In this work a comparison among slope deposits (SD) maps obtained by integrating field measurements of SD depth and cluster analysis of morphometric data has been performed. Three SD depth maps have been obtained for the same area (SA1) by using different approaches. Two maps have been achieved by implementing both the supervised and unsupervised approaches and exploiting the dataset of SD depths previously collected in a region (SA2) characterized by the same bedrock lithology, although located 35 km far from the SA1. The results have been validated against a reference map based on SD depth measurements acquired during this work within the SA1 and mapped by unsupervised clustering. The outcome of the study shows the feasibility of the methodology proposed to obtain depth maps of SD. Nevertheless the very low map accuracy suggests that relationships among main morphometric variables and slope deposits depth are not constant at regional scale, although considering areas characterized by the same bedrock lithology. Hence, maps of SD depth should be based on depth data specifically acquired within the area under study. In order to improve the exploitation of SD depth datasets outside their provenance area, further research are necessary on clustering algorithms performance as well as additional morphometric and environmental variables to be employed in spatial analysis.

Venturini, T., Trefolini, E., Patelli, E., Broggi, M., Tuliani, G., Disperati, L. (2016). Mapping slope deposits depth by means of cluster analysis: A comparative assessment. RENDICONTI ONLINE DELLA SOCIETÀ GEOLOGICA ITALIANA, 39, 47-50 [10.3301/ROL.2016.44].

Mapping slope deposits depth by means of cluster analysis: A comparative assessment

Venturini, Tiziano
Writing – Original Draft Preparation
;
Trefolini, Emanuele
Membro del Collaboration Group
;
Disperati, Leonardo
Writing – Review & Editing
2016-01-01

Abstract

In this work a comparison among slope deposits (SD) maps obtained by integrating field measurements of SD depth and cluster analysis of morphometric data has been performed. Three SD depth maps have been obtained for the same area (SA1) by using different approaches. Two maps have been achieved by implementing both the supervised and unsupervised approaches and exploiting the dataset of SD depths previously collected in a region (SA2) characterized by the same bedrock lithology, although located 35 km far from the SA1. The results have been validated against a reference map based on SD depth measurements acquired during this work within the SA1 and mapped by unsupervised clustering. The outcome of the study shows the feasibility of the methodology proposed to obtain depth maps of SD. Nevertheless the very low map accuracy suggests that relationships among main morphometric variables and slope deposits depth are not constant at regional scale, although considering areas characterized by the same bedrock lithology. Hence, maps of SD depth should be based on depth data specifically acquired within the area under study. In order to improve the exploitation of SD depth datasets outside their provenance area, further research are necessary on clustering algorithms performance as well as additional morphometric and environmental variables to be employed in spatial analysis.
2016
Venturini, T., Trefolini, E., Patelli, E., Broggi, M., Tuliani, G., Disperati, L. (2016). Mapping slope deposits depth by means of cluster analysis: A comparative assessment. RENDICONTI ONLINE DELLA SOCIETÀ GEOLOGICA ITALIANA, 39, 47-50 [10.3301/ROL.2016.44].
File in questo prodotto:
File Dimensione Formato  
12_Venturini_et_al_GIT2015_OK.pdf

non disponibili

Descrizione: Articolo principale
Tipologia: PDF editoriale
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 1.63 MB
Formato Adobe PDF
1.63 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/1039743