Vertical land motion (VLM), angular distortion, and building risks for 28 urban cities in the United States. The file also contains supplementary tables 1 to 8.Abstract: Land subsidence is a slow-moving hazard with adverse environmental and socioeconomic consequences worldwide. However, spatially dense subsidence rates to capture granular variations at high spatial density are often lacking, hindering assessment of associated infrastructure risk. We use space geodetic measurements from 2015 to 2021 to create high resolution maps of subsidence rates for 28 most populous US cities. We estimate that at least 20% of the urban area is sinking in all cities, mainly due to groundwater extraction, affecting ~34 million people. Additionally, more than 29,000 buildings are located in high and very high damage risk areas, indicating a greater likelihood of infrastructure damage. These datasets and information are crucial for developing ad hoc policies to adapt urban centers to these complex environmental challenges.

The property subsidence assessment dataset provides an understanding of the shrink-swell hazard at both the individual property and/or postcode level for England and Wales. It builds upon the BGS 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 data consist of 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 these 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 (BGS GeoSure Insurance Product) 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. BGS GeoSure - a series of GIS digital maps identifying areas of potential natural ground movement hazard in Great Britain

The 5km Hex GS Collapsible Deposits dataset shows a generalised view of the GeoSure Collapsible Deposits v7 dataset to a hexagonal grid resolution of 64.95km coverage area (side length of 5km). This dataset indicates areas of potential ground movement in a helpful and user-friendly format. The rating is based on a highest level of susceptibility identified within that Hex area: Low (1), Moderate (2), Significant (3). Areas of localised significant rating are also indicated. The summarising process via spatial statistics at this scale may lead to under or over estimation of the extent of a hazard. The supporting GeoSure reports can help inform planning decisions and indicate causes of subsidence. The reports can help inform planning decisions and indicate causes of subsidence. The Collapsible Ground dataset provides an assessment of the potential for a geological deposit to collapse (to subside rapidly) as a consequence of a metastable microfabric in loessic material. Such metastable material is prone to collapse when it is loaded (as by construction of a building, for example) and then saturated by water (as by rising groundwater, for example). Collapse may cause damage to overlying property. The methodology is based on the BGS Digital Map (DiGMapGB-50) and expert knowledge of the origin and behaviour of the formations so defined. It provides complete coverage of Great Britain, subject to revision in line with changes in DiGMapGB lithology codes and methodological improvements.

Waikato District Council - Proposed District Plan (Stage 2 Natural Hazards), Notified 27 July 2020. This layer is a spatial representation of an overlay in the Proposed District Plan and indicates where land use will be regulated by various associated rules. It will be used as a guide in the regulatory process of implementing the Proposed District Plan and managing land use, subdivision, the environment and economy. This dataset is subject to changes undertaken through the Resource Management act. Note individual Proposed Plan rules can have different statuses, some may have current legal effect and others will not until the Proposed Plan becomes operative. This data is provided for use in the District Plan only.

The Mine Subsidence Risk Area identifies land in Huntly East that is currently at risk of subsidence due to historic underground coal mining activities and the subsequent closure and refilling of the Huntly East underground mine. An assessment has been carried out to confirm the likelihood of ongoing mine subsidence and methane gas migration from mine workings to the ground surface above the Huntly East mine and the South Headings as a result of the closure of the Huntly East Mine and subsequent flooding of the underground mine workings (see Appendix 5(c) of Section 32 report Natural Hazards and Climate Change). This belongs to the series of data relating to Natural Hazards which includes the following groups - coastal erosion, coastal inundation, inland flooding, and land subsidence. This layer belongs to the land subsidence group (this is the only layer in this group).

For the Semarang area generally two types of floods are typical and have to be taken into account accordingly: a. Tidal floods in coastal areas due to land subsidence Rates ranging from 1 to 17 cm/year. These results are confirmed by the recent InSAR subsidence calculation based on Sentinel 1 Radar Data performed by JR within the frame of this project. b. Short-term local floods and river floods after heavy thunderstorms. The present Geodatabase includes 12 stages of coastal water extent between 1995 and 2017 to demonstrate the increase of flooded areas.

The newGeoSure Insurance Product (newGIP) provides the potential insurance risk due to natural ground movement. It incorporates the combined effects of the 6 GeoSure hazards on (low-rise) buildings: landslides, shrink-swell clays, soluble rocks, running sands, compressible ground, and collapsible deposits. These hazards are evaluated using a series of processes including statistical analyses and expert elicitation techniques to create a derived product that can be used for insurance purposes such as identifying and estimating risk and susceptibility. The evaluated hazards are then linked to a postcode database - the Derived Postcode Database (DPD), which is updated biannually with new releases of Ordnance Survey Code-Point® data (current version used: 2024.3). The newGIP is provided for national coverage across Great Britain (not including the Isle of Man). This product is available in a range of GIS formats including Access (.dbf), ArcGIS (.shp) or MapInfo (*.tab) on request. The newGIP is produced for use at 1:50 000 scale providing 50 m ground resolution.

This feature class describes areas infeasible for infiltration due to the presence of Coal Mine Subsidence Zones. This data was obtained by AESI from the City of Bellevue FTP site on March 24, 2015. AESI excluded Coal Mine Subsidence Zone 1 areas, and clipped Coal Mine Subsidence Zone 2 areas to within the City of Bellevue.This feature class is part of Appendix C, GIS Files and Documentation, of the Infiltration Infeasibility Analysis and Technical Report, prepared for the City of Bellevue Utilities Department by Associated Earth Sciences, Inc, April 4, 2016.

The hazards causing the risk are contained in hazard documents which are included in the presentation report and annexed to R111-3 cavities. These documents are used to map the different intensity levels of each hazard taken into account this R111-3. Each area exposed to one or more cavity hazards existing in this spatial dataset is linked with its GASPAR code: 51DDT20090009.

Genealogy: The so-called geotechnical risk pre-zoning hazards are developed from the overlay of all the hazards of the various subsidence-fall risks of underground cavity based on hazard data and risk probability established by the BRGM. Each of the geographic areas of R111-3 subjected to one or more hazards can then be extracted by overlaying zone. Each exposed area, possibly recouped, is then described by a record in this resource.

This Data Set (JDD) is part of a data set that describes land use constraints related to anthropogenic risks, including, for each constraint, the government services or communities to be consulted. The initial target corresponds to those involved in the management of urban planning who wish to know these constraints in a given area of the Greater East region.

The JDD “Knowledge Mining Risks” represents the municipalities or areas in which constraints induced by mining risks are present and meet the following criteria: • The risks and associated constraints are known to DREAL but have not yet been brought to the attention of the mayors of the municipalities concerned, OR these risks and the associated constraints are being acquired/study by DREAL • DREAL wishes to be consulted in the event of a project likely to be impacted by these constraints

In Lorraine, for some of these constraints, the precision of this JDD is the perimeter of the constraint. Otherwise, for the whole of the Grand-Est region, precision is the commune.

This dataset specifies: • The department • The name of the municipality • The insee number of the municipality • Information enabling the site to be identified • Types of SDAs and projects affected by public utility easements • The service of the State concerned • The approach to obtain further information • Description of the perimeter of the constraints • Regulatory sources of the scope of constraints • Data sources • The scale of the data • The internal contact SPRA • The date of the initial state of play • Layer Update Dates

The objective of the layer is to identify the constraints induced by known mining risks, to make available the information described above, and in particular to direct any consultations to the relevant interlocutor who is DREAL.

The data is intended for all persons who may consult the UDs and the SPRA on subjects related to anthropogenic risks, including the local authorities’ teaching services, the other departments of DREAL and the State, the notaries.

Contact point: The agent of the Anthropic Risk Prevention Service (SPRA) in charge of operational planning.

Name of the GIS layer: MU_MINE_EN_COURS_DREAL_R44

This dataset represents ground subsidence potential at a scale of 1:24,000.

Bandung is the capital of the West Java province of Indonesia. The larger metropolitan area of Bandung has a population of more than 8 million people, and a strong exposure to a variety of geohazards. Satellite SAR data provide information on ground deformation, needed to monitor and model the various sources of these hazards and to perform multi-hazard risk analysis.

We show the results of an ALOS-1 and COSMO-SkyMed SAR data investigation over the Bandung metropolitan area retrieved by means of InSAR multi temporal technique aimed mainly at mapping urban subsidence.

This relates to land located above shallow underground mines in the Huntly East area where subsidence occurred in around 1977 and where there is still an unconfirmed risk of further subsidence. The boundaries were defined by Coalcorp and the Department of Survey and Land Information and at the time had identified an area of limited risk and an area of higher risk. The area of high risk was derived from the Crown’s Huntly East Land Subsidence Policy 1993–94. The high risk and limited risk areas were combined as one layer in the 2004 DPR. Areas have been identified in Subsidence reports and in accordance with mining activity.

The Waikato District Council District Plan is has been produced under the Resource Management Act 1991, and has been distributed to allow better public access to the data underlying the Plan. While you are free to crop, export and repurpose the data, we ask that you attribute the Waikato District Council, link to this page, and clearly state that your work is a derivative and not the authoritative data source. Please include this statement when distributing any work derived from this data:

This work is a derivative of Policy Series, part of the Waikato District Council District Plan. You can find the full District Plan at Waikato District E-Plan (https://www.waikatodistrict.govt.nz/your-council/plans-policies-and-bylaws/plans/district-plan)

A large-scale subsidence takes place in the Bad Reichenhall basin (Starzmann 1979:114). This subsidence area was demarcated on the basis of the site plan contained in this publication and on the basis of the geological and tectonic conditions. Since the leveling cited does not cover the entire Reichenhall Basin, the possible subsidence area has been extended to the valley areas potentially affected by subsidence, in part with a safety margin. For a customary local development, the subsidence there is usually irrelevant. Only in the case of large and sensitive structures, damage due to differences in settlement cannot be ruled out. Subsoil and foundation reports have to take this special problem into account if necessary. Large-scale subsidence is also known from the area around the Grögern Weiher in Bayerisch Gmain. The demarcation of this area was based on the files at the LfU. The documents available to the LfU do not fully cover the subsidence area. A demarcation, especially to the south-west, is therefore only provisional. An even further extension of the subsidence area is possible, but there are no concrete indications of this. In any case, in the Grögern Weiher subsidence area, the preparation of subsoil and foundation reports that take this problem into account is recommended. Further information on the interpretation and the procedure for creating the hazard index map can be found in the reports on the hazard index maps: https://www.lfu.bayern.de/geologie/massebewegungen_karten_daten/ dangers index cards/index.htm

This dataset contains the result of risk analyzes about the vulnerability of national monuments to various topics related to climate change. The national monuments are superimposed on (raster) map layers and the relevant risk classes are given. The topics covered are: - Flood risk: risk of flood damage to national monuments outside the dykes. - Land subsidence: risk of subsidence of national monuments. - Drought and salinization: - Risk of drought of green/blue heritage based on the average lowest groundwater level in 2050. - Risk of salinization of green/blue heritage based on brackish groundwater height. - Flooding due to heavy precipitation: risk of flooding after short-term heavy precipitation of more than 140mm. Vulnerability classes have been determined for each subject, assessed on the basis of the values ​​provided by the (raster) map layers. The data has been processed in a viewer.

Soil map units are the basic geographic unit of the Soil Survey Geographic Database (SSURGO). The SSURGO dataset is a compilation of soils information collected over the last century by the Natural Resources Conservation Service (NRCS). Map units delineate the extent of different soils. Data for each map unit contains descriptions of the soil’s components, productivity, unique properties, and suitability interpretations.Each soil type has a unique combination of physical, chemical, nutrient and moisture properties. Soil type has ramifications for engineering and construction activities, natural hazards such as landslides, agricultural productivity, the distribution of native plant and animal life and hydrologic and other physical processes. Soil types in the context of climate and terrain can be used as a general indicator of engineering constraints, agriculture suitability, biological productivity and the natural distribution of plants and animals.Dataset SummaryPhenomenon Mapped: Soils of the United States and associated territoriesCoordinate System: Web Mercator Auxiliary SphereExtent: The 50 United States, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaVisible Scale: 1:144,000 to 1:1,000Resolution/Tolerance: 1 meter/2 metersNumber of Features: 36,543,233Feature Request Limit: 10,000Source: USDA Natural Resources Conservation ServicePublication Date: October 1, 2019ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/rest/servicesData from the gNATSGO database was used to create the layer for the contiguous United States, Alaska, Puerto Rico, and the U.S. Virgin Islands. The remaining areas were created with the gSSURGO database (Hawaii, Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa).AttributesKey fields from nine commonly used SSURGO tables were compiled to create the 173 attribute fields in this layer. Some fields were joined directly to the SSURGO Map Unit polygon feature class while others required summarization and other processing to create a 1:1 relationship between the attributes and polygons prior to joining the tables. Attributes of this layer are listed below in their order of occurrence in the attribute table and are organized by the SSURGO table they originated from and the processing methods used on them.Map Unit Polygon Feature Class Attribute TableThe fields in this table are from the attribute table of the Map Unit polygon feature class which provides the geographic extent of the map units.Area SymbolSpatial VersionMap Unit SymbolMap Unit TableThe fields in this table have a 1:1 relationship with the map unit polygons and were joined to the table using the Map Unit Key field.Map Unit NameMap Unit KindFarmland ClassInterpretive FocusIntensity of MappingIowa Corn Suitability RatingLegend TableThis table has 1:1 relationship with the Map Unit table and was joined using the Legend Key field.Project ScaleSurvey Area Catalog TableThe fields in this table have a 1:1 relationship with the polygons and were joined to the Map Unit table using the Survey Area Catalog Key and Legend Key fields.Survey Area VersionTabular VersionMap Unit Aggregated Attribute TableThe fields in this table have a 1:1 relationship with the map unit polygons and were joined to the Map Unit attribute table using the Map Unit Key field.Slope Gradient - Dominant ComponentSlope Gradient - Weighted AverageBedrock Depth - MinimumWater Table Depth - Annual MinimumWater Table Depth - April to June MinimumFlooding Frequency - Dominant ConditionFlooding Frequency - MaximumPonding Frequency - PresenceAvailable Water Storage 0-25 cm - Weighted AverageAvailable Water Storage 0-50 cm - Weighted AverageAvailable Water Storage 0-100 cm - Weighted AverageAvailable Water Storage 0-150 cm - Weighted AverageDrainage Class - Dominant ConditionDrainage Class - WettestHydrologic Group - Dominant ConditionIrrigated Capability Class - Dominant ConditionIrrigated Capability Class - Proportion of Mapunit with Dominant ConditionNon-Irrigated Capability Class - Dominant ConditionNon-Irrigated Capability Class - Proportion of Mapunit with Dominant ConditionRating for Buildings without Basements - Dominant ConditionRating for Buildings with Basements - Dominant ConditionRating for Buildings with Basements - Least LimitingRating for Buildings with Basements - Most LimitingRating for Septic Tank Absorption Fields - Dominant ConditionRating for Septic Tank Absorption Fields - Least LimitingRating for Septic Tank Absorption Fields - Most LimitingRating for Sewage Lagoons - Dominant ConditionRating for Sewage Lagoons - Dominant ComponentRating for Roads and Streets - Dominant ConditionRating for Sand Source - Dominant ConditionRating for Sand Source - Most ProbableRating for Paths and Trails - Dominant ConditionRating for Paths and Trails - Weighted AverageErosion Hazard of Forest Roads and Trails - Dominant ComponentHydric Classification - PresenceRating for Manure and Food Processing Waste - Weighted AverageComponent Table – Dominant ComponentMap units have one or more components. To create a 1:1 join component data must be summarized by map unit. For these fields a custom script was used to select the component with the highest value for the Component Percentage Representative Value field (comppct_r). Ties were broken with the Slope Representative Value field (slope_r). Components with lower average slope were selected as dominant. If both soil order and slope were tied, the first value in the table was selected.Component Percentage - Low ValueComponent Percentage - Representative ValueComponent Percentage - High ValueComponent NameComponent KindOther Criteria Used to Identify ComponentsCriteria Used to Identify Components at the Local LevelRunoff ClassSoil loss tolerance factorWind Erodibility IndexWind Erodibility GroupErosion ClassEarth Cover 1Earth Cover 2Hydric ConditionHydric RatingAspect Range - Counter Clockwise LimitAspect - Representative ValueAspect Range - Clockwise LimitGeomorphic DescriptionNon-Irrigated Capability SubclassNon-Irrigated Unit Capability ClassIrrigated Capability SubclassIrrigated Unit Capability ClassConservation Tree Shrub GroupGrain Wildlife HabitatGrass Wildlife HabitatHerbaceous Wildlife HabitatShrub Wildlife HabitatConifer Wildlife HabitatHardwood Wildlife HabitatWetland Wildlife HabitatShallow Water Wildlife HabitatRangeland Wildlife HabitatOpenland Wildlife HabitatWoodland Wildlife HabitatWetland Wildlife HabitatSoil Slip PotentialSusceptibility to Frost HeavingConcrete CorrosionSteel CorrosionTaxonomic ClassTaxonomic OrderTaxonomic SuborderGreat GroupSubgroupParticle SizeParticle Size ModCation Exchange Activity ClassCarbonate ReactionTemperature ClassMoist SubclassSoil Temperature RegimeEdition of Keys to Soil Taxonomy Used to Classify SoilCalifornia Storie IndexComponent KeyComponent Table – Weighted AverageMap units may have one or more soil components. To create a 1:1 join, data from the Component table must be summarized by map unit. For these fields a custom script was used to calculate an average value for each map unit weighted by the Component Percentage Representative Value field (comppct_r).Slope Gradient - Low ValueSlope Gradient - Representative ValueSlope Gradient - High ValueSlope Length USLE - Low ValueSlope Length USLE - Representative ValueSlope Length USLE - High ValueElevation - Low ValueElevation - Representative ValueElevation - High ValueAlbedo - Low ValueAlbedo - Representative ValueAlbedo - High ValueMean Annual Air Temperature - Low ValueMean Annual Air Temperature - Representative ValueMean Annual Air Temperature - High ValueMean Annual Precipitation - Low ValueMean Annual Precipitation - Representative ValueMean Annual Precipitation - High ValueRelative Effective Annual Precipitation - Low ValueRelative Effective Annual Precipitation - Representative ValueRelative Effective Annual Precipitation - High ValueDays between Last and First Frost - Low ValueDays between Last and First Frost - Representative ValueDays between Last and First Frost - High ValueRange Forage Annual Potential Production - Low ValueRange Forage Annual Potential Production - Representative ValueRange Forage Annual Potential Production - High ValueInitial Subsidence - Low ValueInitial Subsidence - Representative ValueInitial Subsidence - High ValueTotal Subsidence - Low ValueTotal Subsidence - Representative ValueTotal Subsidence - High ValueCrop Productivity IndexEsri SymbologyThis field was created to provide symbology based on the Taxonomic Order field (taxorder). Because some mapunits have a null value for soil order, a custom script was used to populate this field using the Component Name (compname) and Mapunit Name (muname) fields. This field was created using the dominant soil order of each mapunit.Esri SymbologyHorizon TableEach map unit polygon has one or more components and each component has one or more layers known as horizons. To incorporate this field from the Horizon table into the attributes for this layer, a custom script was used to first calculate the mean value weighted by thickness of the horizon for each component and then a mean value of components weighted by the Component Percentage Representative Value field for each map unit. K-Factor Rock FreeEsri Soil OrderThese fields were calculated from the Component table using a model that included the Pivot Table Tool, the Summarize Tool and a custom script. The first 11 fields provide the sum of Component Percentage Representative Value for each soil order for each map unit. The Soil Order Dominant Condition field was calculated by selecting the highest value in the preceding 11 soil order fields. In the case of tied values the component with the lowest average slope value (slope_r) was selected. If both soil order and slope

Activation date: 2021-04-30
Event type: Mass movement

Activation reason:
The service was activated by a request from the Federal Office of Civil Protection and Disaster Assistance (BBK) on behalf of Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) – authorized user, and the University of Philippines – local user. Several sources suggest that the Manila NCR and lower Pampanga river basin, Philippines, has been affected by ground subsidence phenomena impacting settlements and increasing flood risk.The EMS service aims to provide evidence of ground motion patterns in the targeted areas using multi-temporal satellite SAR data analysis – by persistent scatterers interferometry. Product derived from time series of Sentinel-1 imagery provides insight into localization and extent of sinking zones and severity of phenomena related to estimated motion velocity or different adversary patterns.The ground motion map shows average annual vertical and horizontal ground motion velocities. Furthermore, the vector product provides value-adding features such as temporally coherent targets, comparing annual motion trends and classification of motion dynamics such as motion acceleration.

This file contains 1424 household responses to two scales. First, the demographic scale results for the Solotvyno household survey. The demographic household survey contained the following variables:1) Age; 2)Sex; 3) Family type; 4) Religion; 5) Ethnic Origin; 6) Education; 7) Housing; 8) Annual income (in USD); 9) Years of stay; 10) Housing Type; 11) Living Situation and 12) disability.

Second, the results from the Solotvyno Municipality Risk Evaluation scale. Risk assessment and ranking is part of WP1 work, however, the task of WP3 is to conduct an evaluation of the risk assessment and incorporate the community values.Based on the community values and the evidence gathered under WP1, the risk rating matrix can be colour-coded to visualise risk rankings and designate the high, medium and low-risk zones. This would enable the Solotvyno community at-a-glance to view which risks require to be prioritised. In addition, there is geo-referenced data collected on the street where the communities reside to map the community exposure to the land subsidence risk.

This dataset is the Derived Postcode Database issued as part of the GeoSure Insurance V7 incorporating postcode data from OS Code-Point Open version 2016.1. The GeoSure Insurance Product (including the Derived Postcode Database) represents the end of an interpretation process, starting with the BGS Digital Geological Map of Great Britain at the 1:50,000 scale (DiGMapGB-50). This digital map is the definitive record of the types of rocks underlying Great Britain (excluding the Isle of Man), as represented by various layers, starting with Bedrock and moving up to overlying Superficial layers. In 2003, the BGS also published a series of GIS digital maps identifying areas of potential natural ground movement hazard in Great Britain, called GeoSure. There are six separate hazards considered - shrink-swell clays, slope instability, dissolution of soluble ground, running sand, compressible and collapsible deposits. These maps were derived by combining the rock-type information from DiGMapGB-50 with a series of other influencing factors which may cause the geological hazards (e.g. steep slopes, groundwater). In 2005, the BGS used the GeoSure maps to make an interpretation of subsidence insurance risk for Great Britain property insurance industry, released as the new GeoSure Insurance Product. This represents the combined effects of the 6 GeoSure hazards on (low-rise) buildings in a postcode database - the Derived Postcode Database, which can be accompanied by GIS maps showing the most significant hazard areas. The combined hazard is represented numerically in the Derived Postcode Database as the Total Hazard Score, with a breakdown into the component hazards. The GeoSure Derived Postcode Database (DPD) is a stand-alone database, which can be provided separately to the full GeoSure Insurance Product V7. The methodology behind the DPD involves balancing the 6 GeoSure natural ground stability hazards against each other. The GeoSure maps themselves have a fivefold coding (A to E), and the balancing exercise involves comparing each level across the six hazards e.g. comparing a level C shrink-swell clay area with a level C running sand area. The comparison is done by a process involving expert analysis and statistical interpretations to estimate the potential damage to a property (specifically low-rise buildings only). Each level of each of the hazards is given a 'hazard score' which can then be added together to derive a Total Hazard Score at a particular location (e.g. within a given postcode).

The dataset contains Interferometric Synthetic Aperture Radar (InSAR)-derived Vertical Land Motion (VLM) measurements and building damage risk maps for five rapidly growing Indian megacities: New Delhi, Mumbai, Bengaluru, Chennai, and Kolkata. Researchers can visualize and extract values, including latitude and longitude information, using ArcGIS, QGIS, or any programming language that supports the ESRI shapefile format.

The 5km Hex GS Shrink Swell dataset shows a generalised view of the GeoSure Shrink Swell v8 dataset to a hexagonal grid resolution of 64.95km coverage area (side length of 5km). This dataset indicates areas of potential ground movement in a helpful and user-friendly format. The rating is based on a highest level of susceptibility identified within that Hex area: Low (1), Moderate (2), Significant (3). Areas of localised significant rating are also indicated. The summarising process via spatial statistics at this scale may lead to under or over estimation of the extent of a hazard. The supporting GeoSure reports can help inform planning decisions and indicate causes of subsidence. The Shrink Swell methodology is based on the BGS Digital Map (DiGMapGB-50) and expert knowledge of the behaviour of the formations so defined. This dataset provides an assessment of the potential for a geological deposit to shrink and swell. Many soils contain clay minerals that absorb water when wet (making them swell), and lose water as they dry (making them shrink). This shrink-swell behaviour is controlled by the type and amount of clay in the soil, and by seasonal changes in the soil moisture content (related to rainfall and local drainage). The rock formations most susceptible to shrink-swell behaviour are found mainly in the south-east of Britain. Clay rocks elsewhere in the country are older and have been hardened by burial deep in the earth and are less able to absorb water. The BGS has carried out detailed geotechnical and mineralogical investigations into rock types known to shrink, and are modelling their properties across the near surface. This research underpins guidance contained in the national GeoSure dataset, and is the basis for our responses to local authorities, companies and members of the public who require specific information on the hazard in their areas. The BGS is undertaking a wide-ranging research programme to investigate this phenomenon by identifying those areas most at risk and developing sustainable management solutions. Complete Great Britain national coverage is available.