Property Subsidence Assessment dataset 2023_3

The BGS PSA dataset provides insurers and homeowners access to a better understanding of the shrink-swell hazard at both the individual property and/or postcode level for Great Britain. It builds upon the GeoSure shrink-swell data by mapping the hazard to the individual building polygon and considering the other susceptibility factors of building type, foundation depth, and drainage and tree proximity. The user receives GIS building polygons with an overall susceptibility to subsidence score between 1-100. Scores are also classified from non-plastic to very high. Each building polygon is also scored from 1-10 for each subsidence factor (geology, foundation, drainage, building type, building storey and tree proximity). Postcode data is also available as a table and shapefiles showing the ‘average’ PSA score for all buildings within the postcode. The identification of shrink-swell related subsidence prone areas, alongside the inclusion of potential sources to exacerbate this phenomena, can better inform insurers and homeowners and form the basis to make decisions concerning prevention and remediation. The product enhances geological information obtained from GIP and GeoSure via the inclusion of the crucial shrink-swell susceptibility factors (proximity to trees and foundation depth). This therefore allows the derivation of a risk element for the housing stock at Building level, which is then generalised to Postcode level.

Date (Creation): 2023-10

Citation identifier: http://data.bgs.ac.uk/id/dataHolding/13608318

Point of contact

Organisation name	Individual name	Electronic mail address	Role
British Geological Survey	Enquiries	enquiries@bgs.ac.uk	Distributor
British Geological Survey	Enquiries	enquiries@bgs.ac.uk	Point of contact
British Geological Survey	Enquiries	not available	Distributor
British Geological Survey	Enquiries	not available	Point of contact

Maintenance and update frequency: Unknown

GEMET - INSPIRE themes, version 1.0

Geology

BGS Thesaurus of Geosciences

BGS Data Products
Citable Data
UK Location (INSPIRE)

dataCentre

Keywords

NERC_DDC

Access constraints: Other restrictions

Other constraints: license

Other constraints: Either : (i) the dataset has not been formally approved by BGS for access and use by external clients under license; and / or (ii) the dataset contains 3rd party data or information obtained by BGS under terms and conditions that must be consulted before the dataset can be provided to, or accessed by, BGS staff or external clients. Refer to the BGS staff member responsible for the creation of the dataset if further advice is required. He / she should be familiar with the composition of the dataset, particularly with regard to 3rd party IPR contained in it, and any resultant access restrictions. This staff member should revert to the IPR Section (IPR@bgs.ac.uk) for advice, should the position not be clear.

Use constraints: Other restrictions

Other constraints: The copyright of materials derived from the British Geological Survey's work is vested in the Natural Environment Research Council [NERC]. No part of this work may be reproduced or transmitted in any form or by any means, or stored in a retrieval system of any nature, without the prior permission of the copyright holder, via the BGS Intellectual Property Rights Manager. Use by customers of information provided by the BGS, is at the customer's own risk. In view of the disparate sources of information at BGS's disposal, including such material donated to BGS, that BGS accepts in good faith as being accurate, the Natural Environment Research Council (NERC) gives no warranty, expressed or implied, as to the quality or accuracy of the information supplied, or to the information's suitability for any use. NERC/BGS accepts no liability whatever in respect of loss, damage, injury or other occurence however caused.

Other constraints: The dataset is made available to external clients under BGS Digital Data Licence terms and conditions. Revert to the IPR Section ( iprdigital@bgs.ac.uk) if further advice is required with regard to permitted usage.

Spatial representation type: Vector

Language: English

Topic category

Geoscientific information

Geographic identifier: GBN
ISO 3166_2 2009 revision

Geographic identifier: GREAT BRITAIN [id=139600]
British Geological Survey Gazetteer: Geographical hierarchy from Geosaurus 1979 creation

Begin date: 2011

End date: 2023

Unique resource identifier: OSGB 1936 / British National Grid (EPSG::27700)

Distribution format

Name	Version
ESRI shapefile
txt

Distributor contact

Organisation name	Individual name	Electronic mail address	Role
British Geological Survey	Enquiries	enquiries@bgs.ac.uk	Distributor

Distributor contact

Organisation name	Individual name	Electronic mail address	Role
British Geological Survey	Enquiries	not available	Distributor

OnLine resource

Protocol	Linkage	Name
	https://www.bgs.ac.uk/datasets/property-subsidence-assessment/	Data

OnLine resource

Protocol	Linkage	Name
	https://doi.org/10.5285/66240217-3b3b-48cb-a643-f232514096ef	Digital Object Identifier (DOI)

Hierarchy level: Dataset

Other: dataset

Conformance result

Title: INSPIRE Implementing rules laying down technical arrangements for the interoperability and harmonisation of Geology

Date (Publication): 2011

Explanation: See the referenced specification

Pass: No

Conformance result

Title: Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services

Date (Publication): 2010-12-08

Explanation: See http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2010:323:0011:0102:EN:PDF

Pass: No

Statement: Input data: OS OpenMap Local building polygons GeoSure shrink-swell National Tree Map (Bluesky) Office for National Statistics (UK property build period) Office for National Statistics (UK property type) OS Code Point open OS Codepoint with polygons Process: GeoSure and the other input datasets are mapped to the OS Open building polygons. Each building is then scored for each input factor. Input factors are then combined via a weighted algorithm to derive the PSA score for each building, this score is then classified into the PSA classes. Building polygon scores are aggregated to produce the postcode score. Processing was carried out using series of python scripts using Visual Studio Code and all the processed files are tested in ArcGIS Pro for all required BGS standard checks.