Mapping Slope Deposits Depth by Means of Cluster Analysis: A Comparative Assessment

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autorschaft

  • Tiziano Venturini
  • Emanuele Trefolini
  • Edoardo Patelli
  • Matteo Broggi
  • Giacomo Tuliani
  • Leonardo Disperati

Externe Organisationen

  • University of Siena
  • University of Pisa
  • University of Strathclyde
  • The University of Liverpool
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Details

OriginalspracheEnglisch
Seiten (von - bis)47-50
Seitenumfang4
FachzeitschriftRendiconti Online Societa Geologica Italiana
Jahrgang39
PublikationsstatusVeröffentlicht - März 2016

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.

ASJC Scopus Sachgebiete

  • Erdkunde und Planetologie (insg.)
  • Geologie

Zitieren

Mapping Slope Deposits Depth by Means of Cluster Analysis: A Comparative Assessment. / Venturini, Tiziano; Trefolini, Emanuele; Patelli, Edoardo et al.
in: Rendiconti Online Societa Geologica Italiana, Jahrgang 39, 03.2016, S. 47-50.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

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 Societa Geologica Italiana, Jg. 39, S. 47-50. https://doi.org/10.3301/rol.2016.44
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 Societa Geologica Italiana, 39, 47-50. https://doi.org/10.3301/rol.2016.44
Venturini T, Trefolini E, Patelli E, Broggi M, Tuliani G, Disperati L. Mapping Slope Deposits Depth by Means of Cluster Analysis: A Comparative Assessment. Rendiconti Online Societa Geologica Italiana. 2016 Mär;39:47-50. doi: 10.3301/rol.2016.44
Venturini, Tiziano ; Trefolini, Emanuele ; Patelli, Edoardo et al. / Mapping Slope Deposits Depth by Means of Cluster Analysis: A Comparative Assessment. in: Rendiconti Online Societa Geologica Italiana. 2016 ; Jahrgang 39. S. 47-50.
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title = "Mapping Slope Deposits Depth by Means of Cluster Analysis: A Comparative Assessment",
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.",
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author = "Tiziano Venturini and Emanuele Trefolini and Edoardo Patelli and Matteo Broggi and Giacomo Tuliani and Leonardo Disperati",
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AU - Venturini, Tiziano

AU - Trefolini, Emanuele

AU - Patelli, Edoardo

AU - Broggi, Matteo

AU - Tuliani, Giacomo

AU - Disperati, Leonardo

N1 - Publisher Copyright: © Società Geologica Italiana, Roma 2016.

PY - 2016/3

Y1 - 2016/3

N2 - 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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