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Enriching Great Britain's National Landslide Database by searching newspaper archives

Taylor, Faith E.; Malamud, Bruce D.; Freeborough, Katy; Demeritt, David. 2015 Enriching Great Britain's National Landslide Database by searching newspaper archives. Geomorphology, 249. 52-68. 10.1016/j.geomorph.2015.05.019

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Abstract/Summary

Our understanding of where landslide hazard and impact will be greatest is largely based on our knowledge of past events. Here, we present a method to supplement existing records of landslides in Great Britain by searching an electronic archive of regional newspapers. In Great Britain, the British Geological Survey (BGS) is responsible for updating and maintaining records of landslide events and their impacts in the National Landslide Database (NLD). The NLD contains records of more than 16,500 landslide events in Great Britain. Data sources for the NLD include field surveys, academic articles, grey literature, news, public reports and, since 2012, social media. We aim to supplement the richness of the NLD by (i) identifying additional landslide events, (ii) acting as an additional source of confirmation of events existing in the NLD and (iii) adding more detail to existing database entries. This is done by systematically searching the Nexis UK digital archive of 568 regional newspapers published in the UK. In this paper, we construct a robust Boolean search criterion by experimenting with landslide terminology for four training periods. We then apply this search to all articles published in 2006 and 2012. This resulted in the addition of 111 records of landslide events to the NLD over the 2 years investigated (2006 and 2012). We also find that we were able to obtain information about landslide impact for 60–90% of landslide events identified from newspaper articles. Spatial and temporal patterns of additional landslides identified from newspaper articles are broadly in line with those existing in the NLD, confirming that the NLD is a representative sample of landsliding in Great Britain. This method could now be applied to more time periods and/or other hazards to add richness to databases and thus improve our ability to forecast future events based on records of past events.

Item Type: Publication - Article
Digital Object Identifier (DOI): 10.1016/j.geomorph.2015.05.019
ISSN: 0169555X
Date made live: 23 Feb 2016 10:17 +0 (UTC)
URI: http://nora.nerc.ac.uk/id/eprint/513054

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