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

Tiziano Venturini (a,b), Emanuele Trefolini (a,b), Edoardo Patelli (c), Matteo Broggi (c), Giacomo Tuliani (a) & Leonardo Disperati (a,d)
(a) Università degli Studi di Siena, Dipartimento di Scienze Fisiche, della Terra e dell'Ambiente, Siena (IT) (b) Università di Pisa, Dipartimento di Scienze della Terra, Pisa (IT) (c) Institute for Risk and Uncertainty, School of Engineering, University of Liverpool (EN) (d) Istituto di Geoscienze e Georisorse (IGG-CNR) (IT)

DOI:         Pages: 47-50


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.


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