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A data driven approach to landslide susceptibility mapping in Great Britain

Williams, C.; Bee, E.; Dashwood, C.; Marchant, B.. 2018 A data driven approach to landslide susceptibility mapping in Great Britain. [Poster] In: EGU General Assembly 2018, Vienna, Austria, 8-13 April 2018. British Geological Survey. (Unpublished)

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Abstract/Summary

Landslides are a geo-hazard which can have significant societal impacts including loss of human life, physical damage to infrastructure and financial loss. The ability to assess where landslides will occur is therefore of great interest for the public good and can be approached both theoretically and empirically. With the ever increasing availability of spatial data, information on landslide events is now much more readily available ranging from initiation point coordinates to high (sub-metre) resolution topographic information and associated derivatives on affected (and unaffected) areas. Coupled with information on the geology of a region, it is possible to build up a detailed location specific profile of past events, all of which may prove useful for informing where future events may occur. We present preliminary results from an assessment of various data to reassess current British landslide susceptibility datasets. These could be used in future to provide additional information to support landslide forecasting. We define susceptibility as: The potential for the occurrence of a hazard within a specified area. This is currently provided for by the BGS GeoSure Landslides product [1] which classifies landslide prone areas on an A-E (low-high) basis, based on heuristics as well as consideration of lithology, discontinuities and slope angle. Data-driven analyses may provide further insights into where and why landslides occur. Using this knowledge, we hope to improve our current landslide susceptibility model. Consequently, this will enable us to be more confident in the identification of areas where landslides may occur in the future.

Item Type: Publication - Conference Item (Poster)
Date made live: 25 May 2018 14:05 +0 (UTC)
URI: http://nora.nerc.ac.uk/id/eprint/520164

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