Abstract
Insights into flood dynamics, rather than solely flood extent, are critical for effective flood disaster management, in particular in the context of emergency relief and damage assessment. Although flood dynamics provide insight in the spatio-temporal behaviour of a flood event, to date operational visualization tools are scarce or even non-existent. In this letter, we distil a flood dynamics map from a radar satellite image time series (SITS). For this, we have upscaled and refined an existing design that was originally developed on a small area, describing flood dynamics using an object-based approach and a graph-based representation. Two case studies are used to demonstrate the operational value of this method by visualizing flood dynamics which are not visible on regular flood extent maps. Delineated water bodies are grouped into graphs according to their spatial overlap on consecutive timesteps. Differences in area and backscatter are used to quantify the amount of variation, resulting in a global variation map and a temporal profile for each water body, visually describing the evolution of the backscatter and number of polygons that make up the water body. The process of upscaling led us to applying a different water delineation approach, a different way of ensuring the minimal mapping unit and an increased code efficiency. The framework delivers a new way of visualizing floods, which is straightforward and efficient. Produced global variation maps can be applied in a context of data assimilation and disaster impact management.
Highlights
The emergence of several new Synthetic Aperture Radar (SAR) missions throughout the past decade has boosted the field of flood remote sensing
While selecting cases for upscaling, the following criteria were considered: (1) The flood area should be about 100 times larger than in the previous prove of concept [9]; (2) the images should fall completely within single Sentinel-1 captures in order to avoid stitching; (3) at least one external flood extent map should be available for comparison; (4) the cases should be different in nature to detect possible different behaviors
Because flood duration fails to incorporate spatio-temporal dynamics, we propose to combine both flood duration and variation
Summary
The emergence of several new Synthetic Aperture Radar (SAR) missions throughout the past decade has boosted the field of flood remote sensing. Most studies focus on the development of new or improved flood mapping algorithms, which result in single date flood extents. These products fail to provide information on flood dynamics, which is crucial for several applications. Data assimilation for hydrodynamic forecasting could be improved by preserving information-dense regions, while removing redundant points [5,6,7,8] In this way it is possible to determine where, when, and how often remote sensing data should be acquired for flood extent assimilation to be most effective. We have extended our previous work to cover larger areas This allows for a new way of visualizing flood dynamics. These two non-similar floods were chosen because of their different origin and evolution
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