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Open AccessLetter

A Visualization Tool for Flood Dynamics Monitoring Using a Graph-Based Approach

Remote Sensing | Spatial Analysis Lab (REMOSA), Department of Environment, Ghent University, 9000 Ghent, Belgium
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(13), 2118;
Received: 25 May 2020 / Revised: 25 June 2020 / Accepted: 29 June 2020 / Published: 2 July 2020
(This article belongs to the Section Remote Sensing Letter)
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. View Full-Text
Keywords: object-based change detection; graphs; SAR; floods object-based change detection; graphs; SAR; floods
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MDPI and ACS Style

Debusscher, B.; Landuyt, L.; Van Coillie, F. A Visualization Tool for Flood Dynamics Monitoring Using a Graph-Based Approach. Remote Sens. 2020, 12, 2118.

AMA Style

Debusscher B, Landuyt L, Van Coillie F. A Visualization Tool for Flood Dynamics Monitoring Using a Graph-Based Approach. Remote Sensing. 2020; 12(13):2118.

Chicago/Turabian Style

Debusscher, Bos; Landuyt, Lisa; Van Coillie, Frieke. 2020. "A Visualization Tool for Flood Dynamics Monitoring Using a Graph-Based Approach" Remote Sens. 12, no. 13: 2118.

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