Alluvial fans are among the principal geomorphological features that have an influence on the development of human societies, particularly in arid regions. In view of the salience of these triangular-shaped deposits to environmental management, an accurate mapping of alluvial fans within a specific region could prove significantly advantageous. This study proposes a method for semi-automated detection of alluvial fans based on the analysis of Digital Elevation Models (DEMs). The proposed method is a novel Symmetry Model DEM (SMDEM), which extracts alluvial fans the pseudo-basin concept. This method is capable of accurate detection of alluvial fans and all their segmentations (i.e. lobes), apex, and toe when they are delimited by boundary drainage (lateral and toe drainage channels). The method was tested analyzing different environmental scenarios and was evaluated by comparing the output of the model with satellite data. The alluvial fans analyzed with the SMDEM model are the Lannemezan (12,303 km), Xinhe (5572 km), and Naien (1668 km) fans, which are among the largest in Europe, China, and Iran, respectively.

Semi-automated method for the mapping of alluvial fans from DEM

Norini Gianluca
2021

Abstract

Alluvial fans are among the principal geomorphological features that have an influence on the development of human societies, particularly in arid regions. In view of the salience of these triangular-shaped deposits to environmental management, an accurate mapping of alluvial fans within a specific region could prove significantly advantageous. This study proposes a method for semi-automated detection of alluvial fans based on the analysis of Digital Elevation Models (DEMs). The proposed method is a novel Symmetry Model DEM (SMDEM), which extracts alluvial fans the pseudo-basin concept. This method is capable of accurate detection of alluvial fans and all their segmentations (i.e. lobes), apex, and toe when they are delimited by boundary drainage (lateral and toe drainage channels). The method was tested analyzing different environmental scenarios and was evaluated by comparing the output of the model with satellite data. The alluvial fans analyzed with the SMDEM model are the Lannemezan (12,303 km), Xinhe (5572 km), and Naien (1668 km) fans, which are among the largest in Europe, China, and Iran, respectively.
2021
Istituto di Geologia Ambientale e Geoingegneria - IGAG
Digital alluvial fan map
Digital elevation models (DEMs)
Lannemezan, Xinhe, and Naien alluvial fans
Largest alluvial fans
Quaternary landforms
Symmetry Model DEM (SMDEM)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/446982
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