Search NASA⌕ Search

SEARCH · Search NASA

Results for “GEOLOGICAL SURVEYS”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

MRCI - Final Technical Report

The objective of the Midwest Regional Carbon Initiative (MRCI) project was to implement a collaborative Regional Initiative to accelerate the deployment of carbon capture, utilization, and storage (CCUS) in the Midwest-Northeastern and Mid-Atlantic areas of the United States. This area encompasses a 20-state region with much of the country’s carbon dioxide (CO2) emissions. The MRCI project is co-led by Battelle Memorial Institute (Battelle) in Columbus, Ohio, and the Illinois State Geological Survey (ISGS) in Champaign, Illinois, and benefitted from the experience these organizations have acquired over the past 10-plus years leading two Department of Energy (DOE) Regional Carbon Sequestration Partnerships (RCSPs): the Midwestern Regional Carbon Sequestration Partnership (MRCSP), led by Battelle, and the Midwest Geologic Sequestration Consortium (MGSC), led by the ISGS.

CCS↗
DOE OSTI2020

GBCGE Subsurface Database Explorer and APIs

This submission defines a DOI for the Great Basin Center for Geothermal Energy's (GBCGE) Subsurface Database Explorer web application and underlying data services, and acknowledges the INGENIOUS project as a major source of funding for data compilation and quality assurance. The GBCGE Subsurface Database Explorer is an interactive web mapping application that provides public access to the GBCGE Subsurface Database, and its collection of datasets pertinent to geothermal exploration, oil and gas exploration, critical mineral exploration, and other subsurface characterization for the Great Basin Region, western US. This is a living database, and will be continuously updated with new data and datasets as funding and motivations allow. The underlying database views that populate the web application are on an automated refresh schedule. Data sources and acknowledgements: We thank our partners with the Nevada Division of Minerals (NDOM), the Southern Methodist University (SMU), and Great Basin State Geological Surveys for their active efforts in data curation, schema design, and quality assurance. We also thank contributors among the USGS, Oregon Institute of Technology, State Divisions of Water Resources, State Divisions of Oil, Gas, and Minerals, and State Geological Surveys for open data availability and direct contributions made under the National Geothermal Data System (NGDS).

15 GEOTHERMAL ENERGY↗
NASA NTRS2010

Monitoring Coastal Marshes for Persistent Flooding and Salinity Stress

Our objective is to provide NASA remote sensing products that provide inundation and salinity information on an ecosystem level to support habitat switching models. Project born out of need by the Coastal Restoration Monitoring System (CRMS), joint effort by Louisiana Department of Natural Resources and the U.S. Geological Survey, for information on persistence of flooding by storm surge and other flood waters. The results of the this work support the habitat-switching modules in the Coastal Louisiana Ecosystem Assessment and Restoration (CLEAR) model, which provides scientific evaluation for restoration management. CLEAR is a collaborative effort between the Louisiana Board of Regents, the Louisiana Department of Natural Resources (LDNR), the U.S. Geological Survey (USGS), and the U.S. Army Corps of Engineers (USACE). Anticipated results will use: a) Resolution enhanced time series data combining spatial resolution of Landsat with temporal resolution of MODIS for inundation estimates. b) Potential salinity products from radar and multispectral modeling. c) Combined inundation and salinity inputs to habitat switching module to produce habitat switching maps (shown at left)

Kalcic, Maria↗
DOE OSTI2024

Computed Tomography Scanning and Petrophysical Measurements of Oriskany Core across Eastern Ohio

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) in Morgantown, West Virginia were used to characterize core material from three Ohio wells. These wells are listed below along with their American Petroleum Institute (API) and Ohio Geological Survey (OGS) identification numbers: - New York Central System 1 well (API 34085200170000, OGS Core 855) - Herren Well (API 34099201650000, OGS Core 2914) - Garvin-King Well (API 34121215610000, OGS Core 2939) The primary impetus of this work was to capture a detailed digital representation of the available core from all three wells. The collaboration between the U.S. Department of Energy’s (DOE) NETL and the Ohio Department of Natural Resources, Division of Geological Survey enables other research entities to access information about this potential carbon storage location and its surrounding formations.

58 GEOSCIENCES↗
DOE OSTI2025

Overview of the SCEC/USGS Community Stress Drop Validation Study Using the 2019 Ridgecrest Earthquake Sequence

We present initial findings from the ongoing Community Stress Drop Validation Study to compare spectral stress-drop estimates for earthquakes in the 2019 Ridgecrest, California, sequence. This study uses a unified dataset to independently estimate earthquake source parameters through various methods. Stress drop, which denotes the change in average shear stress along a fault during earthquake rupture, is a critical parameter in earthquake science, impacting ground motion, rupture simulation, and source physics. Spectral stress drop is commonly derived by fitting the amplitude-spectrum shape, but estimates can vary substantially across studies for individual earthquakes. Sponsored jointly by the U.S. Geological Survey and the Statewide (previously, Southern) California Earthquake Center our community study aims to elucidate sources of variability and uncertainty in earthquake spectral stress-drop estimates through quantitative comparison of submitted results from independent analyses. The dataset includes nearly 13,000 earthquakes ranging from M 1 to 7 during a two-week period of the 2019 Ridgecrest sequence, recorded within a 1° radius. Here, in this article, we report on 56 unique submissions received from 20 different groups, detailing spectral corner frequencies (or source durations), moment magnitudes, and estimated spectral stress drops. Methods employed encompass spectral ratio analysis, spectral decomposition and inversion, finite-fault modeling, ground-motion-based approaches, and combined methods. Initial analysis reveals significant scatter across submitted spectral stress drops spanning over six orders of magnitude. However, we can identify between-method trends and offsets within the data to mitigate this variability. Averaging submissions for a prioritized subset of 56 events shows reduced variability of spectral stress drop, indicating overall consistency in recovered spectral stress-drop values.

58 GEOSCIENCES↗
NASA NTRS2001

Hyperspectral Technology Transfer to the US Department of Interior: Summary of Results of the NASA/DOI Hyperspectral Technology Transfer Project

In 1997 the Office of Biological Informatics and Outreach (OBIO), Biological Resources Division, US Geological Survey and NASA, Office of Earth Science (OES), initiated a coordinated effort for applying Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) data and analysis, as a technology transfer project, to critical DOI environmental issues in four study sites throughout the United States. This work was accomplished by four US Department of the Interior (DOI) study teams with support from NASA/OES principal investigators and the Office of Earth Science programs. The studies, including personnel, objectives, background, project plans, and milestones were documented in a project website at . This report summarizes the final outcomes of the project, detailing accomplishments, lessons learned, and benefits realized to NASA, the US Geological Survey, and the participating DOI bureaus.

Root, Ralph↗
DOE OSTI2025

HydroBio: Hydropower Capacity and Freshwater Biodiversity in Conterminous United States Sub-basins

This dataset summarizes existing and potential hydropower capacity and freshwater biodiversity at the sub-basin level throughout the conterminous United States (CONUS). It contains descriptive information regarding each sub-basin (e.g., 8-digit hydrologic unit code identifier, name, states, and size) along with sub-basin-level summaries of: 1) existing hydropower capacity (MW), 2) potential nominal non-powered dam (NPD) capacity (MW), 3) potential capacity of new stream reach development (NSD) (MW), and 4) freshwater biodiversity, including the total richness of fish, crayfish, and mussels and metrics that account for how rare and threatened those species tend to be. Hydropower data were obtained from Oak Ridge National Laboratory data resources (Existing Hydropower Assets, Non-Powered Dam Technical Potential, and New Stream Reach Development). Freshwater biodiversity data were obtained from NatureServe. Sub-basin characteristic information was obtained from the United States Geological Survey. Additionally, long data that provide lists of unique elements within each sub-basin for each constituent data resource (e.g., NatureServe, Existing Hydropower Assets) are provided to enhance dataset utility for users. The dataset provides, for the first time, a national-level assessment of existing and potential hydropower capacity in the context of freshwater biodiversity and is a valuable resource for stakeholders tasked with providing affordable, reliable energy to the American public while maintaining or enhancing invaluable freshwater resources. The dataset contains six data files in comma separated (*.csv) format that are within a zipped file.

Bozeman, Bryan [Oak Ridge National Laboratory (ORN↗
DOE OSTI2025

Streamflow Response to Glacier Mass Loss Varies With Basin Precipitation Across Alaska

Abstract Diminishing glaciers affect streamflow, and given the extent of glaciers in Alaska and adjacent Canada, continued glacier mass loss is likely to have profound effects on ecosystems sensitive to runoff. The effects of glacier mass loss on streamflow are likely to vary across the wide ranges of basin size, glacier cover, and precipitation in this region. In this study, we use U.S. Geological Survey (USGS) streamflow data with satellite‐based glacier volume change estimates to quantify how glacier mass loss subsidized streamflow over the 2000–2019 period for 116 glacierized basins. We examine interannual variability in that subsidy at three USGS‐monitored glaciers to explore the ability of the subsidy to buffer streamflow derived solely from precipitation. We found the relative importance of percent glacier cover on streamflow magnitude increases in drier basins. In the driest basins, glaciers produced 40 times greater percent glacier mass loss subsidies to streamflow for the percent glacier cover compared to the wettest basins. While the subsidy from glacier mass loss buffers interannual variability in streamflow to varying degrees, it can also increase streamflow variability. Smaller amounts of percent glacier cover are needed to produce summer‐melt‐dominated seasonal flow regimes in drier basins than in wetter basins. Decreasing glacier cover will eventually decrease summer streamflow, increasing spring streamflow in drier basins, and attenuating seasonality with increasing spring and autumnal streamflow in wetter basins. Quantifying the downstream effects of continued glacier mass loss without the computational expense of a hydrological model is broadly applicable in this changing climate.

Curran, Janet H. [U.S. Geological Survey Alaska Sc↗
NASA NTRS1976

Use of remote sensing techniques for geological hazard surveys in vegetated urban regions

The feasibility of using aerial photography for lithologic differentiation in a heavily vegetated region is investigated using multispectral imagery obtained from LANDSAT satellite and aircraft-borne photography. Delineating and mapping of localized vegetal zones can be accomplished by the use of remote sensing because a difference in morphology and physiology results in different natural reflectances or signatures. An investigation was made to show that these local plant zones are affected by altitude, topography, weathering, and gullying; but are controlled by lithology. Therefore, maps outlining local plant zones were used as a basis for lithologic map construction.

Stow, S. H.↗
NASA NTRS2012

A Survey of Geologic Resources

This chapter focuses on the resources available from the Moon itself: regolith, geologically concentrated materials, and lunar physical features that will enable habitation and generation of power on the surface. This chapter briefly covers the formation of the Moon and thus the formation of the crust of the Moon, as well as the evolution of the regolith. The characteristics of the regolith are provided in some detail, including its mineralogy and lithology. The location of high concentrations of specific minerals or rocks is noted. Other ideal locations for in situ resource utilization technology and lunar habitation are presented. This chapter is intended to be a brief review of current knowledge, and to serve as a foundational source for further study. Each concept presented here has a wealth of literature associated with it; the reader is therefore directed to that literature with each discussion. With great interest in possible manned lunar landings and continued study of the Moon by multiple satellites, the available information changes regularly.

Edmonson, Jennifer↗
DOE OSTI2024

SCEC/USGS Community Stress-Drop Validation Study: How Spectral Fitting Approaches Influence Measured Source Parameters

Spectral source parameters used to estimate an earthquake’s stress drop (⁠Δσ⁠) can vary significantly across measurement approaches. The Statewide California Earthquake Center/U.S. Geological Survey Community Stress‐Drop Validation Study was initiated to compare source parameter estimates, focusing initially on a dataset from the 2019 Ridgecrest earthquake sequence. As part of that validation effort, here we focus on one potential source of uncertainty: whether spectral fitting approaches alone, applied to a common set of spectra from the 2019 Ridgecrest sequence result in different source parameter estimates. By using a common set of benchmark spectra analyzed across a consistent frequency band of 1–40 Hz, we eliminate many sources of variability. A subgroup of validation study participants volunteered to estimate the low‐frequency displacement (⁠Ω 0 ⁠) and corner frequency (⁠ƒ c ⁠) by fitting a smooth function to benchmark displacement spectra. Participants used linear‐ or log‐sampled spectra, assumed a Brune or Boatwright spectral model, and applied different misfit criteria. We compare 17 approaches used to estimate ⁠Ω 0 ⁠, ƒ c ⁠, and Δσ for 54 earthquake spectra. Our results reveal that 35% of events have Δσ estimates within a factor of two, whereas others exhibit variations exceeding an order of magnitude. The variability in and can largely be attributed to whether a spectrum is consistent with the smooth function of an idealized simple crack model. The trade‐off between Ω 0 and ƒ c may be more pronounced when using linearly sampled spectra, as higher frequency spectral bumps control the fits. As expected, methods that assumed a Boatwright model tended to have lower Ω 0 and somewhat higher ƒ c compared to those assuming a Brune model, although resulting Δσ estimates are similar. Finally, when compared to the overall validation study results, the fitting approach alone may account for between 5% and 90% (25% on average) of the total variability in spectral Δσ⁠.

58 GEOSCIENCES↗
NASA NTRS1974

Techniques for computer-aided analysis of ERTS-1 data, useful in geologic, forest and water resource surveys

Forestry, geology, and water resource applications were the focus of this study, which involved the use of computer-implemented pattern-recognition techniques to analyze ERTS-1 data. The results have proven the value of computer-aided analysis techniques, even in areas of mountainous terrain. Several analysis capabilities have been developed during these ERTS-1 investigations. A procedure to rotate, deskew, and geometrically scale the MSS data results in 1:24,000 scale printouts that can be directly overlayed on 7 1/2 minutes U.S.G.S. topographic maps. Several scales of computer-enhanced "false color-infrared" composites of MSS data can be obtained from a digital display unit, and emphasize the tremendous detail present in the ERTS-1 data. A grid can also be superimposed on the displayed data to aid in specifying areas of interest.

Hoffer, R. M.↗
DOE OSTI2021

Utah FORGE Updated Well, Well Pad, and Seismic Station GPS Coordinates December, 2021

This is a CSV spreadsheet containing UTM and Latitude and Longitude coordinates and elevations for Wells 78-32, 78B-32, 56-32, 58-32, 68-32, and 16A(78)-32 and seismic stations BOR1, BOR2, BOR3, FOR1, FOR2, FOR5, FOR6, FOR 7, FOR8, FORK, FORU, FORW, and FORB. These are from a GPS survey conducted by the Utah Geological Survey completed in December, 2021.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Improving Building Footprint Extraction Using NAIP and 3DEP Lidar Derived Features with Deep Learning

Accurate building footprint extraction is critical for applications ranging from population estimation to disaster management. Although optical imagery provides detailed spectral information, it often struggles with shadows, occlusions, and background clutter in dense urban environments. Lidar data, by contrast, offer precise elevation and structural attributes but face challenges such as variable point density and noise. This study integrates multispectral imagery from the U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) with lidar-derived feature height and intensity from the U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) to improve footprint extraction using a U-Net–based deep learning model. A six-band input stack (RGB, near-infrared, height, intensity) was developed, normalized, and tiled for training and evaluation against Microsoft Global Building Footprints (GBF). Results from the Houston, TX test site show that the six-band model achieved a precision of 0.86, recall of 0.88, F1 score of 0.87, and Intersection-over-Union (IoU) of 0.76, consistently outperforming four-band baselines by reducing false positives while maintaining sensitivity. Predictions on withheld Houston tiles confirmed strong within-region generalization, yielded a precision of 0.78, recall of 0.81, F1 score of 0.79, and IoU of 0.66. Qualitative analysis further revealed limitations stemming from both training label quality and vegetation–building confusion. These findings demonstrate the complementary value of integrating spectral and structural information for robust building footprint extraction and how domain adaptation strategies can be used to enhance cross-regional transferability.

Liu, Jung Kuan [United States Geological Survey (U↗
DOE OSTI2025

Computed Tomography Scanning and Geophysical Measurements of the Clinton Formation in Ohio

Computed tomography and multi-sensor core logging of core material from twelve Ohio wells held by the Ohio Department of Natural Resources, Division of Geological Survey to make publicly available core information from the Early Silurian Clinton Formation in Eastern Ohio. Describes data available can be accessed from NETL’s Energy Data eXchange (EDX) online system, https://edx.netl.doe.gov/dataset/ct-and-geophysical-data-of-ohio-clinton-sands.

58 GEOSCIENCES↗
DOE OSTI2025

Alabama Carbon Storage: Bringing Data to the People

The Gulf Coastal Plain of Alabama has proven potential for geologic carbon storage and current interest in the area for large carbon capture and storage (CCS) projects is high. Extensive CCS relevant data exist in the records of the Geological Survey of Alabama and State Oil and Gas Board of Alabama, however, most of this data is not publicly available or is scattered in separate databases, file cabinets, and tables in publications. The “Alabama Carbon Storage: Data Sharing and Engagement” (ACS-DSE) project seeks to accelerate the responsible development of large CCS projects in the Gulf Coastal Plain of Alabama and offshore in state waters through a publicly accessible database of geologic carbon storage models and data across the region. The ACS-DSE draws on the over 150 years of geologic research and over 20 years of experience in CCS research to place relevant geologic, geophysical, and infrastructure data on a single web platform. Datasets available will include formation depths and elevations, geologic structures, reservoir properties, digital well logs (LAS files), existing penetrations, and geologic models. In addition to downloadable datasets, links to CCS related regulatory agencies and other sources of information will be included (for example, Class VI UIC permitting regulations and pipeline regulations). By making these datasets and models available in commonly used formats on a public website, the project will increase transparency in decision making and decrease the data acquisition time for industry.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Utah FORGE: Updated Phase 2C Well Location Coordinates

Utah FORGE has been established to develop, test, and improve the technologies and techniques required to develop EGS-type geothermal resources. Drilling of the first of two deep deviated wells, 16A(78)-32, will begin in the second half of 2020. This well will serve as the injection well for the injection-production well pair that will form the heart of the laboratory. This submission contains an archive of well location data within the Roosevelt Hot Springs geothermal area. An Excel spreadsheet is included containing updated GPS data for Utah FORGE wells drilled during Phase 2C (56-32, 68-32, 78-32). This data was collected over time by the Utah Geological Survey and contains all coordinates collected and the final averaged XY coordinates in both Longitude and Latitude and UTM Zone 12, NAD83. Elevation is also included. GIS shapefiles with well points are provided in the archive.

15 GEOTHERMAL ENERGY↗