Abstract
Driven by vegetation and environmental changes caused by global warming and an ongoing loss of biodiversity, there is an increasing demand for updated image data in a high time rate. These requirements, as well as economic reasons, ask for automated image analysis techniques. This article presents a synthesis of two complementary, preceding studies (Preiner et al., 2006; Weinke and Lang, 2006) on semi-automated habitat delineation. The work has been carried out in two neighboring study sites, which are situated in the Berchtesgaden National Park, in the Alpine region of south-eastern Germany. Both test sites represent a mountainous area, characterized by a high bio- and habitat diversity and a cliffy relief. The NPB has been involved in the European Interreg-IIIb project HABITALP (Alpine Habitat Diversity), which came up with harmonized methods for trans-Alpine monitoring of habitat diversity and environmental changes by standardized, comparative habitat interpretation on color infrared (CIR) aerial photographs. The work presented evaluates the potential of object-based image analysis (OBIA) for partly automising this process. In both studies we used pan-sharpened data from the same QuickBird scene. First, two different approaches, i.e. iterative one-level representation (OLR) strategy and multi-scale segmentation/object relationship modeling (MSS/ORM), are described. Both are meant for dealing with high spectral and spatial variability. They are discussed in the light of specific settings: whereas iterative OLR was used for delineating homogeneous, but differently scaled single habitat types, MSS/ORM proved suitable for classifying hierarchically structured patches of mountain pine (Pinus mugo). Second, based on the results from iterative OLR, a spatial overlay method (‘virtual overlay’, cf. Schöpfer and Lang, 2006) is applied to characterize habitat fate. The aim is to tell ‘real’ object changes from differences originating from different ways of delineation, i.e. visual interpretation in the year 2003 vs. automated delineation in 2005. The results showed that both strategies in combination with object-oriented image analysis software are suited to delineate habitats similar to the habitats as addressed by the HABITALP project.
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Weinke, E., Lang, S., Preiner, M. (2008). Strategies for semi-automated habitat delineation and spatial change assessment in an Alpine environment. In: Blaschke, T., Lang, S., Hay, G.J. (eds) Object-Based Image Analysis. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77058-9_39
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