In this work, we tested the reliability of two different methods of automated landform classification (ACL) in three geological domains of the southern Italian chain with contrasting morphological features. ACL maps deriving from the TPI-based (topographic position index) algorithm are strictly dependent to the search input parameters and they are not able to fully capture landforms of different size. Geomorphons-based classification has shown a higher potential and can represent a powerful method of ACL, although it should be improved with the introduction of additional DEM-based parameters for the extraction of landform classes
Comparison of Different Methods of Automated Landform Classification at the Drainage Basin Scale: Examples from the Southern Italy
Maria Danese;Mario Bentivenga;Eva Pescatore;Salvatore Ivo GianoProject Administration
2020-01-01
Abstract
In this work, we tested the reliability of two different methods of automated landform classification (ACL) in three geological domains of the southern Italian chain with contrasting morphological features. ACL maps deriving from the TPI-based (topographic position index) algorithm are strictly dependent to the search input parameters and they are not able to fully capture landforms of different size. Geomorphons-based classification has shown a higher potential and can represent a powerful method of ACL, although it should be improved with the introduction of additional DEM-based parameters for the extraction of landform classesFile | Dimensione | Formato | |
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