Floodalyzer: A QGIS Plugin for Accessible and Rapid Flood Event Assessment

Floods are among the most devastating natural disasters, causing significant loss of life and economic damage. As extreme flood events become more frequent, rapid and accessible flood analysis tools are crucial in guiding early recovery efforts. This study presents the QGIS plugin ‘Floodalyzer’ developed to provide a quick and easy workflow for flood event analysis. By automating the processing and visualization of flood extent data from the Global Flood Monitoring System (GFM), derived from remote sensing, in combination with building footprints from various data sources, the plugin enables users to analyze past flood events without requiring expert knowledge or expensive proprietary software.

Floodalyzer operates within the widely used open-source GIS platform QGIS, making it highly accessible. Users manually download raster data and shapefiles from the web, which serve as inputs for automated analysis. The plugin then processes the data and generates output files, including a shapefile showing which buildings were flooded and for how long. Additionally, it compiles a HTML report including graphs that further describe the area of interest and summarize the plugin’s results (e.g. Building Footprint Heatmap, Observed Flood Extent Raster Calendar Display, Flooded Area Duration Bar Chart). The effectiveness of the tool was evaluated using case studies in Pakistan and Germany, where results were compared against CEMS’s Rapid Mapping Product. The CEMS product was not captured at the time of maximum flooding and therefore shows smaller inundated areas in many places compared to the plugin’s results. However, the locations and overall shapes of the flooded areas are generally consistent.

The case studies highlight the unique selling point of Floodalyzer – it’s ability to process flood extent data over extended time periods to analyze flood duration and damage, which enables a more comprehensive analysis of the available data. At the same time the results highlight uncertainties in flood extent, primarily originating from the GFM input data. Large exclusion mask areas indicate zones of high uncertainty, especially in urban environments where flood detection is more challenging. Temporal uncertainties also arise from gaps in satellite coverage, limiting data availability, especially in regions between the tropics.

Future improvements will focus on reducing runtime, and integrating statistical uncertainty assessments in the plugin’s output with human-readable explanations. Further, automated GFM data retrieval from the Global Flood Awareness System automating the download of the flood masks given an input AOI, would eliminate the need for manual downloads and thereby streamline the analysis process. By bridging the gap between high, complex data amounts and the need for a rapid response to flooding events, this tool provides decision-makers with a sound basis for dealing with the impacts of flooding in the response and recovery phase. Floodalyzer thus supports improved flood management through broader uptake of remotely sensed flood information, by lowering barriers to accessibility for flood extent data.