Surface Water Extent Mapping in Denmark: Comparing Airborne Thermal Imagery and Satellite Earth Observation

Mapping and prediction of inundated areas are increasingly important for climate change adaptation and emergency preparedness. Flood forecasting tools and flood risk models have to be compared to observe flooding patterns for training, calibration, validation, and benchmarking. At the regional to continental scales, satellite earth observation (EO) is the established method for surface water extent (SWE) mapping, and several operational global-scale data products are available. However, the spatial resolution of satellite-derived SWE maps remains a limiting factor, especially in low-lying areas with complex hydrography, such as Denmark. We collected thermal imagery using an unmanned airborne system (UAS) for three areas in Denmark shortly after major flooding events. We combined the thermal imagery with an airborne lidar-derived high-resolution digital surface model of the country to retrieve high-resolution (40 cm) SWE maps. The resulting SWE maps were compared with low-resolution SWE maps derived from satellite earth observation and with potential flooded areas derived from the high-resolution digital elevation model. We conclude that UASs have significant potential for SWE mapping at intermediate scales (up to a few square kilometers), can bridge the scale gap between ground observations and satellite EO, and can be used to benchmark and validate SWE mapping products derived from satellite EO as well as models predicting inundation.

Automated summary

The study shows that using drones for SWE mapping at intermediate scales (up to a few square kilometers) has significant potential, bridging the scale gap between ground observations and satellite EO, and can be used for benchmarking and validating SWE mapping products as well as models predicting inundation.