion Contest Flood Rapid Mapping

The Challenge Task

As a result of climate change, extreme hydrometeorological events are becoming increasingly frequent. Flood rapid mapping products play an important role in informing flood emergency response and management. These maps are generated quickly from remote sensing data during or after an event to show the extent of flooding. They provide important information for emergency response, and damage assessment. The aim of this challenge is to develop data fusion algorithms that generate flood maps by processing spatial data from a variety of sources.

The goal of this IEEE challenge (sponsored by NASA and CNES) is to design and develop an algorithm that will combine multi-source data to classify flood surface water extent–that is, water and non-water areas. Provided data sources include optical and SAR remote sensing images as well as a digital terrain model. The output is a gridded flood map where each grid cell is labeled water or non-water.

The difficulty of detecting flooded areas can vary greatly depending on the conditions in the area of interest and the event. This data fusion challenge has two tracks representing this variance.