Skip to main content
U.S. flag

An official website of the United States government

Margaret A Goldman

Margaret Goldman is a Physical Scientist with the Geology, Geophysics, and Geochemistry Science Center.

Science and Products

link
USGS

Extracting data from maps: applying lessons learned from the AI for Critical Mineral Assessment Competition

This project will share techniques developed in two AI/ML competitions run in Fall 2022, Automated Map Georeferencing, and Automated Map Feature Extraction with USGS stakeholders. We will develop a strategy to operationalize successful approaches, benefiting any activity that uses legacy map data.
By
Community for Data Integration (CDI)
link

Extracting data from maps: applying lessons learned from the AI for Critical Mineral Assessment Competition

This project will share techniques developed in two AI/ML competitions run in Fall 2022, Automated Map Georeferencing, and Automated Map Feature Extraction with USGS stakeholders. We will develop a strategy to operationalize successful approaches, benefiting any activity that uses legacy map data.
Learn More
link
Image shows an Alaskan Mountain viewed through hyperspectral imaging

Data Management and Spatial Studies - GGGSC

We provide support for geospatial analyses, mobile field data collection, management of geospatial collections including documentation, and distribution of all dataset types (geophysical, geochemistry, remote sensing (hyperspectral), etc.). GIS and data management support are provided including hyperspectral and geophysical studies that improve capabilities and applications for investigating...
By
Mineral Resources Program, Geology, Geophysics, and Geochemistry Science Center
link

Data Management and Spatial Studies - GGGSC

We provide support for geospatial analyses, mobile field data collection, management of geospatial collections including documentation, and distribution of all dataset types (geophysical, geochemistry, remote sensing (hyperspectral), etc.). GIS and data management support are provided including hyperspectral and geophysical studies that improve capabilities and applications for investigating...
Learn More
link
USGS mineral resource assessment workflow diagram

21st Century Prospecting: AI-assisted Surveying of Critical Mineral Potential

The USGS Mineral Resources Program entered a partnership with the Defense Advanced Research Project Agency (DARPA). The partnership objective is to accelerate advances in science for understanding critical minerals, assessing unknown resources, and increase mineral security for the Nation so USGS can more efficiently assess critical mineral deposits within the United States.
By
Mineral Resources Program, Geology, Energy & Minerals Science Center, Geology, Geophysics, and Geochemistry Science Center
link

21st Century Prospecting: AI-assisted Surveying of Critical Mineral Potential

The USGS Mineral Resources Program entered a partnership with the Defense Advanced Research Project Agency (DARPA). The partnership objective is to accelerate advances in science for understanding critical minerals, assessing unknown resources, and increase mineral security for the Nation so USGS can more efficiently assess critical mineral deposits within the United States.
Learn More
link
U.S. potassium concentration map

Update of North American Airborne Radiometric Survey Data Using Advanced Statistical Techniques and Parallel Computing

The purpose of this project is to update the current gridded products created from the North American airborne gamma ray spectrometry data using new statistical techniques to analyze spatial data and to create higher quality national airborne radiometric grids.
By
Mineral Resources Program, Geology, Geophysics, and Geochemistry Science Center
link

Update of North American Airborne Radiometric Survey Data Using Advanced Statistical Techniques and Parallel Computing

The purpose of this project is to update the current gridded products created from the North American airborne gamma ray spectrometry data using new statistical techniques to analyze spatial data and to create higher quality national airborne radiometric grids.
Learn More
link
USGS science for a changing world

Mineral Resource Assessment Training

The USGS Mineral Resources Program conducts mineral resource assessments and is training USGS scientists in how to conduct these assessments for future work. As a practical exercise, the scientists will conduct an assessment for tungsten in the U.S.
By
Mineral Resources Program, Geology, Minerals, Energy, and Geophysics Science Center
link

Mineral Resource Assessment Training

The USGS Mineral Resources Program conducts mineral resource assessments and is training USGS scientists in how to conduct these assessments for future work. As a practical exercise, the scientists will conduct an assessment for tungsten in the U.S.
Learn More

Training and validation data from the AI for Critical Mineral Assessment Competition

Extracting useful and accurate information from scanned geologic and other earth science maps is a time-consuming and laborious process involving manual human effort. To address this limitation, the USGS partnered with the Defense Advanced Research Projects Agency (DARPA) to run the AI for Critical Mineral Assessment Competition, soliciting innovative solutions for automatically georeferencing and

By
Mineral Resources Program, Geology, Geophysics, and Geochemistry Science Center

GIS data and scripts for Colorado Legacy Mine Lands Watershed Delineation and Scoring tool (WaDeS)

This data release includes GIS datasets supporting the Colorado Legacy Mine Lands Watershed Delineation and Scoring tool (WaDeS), a web mapping application available at https://geonarrative.usgs.gov/colmlwades/. Water chemistry data were compiled from the U.S. Geological Survey (USGS) National Water Information System (NWIS), U.S. Environmental Protection Agency (EPA) STORET database, and the USGS
By
Mineral Resources Program, Geology, Geophysics, and Geochemistry Science Center

Spatial data associated with tungsten skarn resource assessment of the Northern Rocky Mountains, Montana and Idaho

A mineral resource assessment was performed by the U.S. Geological Survey (USGS) to assess the potential of undiscovered skarn-hosted tungsten resources in the Northern Rocky Mountain region of eastern Idaho and western Montana. This region has seen moderate tungsten trioxide (WO3) production in the past from a variety of mineralization styles including skarn, vein and replacement, and wolframite-
By
Mineral Resources Program, Geology, Energy & Minerals Science Center, Geology, Geophysics, and Geochemistry Science Center, Geology, Minerals, Energy, and Geophysics Science Center

Digital geologic map of the Elizabethtown Quadrangle, Essex County, New York

This website provides digitized shapefiles representing surface geologic features depicted in Matthew S. Walton's unpublished 1960 geologic map of the Elizabethtown quadrangle, Essex County, New York. Features represented by these files include geologic units representing Precambrian basement rock, geologic structures, diabase dikes, mine shaft locations, and water bodies. The shape files in this
By
Mineral Resources Program, Geology, Geophysics, and Geochemistry Science Center

Bayesian modeling of NURE airborne radiometric data for the conterminous United States: predictions and grids

This data release includes estimates of potassium (K), equivalent uranium (eU), and equivalent thorium (eTh) for the conterminous United States derived from the U.S. Geological Survey's national airborne radiometric data compilation (Duval and others, 2005). Airborne gamma ray spectrometry (AGRS) measures the gamma-rays that are emitted from naturally occurring radioactive isotopes found in rocks
By
Mineral Resources Program, Geology, Geophysics, and Geochemistry Science Center

Three GIS datasets defining areas permissive for the occurrence of uranium-bearing, solution-collapse breccia pipes in northern Arizona and southeast Utah

Some of the highest grade uranium (U) deposits in the United States are hosted by solution-collapse breccia pipes in the Grand Canyon region of northern Arizona. These structures are named for their vertical, pipe-like shape and the broken rock (breccia) that fills them. Hundreds, perhaps thousands, of these structures exist. Not all of the breccia pipes are mineralized; only a small percentage o
By
Mineral Resources Program, Geology, Geophysics, and Geochemistry Science Center
No results found.

Automated georeferencing and feature extraction of geologic maps and mineral sites

The predictive power of mineral prospectivity analysis depends on high quality, spatially accurate, analysis-ready datasets. Of paramount importance are geologic maps and mineral site data, but the state of readiness for utilizing these datasets remains sub-optimal for advanced computational techniques. As the U.S. Geological Survey (USGS) fulfils its mission to map the distribution of critical mi
Authors
Graham W. Lederer, Joshua Mark Rosera, Margaret A. Goldman, Garth E. Graham, Asitang Mishra, Amanda Towler, Brian Wilson, Dustin Graf, Michael Milano, Elizabeth Roberts, Gabrielle Hedrick, Carsten Oertel, Anastassios Dardas, Thomas McEntee
By
Mineral Resources Program, Geology, Energy & Minerals Science Center, Geology, Geophysics, and Geochemistry Science Center

Tungsten resources of the northern Rocky Mountains, Montana and Idaho— A synthesis and quantitative assessment of skarn-hosted resources

Mineral resource assessments performed by the U.S. Geological Survey provide a synthesis of available information about the location of known and suspected mineral deposits. This study focuses on skarn-hosted tungsten resources in the northern Rocky Mountain region of east-central Idaho and western Montana which have seen moderate tungsten trioxide production in the past from a variety of minerali
Authors
Allen K. Andersen, Margaret A. Goldman, Mitchell M. Bennett, Connie L. Dicken, Philip J. Brown, Heather L. Parks
By
Geology, Minerals, Energy, and Geophysics Science Center

User guide to the bayesian modeling of non-stationary, univariate, spatial data using R language package BMNUS

Bayesian modeling of non-stationary, univariate, spatial data is performed using the R-language package BMNUS. A unique advantage of this package is that it can map the mean, standard deviation, quantiles, and probability of exceeding a specified value. The package includes several R-language classes that prepare the data for the modeling, help select suitable model parameters, and help analyze th
Authors
Karl J. Ellefsen, Margaret A. Goldman, Bradley S. Van Gosen
By
Geology, Geophysics, and Geochemistry Science Center

Colorado Legacy Mine Lands Watershed Delineation and Scoring tool (WaDeS)

This web application, a summarized compilation of central Colorado water chemistry datasets from USGS and EPA, identifies legacy mine sites within the headwaters of central Colorado that could be good candidates for future remediation work based on stream metal concentrations, the number and complexity of mine features, and the potential for high natural background metal concentrations.

By
Mineral Resources Program, Colorado Water Science Center, Geology, Geophysics, and Geochemistry Science Center

Airborne Geophysical Survey Inventory of the US Interactive Application

This is a web application providing interactive search, query, and download of the Airborne Geophysical Survey Inventory of the Conterminous United States, Alaska, Hawaii, and Puerto Rico (Johnson and others, 2019). 

By
Mineral Resources Program, Geology, Geophysics, and Geochemistry Science Center, Earth Mapping Resources Initiative (Earth MRI)

Software for Bayesian Mapping of Regionally Grouped, Sparse, Univariate Earth Science Data (Program BMRGSU)

BMRGSU is software developed by the U.S. Geological Survey for Bayesian mapping of regionally-grouped, sparse, univariate, Earth-science data. This software implements an algorithm that smooths the estimated property across regions so that the deleterious effects of sparse data are mitigated. The algorithm can account for measurements that are censored, it can process multiple datasets with differ
By
Mineral Resources Program, Geology, Geophysics, and Geochemistry Science Center

Science and Products