The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article investigates these development and its implications and asks whether or not this is a new paradigm in remote sensing and Geographic Information Science (GIScience). We first discuss several limitations of prevailing per-pixel methods when applied to high resolution images. Then we explore the paradigm concept developed by Kuhn (1962) and discuss whether GEOBIA can be regarded as a paradigm according to this definition. We crystallize core concepts of GEOBIA, including the role of objects, of ontologies and the multiplicity of scales and we discuss how these conceptual developments support important methods in remote sensing such as change detection and accuracy assessment. The ramifications of the different theoretical foundations between the ‘per-pixel paradigm’ and GEOBIA are analysed, as are some of the challenges along this path from pixels, to objects, to geo-intelligence. Based on several paradigm indications as defined by Kuhn and based on an analysis of peer-reviewed scientific literature we conclude that GEOBIA is a new and evolving paradigm.

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Abstract. The assessment of vulnerability has moved to centre-stage of the debate between different scientific disciplines related to climate change and disaster risk management. Composed by a combination of social, economical, physical and environmental factors the assessment implies combining different domains as well as quantitative with qualitative data and makes it therefore a challenge to identify an integrated metric for vulnerability. In this paper we define vulnerability in the context of climate change, targeting the hazard "flood". The developed methodology is being tested in the Salzach river catchment in Austria, which is largely prone to floods. The proposed methodology allows the spatial quantification of vulnerability and the identification of vulnerability units. These units build upon the geon concept which acts as a framework for the regionalization of continuous spatial information according to defined parameters of homogeneity. Using geons, we are capable of transforming singular domains of information on specific systemic components to policy-relevant, conditioned information. Considering the fact that vulnerability is not directly measurable and due to its complex dimension and social construction an expert-based approach has been chosen. Established methodologies such as Multicriteria Decision Analysis, Delphi exercises and regionalization approaches are being integrated. The method not only enables the assessment of vulnerability independent from administrative boundaries, but also applies an aggregation mode which reflects homogenous vulnerability units. This supports decision makers to reflect on complex issues such as vulnerability. Next to that, the advantage is to decompose the units to their underlying domains. Feedback from disaster management experts indicates that the approach helps to improve the design of measures aimed at strengthening preparedness and mitigation.Correspondence to: S. Kienberger (stefan.kienberger@sbg.ac.at) From this point of view, we reach a step closer towards validation of the proposed method, comprising critical useroriented aspects like adequateness, practicability and usability of the provided results in general.

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