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887 records · Page 36Linked to original sources
USGS2024

Turbidite correlation for paleoseismology

Marine turbidite paleoseismology relies on the assumption of synchronous triggering of turbidity currents by earthquake shaking to infer rupture extent and recurrence. Such inference commonly depends on age dating and correlation of the physical stratigraphy of deposits carried by turbidity currents (i.e., turbidites) across great distances. Along the Cascadia subduction zone, which lies offshore the Pacific Northwest, USA, turbidite facies in core photographs, X-ray computed tomography images, and magnetic susceptibility (MS) data exhibit differences in character over relatively short distances, which implies that not all deposits can be correlated with confidence. Thus, subjective correlation based on expected similarity over great distances and weak age constraints does not independently support paleoseismic models. We present a new method for correlating turbidites along the Cascadia margin that can yield a more objective and repeatable stratigraphic framework to underpin earthquake recurrence. We use dynamic time warping to correlate MS logs and measure correlation coefficients of core pairs to evaluate correlation strength. We then compare these measures to a distribution of correlation coefficients of randomly generated turbidite sequences and find that only a small number of core pairs can be correlated more confidently than randomly stacked turbidites. This methodology promises a more robust correlation strategy for future stratigraphic studies.

Oregon, Washington↗
USGS2026

Remote sensing enables basin-scale inventories of coal mine methane

Underground coal mines are important global sources of methane, but emission estimates are uncertain. We show that emission estimates for individual mines from aircraft remote-sensing surveys in the United States agree within 40% with direct measurements used for national emission reporting (IPCC Tier 3 estimate). Such direct measurements are unavailable in most countries, which rely on estimated emission factors (EFs) applied to coal-production rates. We find that EFs from IPCC Tier 1 and the Model for Calculating Coal Mine Methane (MC2M) methods overestimate U.S. emissions 3-fold due to incorrect dependence on mine depth. An IPCC Tier 2 method using measured basin-specific mine gas content agrees with direct emission measurements but does not account for gob well emissions and requires gas content data that are generally unavailable. We show that aircraft remote sensing for a small sample of mines can successfully estimate basin-specific EFs for ventilation shafts and gob wells, enabling estimates of basin- and national-scale emissions. We discuss how the method can be applied with satellite remote sensing to quantify coal emissions worldwide.

Alabama, Colorado, Kentucky, New Mexico, Ohio, Pen↗
USGS1991

Reconnaissance of the occurrence of agricultural chemicals in ground water in Haywood, Lake, Obion and Shelby Counties, Tennessee

Data on the occurrence of agricultural chemicals in ground wafer in Tennessee are sparse. The surficial alluvial aquifer is an important source of domestic water supply in West Tennessee, and potentially is subject fo contamination from the application of agricultural chemicals in the area. Nineteen shallow wells completed in the alluvial aquifers in areas of high density agricultural use were sampled in the winter and again in the summer of 1988 to ascertain the occurrence of agricultural chemical in ground water. Although no triazine herbicides or organophosphorus insecticides were detected in any of the wells sampled, elevated nitrite plus nitrate (as nitrogen) concentrations were detected. Results from the winter sampling period indicate a range of nitrite plus nitrate (as nitrogen) concentrations of less than 0.1 to 7.8 milligrams per liter with a median concentration of 2.6 milligrams per liter. Results from the summer sampling period indicate a range of nitrite plus nitrate (as nitrogen) concentrations of less than 0.1 to 8.9 milligrams per liter, median, 2.5 milligrams per liter. The highest concentrations occurred in the shallowest wells, and, in one instance, in a shallow well near a heavily irrigated field.

Tennessee↗
USGS2026

USGS 2025 critical minerals review

The United States Geological Survey (USGS) provides scientific information for the Department of Interior and the nation, consistent with its original mission expressed in the Organic Act of 1879 (43 U.S.C. 31): “the classification of the public lands and examination of the geological structure, mineral resources, and products within and outside the national domain.” Legislation such as the Energy Act of 2020 and the 2022 Infrastructure Investment and Jobs Act (43 USC 31l) and recent executive actions (Executive Orders 14154 , 14153, 14241 Secretary’s Orders 3417, 3418, 3422, 3436) underscore the importance of mineral resources and focus USGS activities on mapping and assessing mineral resources, with a particular focus on those presently identified as critical, both in ground and above ground in mine wastes. This article reviews selected activities and accomplishments by the USGS Mineral Resources Program related to critical minerals in 2025. Highlights include a new List of Critical Minerals, a first-ever national mine waste inventory, international minerals partnerships, mineral resource assessment advancements, and national data collection activities and outcomes of the Earth Mapping Resources Initiative (Earth MRI). The selected contributions are not comprehensive but are intended to demonstrate USGS leadership in critical mineral mapping and assessment, the importance of domestic and global partnerships, and the breadth of research activities that are responsive to national needs and priorities.

Mining Engineering↗
USGS2026

Testing characteristic magnitude distributions in modern PSHA models

The characteristic magnitude distribution hypothesis predicts a higher rate of large earthquakes than a Gutenberg–Richter extrapolation of the small‐earthquake rate would imply. Characteristic magnitude distributions have been commonly applied to faults in probabilistic seismic hazard analysis (PSHA), and in modern models they can emerge from the way short‐term seismicity constraints are combined with long‐term geologic and geodetic constraints. We test the characteristic magnitude distribution hypothesis by comparing the fault‐based magnitude distributions from the 2023 update to the National Seismic Hazard Model (NSHM23) in the Western United States with observed seismicity over the past 93 yr. We find that observed magnitude distributions fall outside the model‐predicted confidence bounds in regions where NSHM23 produces characteristic magnitude distributions: in these regions, the model predicts higher rates of large earthquakes than are observed. An analysis of the earlier California model (Uniform California Earthquake Rupture Forecast, version 3) also reveals discrepancies between the modeled and observed magnitude distributions. In addition, we find that observed magnitude distributions near modeled faults are not significantly different from those in background regions. These results challenge the prevalence of characteristic magnitude distributions in fault‐based seismic hazard models and call for a reassessment of how disparate data sets are integrated in PSHA.

western United States↗
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↗
USGS2026

Spectral characteristics and mapping of lithium-rich playas in the Basin and Range Province, western United States

This report presents a comprehensive set of prospectivity maps for lithium in brines located within the playas of the Basin and Range Province of western United States. The prospectivity assessment is based on criteria established in the descriptive deposit model outlined in a previous U.S. Geological Survey report, with a focus on regional remote sensing methodologies. The playas within the study area have been systematically ranked according to several key factors, including size, the presence and abundance of source rocks, vegetation as an indicator of water availability, documented prospects, and data products derived from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor. Notably, the deposits in the playa of Clayton Valley make it stand out as the sole lithium brine-producing playa in the United States. The ASTER sensor provides optimal regional coverage, characterized by a 60-kilometer swath width and unique multispectral capabilities that are not available with other remote sensing instruments. This report and the accompanying maps are intended to serve as resources for further multidisciplinary assessments of lithium or other elements or commodities where prospectivity can be inferred from the presence of proxies such as alteration minerals.

Arizona, Baja California, California, Chihuahua, I↗
USGS2024

Classification of lakebed geologic substrate in autonomously collected benthic imagery using machine learning

Mapping benthic habitats with bathymetric, acoustic, and spectral data requires georeferenced ground-truth information about habitat types and characteristics. New technologies like autonomous underwater vehicles (AUVs) collect tens of thousands of images per mission making image-based ground truthing particularly attractive. Two types of machine learning (ML) models, random forest (RF) and deep neural network (DNN), were tested to determine whether ML models could serve as an accurate substitute for manual classification of AUV images for substrate type interpretation. RF models were trained to predict substrate class as a function of texture, edge, and intensity metrics (i.e., features) calculated for each image. Models were tested using a manually classified image dataset with 9-, 6-, and 2-class schemes based on the Coastal and Marine Ecological Classification Standard (CMECS). Results suggest that both RF and DNN models achieve comparable accuracies, with the 9-class models being least accurate (~73–78%) and the 2-class models being the most accurate (~95–96%). However, the DNN models were more efficient to train and apply because they did not require feature estimation before training or classification. Integrating ML models into benthic habitat mapping process can improve our ability to efficiently and accurately ground-truth large areas of benthic habitat using AUV or similar images.

Michigan, Wisconsin↗
USGS2025

A method to obtain remotely sensed grain size distributions from nonplanar granular deposits

Constraining the grain size distribution of granular deposits with complex surfaces is difficult with existing approaches. Field and laboratory techniques are time consuming and limited by the maximum grain size that laboratories can accommodate. In this study, we present a new method to identify the coarse fraction of the grain size distribution at a debris-flow fan deposit surveyed with terrestrial laser scanning (TLS) in Glenwood Canyon, Colorado, USA. This method is a novel grain segmentation algorithm developed for application to point cloud data of deposits with complex surfaces and angular grains ranging in size from centimeters to a meter. This approach combines an existing random forest machine learning method with a novel iterative clustering algorithm. We compared the grain size distribution from our algorithm with a Wolman pebble count conducted in the field, and found a root mean squared error of less than 2 cm from the 5th to 95th percentile of the grain size distribution of grains ranging from cobble to boulder sized (6.3–78 cm in our application). Finally, we compared our new algorithm with an existing open-source grain segregation algorithm, and our method outperformed the selected alternative when applied to the debris-flow deposit point cloud.

Colorado↗
USGS2026

Colored shaded-relief bathymetric and acoustic-backscatter maps of Jenkinson Lake with orthomosaic of the Sly Park Creek and Hazel Creek area, California

The Caldor Fire was ignited on August 14, 2021, and burned almost 222,000 acres (898 square kilometers) in forested terrain of the central and western Sierra Nevada, California. During the subsequent two months, the fire burned nearly all of Sly Park Creek watershed in El Dorado County. The El Dorado Irrigation District manages the water supply for the area using storage in Jenkinson Lake, a 1.6-kilometer- (1.0-mile-) wide and 3.6-kilometer- (2.2-mile-) long reservoir, located south of the town of Pollock Pines. Several weeks after the fire, the U.S. Geological Survey began investigations into post-fire landscape responses, including sediment yield, by measuring new sediment deposition in Jenkinson Lake. This study focused on the collection and processing of bathymetric and acoustic-backscatter data, as well as onshore aerial imagery in and around Jenkinson Lake, to support wildfire science after the Caldor Fire. A colored shaded-relief bathymetric map (sheet 1) and an acoustic backscatter map (sheet 2) show the lake floor morphology and backscatter intensities.

California↗
USGS2025

Long-term trends in microseismicity during operational shut-ins at the Coso Geothermal Field, California

Pausing injection and production can lead to induced seismicity in a variety of settings, with some of the largest events occurring during these so-called shut-ins. In geothermal fields, shut-ins are periodically conducted for maintenance on wells and surface infrastructure, thereby offering recurring means of estimating stress changes in the subsurface that lead to increased seismicity rates. Here, we examine daily production and microseismicity data from the Coso Geothermal Field (CGF) in California between 1996 and 2010 to investigate the repetitive trends of operational shut-in microseismicity. Using 24 local seismic stations, we first analyze spatial and temporal trends of over 60,000 earthquakes with magnitudes between -0.4 to 3.8. We find that the northern region exhibits no significant seismicity changes during shut-ins, whereas the rest of the field experiences induced seismicity during almost every shut-in with an increasing intensity towards the southern and eastern portions of the field, highlighting local differences in stress within the CGF. Additionally, we cluster the seismicity using waveform cross-correlation, revealing several earthquake clusters primarily occurring during shut-in periods. These observations suggest that certain fracture and fault sections respond quicker to changes in pore pressure and poroelastic stresses within the geothermal system, possibly highlighting main fluid pathways.

California↗
USGS2026

Production of mineral commodities and geospatial map of the mineral industries and related infrastructure of China

As part of the U.S. Geological Survey’s (USGS) mission to distribute global mineral information and analyze supply chains, this study provides a comprehensive review of the global significance of China’s mineral production and capacity in 2023. Of 77 mineral commodities in the USGS dataset, China produced 74 and was the world’s first-ranked producer for 39 of the 74. Compared to the high share of global mineral production, including up to 98 percent of global gallium production, the country’s share of global mineral reserves was relatively small, ranging from 20 percent (zinc ore) to 52 percent (tungsten ore). China’s imports of metal ores, slag, and ash accounted for 64 percent of global imports of such commodities by value. The country’s exports of base metals and articles of base metal accounted for 17 percent of the global exports. To help nongeographic information system users assess the spatial distribution of mineral mines, processing facilities, and ports for trades in China, this study created a geospatial (also called “georeferenced”) portable document format (GeoPDF) map. In addition, the GeoPDF contains mineral resource tracts (such as antimony, copper, potash, coal, and oil and gas), exploration sites, and energy infrastructure based on the preexisting USGS data.

Open-File Report↗
USGS2026

Understanding the resource potential of natural hydrogen on Earth: Scientific gaps, uncertainties and recommendations

A comprehensive scientific research roadmap is essential to bridge knowledge gaps and deepen the understanding of key geological, geochemical, and geophysical aspects of natural hydrogen (H 2 ) as a potential new energy resource. This paper reviews major scientific uncertainties on natural H 2 , suggesting research priorities, as a guide for defining exploration strategies, techniques, and data interpretation. The uncertainties concern all phases of the natural H 2 cycle, from generation (source rocks) through migration (advection and diffusion) and accumulation (reservoir and cap rocks) to the application and interpretation of subsurface and surface geochemical and geophysical exploration techniques. Understanding H 2 sources and generation rates (the amount of H 2 generated by a given volume of rock over time) is crucial for determining whether a geological H 2 system operates as a short-term dynamic system with rapid H 2 production and release, or as a conventional gas system with long-term accumulations, analogous to petroleum reservoirs. Preliminary estimates for serpentinisation, radiolysis, and organic matter degradation suggest that H 2 generation is not inherently fast, especially for non-hydrothermal continental systems (crystalline basement of shields, ophiolites, peridotite massifs, sedimentary basins), and long-term accumulations, like those of fossil natural gas systems, represent the most likely scenario. The mechanisms of H 2 migration through geological formations require application of fundamental principles of fluid-flow physics, distinguishing advection and diffusion, as well as their forms (from gas-phase, bubble flows to aqueous solutions). Additional studies of H 2 accumulation and retention in subsurface reservoirs could improve understanding of mechanisms of H 2 migration by focusing on the rock fluid-bearing properties and the factors affecting H 2 preservation, such as the presence of cap rocks impermeable to H 2 , pressure conditions, residence times, and microbial or abiotic consumption. Advanced techniques, including reservoir modelling, flow simulations, 3D imaging (micro-CT) of H 2 -bearing rocks, and extraction and analysis of gas occluded in rocks, can provide insights into the stability and potential recoverability of H 2 accumulations. The interpretation of surface exploration techniques, including gas geochemistry, geophysics, and remote sensing, long employed in mineral and energy resource exploration, is now being adapted for natural H 2 studies, but challenges remain in the data interpretation. Distinguishing H 2 seepage due to geological degassing from H 2 produced near the surface by modern microbial processes or artificial sources, such as hammering or drilling for soil-gas sampling, drilling into aquifers, and corrosion in boreholes, is an essential step in exploration. The simple detection of H 2 in soils, even in morphological structures like sub-circular depressions or “fairy circles”, cannot be cursorily interpreted as a signal of natural H 2 seepage from a deep source. A holistic geochemical approach, including isotopic analyses of gases associated with H 2 , is recommended to distinguish among the variety of possible H 2 origins. Observations of H 2 in wells should be interrogated to rule out possible artifacts such as corrosion and drill bit metamorphism. The integration of multiple geophysical methods, including seismic, gravimetric, magnetic, and electro-magnetic surveys, is recommended to mitigate interpretation ambiguities regarding the structure of a subsurface H 2 system (source and reservoir rocks, including fluid and gas storage), due to the non-uniqueness of rock-specific physical properties.

Earth-Science Reviews↗
USGS2026

Coastal barrier resilience and resistance: Analysis and metrics for characterizing coastal state

Barrier islands are shaped by a variety of short- and long-term environmental processes such as storms and relative sea-level rise. These islands, found along the estuarine-marine interface, provide ecosystem services including storm surge and wave attenuation, erosion protection to inland marshes, habitat for fish and wildlife, and recreation. Natural resource managers require actionable information on how barrier island resilience and resistance changes over time to understand how an island’s current state relates to past conditions and to inform restoration prioritization and implementation. The U.S. Geological Survey and The Water Institute collaborated on a study to develop indicators of resilience and resistance for barrier islands in Louisiana. Here, resilience captures island persistence on yearly to decadal time scales, and resistance captures persistence on event time scales of days to weeks. The indicators fall in two categories: Tier 1 Screening Metrics, that can be readily calculated from available data, are easily interpretable as an evaluation of barrier condition, and provide a high-level snapshot of overall barrier resilience and resistance; and Tier 2 Analysis Metrics, which are detailed metrics that required specialized analysis and interpretation and are more applicable to answering specific questions managers may have about barrier state. The research team derived Tier 1 resilience indicators from subaerial land and vegetation cover calculated from publicly available maps and products based on satellite imagery. By benchmarking the total land and vegetation extent against their respective historical maxima, this metric provides a snapshot of an island’s current state in the context of its long-term trajectory. The research team developed Tier 1 resistance indicators based on subaerial island configuration and water level recurrence as a proxy for evaluating island resistance to storms, which are the primary driver of short-term change. These Tier 1 metrics can be analyzed over time to provide a high-level assessment of how an island’s resistance decreases because of elevation loss or sea-level rise or increases due to restoration or natural recovery. The research team developed Tier 2 resilience and resistance indicators and associated analyses to provide detailed information for specific time periods or applications (e.g., wildlife management). These metrics include habitat coverage from high-resolution maps, which show composition changes over time to capture the evolving resilience of specific habitat types; high tide flooding analysis, which evaluate island area relative to specified flooding thresholds to characterize resistance in the short-term or, if analyzed over time, indicate changes in resilience; and hypsometric curve analysis, which allows managers to evaluate island area changes above their own elevation benchmarks of interest and similarly characterize resistance in the short-term or indicate changes in resilience if assessed over time. The research team calculated Tier 1 metrics of the barrier islands and headlands along the coast of Louisiana for the period of 1984 through 2021 and Tier 2 metrics for select times during that period depending on data available and quality. The results were captured in a report card for each barrier, which also includes an overview of the metrics and their interpretation; a restoration and storm history; and Tier 1 and Tier 2 metric analysis, including benchmarking against coastwide and regional values as well as to an island’s pre-restoration trajectory. These report cards provide a readily digestible synthesis of barrier condition and trajectory that coastal managers can use to support restoration prioritization and other decisions.

Louisiana↗
USGS2024

Interactive effects of salinity and hydrology on radial growth of bald cypress (Taxodium distichum (L.) Rich.) in coastal Louisiana, USA

Tidal freshwater forests are usually located at or above the level of mean high water. Some Louisiana coastal forests are below mean high water, especially bald cypress ( Taxodium distichum (L.) Rich.) forests because flooding has increased due to the combined effects of global sea level rise and local subsidence. In addition, constructed channels from the coast inland act as conduits for saltwater. As a result, saltwater intrusion affects the productivity of Louisiana’s coastal bald cypress forests. To study the long-term effects of hydrology and salinity on the health of these systems, we fitted dendrometer bands on selected trees to record basal area increment as a measure of growth in permanent forest productivity plots established within six bald cypress stands. Three stands were in freshwater sites with low salinity rooting zone groundwater (0.1–1.3 ppt), while the other three had higher salinity rooting zone groundwater (0.2–4.9 ppt). Water level was logged continuously, and salinity was measured monthly to quarterly on the surface and in groundwater wells. Higher groundwater salinity levels were related to decreased bald cypress radial growth, while higher freshwater flooding increased radial growth. With these data, coastal managers can model rates of bald cypress forest change as a function of salinity and flooding.

Louisiana↗
USGS2024

Development of USGS NSHMs: Do small changes in hazard imply small changes in risk?

One of the flagship products from the U.S. Geological Survey (USGS) is the National Seismic Hazard Model (NSHM). Since 1976, the NSHM has been periodically updated to reflect newly published earthquake science and provide probabilistic estimates of seismic hazard for the United States. During each update cycle, alternative models are deliberated, analyzed, and documented through logic trees and their corresponding logic tree branch weights. For example, the decision to modify a logic tree branch weight may be influenced by sensitivity analyses of the logic tree branches in their effects on the mean hazard. However, do small changes in traditional measures of hazard imply small changes in risk? In this study, we make use of two update cycles of the USGS NSHMs and a National Bridge Inventory (NBI) from the Federal Highway Administration (FHWA) to explore the preceding question. Specifically, we first identify geographic locations in the conterminous United States in which the change in hazard from one cycle to another is relatively small. Next, we model the seismic risk to highway bridges for these locations and for each update cycle, while simultaneously distinguishing low hazard environments from high hazard environments. These data enable quantitative analysis of how much changes in risk can be expected given small changes in hazard, investigating the importance of risk models in decision-making during development of the USGS NSHMs.

Conference Paper↗
USGS2023

3D Dynamic rupture modeling of the 6 February 2023, Kahramanmaraş, Turkey Mw 7.8 and 7.7 earthquake doublet using early observations

The 2023 Turkey earthquake sequence involved unexpected ruptures across numerous fault segments. We present 3D dynamic rupture simulations to illuminate the complex dynamics of the earthquake doublet. Our models are constrained by observations available within days of the sequence and deliver timely, mechanically consistent explanations of the unforeseen rupture paths, diverse rupture speeds, multiple slip episodes, heterogeneous fault offsets, locally strong shaking, and fault system interactions. Our simulations link both earthquakes, matching geodetic and seismic observations and reconciling regional seismotectonics, rupture dynamics, and ground motions of a fault system represented by 10 curved dipping segments and embedded in a heterogeneous stress field. The M w 7.8 earthquake features delayed backward branching from a steeply branching splay fault, not requiring supershear speeds. The asymmetrical dynamics of the distinct, bilateral M w 7.7 earthquake are explained by heterogeneous fault strength, prestress orientation, fracture energy, and static stress changes from the previous earthquake. Our models explain the northward deviation of its eastern rupture and the minimal slip observed on the Sürgü fault. 3D dynamic rupture scenarios can elucidate unexpected observations shortly after major earthquakes, providing timely insights for data‐driven analysis and hazard assessment toward a comprehensive, physically consistent understanding of the mechanics of multifault systems.

The Seismic Record↗
USGS2026

Geologic map of the Sierra Nevada, California and western Nevada

THE GEOLOGIC MAP OF THE SIERRA NEVADA is a core component of the Sierra Nevada Earth Science Atlas, which also includes geophysical, neotectonic, economic, and geochronologic data. The map illustrates the distribution of geologic units across the Sierra Nevada and related adjacent areas. Geologic units are grouped by type and age into three categories: Principally Paleozoic and Mesozoic metasedimentary and metavolcanic wall rocks, most of which are grouped into terranes; Paleozoic and Mesozoic plutons and intrusive suites, which intrude the wall rocks and form the core batholith of the range; and Late Cretaceous and Cenozoic sedimentary and volcanic rocks and surficial deposits that unconformably overlap the older units. Related rock units were combined and simplified for presentation at a scale of 1:400,000, as shown in the list of map units and associated correlation of map units (Plate 1B) and description of map units (Appendix A). Tectonic faulting, folding and uplift have overprinted the rocks and have strongly influenced the spatial distribution of units and the distinct morphology of the Sierra Nevada as we see it today. The Atlas is the result of collaborative work by scientists and mapmakers from the California Geological Survey and the U.S. Geological Survey. The Atlas was originally envisioned by the late geologist Warren Nokleberg (1939-2021), who contributed much to the initial geologic map compilation

California, Nevada↗