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Many ongoing processes in today's landscapes impact our environment considerably. Thus, it is enormously important to gather information on qualitative characteristics of our landscapes in order to effectively counteract the negative developments. Structural functionality as proxy for the assessment of habitat quality and species patterns has already proven potential to successfully describe ecological values. Completed by the measurement of green infrastructure information for a defined profile of a functional trait, a rapid and rough assessment of the qualitative state of habitats seems feasible. We therefore present in this study (i) an assessment of structural functionality based on the statistical analysis of landscape metrics, (ii) the measurement of green infrastructure and travelling costs for the ecoprofile of a Disturbance Sensitive Species Group (DSG) and (iii) an investigation if functionality and green infrastructure change between different types of landscapes and protection status. In the Lake Neusiedl region we selected 41 landscape samples based on a stratified random process. Based on orthophoto interpretation, we calculated landscape metrics with FRAGSTATS and reduced them to a core set of 13 indices by combining statistical results with literature review. Their relation to main ecological processes determined if the individual metric related positively or negatively with the land cover category and structural functionality was given by the average value of the landscape metrics. Green infrastructure elements were allocated with GUIDOS, whereas the travelling costs to move between them was also considered. Landscape elements of valuable matrix and connecting corridors ranked highest in structural functionality based on the calculated landscape indices but showed large differences between different land use regimes. Correlation and regression analysis confirmed the dependence of green infrastructure elements (corr. r²=0.877) as well as travelling costs (corr. r²=0.669) to functionality values. Protection status of the landscape samples proved to be a determining factor because functionality values as well as green infrastructure differed significantly (both with a p-value
