Filters: Tags: natural resource assessment (X) > partyWithName: Jonathan M Glen (X)
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This data release contains all digital geographic data used and produced by the Snake River Plain Play Fairway Analysis (DE EE0006733) for Phase 1 (ArcGIS shapefiles and raster files) as well as the model processing script, tables, and documentation used to generate data outputs. Brief descriptions of data layers are in the metadata of GIS files, greater detail is available in the ‘Larger Work,' the Snake River Plain Play Fairway Analysis Phase 1 report. A link to the report is available in the ‘Related External Resources’ section.
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 features. The vector data in this release include the gravity stations, HGM of gravity and magnetics, ‘generalized’ lineations for gravity and magnetics, gravity and magnetic lineation terminations and intersections, and ‘well-constrained’ HGM saddles.
This data release contains all digital geographic data used and produced by the Snake River Plain Play Fairway Analysis (DE EE0006733) for Phase 2 (ArcGIS shapefiles and raster files) as well as the model processing script, tables, and documentation used to generate data outputs. Phase 2 examines two subset areas of the Phase 1 study area, Mountain Home and Camas Prairie. Brief descriptions of data layers are in the metadata of GIS files, greater detail is available in the ‘Larger Work,' the Snake River Plain Play Fairway Analysis Phase 2 report. A link to the report is available in the ‘Related External Resources’ section.
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 northern Nevada. The geophysics data include map surfaces related to gravity and magnetic data, and line and point data derived from those surfaces. Heat flow data include an interpolated map of heat flow in mW/m², an error surface, and well data used to construct them. The dilation and slip tendency information exist as attributes assigned...
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