This study focuses on a geomorphometric analysis of a small headwater basin of the Dolomites (Eastern Italian Alps). The analysis of the fine-scale surface morphology was performed on a high-resolution digital elevation model (cell size 2 m) derived from an airborne LiDAR survey. The topography was synthesized by a set of spatial-statistical indexes representing a signature of the local surface morphology, and the relationships between the geomorphometric indexes and morphological features were evaluated. The studied basin was then segmented by means of a fuzzy k-means classification algorithm into different spatial subdomains characterized by specific local geomorphic signatures. This method allows us to objectively choose the optimal combination of the number of classes and degree of fuzziness characterizing the studied basin. Accordingly, the analysis can be adopted to the characteristics of the studied area, improving the interpretation of surface morphology and offering a valuable tool for comparative analysis between different geomorphological contexts. The results of the classification were compared with the actual surface morphology based on high-resolution orthophotos, aerial photos, and field surveys.

Surface texture analysis of a high-resolution DTM: Interpreting an alpine basin

Cavalli M;Marchi L
2012

Abstract

This study focuses on a geomorphometric analysis of a small headwater basin of the Dolomites (Eastern Italian Alps). The analysis of the fine-scale surface morphology was performed on a high-resolution digital elevation model (cell size 2 m) derived from an airborne LiDAR survey. The topography was synthesized by a set of spatial-statistical indexes representing a signature of the local surface morphology, and the relationships between the geomorphometric indexes and morphological features were evaluated. The studied basin was then segmented by means of a fuzzy k-means classification algorithm into different spatial subdomains characterized by specific local geomorphic signatures. This method allows us to objectively choose the optimal combination of the number of classes and degree of fuzziness characterizing the studied basin. Accordingly, the analysis can be adopted to the characteristics of the studied area, improving the interpretation of surface morphology and offering a valuable tool for comparative analysis between different geomorphological contexts. The results of the classification were compared with the actual surface morphology based on high-resolution orthophotos, aerial photos, and field surveys.
2012
Istituto di Ricerca per la Protezione Idrogeologica - IRPI
Geomorphometry
High-resolution DTM
Surface texture
Variogram
Fuzzy clustering
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Descrizione: Surface texture analysis of a high-resolution DTM: Interpreting an alpine basin
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/223341
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