This data release, RI_WRpts.gdb, consists of information from Rhode Island Ground-water maps published by the Rhode Island Water Resources Coordinating Board, the Rhode Island Port and Industrial Development Commission, Rhode Island Industrial Commission, and the Rhode Island Development Council; in cooperation with the U.S. Geological Survey. The point data on these maps have been digitized into a standard ArcGIS geodatabase format. Data about wells and test borings consists of geographic location, identification number, geologic material (bedrock or unconsolidated), altitude in feet of the bedrock surface or altitude of the bottom of well, and data source. Seismic survey locations and bedrock outcrops where they are shown as points on the source maps are also included. The Ground-water maps, published between 1948 and 1964, also show geologic information which is being used to create a revised surficial materials database for future publication.

This map is a new construct that incorporates existing geologic maps where prior mappers had adequate ground control, and new interpretations based on drill hole, geophysical, and unpublished data where they did not. The interpretation differs significantly from previous maps to reflect new data and accommodate scale. It portrays our current geologic understanding of the temporal and geographic distribution of units within major Precambrian terranes and of the Phanerozoic strata. The western part of the mapped Precambrian terrane is inferred largely from geophysical maps, anchored locally by drilling. In many places, contacts are drawn between units of the same or similar apparent rock type (and same unit label); these are recognized as geometrically distinct, though geophysically or lithologically similar. Digital files corresponding to this map allow removal of Cretaceous, Paleozoic, and some parts of Mesoproterozoic strata to reveal an interpretation of the underlying Precambrian bedrock.

Note: This publication supersedes the bedrock geologic map elements of MGS Open-File OF10-02. Other components of OF10-02 are still valid, including the state-wide maps of bedrock topography, depth to bedrock, and outcrop locations, and the geochronology shapefiles.

This digital data release contains geospatial data for the 1:250,000 scale geologic map of the Grand Island 1 degree by 2 degree quadrangle, Nebraska, originally published by Dreeszen and others (1973). The database includes line and polygon features depicting the extent of the Miocene Ogallala Formation and underlying Cretaceous rocks. The original map also included shaded patches indicating outcrop areas, and contour lines depicting the thickness of Quaternary deposits; these are not included in this database. The spatial data are accompanied by non-spatial tables that describe the sources of geologic information, a description of geologic map units, a glossary of terms, and a Data Dictionary that duplicates the Entity and Attribute information contained in the metadata file.

Absolute depth to bedrock (in cm) predicted using the global compilation of soil ground observations. Accuracy assessement of the maps is availble in Hengl et at. (2017) DOI: 10.1371/journal.pone.0169748. Data provided as GeoTIFFs with internal compression (co='COMPRESS=DEFLATE'). Measurement units: cm.

Depth to bedrock. A raster showing the depth to the bedrock surface (thickness of Quaternary glacial sediments) from the land surface, in feet, across the state of Minnesota and includes that part of Minnesota that lies in the western part of the Lake Superior basin. The bedrock surface is an erosional surface comprised of Cretaceous (Mesozoic) rocks and sediments, Paleozoic rocks, and Precambrian rocks. Tribal areas of Grand Portage and Mille Lacs have been removed as per tribal request.

This digital data release contains spatial datasets of bedrock geology, volcanic ash bed locations, test hole locations, bedrock outcrops, and structure contours of the top of bedrock and the base of the Ogallala Group from a previously published map (Souders, 2000). The GeologicMap feature dataset contains separate feature classes for the Ogallala Group map unit (ContactsAndFaults and MapUnitPolys) and the underlying pre-Ogallala bedrock map units (ContactsAndFaults_Bedrock and MapUnitPolys_Bedrock). The VolcanicAshBedPoints feature class contains the locations of volcanic ash beds within the Ogallala Group. The contours depicting the elevation of the top of bedrock (top of Ogallala Group where present and top of pre-Ogallala bedrock where Ogallala is absent) are contained in the IsoValueLines_TopBedrock feature class. The contours depicting the elevation of the base of the Ogallala Group are contained in the IsoValueLines_BaseOgallala feature class. Contoured values are given in both feet and meters. Feature classes containing the location of test holes (TestHolePoints) and bedrock outcrops (OverlayPolys) that were used in generating the structure contour surfaces are included. Nonspatial tables define the data sources used, define terms used in the dataset, and describe the geologic units. A tabular data dictionary describes the entity and attribute information for all attributes of the geospatial data and the accompanying nonspatial tables. Surficial geologic units that are only represented as cross-sections on the original map publication, and the cross-sections themselves, are not included in this digital data release.

Digital Data from VG96-526A Ratcliffe, NM�and Burton, WC, 1996,�Digital bedrock geologic map of the Weston quadrangle, Vermont: USGS Open-File Report 96-526, 2 plates, scale 1:24000. The bedrock geologic map data at a scale of 1:24,000 depicts types of bedrock underlying unconsolidated materials in Vermont. Data is created by mapping on the ground using standard geologic pace and compass techniques and/or GPS on a USGS 1:24000 topographic base map. Data may be organized by town, quadrangle or watershed. Each data bundle may includes point, line and polygon data and some or all of the following: 1) contacts (lithogic contacts), 2) fault_brittle, 3) fault_ductile, 4) fault_thrust, 5) fault_bed_plane (bedding plane thrust), 6) bedding, 7) bedding_graded (graded bedding) 8) bedding_overturn (overturned bedding), 9) bedding_select (selected points for published map), 10) foliation_n1, n2, n3 etc (foliation data), 11) outcrop (exposed outcrops), 12) field_station (outcrop and data collection point), 13) fold_axis, 14) axial_plane, 15) lamprophyre, 16) water_well_log (water well driller information), 16) linear_int (intersection lineation), 17) linear_str (stretching lineation) 18) x_section_line (line of cross-section), and photolinear (lineaments identified from air photos). Other feature classes may be included with each data bundle. (https://dec.vermont.gov/geological-survey/publication-gis/ofr).

The Bedrock Topography map represents the elevation (in feet above mean sea level) of the top of bedrock and the bottom of Quaternary sediments mapped in Pipestone County, Minnesota. The Depth to Bedrock map portrays the thickness (in feet) of Quaternary sediments overlying the bedrock surface. The depth to bedrock is equal to the depth from the land surface to the underlying bedrock surface.

Please cite the work as: Kewei Li, Junju Xie, Xiaojun Li, Wenxiang Jiang, Chuanbin Zhu, Yong Zhang. 2025. A 100-meter-resolution site-condition map of China based on surface geology and bedrock depth. Engineering Geology, 354: 108199. https://doi.org/10.1016/j.enggeo.2025.108199.

We proposed a hybrid V_S30 prediction method that incorporates geological unit characteristics and bedrock depth to account for physical property variations within the units. By applying this model with regional adjustments based on geological environmental differences, we produced a nationwide 100-meter resolution V_S30 map and a same resolution site condition map for China.

This data release consists of a single ESRI shapefile, Hydrogeo_SECTpts, with geologic information from the previously published Hydrogeology of Southeastern Connecticut (Melvin, 1974). Test boring location points digitized from georeferenced area maps (1:24,000 scale) are attributed with associated well log information: town, identification numbers, altitude, depth to bottom, and remarks regarding the geology of the well finish. Descriptions for the bottoms of boreholes recorded the source driller's logs.

This is Version 2 of the Depth of Regolith product of the Soil and Landscape Grid of Australia (produced 2015-06-01).

The Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).

Attribute Definition: The regolith is the in situ and transported material overlying unweathered bedrock; Units: metres; Spatial prediction method: data mining using piecewise linear regression; Period (temporal coverage; approximately): 1900-2013; Spatial resolution: 3 arc seconds (approx 90m); Total number of gridded maps for this attribute:3; Number of pixels with coverage per layer: 2007M (49200 * 40800); Total size before compression: about 8GB; Total size after compression: about 4GB; Data license : Creative Commons Attribution 4.0 (CC BY); Variance explained (cross-validation): R^2 = 0.38; Target data standard: GlobalSoilMap specifications; Format: GeoTIFF. Lineage: The methodology consisted of the following steps: (i) drillhole data preparation, (ii) compilation and selection of the environmental covariate raster layers and (iii) model implementation and evaluation.

Drillhole data preparation: Drillhole data was sourced from the National Groundwater Information System (NGIS) database. This spatial database holds nationally consistent information about bores that were drilled as part of the Bore Construction Licensing Framework (http://www.bom.gov.au/water/groundwater/ngis/). The database contains 357,834 bore locations with associated lithology, bore construction and hydrostratigraphy records. This information was loaded into a relational database to facilitate analysis.

Regolith depth extraction: The first step was to recognise and extract the boundary between the regolith and bedrock within each drillhole record. This was done using a key word look-up table of bedrock or lithology related words from the record descriptions. 1,910 unique descriptors were discovered. Using this list of new standardised terms analysis of the drillholes was conducted, and the depth value associated with the word in the description that was unequivocally pointing to reaching fresh bedrock material was extracted from each record using a tool developed in C# code.

The second step of regolith depth extraction involved removal of drillhole bedrock depth records deemed necessary because of the “noisiness” in depth records resulting from inconsistencies we found in drilling and description standards indentified in the legacy database.

On completion of the filtering and removal of outliers the drillhole database used in the model comprised of 128,033 depth sites.

Selection and preparation of environmental covariates The environmental correlations style of DSM applies environmental covariate datasets to predict target variables, here regolith depth. Strongly performing environmental covariates operate as proxies for the factors that control regolith formation including climate, relief, parent material organisms and time.

Depth modelling was implemented using the PC-based R-statistical software (R Core Team, 2014), and relied on the R-Cubist package (Kuhn et al. 2013). To generate modelling uncertainty estimates, the following procedures were followed: (i) the random withholding of a subset comprising 20% of the whole depth record dataset for external validation; (ii) Bootstrap sampling 100 times of the remaining dataset to produce repeated model training datasets, each time. The Cubist model was then run repeated times to produce a unique rule set for each of these training sets. Repeated model runs using different training sets, a procedure referred to as bagging or bootstrap aggregating, is a machine learning ensemble procedure designed to improve the stability and accuracy of the model. The Cubist rule sets generated were then evaluated and applied spatially calculating a mean predicted value (i.e. the final map). The 5% and 95% confidence intervals were estimated for each grid cell (pixel) in the prediction dataset by combining the variance from the bootstrapping process and the variance of the model residuals. Version 2 differs from version 1, in that the modelling of depths was performed on the log scale to better conform to assumptions of normality used in calculating the confidence intervals. The method to estimate the confidence intervals was improved to better represent the full range of variability in the modelling process. (Wilford et al, in press)

This dataset is a compilation of depth to bedrock surface data for state of Iowa, compiled by the Iowa Geological and Water Survey and provided by Illinois State Geological Survey. Iowa Bedrock Depth Dataset is published as a Web feature service, a web map service, and an ESRI service for the National Geothermal Data System. For more information on these data see links provided.

Depth-to-bedrock maps of China (divided into 2 blocks: DTB100_ENSEMBEL_BLOCK*.tif) at a spatial resolution 100 meters, produced based on an ensemble model.Depth-to-bedrock maps of China(DTB_QRF_MEAN_100.tif) with uncertainty map (divided into 2 blocks: DTB_UNCERTAINTY_BLOCK*.tif) of prediction at at a spatial resolution of 100 meters, produced based on quantile regression forests model.

These data were compiled to demonstrate new predictive mapping approaches and provide comprehensive gridded 30-meter resolution soil property maps for the Colorado River Basin above Hoover Dam. Random forest models related environmental raster layers representing soil forming factors with field samples to render predictive maps that interpolate between sample locations. Maps represented soil pH, texture fractions (sand, silt clay, fine sand, very fine sand), rock, electrical conductivity (ec), gypsum, CaCO3, sodium adsorption ratio (sar), available water capacity (awc), bulk density (dbovendry), erodibility (kwfact), and organic matter (om) at 7 depths (0, 5, 15, 30, 60, 100, and 200 cm) as well as depth to restrictive layer (resdept) and surface rock size and cover. Accuracy and error estimated using a 10-fold cross validation indicated a range of model performances with coefficient of variation (R2) for models ranging from 0.20 to 0.76 with mean of 0.52 and a standard deviation of 0.12. Models of pH, om and ec had the best accuracy (R2 > 0.6). Most texture fractions, CaCO3, and SAR models had R2 values from 0.5-0.6. Models of kwfact, dbovendry, resdept, rock models, gypsum and awc had R2 values from 0.4-0.5 excepting near surface models which tended to perform better. Very fine sands and 200 cm estimates for other models generally performed poorly (R2 from 0.2-0.4), and sample size for the 200 cm models was too low for reliable model building. More than 90% of the soils data used was sampled since 2000, but some older samples are included. Uncertainty estimates were also developed by creating relative prediction intervals, which allow end users to evaluate uncertainty easily.

A series of maps describing geological factors relevant to offshore seabed activities. Produced in collaboration with The Crown Estate in 2014. The Bedrock Summary Lithologies dataset is a digital geological map across the bulk of the UK Continental Shelf (UKCS), for areas up to a water depth of 200m, which groups the bedrock lithologies (rock types) into classes based on similar engineering geology characteristics. The map is derived from the 1:250,000 scale digital bedrock map of the UKCS, called DiGRock250k, which is available separately from the BGS. The map was produced in 2014 in collaboration with The Crown Estate as part of a project to assess seabed development opportunities across the UKCS. This map has been released for viewing on the Offshore GeoIndex alongside a series of other offshore geological maps from the BGS.

The Bedrock Topography map represents the elevation (in feet above mean sea level) of the top of bedrock and the bottom of Quaternary sediments mapped in Dakota County, Minnesota. The Depth to Bedrock map portrays the thickness (in feet) of Quaternary sediments overlying the bedrock surface. The depth to bedrock is equal to the depth from the land surface to the underlying bedrock surface.

Digital Data from VG94-654A Walsh, G.J., and Ratcliffe, N.M., 1994,�Digital bedrock geologic map of the Plymouth quadrangle, Vermont: USGS Open-File Report 94-654, 2 plates, scale 1:24,000. The bedrock geologic map data at a scale of 1:24,000 depicts types of bedrock underlying unconsolidated materials in Vermont. Data is created by mapping on the ground using standard geologic pace and compass techniques and/or GPS on a USGS 1:24000 topographic base map. Data may be organized by town, quadrangle or watershed. Each data bundle may includes point, line and polygon data and some or all of the following: 1) contacts (lithogic contacts), 2) fault_brittle, 3) fault_ductile, 4) fault_thrust, 5) fault_bed_plane (bedding plane thrust), 6) bedding, 7) bedding_graded (graded bedding) 8) bedding_overturn (overturned bedding), 9) bedding_select (selected points for published map), 10) foliation_n1, n2, n3 etc (foliation data), 11) outcrop (exposed outcrops), 12) field_station (outcrop and data collection point), 13) fold_axis, 14) axial_plane, 15) lamprophyre, 16) water_well_log (water well driller information), 16) linear_int (intersection lineation), 17) linear_str (stretching lineation) 18) x_section_line (line of cross-section), and photolinear (lineaments identified from air photos). Other feature classes may be included with each data bundle. (https://dec.vermont.gov/geological-survey/publication-gis/ofr).

Data obtained from New York State Geological Survey. Coverage identifies only broad classifications of Surficial Geology in County. For more information contact: https://www.nysm.nysed.gov/research-collections/geology

Digital Data from VG98-1 Springston, G., Kim, J., and Applegate, G.S., 1998,�Digital bedrock geologic map of the Morrisville quadrangle,�Vermont: VGS Open-File Report VG98-1, 2 plates, scale 1:24000. The bedrock geologic map data at a scale of 1:24,000 depicts types of bedrock underlying unconsolidated materials in Vermont. Data is created by mapping on the ground using standard geologic pace and compass techniques and/or GPS on a USGS 1:24000 topographic base map. Data may be organized by town, quadrangle or watershed. Each data bundle may includes point, line and polygon data and some or all of the following: 1) contacts (lithogic contacts), 2) fault_brittle, 3) fault_ductile, 4) fault_thrust, 5) fault_bed_plane (bedding plane thrust), 6) bedding, 7) bedding_graded (graded bedding) 8) bedding_overturn (overturned bedding), 9) bedding_select (selected points for published map), 10) foliation_n1, n2, n3 etc (foliation data), 11) outcrop (exposed outcrops), 12) field_station (outcrop and data collection point), 13) fold_axis, 14) axial_plane, 15) lamprophyre, 16) water_well_log (water well driller information), 16) linear_int (intersection lineation), 17) linear_str (stretching lineation) 18) x_section_line (line of cross-section), and photolinear (lineaments identified from air photos). Other feature classes may be included with each data bundle. (https://dec.vermont.gov/geological-survey/publication-gis/ofr).

Digital Data from VG97-04C Stanley, RS, and Roy, D, 1997,�Bedrock geologic map of the Jay and North Troy area, Vermont: VGS Open-File Report VG97-04c, scale 1:24000. Supersedes VG97-04A. The bedrock geologic map data at a scale of 1:24,000 depicts types of bedrock underlying unconsolidated materials in Vermont. Data is created by mapping on the ground using standard geologic pace and compass techniques and/or GPS on a USGS 1:24000 topographic base map. Data may be organized by town, quadrangle or watershed. Each data bundle may includes point, line and polygon data and some or all of the following: 1) contacts (lithogic contacts), 2) fault_brittle, 3) fault_ductile, 4) fault_thrust, 5) fault_bed_plane (bedding plane thrust), 6) bedding, 7) bedding_graded (graded bedding) 8) bedding_overturn (overturned bedding), 9) bedding_select (selected points for published map), 10) foliation_n1, n2, n3 etc (foliation data), 11) outcrop (exposed outcrops), 12) field_station (outcrop and data collection point), 13) fold_axis, 14) axial_plane, 15) lamprophyre, 16) water_well_log (water well driller information), 16) linear_int (intersection lineation), 17) linear_str (stretching lineation) 18) x_section_line (line of cross-section), and photolinear (lineaments identified from air photos). Other feature classes may be included with each data bundle. (https://dec.vermont.gov/geological-survey/publication-gis/ofr).