Scaling and multivariate analysis of medium to large landslide events: Haida Gwaii, British Columbia

Les Jagielko, Yvonne Martin () and Darren Sjogren

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2012, vol. 60, issue 2, 344 pages

Abstract: Gimbarzevsky ( 1988 ) collected an exceptional landsliding inventory for Haida Gwaii, British Columbia that included over 8,000 landsliding vectors covering an area of approximately 10,000 km 2 . This database was never published in the referred literature, despite its regional significance. It was collected prior to widespread application of GIS technologies in landsliding studies, limiting the analyses undertaken at the time. Gimbarzevsky identified landslides using 1:50,000 aerial photographs, and transferred the information to NTS map sheets. In our study, we digitized the landslide vectors from these original map sheets and connected each landslide to a digital elevation model. Lengths of landslide vectors are compared to the landsliding inventory for Haida Gwaii analyzed in Rood ( 1984 ), Martin Y et al. BC Can J Earth Sci 39:289–305 ( 2002 ); the latter inventory is based on larger-scale aerial photographs (~1:12,000). Rood’s database contains a more complete record of smaller landslides, while the inventory of Gimbarzevsky provides improved statistical representation of less frequent, medium to large landslides. It is suggested that combined landslide delineation at different scales could provide a more complete landslide record. Discriminant analysis was undertaken to assess which of nine predictor variables, chosen on the basis of mechanical theory, best predict failed versus unfailed locations. Seven of the nine variables were found to be statistically significant in discriminating amongst failed and unfailed locations. Results show that 81.7% of original grouped cases were correctly classified. Copyright Springer Science+Business Media B.V. 2012

Keywords: Landsliding inventory; Scale; Discriminant function analysis; Grouping variable; Predictor variable (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1007/s11069-011-0012-5 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:60:y:2012:i:2:p:321-344

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-011-0012-5

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().