Citation Information - Digital Object Identifier (DOI)
type: Distribution
access URL: https://doi.org/10.5285/ac452027-8bae-424c-94cc-3a6f5a88c842
description: British Geological Survey. (2023). Property Subsidence Assessment dataset 2023. British Geological Survey. (Dataset). https://doi.org/10.5285/ac452027-8bae-424c-94cc-3a6f5a88c842
issued: 2026-08-28T06:01:10.603532
modified: 2026-08-28T06:01:10.559341

BGS Datasets - Property subsidence assessment
type: Distribution
access URL: https://www.bgs.ac.uk/datasets/property-subsidence-assessment/
description: Resource page for dataset with contact and licensing details.
issued: 2026-08-28T06:01:10.603530
modified: 2026-08-28T06:01:10.559254

British Geological Survey (BGS)
type: Organization

Property Subsidence Assessment dataset 2023
type: Dataset
keyword: Subsidence
keyword: Property damage
keyword: NERC_DDC
keyword: Foundations
description: 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 England and Wales. 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 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.
issued: 2026-07-16T17:14:47.246654
modified: 2026-08-28T06:01:10.540239
spatial: Location
  geometry: {"type": "Polygon", "coordinates": [[[2.0000, 49.9000], [-5.8000, 49.9000], [-5.8000, 55.8000], [2.0000, 55.8000], [2.0000, 49.9000]]]}