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 Land Subsidence scale. The first land subsidence risk evaluation sub-scale seeks to answer the following two questions:1) Do you have the following ready in case the land subsides? Please check to each item either 'yes','unsure' or 'no.' and 2) Please rate the difficulty of preparing for each item, by your household, on a five-point scale ranging from 'not difficult at all' to 'extremely difficult.' The second land subsidence sub-scale seeks to answer the following two questions: 1) Please indicate the extent of disaster risk preparedness by your household to each item, by checking either 'yes', 'unsure' or 'no.' 2) Please rate the difficulty of preparing for each item, by your household, on a five-point scale ranging from 'not difficult at all' to 'extremely difficult.'

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

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.

Borehole extensometers are a more site specific method of measuring land subsidence. These instruments consist of a pipe or cable anchored at the bottom of a well casing. Pipe or cable extend from the bottom of the well, through geologic layers susceptible to compaction, to the ground surface. The pipe or cable is connected to a recorder that measures the relative distance between the bottom of the bore hole to the ground surface. These instruments are capable of detecting changes in land surface elevation to 1/100th of a foot. When land subsidence and water depth monitoring activities are paired together, hydraulic and mechanical properties of the aquifer system can be determined. DWR monitors 11 extensometers in the Sacramento Valley.

For more information regarding land subsidence monitoring vist: http://www.water.ca.gov/groundwater/landsubsidence/LSmonitoring.cfm

This dataset represents measurements of vertical ground surface displacement in more than 200 of the high-use and populated groundwater basins across the State of California between January of 2015 and April of 2022. Vertical displacement estimates are derived from Interferometric Synthetic Aperture Radar (InSAR) data that are collected by the European Space Agency (ESA) Sentinel-1A satellite and processed by TRE ALTAMIRA Inc. (TRE), under contract with the California Department of Water Resources (DWR) as part of DWR’s SGMA technical assistance to provide important SGMA-relevant data to GSAs for GSP development and implementation. Sentinel-1A InSAR data coverage began in late 2014 for parts of California, and coverage for the entire study area began in June 13, 2015. Included in this dataset are point data that represent average vertical displacement values for 100 meter by 100 meter areas, as well as GIS rasters that were interpolated from the point data; rasters for total vertical displacement relative to June 13, 2015, and rasters for annual vertical displacement rates with earlier coverage for some areas, both in monthly time steps. Towill Inc. (Towill), also under contract with DWR as part of DWR’s SGMA technical assistance, conducted an independent study comparing the InSAR-based vertical displacement point time series data to data from Continuous Global Positioning System (CGPS) stations. The goal of this study was to ground-truth the InSAR results to best available independent data.

Data update frequency: Quarterly Report update frequency: Annual

The Central Valley, and particularly the San Joaquin Valley, has a long history of land subsidence caused by groundwater development. The extensive withdrawal of groundwater from the unconsolidated deposits of the San Joaquin Valley lowered groundwater levels and caused widespread land subsidence—reaching 9 meters by 1981. More than half of the thickness of the aquifer system is composed of fine-grained sediments, including clays, silts, and sandy or silty clays that are susceptible to compaction. In an effort to aid water managers in understanding how water moves through the aquifer system, predicting water-supply scenarios, and addressing issues related to water competition, the United States Geological Survey (USGS) developed a new hydrologic modeling tool, the Central Valley Hydrologic Model (CVHM; Faunt and others 2009). The data presented in this data release will be used to facilitate updates to the original CVHM and represent subsidence observations (measurements) using g ...

The slopes above streams and rivers are subjected to a variety of processes that cause them to recede and retreat from the river or stream channel. These processes, collectively called mass wasting, can be classified according to rapidity of movement and according to the type of materials that are transported.

Groundwater overdraft gives rise to multiple adverse impacts including land subsidence and permanent groundwater storage loss. Existing methods have been unable to characterize groundwater storage loss at the global scale with sufficient resolution to be relevant for local studies. Here we explore the interrelation between groundwater stress, aquifer depletion, and land subsidence using remote sensing and model-based datasets with a machine learning approach. The developed model predicts global land subsidence magnitude at high spatial resolution (~2 km) and provides a first-order estimate of aquifer storage loss due to consolidation of ~17 km3/year globally. China, the United States, and Iran account for the majority of groundwater storage loss due to consolidation. The model quantifies key drivers of subsidence and has high predictive accuracy, with an F1-score of 0.83 on the validation set. Roughly 73% of the mapped subsidence occurs over cropland and urban areas, highlighting the need for sustainable groundwater management practices over these areas. The results of this study aid in assessing the spatial extents of subsidence in known subsiding areas, and in locating unknown groundwater stressed regions.

Abstract

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

This dataset contains digitised subsidence polygons for Carmichael, China First, Kevins Corner and South Galilee mines. The various mines shapefiles were hand digitised from the QLD State Government report: Carmichael Coal Mine and Rail project: Coordinator-General's evaluation report on the environmental impact statement, May 2014 (PDF saved within the dataset). Guid = 2a595f74-aae6-4d83-9cd7-1459247d751a.

Purpose

This dataset provides a digitised spatial representation of the subsidence within the various Mine Tenements.

Dataset History

Data has been digitised by hand from Figure 2.2 (page 7) of the QLD State Government report: Carmichael Coal Mine and Rail project: Coordinator-General's evaluation report on the environmental impact statement, May 2014 (Copy of PDF saved within the dataset). The digitised dataset was georectified using graticules and drainage as reference points. The mine (onsite) feature was then hand digitised as a polygons.

Dataset Citation

Bioregional Assessment Programme (2014) Galilee subsidence data. Bioregional Assessment Derived Dataset. Viewed 07 December 2018, http://data.bioregionalassessments.gov.au/dataset/45352553-f363-4a67-b4f7-27000e47f697.

Dataset Ancestors

• Derived From Carmichael Coal Mine and Rail Project Environmental Impact Statement

This dataset contains 10 polygon features. "Mine Subsidence" means lateral or vertical ground movement caused by a failure initiated at the mine level, of man made underground mines.

This dataset provides estimates of land subsidence rates for the Delta-X domain area within the Atchafalaya and Terrebonne basins for 2021. The study area is a portion of the Mississippi River Delta in coastal Louisiana, U.S. The total subsidence is calculated as the sum of deep and shallow vertical elevation change rates. The deep subsidence rate is based on information from the Coastal Protection and Restoration Authority (CPRA) of Louisiana, documented in the Phase-4 subsidence trend report prepared for and provided by CPRA (2022). The shallow subsidence is calculated for the Delta-X study area by interpolation of publicly available data provided by CPRA for their coast-wide estimation of shallow subsidence in the 2023 Coastal Master Plan. The total subsidence rates and the estimated uncertainty in the total subsidence rates are provided as separate files in cloud optimized GeoTIFF (COG) format at 30-m (0.0003 decimal degrees) resolution.

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).

This dataset has been superseded by https://data.cnra.ca.gov/dataset/tre-altamira-insar-subsidence This dataset represents measurements of vertical ground surface displacement in Bulletin 118 groundwater basins between spring of 2015 and summer of 2017. Image resolution is 0.0008333 degrees, or approximately 92 meters in north-south direction, and 70-77 meters in east-west direction (low end of range applies to northern latitudes and higher end of range applies to lower latitudes). Vertical ground surface displacement rates are derived from Interferometric Synthetic Aperture Radar (InSAR) data that are collected by the European Space Agency (ESA) Sentinel-1A satellite and processed by the National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL), under contract with to the California Department of Water Resources (DWR). JPL presented preliminary processing results in the Progress Report: Subsidence in California, March 2015 – September 2016, and submitted a later version of the processing results that are still preliminary to the California Department of Water Resources (DWR). These files provided by JPL to DWR are multiband floating point GeoTIFFs with each band representing a date. GeoTIFF pixel values are in inches equal to the cumulative vertical displacement from the first date. JPL processed Sentinel-1A InSAR data separately for three different geographic regions; The Sacramento Valley, the San Joaquin Valley, and the South Central Coast. DWR temporarily interpolated the JPL data to end-of-month values, merged the resulting rasters from all three regions into a single raster for each month, and clipped all rasters to Bulletin 118 groundwater basins. DWR derived rasters for total vertical displacement relative to May 31, 2015, as well as rasters for annual vertical displacement rates, both in monthly time steps. Data are considered public _domain. DWR makes no warranties or guarantees — either expressed or implied — as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. This is an official DWR Image Service, published on 2/9/2018 by Ben Brezing of the DWR Division of Statewide Integrated Water Management, who may be contacted at Benjamin.brezing@water.ca.gov or (916) 651-9291. Date of acquisition: Between Spring of 2015 and Spring of 2017. Date of production: 2017. Date of delivery of product: Delivered from NASA JPL to DWR in September of 2017. Processing steps: See Progress Report: Subsidence in California, March 2015 – September 2016, Tom G. Farr, Cathleen E. Jones, Zhen Liu, Jet Propulsion Laboratory, 2016. Pixel value definitions: Vertical ground surface displacement in inches for time period specified above. Positional accuracy: See Progress Report: Subsidence in California, March 2015 – September 2016, Tom G. Farr, Cathleen E. Jones, Zhen Liu, Jet Propulsion Laboratory, 2016.

Applications of the conventional finite element method to problems of mining subsidence can result in excessive expense, particularly when nonlinear constitutive stress/strain relations are used for the geological medium. An alternative finite element method is proposed which captures the essential characteristics of subsidence observed both in more sophisticated finite element programs and in the field. The alternative method treats the overburden with classical beam theory with the inclusion of shearing deformation. The nonlinear axial response of the pillars as well as the nonlinear response of any backfill that may be present is also modelled. Flexural and bending modes of deformation are included for the pillar and backfill media with classical beam theory. Shearing deflections are also included for these structural members. The development of the constitutive relations, the implementation of the constitutive relations in the computer program and the numerical algorithm for the problem solution are presented. An example problem in subsidence is presented to illustrate the potential of the computer program. Computer cost for the example problem clearly demonstrates that the alternative method for analysis of subsidence problems deserves consideration.

The data set is used as the C2VSimFG observed subsidence data to compare with the simulated subsidence data to evaluate the impact on subsidence, groundwater budgets, and groundwater levels. The subsidence affects stream-aquifer interactions and the decline in groundwater storage due to compaction in the San Joaquin Valley and Tulare Lake Basin. The data contains observed subsidence data over time from the DWR and USGS stations, USGS InSAR RestoreSJR GPS stations, USGS Extensometers, and the Continuous UNAVCO PBO GPS dataset. Most of the observed subsidence data was monitored with almost daily intervals. The GPS Surveys by USGS InSAR RestoreSJR monitoring subsidence stations were monitored biannually. The DWR continuous effort in the subsidence monitoring is part of the Sacramento Valley Subsidence Network, consisting of over 300 monument locations with an average spacing of 4.3 miles, encompassing 11 counties.

The primary forms of damage in subsidence areas are mining subsidence and ground fissures, leading to a unique type of underlying surface that alters the hydrological environment and hydrogeological conditions of the watershed. This phenomenon is common in the Yellow River Basin, a major coal-producing region in China, and requires urgent scientific development and management. In this study, SAR data were collected from the Kuye River sub-basin of the Yellow River Basin, and SBAS-InSAR technology was employed for baseline resolution, data enhancement, differential interference, and phase unwrapping. This approach enabled the assessment of spatial distribution characteristics of surface deformation rates and cumulative surface subsidence in the Kuye River Basin impacted by coal mining. By comparing and analyzing the spatial distribution of surface subsidence areas with coal mining areas, the study identified and extracted coal mining subsidence zones. This provides data support for the management and development of these subsidence areas. The results indicate the formation of 914 coal mining subsidence areas in the Kuye River Basin due to coal mining, covering a total area of 345.76 km², with the largest subsidence area measuring 10.01 km².

The groundwater model used to simulate subsidence in the Gulf Region of Texas. Contact Oklahoma-Texas Water Science Center Public Information Officer, US Geological Survey for questions. Original data published and shared: Knight, J.E, Ellis, J.H, White, J.T., Sneed, M., Hughes, J.D., Ramage, J.K, Braun, C.L., Teeple, A.P., Foster, L., Rendon, S.H., Brandt, J., Duncan, L.L., Traylor, J.P., and Pattison, C.H., 2023, MODFLOW 6 model and ensemble used in the simulation of groundwater flow and land subsidence in the northern part of the Gulf Coast aquifer, 1897-2018 (ver. 2.0. September 2023): U.S. Geological Survey data release, https://doi.org/10.5066/P9XM8A1P.

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.

This data publication provides supplementary material to Motagh et. al (2017), which presents the results of an InSAR time series analysis obtained by the exploitation of Envisat, ALOS and Sentinel-1 (S1) SAR data archives between June 2004, and May 2016. The study investigates land subsidence due to groundwater overexploitation for agriculture and industrial development in the Rafsanjan plain of southeastern Iran. Datasets included are a list of SAR data used for the study and the Line of Sight (LOS) displacement rates from Envisat, ALOS and Sentinel 1 (S1) satellites in ASCII format. More in formation is avalable in Motagh-et-al-2017-Supplementary_Material_readme.pdf.

This repository contains the data used in Aziz Zanjani et al., 2024. It includes InSAR time-series datasets from the Sentinel-1 satellite, acquired over Miami's barrier islands, Florida. The datasets are divided into two time frames: 2016-2023 and 2019-2023. The files "North_20162023" and "North_20192023" cover the Sunny Isles. The files "South_20162023" and "South_20192023" include displacement data for Surfside and Miami Beach. Aziz Zanjani, F., F. Amelung, A. Piter, K. Sobhan, A. Tavakkoliestahbanati, G.P. Eberli, M. Haghshenas Haghighi, M. Motagh, P. Milillo, S. Mirzaee, A. Nanni, and E. Andiroglu. "InSAR observations of construction-induced coastal subsidence on Miami's barrier islands, Florida" Submitted to Earth and Space Science.