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1,665 records · Page 54Linked to original sources
USGS2026

Early Miocene volcanic rocks and associated tectonics, Lava Hills and southern Bristol Mountains, California

Volcanic rocks of latest Oligocene to early Miocene age form an east-west belt across part of the central eastern Mojave Desert from the Whipple Mountains on the east to the Rosamond Hills on the west. We term this the central belt because it is separated from northern and southern belts by swaths with no volcanic rocks. Limited geochronologic data indicate that much of the belt is latest Oligocene and early Miocene in age, about 24 to 19 Ma, a finding that is consistent with these rocks being overlain by the 18.8 Ma Peach Spring Tuff in many places. We describe Miocene geology in a central area of the belt, in the Lava Hills, southern Bristol Mountains, and southern Old Dad Mountains. Sedimentary basins formed coeval with early andesite to rhyolite volcanism, progressing from fluvial and lacustrine tuffaceous sandstone to volcanic lavas, tuffs, and breccias, indicating that early basins formed proximal to volcanic edifices. Higher strata are fluvial and lacustrine with lavas punctuating the sequence. Although basins may partly have been formed within topographic lows bounded by volcanic domes, plateaus, and stratovolcanoes, consistent stratigraphic sections over wide areas indicate that tectonic basin evolution affected broad areas. The volcanic section is capped by local basalt flows and the regional Peach Spring Tuff. Limited data on normal faults support interpretations of early extensional basin development caused by northeast-southwest oriented stretching. Later extension caused stratal rotations, tilting early deposits down to the southwest. This tilted and subsequently beveled basin architecture was overlain by the youngest volcanic deposits, primarily rhyolite and basalt. The Peach Spring Tuff, 18.8 Ma, lies within this upper unit. Similar stratigraphic and structural relations are exposed in the nearby Marble Mountains and Van Winkle Mountain sections, reinforcing that a broad area underwent similar volcanism and tectonism. In our study area the upper unit is only very gently tilted except near dextral strike-slip faults of the eastern California shear zone. These late Miocene to Recent faults are represented as four main fault zones spaced about 5 km apart, representing distributed shear north of the Bristol Lake basin.

California↗
USGS2025

A generalized deep learning model to detect and classify volcano seismicity

Volcano seismicity is often detected and classified based on its spectral properties. However, the wide variety of volcano seismic signals and increasing amounts of data make accurate, consistent, and efficient detection and classification challenging. Machine learning (ML) has proven very effective at detecting and classifying tectonic seismicity, particularly using Convolutional Neural Networks (CNNs) and leveraging labeled datasets from regional seismic networks. Progress has been made applying ML to volcano seismicity, but efforts have typically been focused on a single volcano and are often hampered by the limited availability of training data. We build on the method of Tan et al. [2024] ( 10.1029/2024JB029194 ) to generalize a spectrogram-based CNN termed the VOlcano Infrasound and Seismic Spectrogram Neural Network ( VOISS-Net ) to detect and classify volcano seismicity at any volcano. We use a diverse training dataset of over 270,000 spectrograms from multiple volcanoes: Pavlof, Semisopochnoi, Tanaga, Takawangha, and Redoubt volcanoes\replaced (Alaska, USA); Mt. Etna (Italy); and Kīlauea, Hawai`i (USA). These volcanoes present a wide range of volcano seismic signals, source-receiver distances, and eruption styles. Our generalized VOISS-Net model achieves an accuracy of 87 % on the test set. We apply this model to continuous data from several volcanoes and eruptions included within and outside our training set, and find that multiple types of tremor, explosions, earthquakes, long-period events, and noise are successfully detected and classified. The model occasionally confuses transient signals such as earthquakes and explosions and misclassifies seismicity not included in the training dataset (e.g. teleseismic earthquakes). We envision the generalized VOISS-Net model to be applicable in both research and operational volcano monitoring settings.

Volcanica↗
USGS2026

Mid-Cretaceous porphyritic magmatism in the Beartooth Mountains of the northern Laramide foreland and its connection to Frontier Formation sediment dispersal in Bighorn basin, Montana-Wyoming (USA), and Cordilleran tectonism

Porphyritic intrusions in the southeast Beartooth Mountains and porphyritic cobbles from the Torchlight conglomerate of the Cenomanian Frontier Formation in Bighorn basin (Montana-Wyoming, USA) bear striking resemblance. We utilize geologic mapping, petrography, geochemistry, and geochronology to characterize rocks from both locations and test whether the Beartooth Mountains area was the provenance for Bighorn basin cobbles. Mapping on Line Creek Plateau in the Beartooth Mountains shows three units with porphyritic phenocrysts consisting dominantly of plagioclase, plagioclase + potassium feldspar, and plagioclase + quartz. Petrography shows embayed quartz, opacitic rims, and zoned plagioclase. Geochemistry characterizes the intrusions as trachydacite to trachyte and trace elements exhibit enrichment in light rare earth elements and slight depletion in heavy rare earth elements relative to primitive mantle. Zircon U-Pb dating shows substantial Archean inheritance and ca. 104−92 Ma dates; some samples display multiple mid-Cretaceous date populations. Bighorn basin porphyritic cobbles exhibit similar modal mineralogy, near-identical geochemistry, and Archean inheritance and mid-Cretaceous geochronology. We suggest the porphyritic cobbles were sourced from basement-hosted porphyritic intrusions now exposed in the Beartooth Mountains, given that geochemistry does not agree with coeval volcanic sources along the Frontier Formation depositional fairway (Idaho batholith) or sedimentary-hosted Beartooth Mountains porphyritic sills intruded into Cambrian shale. Stratigraphic evidence does not support kilometer-scale mid-Cretaceous Beartooth Mountains exhumation to expose basement-hosted porphyritic intrusions, and we therefore present a volcanic hypothesis to bring rocks to the surface. This mid-Cretaceous multimillion-year magmatism is unexplained by tectonic models for the north-central Laramide foreland, and thus we further explore the emplacement processes, spatiotemporal significance, and tectonic implications of these rocks.

Montana, Wyoming↗
USGS2025

Estimated average annualized losses from potential building damage and fatalities due to earthquake-generated tsunamis in the United States

Earthquake-generated tsunamis represent substantial economic threats to states and territories in the United States (U.S.), but we are unaware of any effort to quantify potential impacts at the national level. This gap is partially due to the lack of nationally consistent data on tsunamigenic sources and associated return periods. This study addresses this issue and provides estimates of average annualized losses (AAL) for potential residential fatalities and capital stock losses associated with building damage (i.e., structural, non-structural, contents, and inventory damage) in the U.S. by curating tsunami-hazard information based on deterministic scenarios and probabilistic approaches, calculating potential losses, and estimating return periods where necessary. This assessment was done for the U.S. West Coast, Alaska, Hawaii, U.S. Pacific Territories, and U.S. Atlantic Territories. We estimate that earthquake-generated tsunamis that could affect these states and territories collectively represent $1 billion in potential AAL with 79 % of losses due to residential fatalities and 21 % of losses due to capital stock losses from building damage. We identify AAL variations based on county and county equivalents, states and territories, geographic regions, return periods, and departure-delay assumptions for evacuating residents. Results include high AAL values for potential fatalities in Puerto Rico and the U.S. Pacific Northwest region, high AAL values for potential building-related damage in Hawaii and California, and high building- and population-loss ratios for county equivalents in Alaska and U.S. territories.

International Journal of Disaster Risk Reduction↗
USGS2025

Comparing magmatism and hydrothermal alteration using magnetic modelling and stable isotopes at the Clementine porphyry copper prospect, Montana, USA

Recent mapping of the underexplored Clementine prospect in southwestern Montana has revealed evidence of hydrothermal alteration and mineralized breccia vein gossan interpreted to represent the upper expression of a Cretaceous, sediment-hosted copper porphyry system. The prospect is at the nexus of several Cretaceous granites, including the pre-mineralization Butte Granite and Big Hole Canyon plutons and local pre- to post-mineralization granite intrusions. Here, 3D magnetic inversions and stable isotope data are used to evaluate the spatial and genetic relationship of mineralization and Cretaceous magmatism. Magnetic inversions reveal a zone of high magnetic susceptibility beneath the prospect that is related to an exposure of unaltered, likely post-mineralization granite. The granite appears to connect to the Big Hole Canyon pluton at depth, suggesting it is a late-stage differentiate of the cooling, pre-mineralization pluton that may have been one of several potential heat sources for the mineral system at Clementine. This is supported by carbon isotope values of graphite that indicate organic material in shale of the Cretaceous Kootenai Formation was subject to metamorphism. Preliminary light hydrogen isotope values of actinolite hydrothermal orbs suggest formation following magmatic outgassing during thermal advection from an underlying intrusion.

Montana↗
USGS2024

Forecasting storm-induced coastal flooding for 21st century sea-level rise scenarios in the Hawaiian, Mariana, and American Samoan Islands

Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding in the populated Hawaiian, Mariana, and American Samoan Islands as a result of climate change and sea-level rise. We followed a hybrid (dynamical and statistical) downscaling approach to map flooding due to waves and storm surge at 10-square meter resolution along all 1,870 kilometers of these islands’ coastlines for annual (1-year), 20-year, and 100-year return-interval storm events and +0.00 meter (m), +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m sea-level rise scenarios. We quantified the coastal flood depths and extents using the latest climate forcing from Intergovernmental Panel for Climate Change’s Sixth Assessment Report Coupled Model Intercomparison Project. The data generated using these methods provide stakeholders and decision makers with a spatially explicit, rigorous valuation of how, where, and when climate change and sea-level rise increase coastal storm-induced flooding to help identify areas where management and (or) restoration could potentially help reduce the risk to, and increase the resiliency of, the coastal communities in the populated Hawaiian, Mariana, and American Samoan Islands.

Hawaii↗
USGS2025

Noble and base metal distribution and processes affecting ore tenors in the disrupted lower stratigraphy of the Stillwater Complex, USA

Exploration continues for contact-style Ni-Cu sulfide and chromitite-associated PGE mineralization in ultramafic rocks of the Stillwater Complex. At the Iron and Chrome Mountain areas, massive sulfides occur along the complex’s footwall contact and anomalous concentrations of PGE+Au are associated with the three lowermost chromitite seams. Southeast of Chrome Mountain, magmatic layering is highly disrupted by the presence of faults, magmatic breccias, serpentinized discordant dunites, pyroxenite pegmatoids, and disaggregated chromitite seams. The bulk rock chemistry, sulfide chemistry, and noble metal mineralogy of samples from this area were examined to determine the deportment of PGE and processes that led to enrichments in PGE, Au, Cu, Co and Ni. Results show that a sulfide liquid was the principal collector of PGE. If sulfide liquid was initially deposited with chromite, it was disaggregated or redistributed by subsequent melt or fluid infiltration, which may have resulted in the offset of peak PGE(+Cu, Ni) from peak Cr 2 O 3 concentrations, and upgraded PGE tenors. Upon cooling, PGE exsolved from sulfides to form discrete bismuth tellurides, arsenides, arsenic sulfides, antimonides, and alloys, commonly along the margins of sulfide globules. Calculated metal tenors are highest in the disseminated sulfides southwest of Chrome Mountain, whereas massive and net-textured sulfides near the Iron Mountain-Camp zone represent monosulfide solid solution cumulates. At progressively shallower levels, higher metal tenors combined with lower S/Se ratios are consistent with increasing R-factors from 100 to 100,000. Serpentinization and talc-tremolite alteration resulted in S loss through partial replacement of sulfides by secondary silicate+carbonate+magnetite+sulfide assemblages, further upgrading Ni-Cu-PGE tenors. The present work shows that processes responsible for the disruption of magmatic layering and post-magmatic fluid alteration along the intrusion’s lower contact led to noble and base metal enrichments.

Montana↗
USGS2024

Afterslip and creep in the rate-dependent framework: Joint inversion of borehole strain and GNSS displacements for the Mw 7.1 Ridgecrest earthquake

The elusive transition toward afterslip following an earthquake is challenging to capture with typical data resolution limits. A dense geodetic network recorded the Mw 7.1 Ridgecrest earthquake, including 16 Global Navigation Satellite System (GNSS) stations and 3 borehole strainmeters (BSM). The sub-nanostrain precision and sub-second sampling rate of BSMs bridges a gap between conventional seismologic and geodetic methods, exemplified by atypical postseismic shear strain reversals observed at nearfield (<2 km) station B921 that remain unexplained. We jointly invert GNSS displacements and BSM strains for coseismic and postseismic slip spanning hours to months over 7 independent periods. Cosiesmically, our model resolves the largest slip magnitudes of up to 6.6 m on the mainshock rupture plane, with similar patterns to other inferred slip distributions. The foreshock fault appears to slip coincidently with mainshock, revealing potential asperities activated during the preceding Mw 6.4 event. Postseismically, the best-fitting models adhere to mechanical rate-and-state expectations of logarithmically decaying slip adjacent to the coseismic rupture terminus, and where deep rheologic conditions favor creep. Most spatial variation occurs in the early postseismic timeframe (<1–2 weeks), with evidence for regional rheologic control and static stress dependence. Triggered creep on the neighboring Garlock Fault unexpectedly persists for >178 days—further highlighting the importance of fault networks in postseismic stress redistribution, critical to assessing future hazard.

Journal of Geophysics Research↗
USGS2026

High-resolution transboundary vegetation community maps of the Sonoran and Mojave Desert ecoregion to support critical landscape conservation planning and habitat management needs

We produced a 30-m resolution binational land cover map of Bird Conservation Region 33 (BCR 33) for the U.S. North American Bird Conservation Initiative. The region covers large portions of the Sonoran and Mojave Deserts. The map can support the U.S. Fish and Wildlife Service (FWS) Migratory Bird Program’s recovery planning efforts and constitutes the first known binational land cover dataset spanning sections of the United States–Mexico border and using a consistent classification system for both countries. The mapped region includes 152 distinct land cover classes, covering a total area of 38,421,453 ha (148,345 mi 2 ), of which 13,148,345 ha (52,706 mi 2 ) are located in Mexico and 24,770,640 ha (95,639 mi 2 ) in the United States. We primarily used Landsat 8 (OLI) imagery, supplemented by limited ground surveys from two field campaigns, drone-based aerial data, and existing vegetation classification frameworks from both countries. The classification applied a data-fusion approach integrating 30-m Landsat 8 imagery, decadal phenology metrics from vegetation indices, and a random forest model trained mainly with datasets from a comprehensive national mapping project from the U.S. Geological Survey (USGS) GAP Analysis Project (GAP) and federal wildland fire agencies’ Landscape Fire and Resource Management Planning Tools (LANDFIRE) (GAP/LANDFIRE) [United States side] and the National Institute of Statistics and Geography (INEGI) [Mexico side] as well as land cover maps and opportunistic open-access and field observations. Mapping of the full BCR 33 region was carried out in two phases: 1) Phase I, the prototype map, covered a smaller portion of the transboundary area and identified 31 land cover classes, and 2) Phase II, the full BCR 33 map (refer to Figure 1), which resulted in 152 land cover classes. Using a Random Forest classifier, we achieved an overall prediction accuracy of 92% for the Phase I map and 87% for the Phase II full region map. This slight decrease can be attributed to working on a larger, more complex area with a greater number of land cover classes. No formal validation was conducted, aside from using a subset of the collected field observations and training data to assess model performance during and after training. The training sites were further verified using Google Earth (Google, 2026) imagery. Two undergraduate students who worked for over a year visually inspected imagery and open access public images to confirm each training site during model training using in-house developed, online, visual tools. A portion of this field training data was reserved for model validation, and the corresponding results are to be presented in later sections. The project developed an end-to-end, medium- and fine-resolution remote sensing–based data fusion mapping approach. This effort produced a map (Nagler et al., 2025) and the online tools to support a dynamic, live, online map for visualizing the transboundary vegetation communities in BCR 33. The toolset is currently hosted by the University of Arizona (UofA) Vegetation Index and Phenology (VIP) Lab to support FWS partners (https://vip.arizona.edu/viplab_data_explorer?LCM_BCR33). The online map is designed to allow rapid updates using new training, validation, or correction data, making it dynamic and maintainable. The approach we took established a framework for rapid updating and correction of land cover maps, as the model can be quickly retrained with new field observations, updated training data, or other sources. This enables dynamic mapping and change detection of the region’s vegetation. This framework is an advance in data fusion and crowdsourced mapping of complex, vulnerable regions, providing support to regional stakeholders and the wider user community. This transboundary map can inform the protection, conservation, and restoration of vegetation, habitat, and ecosystems, particularly for threatened and endangered species across the two nations using consistent and harmonized binational mapping systems. Beyond supporting land management decisions and stakeholders in the transboundary desert ecoregions, this BCR 33 mapping effort establishes a foundation for future rapid, low-cost, cross-border land cover mapping that can benefit and advance ecosystem management.

Arizona, Baja California, California, Nevada, Sina↗
USGS2022

South Carolina and Landsat

South Carolina, the eighth State admitted to the union, transcends its size with its deep, rich history; striking beauty; vast natural resources; and extensive cultural diversity. Home to part of the Blue Ridge Mountains of the Central Appalachians, the Upstate is graced with more than 100 waterfalls, while the Lowcountry borders the Atlantic Ocean with 187 miles of coastline and 35 barrier islands. Forests cover two-thirds of the State, and forestry and agriculture together, as agribusiness, make up South Carolina’s leading industry. Two historic crops—cotton and tobacco—still rank in the top 10 commodities, though corn and soybeans now rank higher. Poultry, cattle, peanuts, and flowers also make the list. South Carolina’s population totals more than five million. Other residents include a variety of wildlife, bird, reptile, and fish species, including Ursus americanus (black bears), Alligator mississippiensis (American alligators), and Tursiops truncatus (bottlenose dolphins). More than 100 tree species also reside in South Carolina, which pays homage to one with its “The Palmetto State” nickname. South Carolina’s subtropical climate, long coastline, and lower elevations make it highly susceptible to tornado and hurricane activity and coastal flooding. Projected sea-level rise is a growing concern. A view from space can help monitor and manage natural resources on the land and in rivers, marshes, and the coast. Landsat reveals not just what an area looks like now, but also insights from decades ago.

South Carolina↗
USGS2026

2025 USGS National Seismic Hazard Model for Puerto Rico and the U.S. Virgin Islands: Overview of model and hazard results

The U.S. Geological Survey recently updated the National Seismic Hazard Model (NSHM) for Puerto Rico and the U.S. Virgin Islands (PRVI). The first version of the PRVI NSHM was released in 2003, and therefore this 2025 update includes over 20 years of new geologic, geophysical, and engineering data, methods, and models. Updates follow similar efforts performed in the recent 2023 50-state NSHM. However, this is the first NSHM in which we: (1) apply an inversion methodology to subduction interface fault sources in the earthquake rupture forecast (ERF) model; (2) develop scaled backbone median ground-motion models and independent aleatory variability models that are applied in the ground-motion characterization (GMC) model; and (3) calculate epistemic uncertainty related to alternative scenarios in the ERF and GMC models for all grid points in the study region. Long-term time-independent mean hazard calculations were performed for peak ground acceleration and 5%-damped pseudospectral acceleration at 21 spectral periods from 0.01- to 10.0-s, for eight National Earthquake Hazards Reduction Program site conditions ranging from V S30 = 150 to 1500 m/s, and for 2%, 5%, and 10% in 50-year probabilities of exceedance (return periods of 2475, 975, and 475 years, respectively). Epistemic uncertainty, in the form of selected percentiles, is also provided for a suite of test sites and all grid points in the study region for limited periods, site conditions, and probabilities of exceedance. Selected results, including comparisons with the 2003 PRVI NSHM, are shown and discussed for selected periods, site conditions, and probabilities of exceedance. When comparing the 2025 PRVI NSHM with the 2003 PRVI NSHM, hazard is generally higher at shorter periods and lower at longer periods, as a result of updates in both ERF and GMC models. The 2025 PRVI NSHM is applicable for return periods greater than ∼475 or less than ∼10,000 years.

Puerto Rico, U.S. Virgin Islands↗
USGS2024

Apatite and monazite geochemistry record magmatic and metasomatic processes in rare earth element mineralization at Mountain Pass, California

The largest rare earth element (REE) deposit in the United States is a carbonatite intrusion at Mountain Pass in the Mojave Desert, California. Despite a clear spatiotemporal association of alkaline silicate and carbonatite intrusions at Mountain Pass, a genetic model of their mutual formation has not been resolved. The Mountain Pass carbonatite has long been upheld as an example of a primary magmatic body, but recent work has suggested it could be fluid-derived. This study investigates the geochemistry of apatite and monazite grains from the alkaline silicate and carbonatite stocks and dikes of the Mountain Pass district, to elucidate the magmatic history of the intrusive suite and identify the role of fluids in rare earth element mineralization. Three apatite populations are identified in the alkaline silicate rocks. A primary magmatic apatite group supports intrusion of the stocks as separate pulses of magma derived from a spatially extensive metasomatized mantle source region. The second group implicates the role of a regional fluid that mobilized light rare earth elements from apatite grains. A minor group of inherited apatite cores, identified by low Sr and negative Eu anomalies, supports assimilation of crustal material in the formation of the intrusive suite. Analyses of monazite and apatite grains from the carbonatite orebody also reveal a mix of primary magmatic and metasomatic (fluid-related) minerals. Compositional similarities between primary phosphates in the carbonatite and alkaline silicate rocks support a genetic link between the intrusive suites. The presence of fluids regionally and within the carbonatite orebody indicates the Mountain Pass carbonatite should not be classified as a purely magmatic REE deposit.

Arizona, California, Nevada↗
USGS2026

Variability and consistency in wildfire susceptibility: Insights from a national compilation

Background Wildfire risk in the United States is rising and remains a land management priority. The quantitative wildfire risk assessment (QWRA) framework integrates fuels, topography, weather and values at risk to estimate the potential change in value from wildfire. Within this, response functions (RFs) represent how values respond to fire intensity. These are often based on expert judgment, but variation across assessments is unclear. Aims This study uses data from the US Geological Survey (USGS) Wildfire Hazard and Risk Assessment Clearinghouse to characterize consistency and variation across categories and contexts. Methods We applied descriptive statistics to summarize RFs, using tables, box-and-whisker plots and heat maps stratified by highly valued resource or asset (HVRA) category and spatial scale. Key results RFs and value definitions vary, especially for ecosystem-related resources. Some functions, such as for buildings in the wildland–urban interface (WUI), translate well across contexts, while others require more input. Conclusions Some functions are broadly transferable, while others need customization. This analysis provides references and starting points for improvement to RFs in QWRAs. Interpretations Expanding the clearinghouse and dataset and building more transparency in expert elicitation can build trust among communities, agencies and end-users, and can support efficient use of limited resources to mitigate wildfire risk.

International Journal of Wildland Fire↗
USGS2023

The Saudi Geological Survey-U.S. Geological Survey northern Harrat Rahat project—Styles, rates, causes, and hazards of volcanism near Al Madīnah al Munawwarah, Kingdom of Saudi Arabia

Active volcanic systems pose serious hazards to people and property including inundation and incineration by lava, blanketing by tephra (volcanic ash), exposure to noxious volcanic gases, and damage from shallow earthquakes triggered by ascending molten material (magma). To improve understanding of volcanism and associated seismicity on the western Arabia Plate, the Saudi Geological Survey and the U.S. Geological Survey conducted a multi-year investigation of the northern Harrat Rahat volcanic field adjacent to the city of Al Madīnah al Munawwarah, Kingdom of Saudi Arabia. Project components included creation of a high-resolution digital topographic base; interpretation of eruptive history supported by detailed geologic mapping, paleomagnetism, and abundant high-precision geochronology of volcanic deposits; assessments of eruptive styles and volcanic hazards by physical volcanology; investigation of the origins of magmas in the mantle and of their differentiation in the crust revealed by chemical and isotopic petrology; gravity and magnetotelluric surveys to reveal crustal structures and to search for magma reservoirs; and regional and local seismic tomography and analyses of seismic hazards. Project results are presented in this Professional Paper as chapters written for technical scientific audiences. This initial chapter introduces the project and briefly summarizes results in plain language for readers who have more general backgrounds.

Al Madīnah al Munawwarah↗
USGS2024

3-D mapping of the conterminous U.S. within the USGS National Cooperative Geologic Mapping Program: Progress and future prospects

The U.S. Geological Survey (USGS) National Cooperative Mapping Program (NCGMP) is bringing together subsurface and three-dimensional information at multiple scales for the conterminous United States from data produced throughout the USGS and by federal and state partners. Components of this work include data inventory and catalog development, data integration and database development, and construction of subregional and basin-scale three-dimensional (3-D) geologic models. At small scales, the NCGMP is compiling subsurface data to create a limited number of subsurface layers that map the majority of the lower 48 States. At larger scales, 3-D models of stratigraphic units are intended to be the subsurface analog and extension of the surface geologic maps made within the Program. The Mapping Program is developing methods of storing, visualizing, and distributing 3-D models and subsurface data from multiple sources in easily shareable, queryable, non-proprietary format(s). We report on progress in 3-D mapping of the conterminous U.S. and on future prospects.

conterminous United States↗