Remote sensing-based classification of habitat types in floodplains and their application in planning practice

Recurrent floods and especially some extreme events in recent years emphasise the great importance of effective flood protection. Hydrodynamic-numerical models (HN models), which simulate water flows and water levels, are a key tool for better flood protection measures. So-called roughness coefficients, which are strongly influenced by the vegetation structure, are decisive for their accuracy. At present, generalised values are usually used for this, which limits the explanatory power of the models.

In our project funded by the German Federal Environmental Foundation (Deutsche Bundesstiftung Umwelt, DBU), the ‘Google4Habitat’ tool (Egger et al., 2024) will be further developed, which can be used to classify vegetation types using high-resolution, multispectral satellite images in combination with field data. The tool is implemented on the Google Earth Engine (GEE) platform. Each vegetation type (such as pioneer vegetation, willow scrub and riparian forest) is assigned roughness coefficients and this information is integrated into HN models. 

The objectives of the project include the development of a GEE tool for recording vegetation structures, the application of the tool to different river types, the analysis of vegetation dynamics after flood events and the optimisation of the tool with feedback from ecology and water authorities, offices and NGOs.

With ‘Google4Habitat’, existing approaches for classifying vegetation structure or habitat types can be made more efficient and less time-consuming and cost-intensive for larger areas.

A more detailed project description can be found on the DBU website (in German): https://www.dbu.de/en/projektdatenbank/39546-01/  

Egger, G.; Preinstorfer, S.; Kollmann, M.; Becker, I.; Izquierdo-Verdiguier, E.; Paul, M. (2024). Google4Habitat – a novel method for remote sensing-based habitat classification using Google Earth Engine. Carinthia.2: Mitteilungen des Naturwissenschaftlichen Vereins für Kärnten, Part3, Vol.1 (1), 8–28.