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Geographic Information System Layer of a Map Depicting Susceptibility to Landslides Triggered by Intense Rainfall, Puerto Rico Geographic Information System Layer of a Map Depicting Susceptibility to Landslides Triggered by Intense Rainfall, Puerto Rico
This data release comprises a georeferenced raster layer depicting the estimated susceptibility to intense rainfall-induced landslides in Puerto Rico, which is a supplement to: Hughes, K.S., and Schulz, W.H., 2020, Map depicting susceptibility to landslides triggered by intense rainfall, Puerto Rico: U.S. Geological Survey Open-File Report 2020-1022, 91 p., 1 plate, scale 1:150,000...
Reflectance and confocal laser scanning fluorescence spectroscopy of bituminite in Kimmeridge Clay Reflectance and confocal laser scanning fluorescence spectroscopy of bituminite in Kimmeridge Clay
This work investigates the characterization of bituminite (amorphous sedimentary organic matter) in Kimmeridge Clay source rock via confocal laser canning microscopy (CLSM) and atomic force microscopy (AFM). As part of an International Committee for Coal and Organic Petrology working group, an immature (0.42% vitrinite reflectance), organic-rich (44.1 wt.% total organic carbon content)...
Observations Documenting Premature Mortality Among Alaska's Pacific Salmon in 2019 Observations Documenting Premature Mortality Among Alaska's Pacific Salmon in 2019
These data are a compilation of geographically widespread observations of premature mortality in Pacific salmon across their range in Alaska in 2019. Premature mortality observations primarily spanned an area of western and southcentral Alaska that is approximately one million km2 and included all five species of Pacific salmon. Observations were obtained and compiled in a single...
USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Geophysics Data USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Geophysics Data
This package contains gravity and magnetics data and products generated for the Nevada Machine Learning (NVML) project (DE-FOA-0001956). Data products contained in this release consist of grids and vector data. Grids include: primary anomaly maps (isostatic and PSG), match-filtered maps, horizontal gradient (HG) maps, confidence maps, and maps showing density of specific key structural...
USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Geophysics, Heat Flow, Slip and Dilation Tendency USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Geophysics, Heat Flow, Slip and Dilation Tendency
This package contains USGS data contributions to the DOE-funded Nevada Geothermal Machine Learning Project (DE-FOA-0001956), with the objective of developing a machine learning approach to identifying new geothermal systems in the Great Basin. This package contains three major data products (geophysics, heat flow, and fault dilation and slip tendencies) that cover a large portion of...
USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Heat Flow Data USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Heat Flow Data
This package contains a map surface that depicts the estimated spatial variation of conductive heat flow (mW/m?) in a portion of northern Nevada, the extent of the ?Nevada Machine Learning Project? (DE-EE0008762). It was generated using well locations that had an estimated heat flow value from a measured thermal gradient and thermal conductivity, mainly using data from Southern Methodist