Bedrock geologic map of Organ Pipe Cactus National Monument and vicinity, southwest Arizona
No abstract available.
Arizona↗
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Results for “Scientific Investigations Map”
Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.
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Geophysical identification of potential groundwater – surface water interactions in the Bonita Peak Mining District, San Juan County, Colorado
This report includes the results and interpretation of geophysical investigations to aid in the location, identification, and conceptual site model (CSM) development of the near surface groundwater and surface water hydrology of the Upper Cement Creek and California Gulch of the Animas Rivers within the Bonita Peak Mining Districts (BPMD). Mine influenced water (MIW) from numerous mine adits within the BPMD has altered the geochemistry and ecology of these ground and surface waters. Many studies of varying scales have investigated the geology, hydrogeology, geochemistry, and aqueous chemistry of these adits and impacted areas. Field investigations using non-invasive geophysical methods were conducted in the summer of 2019 to aid in identifying potential groundwater inputs to these streams and further the CSM of the near surface within and along these streams. Two field deployments were completed in August and September of 2019. In August 2019, Phase 1 was completed using multifrequency electromagnetic induction (EMI) and thermal infrared imaging (TIR) to measure the bulk electrical conductivity, magnetic susceptibility, and the temperature response at known and suspected groundwater seeps into the Upper Cement Creek and California Gulch stretches of these alpine streams. Results and interpretation from Phase 1 were used to co-locate stretches of these streams for further detailed fiber optic distributed temperature system (FODTS) monitoring of the temperature dynamics for submeter identification of potential groundwater seeps during Phase 2. Phase 2 included additional EMI measurements, FODTS measurements, and repeated some Phase 1 measurements for improved data quality. All these data were used for the combined qualitative interpretation identifying seep locations. The data from both Phase 1 and Phase 2 are available in the USGS data release at: https://www.sciencebase.gov/catalog/item/5f18a30082cef313ed84879b. These data include detailed near-surface electrical conductivity and magnetic susceptibility mapping, discrete TIR imaging, and several kilometers of FODTS data. These data were georeferenced and used to identify potential groundwater seeps into these streams. The results indicate a complex near surface geophysical and hydrogeologic regime. Seeps are classified and spatially correlated to the EMI, TIR, and geochemical sampling results. This report is a thorough compilation of the geophysical field efforts in the summer of 2019, the data processing, and interpretations of these data. These data alone should not be used for final interpretations of the complex hydrogeology within these alpine systems. Rather, these data should be combined with other known data from various investigations to further refine the CSM and guide decisions for future investigations, watershed protective measures, and other site decisions. Geographical information system (GIS) layers of these results are available to project managers for such integration and combined interpretations.
Colorado↗
Bayesian mapping of regionally grouped, sparse, univariate earth science data
Some earth science data are naturally grouped by region, and it is often desirable to map these data by region. However, if there are only a few samples within each region, then the map should be smoothed in an appropriate way to mitigate the problems that arise from having only a few samples. A smoothing algorithm based on a Bayesian hierarchical model is developed and presented in this report. This algorithm has several features that make it especially suitable for mapping earth science data: it can account for measurements that are censored, it can process multiple datasets with different measurement errors and different censoring thresholds, and it can calculate the uncertainty in any statistic that is mapped. The algorithm is demonstrated by mapping gold concentrations that are measured in streambed sediments in the Taylor Mountains quadrangle in southwestern Alaska.
Alaska↗
Prospectivity modeling of the NASA VIPER landing site at Mons Mouton near the Lunar South Pole
We use a high-resolution digital elevation model and a numerical thermal model to produce a variety of inputs for a water-ice prospectivity model for the Volatiles Investigating Polar Exploration Rover (VIPER) landing site. These input data are maps of topography, surface slope, surface aspect, surface curvature, maximum temperature, depth to ice stability, permanently shadowed regions (PSRs), distance to PSRs, and PSR density. This model predicts where water ice is most likely within the top meter of regolith, assuming plausible relationships between ice concentration and the various inputs. The model is designed to be adjusted in near-real time as data are collected during the VIPER mission. As such, it is a tool for both analyzing data from the mission as well as planning operations. Since the current model, at this point, relies only on orbital remote sensing, the final version will also be a tool to extrapolate the VIPER mission results across the lunar poles.
Planetary Science Journal↗
Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning
Accurate, high-resolution maps of bedrock outcrops can be valuable for applications such as models of land–atmosphere interactions, mineral assessments, ecosystem mapping, and hazard mapping. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock outcrop maps. In the United States, the existing 30 m U.S. Geological Survey (USGS) National Land Cover Database (NLCD) tends to misestimate extents of barren land, which includes bedrock outcrops. This impacts many calculations beyond bedrock mapping, including soil carbon storage, hydrologic modeling, and erosion susceptibility. Here, we tested if a machine learning (ML) model could more accurately map exposed bedrock than NLCD across the entire Sierra Nevada Mountains (California, USA). The ML model was trained to identify pixels that are likely bedrock from 0.6 m imagery from the National Agriculture Imagery Program (NAIP). First, we labeled exposed bedrock at twenty sites covering more than 83 km 2 (0.13%) of the Sierra Nevada region. These labels were then used to train and test the model, which gave 83% precision and 78% recall, with a 90% overall accuracy of correctly predicting bedrock. We used the trained model to map bedrock outcrops across the entire Sierra Nevada region and compared the ML map with the NLCD map. At the twenty labeled sites, we found the NLCD barren land class, even though it includes more than just bedrock outcrops, accounted for only 41% and 40% of mapped bedrock from our labels and ML predictions, respectively. This substantial difference illustrates that ML bedrock models can have a role in improving land-cover maps, like NLCD, for a range of science applications.
California↗
Using surficial geologic maps, vegetation, and monitoring to address erosion impacts from grazing in Channel Islands National Park, California
Employing a map-unit classification scheme based on geomorphic process and age, the U.S. Geological Survey (USGS) mapped Quaternary surficial deposits of the five islands comprising Channel Islands National Park (CHIS), California, as no such maps previously existed. Mapping was motivated through an agreement with the National Park Service (NPS) to aid natural resource assessments, including post-grazing disturbance recovery and identification of mass wasting and tectonic hazards. The resulting detailed (1:12,000 scale) maps portray areas of upland erosional transport processes and alluvial, fluvial, eolian, beach, marine terrace, mass wasting, and mixed depositional processes at a scale commensurate with the process signal on the landscape. Detailed, GPS-located observations of sedimentology, pedogenic development, landscape position, and geomorphology constrain map unit identification. In addition, map-unit boundary delineation was determined in a GIS using a variety of high-resolution (sub-meter) aerial imagery and lidar-based DEMs complemented by derivative raster products. The GIS geodatabase schema used is GeMS compliant. Resolvable map-unit widths are as small as 10-15 meter. Locational accuracy of unit boundaries is estimated to be as low as 10 m or better. Detailed mapping is at a scale allowing determination of geomorphic transport processes operating on the landscape and conveys geologic information to land managers at a resolution commensurate with park resources. Map unit ages are constrained by relative soil chronostratigraphy, vertebrate and invertebrate fossils, and materials collected for dating control using radiogenic, luminescence, and cosmogenic radionuclide techniques. Associated topical studies examined connections between geology, surface water, and vegetation distribution and restoration.
California↗
Airborne radiometric data map alteration of porphyry copper systems in the Elkhorn district, MT
The Elkhorn district in southwestern Montana is known for past production of high-grade base and precious metals from skarn and carbonate replacement deposits. The district also hosts a porphyry Cu-Mo deposit. A radiometric survey flown over the district and surrounds provides maps of surficial concentrations of potassium, thorium, and uranium. Handheld gamma ray spectrometer measurements on altered and unaltered rocks in the district and surrounding region provide a means to ground truth the airborne data. We demonstrate that the airborne and ground-based measurements show similar map patterns. We calculate ratios of the radioelement concentrations and present a potassium enhancement map that combines potassium and ratios of potassium to thorium and uranium. The results highlight the rocks previously mapped as having K-feldspar-biotite and quartz-sericite alteration assemblages in the Elkhorn district and map additional hydrothermal systems in the region, including known alteration in the Radersburg district. The data enhancement techniques can be used as a screening tool for mapping additional porphyry copper systems.
Montana↗
Bathymetric and acoustic-backscatter mapping of Lake Sammamish, Washington, during USGS field activity 2021-656-FA
In 2021, scientists from the U.S. Geological Survey (USGS) acquired bathymetric and acoustic-backscatter data within Lake Sammamish, Washington. Mapping was completed to find evidence of past earthquakes such as underwater landslides and is part of a larger USGS project to understand the overall geologic hazards history of the Cascadia Margin region. The survey was conducted using the USGS research vessel Parke Snavely outfitted with an interferometric sidescan-sonar system for swath mapping. Three estimates of bathymetric uncertainty were calculated from the post-processed bathymetric data. This report provides a summary of the mapping mission.
Washington↗
Assessment of density pattern retention of generalized data for 1:100,000-scale United States topographic maps
Cartographic generalization reduces the complexity of geographic data to produce legible, smaller-scale displays that retain essential information and logical geographic patterns. Generalization is a vital process in topographic map production. An important challenge in this process is managing and evaluating consistency across scale in the density and spatial distribution of map features such as buildings, roads, streams, water bodies, and elevation contours. Density patterns in these features reflect underlying physiographic conditions, which include factors such as bedrock geology, tectonics, climate, and landforms. Assessments of an acceptable level of change in feature density patterns are critical to ensuring the readability, usability, and accuracy of generalized maps and data. Preserving realistic density patterns across mapping scales also supports sustainable development goals in cartography, by helping to prioritize and communicate the relative reliability of geospatial data at specific scales.
Conference Paper↗
The National Map Corps—Federal Emergency Management Agency and Oak Ridge National Laboratory pilot project report
This report provides an overview of the U.S. Geological Survey National Map Corps —Federal Emergency Management Agency and Oak Ridge National Laboratory pilot project in St. James Parish, Louisiana, that began in February 2024 and ended at the end of March 2024. The project used the power of The National Map Corps’ volunteer community to improve building classifications in the original Federal Emergency Management Agency’s U.S.A. Structures dataset. The report highlights the project’s completion and details the work and results achieved through a collaborative effort to enhance geospatial data quality and utility.
Open-File Report↗
Seamless Geologic Map Database for the Intermountain West, United States: A foundational dataset for mineral systems analysis
The Intermountain West has a complex geologic history, resulting in the formation of a diverse array of mineral deposits. Effective mineral exploration requires understanding the spatial and temporal relationships among geologic processes and events, a key focus of the mineral systems approach to exploration. This paper presents the Intermountain West Seamless Geologic Map Database, a unified dataset designed to support mineral exploration. Integrating geologic provinces, structural settings, and hydrothermal alteration, the database leverages the Seamless Integrated Geologic Mapping (SIGMa) extension to the USGS Geologic Map Schema (GeMS) to standardize geologic data from varied sources. SIGMa's hierarchical stratigraphic organization and feature-level metadata enhance data interoperability and reusability, enabling seamless query, analysis, and visualization of lithology, structural features, mineral deposits, geochronology, hydrothermal alteration. volcanic activity, and By providing a regionally consistent and dynamically evolving geologic map, this database provides a foundational framework for mineral exploration and geologic research. It also allows for an efficient workflow that expedites the publication of integrated geologic map databases.
Conference Paper↗
Ground-water quality atlas of Oakland County, Michigan
The U.S. Geological Survey (USGS), in cooperation with Oakland County Health Division (OCHD), collected 140 water samples from 38 wells in Oakland County during 1998 to better understand ground-water quality. OCHD had observed temporal variations in concentrations of various constituents, so two additional sets of samples were collected to evaluate potential short-term variability related to sample collection procedures and long-term seasonal variability. Replicate samples from 28 wells were analyzed in the Michigan Department of Environmental Quality (MDEQ) Drinking Water Laboratory to compare MDEQ’s analytical results to those obtained from the USGS National Water Quality Laboratory. Several additional databases describing population, land use, water supply, soils, geology, and flows of ground water and surface water are presented in the first part of the report to assist in interpreting the water-quality data. Maps created from these databases are provided in the first portion of the report as an extension of the study-area description. The U.S. Environmental Protection Agency (USEPA) has established Maximum Contaminant Levels (MCL) and Secondary Maximum Contaminant Levels (SMCL) for which samples were analyzed in this study. Water from the 38 wells sampled by the USGS did not exceed the SMCL or MCL for sulfate, fluoride, or nitrite. However, water from 26 wells exceeded the SMCL for iron, water from 12 wells exceeded the SMCL for manganese, and water from 12 wells exceeded the SMCL for dissolved solids. Water from two wells exceeded the MCL for nitrate, although nitrate concentrations in water from most wells was below the detection limit. Water from seven wells exceeded the SMCL for chloride, and water from all wells contained detectable concentrations of chloride. Water from five wells exceeded the MCL for arsenic, and most of the wells sampled contained detectable concentrations of arsenic. These five wells were identified from previous MDEQ analyses to have elevated arsenic concentrations, and were sampled to obtain additional chemistry information. Replicate samples were collected from 26 of the 38 wells for analysis at the MDEQ Drinking-Water Laboratory to compare the results with the USGS National Water Quality Laboratory. The results of the replicate analyses indicate close agreement between the laboratories, with mean differences for nitrate, chloride, and arsenic of 0.10 milligrams per liter (mg/L) as nitrogen, 6.8 mg/L, and 0.0008 mg/L, respectively between the USGS and MDEQ analyses. Potential health effects associated with ingesting nitrate, chloride, and arsenic are provided with the water-quality data, along with references for further information.
Michigan↗
A synthesis engine for constructing geologic maps of the United States
The geologic history of the United States is cataloged in thousands of geologic maps produced during many decades. However, the disparate nature of these individual maps makes it challenging to assess resources, research geologic histories, or characterize natural hazards holistically across the Nation. The U.S. House of Representatives 2020 appropriations bill for the U.S. Department of the Interior (H.R. 116-100) requires the U.S. Geological Survey to “bring together detailed national and continental-resolution [two-dimensional] and [three-dimensional] information produced throughout the Survey and by [F]ederal and [S]tate partners.” In response to this directive, this report presents a compilation and synthesis of geologic maps across the United States in the form of a relational database. The synthesis database includes thematic maps that synthesize the Nation’s geology, and retains the original input maps as well as linkages to standardized vocabularies to aid the discoverability of geologic information. Specifically, the synthesis database is targeted toward producing four National-resolution maps for the conterminous United States: Quaternary geology, the geology at the Earth’s surface, pre-Quaternary geology, and Precambrian geology. In addition, the synthesis database includes the infrastructure necessary to expand to additional resolutions in the future.
conterminous United States↗
Extracting data from maps: Lessons learned from the artificial intelligence for critical mineral assessment competition
The U.S. Geological Survey (USGS), Defense Advanced Projects Research Agency (DARPA), NASA Jet Propulsion Laboratory (JPL), and MITRE ran a 12-week machine learning competition aimed at accelerating development of AI tools for critical mineral assessments. The Artificial Intelligence for Critical Mineral Assessment Competition solicited innovative solutions for two challenges: 1) automated georeferencing of historical maps, and 2) automated feature extraction from historical maps. Competitors used a new dataset of historical map images to train, validate, and evaluate their models. Automated georeferencing pipelines attained a median root-mean square error of 1.1 km. Prompt-based extraction (i.e., with user input) of polygons, polylines, and points from geologic maps yielded median F1-scores of 0.77, 0.56, 0.35, respectively. Geologic maps pose numerous challenges for AI workflows because they vary significantly. However, despite its short duration, the competition yielded promising results that have since spurred further innovation in this area and led to the development of new AI tools to semi-automate key, time-consuming parts of the assessment workflow.
Applied Computing and Geosciences↗
The U.S. Geological Survey, the U.S. Department of Defense, and the U.S. Intelligence Community—100 years of mapping and remote sensing collaboration, 1879–1979
Introduction The U.S. Geological Survey (USGS)—a Federal civilian agency—and U.S. military and intelligence agencies collaborate on mapping and remote sensing and have since the establishment of the USGS. The organizations exchange data and information and share technology to further their respective missions in service to the American people. Often referred to as examples of “good government” or “whole of government,” the collaboration avoids costly duplication and maximizes time and effort for the government sectors. Collaboration between these sectors started with the original mapping of the United States and evolved to include remote sensing after the advent of aerial photography and satellite imagery.
Circular↗
A review of abrupt permafrost thaw: Definitions, usage, and a proposed conceptual framework
Purpose of Review We review how ‘abrupt thaw’ has been used in published studies, compare these definitions to abrupt processes in other Earth science disciplines, and provide a definitive framework for how abrupt thaw should be used in the context of permafrost science. Recent Findings We address several aspects of permafrost systems necessary for abrupt thaw to occur and propose a framework for classifying permafrost processes as abrupt thaw in the future. Based on a literature review and our collective expertise, we propose that abrupt thaw refers to thaw processes that lead to a substantial persistent environmental change within a few decades. Abrupt thaw typically occurs in ice-rich permafrost but may be initiated in ice-poor permafrost by external factors such as hydrologic change (i.e., increased streamflow, soil moisture fluctuations, altered groundwater recharge) or wildfire. Summary Permafrost thaw alters greenhouse gas emissions, soil and vegetation properties, and hydrologic flow, threatening infrastructure and the cultures and livelihoods of northern communities. The term ‘abrupt thaw’ has emerged in scientific discourse over the past two decades to differentiate processes that rapidly impact large depths of permafrost, such as thermokarst, from more gradual, top-down thaw processes that impact centimeters of near-surface permafrost over years to decades. However, there has been no formal definition for abrupt thaw and its use in the scientific literature has varied considerably. Our standardized definition of abrupt thaw offers a path forward to better understand drivers and patterns of abrupt thaw and its consequences for global greenhouse gas budgets, impacts to infrastructure and land-use, and Arctic policy- and decision-making.
Current Climate Change Reports↗
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↗
Updated three-dimensional temperature maps for the Great Basin, USA
As part of the periodic update of the geothermal energy assessments for the USA (e.g., last update by Williams and others, 2008), a new three-dimensional temperature map has been constructed for the Great Basin, USA. Williams and DeAngelo (2011) identified uncertainty in estimates of conductive heat flow near land surface as the largest contributor to uncertainty in previously published temperature maps. The new temperature maps incorporate new conductive heat flow estimates developed by DeAngelo and others (2023). Predicted temperatures at depth are compared with representative measurements (for conductively dominated conditions), showing good agreement under relatively simple uniform conditions. Inputs included radiogenic heat production for all layers of 1.89 μW/m 3 , effective bulk thermal conductivity of 2.7 W/m/°C for all rocks underlying sedimentary basins, and a previously published (Williams and DeAngelo, 2011) empirically driven estimate of increasing thermal conductivity with depth in sedimentary sequences. The resulting three-dimensional temperature model is published in a USGS data release associated with this manuscript (Burns and others, 2023).
Arizona, California, Idaho, Nevada, Oregon, Utah↗