Pan-European distribution modelling of stream riparian zones based on multi-source Earth Observation data

Freshwater ecosystems are among the most degraded and threatened globally. A need for systematic assessment of riverine habitats is thus well-documented. Riparian zones are especially important due to the large array of ecosystem and social services they can provide, while also recently gaining a major role in the new European biodiversity policy. In this context, the necessity to gather spatial information on extent, distribution and characteristics of the riparian zones is clear. This paper presents the development of a novel model to derive geographical distribution and basic characteristics of stream riparian zones in Europe, including both river-floodplain systems and the riparian networks of minor and ephemeral streams. A series of relevant descriptive attributes (water boundary, vegetation presence, land-cover, upland boundary and local geomorphology) is initially selected from the existing literature to describe the presence of riparian zones. Spatially explicit estimates of these attributes are obtained using available Earth Observation data and pan-European thematic datasets. Finally, the information layers are combined through an aggregation system that assigns a degree of belonging to the riparian zone class using two fuzzy membership functions to evaluate water influence and presence of natural vegetation, respectively. Riparian zones with no hydrological connection are also incorporated in by the model based on functional considerations. The distribution of stream riparian zones was derived and mapped for the whole of Europe at fine resolution. Modelled riparian zones extend for approximately 91,000 km ², considering the entire range of low to high membership to the riparian class. A characterization of land-cover types was derived based on Corine Land Cover 2000 data, showing that European riparian zones are strongly dominated by forest habitats. Accuracy assessment was performed using independent ecological datasets and visual validation, indicating that producer accuracy is equal to 84.5 ± 1.3% and user accuracy to 72.6 ± 5.8% at 95% confidence level. The proposed model and output can represent valuable information for large-scale research activities of riparian environments and to support national and supra-national conservation programmes.