nerc.ac.uk

Property attribution of 3D geological models in the Thames Gateway, London : new ways of visualising geoscientific information

Royse, Katherine; Rutter, Helen; Entwisle, David. 2009 Property attribution of 3D geological models in the Thames Gateway, London : new ways of visualising geoscientific information. Bulletin of Engineering Geology and the Environment, 68 (1). 1-16. 10.1007/s10064-008-0171-0

Before downloading, please read NORA policies.
[thumbnail of Royse_et_al2008.pdf]
Preview
Text
Royse_et_al2008.pdf

Download (1MB) | Preview

Abstract/Summary

Rapid developments in information technology and the increasing collection and digitisation of geological data by the British Geological Survey now allow geoscientists to produce meaningful 3D spatial models of the shallow subsurface in many urban areas. Using this new technology, it is possible to model and predict not only the type of rocks in the shallow subsurface, but also their engineering properties (rock strength, shrink-swell characteristics and compressibility) and hydrogeological properties (permeability, porosity, thickness of the unsaturated zone or the likelihood of perched water tables) by attribution of the 3D model with geological property data. This paper describes the hydrogeological, engineering and confidence (uncertainty) attribution of high resolution models of the Thames Gateway Development Zone (TGDZ) east of London UK and proposes a future in which site investigation sets out to test a pre-existing spatial model based on real data rather than a conceptual model.

Item Type: Publication - Article
Digital Object Identifier (DOI): 10.1007/s10064-008-0171-0
Programmes: BGS Programmes 2008 > Land use and development
ISSN: 1435-9529
Additional Information. Not used in RCUK Gateway to Research.: The original publication is available at www.springerlink.com
NORA Subject Terms: Earth Sciences
Date made live: 06 Nov 2008 14:10 +0 (UTC)
URI: https://nora.nerc.ac.uk/id/eprint/4824

Actions (login required)

View Item View Item

Document Downloads

Downloads for past 30 days

Downloads per month over past year

More statistics for this item...