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Object-based classification of landforms based on their local geometry and geomorphometric context

Gerçek, Deniz
Terrain as a continuum can be categorized into landform units that exhibit common physiological and morphological characteristics which might serve as a boundary condition for a wide range of application domains. However, heterogeneous views, definitions and applications on landforms yield inconsistent and incompatible nomenclature that lack interoperability. Yet, there is still room for developing methods for establishing a formal background for general type of classification models to provide different disciplines with a basis of landscape description that is also commonsense to human insight. This study proposes a method of landform classification that reveals general geomorphometry of the landscape. Landform classes that are commonsense to human insight and relevant to various disciplines is adopted to generate landforms at the landscape scale. Proposed method integrates local geometry of the surface with geomorphometric context. A set of DTMs at relevant scale are utilized where local geometry is represented with morphometric DTMs, and geomorphometric context is incorporated through relative terrain position and terrain network. “Object-based image analysis (OBIA)” tools that have the ability to segment DTMs into more representative terrain objects and connect those objects in a multi-level hierarchy is adopted. A fuzzy classification approach is utilized via semantic descriptions to represent ambiguities both in attribute and geographical space. Method is applied at different case areas to evaluate the efficiency and stability of the classification. Outcomes portray reasonable amount of consistency where the results can be utilized as general or multi-purpose regarding some ambiguity that is inherent in landforms as well.