Clemens Eisank

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In most landform classification studies – either per cell or object-based – the authors have ignored modeling the semantics of landforms explicitly. Thus, landform classification schemes rely on individual knowledge, and are too much tailored to specific areas and/or scales. Integration of structured knowledge models in the classification process has been(More)
Landform mapping is more important than ever before, yet the automatic recognition of specific landforms remains difficult. Object-based image analysis (OBIA) steps out as one of the most promising techniques for tackling this issue. Using the OBIA approach, in this study, a multiscale mapping workflow is developed and applied to two different input data(More)
Earth surface processes operate on various spatio-temporal scales and produce landforms that are structured in a nested hierarchical manner. Semi-automated extraction of selected landform types from digital elevation models (DEMs) is of great importance in geomorphology. Object-based image analysis (OBIA) provides an attractive framework for multi-scale(More)