Margaret Goldman is a Geographer with the Geology, Geophysics, and Geochemistry Science Center.
Science and Products
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.
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...
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.
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.
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-
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This website provides digitized shapefiles representing surface geologic features depicted in Matthew S. Walton's unpublished 1960 geologic map of the Elizabethtown quadrangle, Essex County, New York.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
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
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
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
Science and Products
- Science
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.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...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.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. - Data
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-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 thisBayesian 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 rocksThree 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 - Publications
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 - Multimedia