Filters: Tags: Earth Magnetic Field (X)
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This dataset consists of 16 repeated magnetotelluric (MT) stations collected on Mount Tongariro, New Zealand, before (2009) and after (2013) the 2012 eruption. The data were collected in same locations with similiar instruments. Preeruption and posteruption electromagnetic magnetotelluric measurements determine variation in subsurface electrical properties resulting from changes in magmatic system associated with the 2012 eruptive cycle.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Apparent Resistivity,
Earth Magnetic Field,
GMEGSC,
Geology, Minerals, Energy, and Geophysics Science Center,
Geophysics,
This dataset consists of 65 magnetotelluric (MT) stations collected in 2015 near Mountain Pass, California. The U.S. Geological Survey acquired these data to create a regional conductivity model near the Mountain Pass mine. This work is in support of characterizing mineral deposits.
This dataset consists of 65 magnetotelluric (MT) stations collected in 2015 near Mountain Pass, California. The U.S. Geological Survey acquired these data to create a regional conductivity model near the Mountain Pass mine. This work is in support of characterizing mineral deposits.
This dataset consists of 65 magnetotelluric (MT) stations collected in 2015 near Mountain Pass, California. The U.S. Geological Survey acquired these data to create a regional conductivity model near the Mountain Pass mine. This work is in support of characterizing mineral deposits.
This dataset consists of 65 magnetotelluric (MT) stations collected in 2015 near Mountain Pass, California. The U.S. Geological Survey acquired these data to create a regional conductivity model near the Mountain Pass mine. This work is in support of characterizing mineral deposits.
This dataset consists of 65 magnetotelluric (MT) stations collected in 2015 near Mountain Pass, California. The U.S. Geological Survey acquired these data to create a regional conductivity model near the Mountain Pass mine. This work is in support of characterizing mineral deposits.
This dataset consists of 65 magnetotelluric (MT) stations collected in 2015 near Mountain Pass, California. The U.S. Geological Survey acquired these data to create a regional conductivity model near the Mountain Pass mine. This work is in support of characterizing mineral deposits.
This dataset consists of 14 magnetotelluric (MT) stations collected in 2015 near San Pablo Bay, California along a east-northeast profile. The U.S. Geological Survey acquired these data to understand the fault geometry of the Hayward Fault and the Rodgers Creek Fault.
This dataset consists of 14 magnetotelluric (MT) stations collected in 2015 near San Pablo Bay, California along a east-northeast profile. The U.S. Geological Survey acquired these data to understand the fault geometry of the Hayward Fault and the Rodgers Creek Fault.
This dataset consists of 24 magnetotelluric (MT) stations collected in 2017 in Gabbs Valley, Nevada. The U.S. Geological Survey acquired these data as part of Phase 2 of the Nevada Play Fairway Analysis Project led by the University of Nevada at Reno and funded by the Department of Energy (grant number DE-EE0006731) with support from the U.S. Geological Survey's Energy Program.
This dataset consists of 65 magnetotelluric (MT) stations collected in 2015 near Mountain Pass, California. The U.S. Geological Survey acquired these data to create a regional conductivity model near the Mountain Pass mine. This work is in support of characterizing mineral deposits.
This dataset consists of 65 magnetotelluric (MT) stations collected in 2015 near Mountain Pass, California. The U.S. Geological Survey acquired these data to create a regional conductivity model near the Mountain Pass mine. This work is in support of characterizing mineral deposits.
This dataset consists of 65 magnetotelluric (MT) stations collected in 2015 near Mountain Pass, California. The U.S. Geological Survey acquired these data to create a regional conductivity model near the Mountain Pass mine. This work is in support of characterizing mineral deposits.
This dataset consists of 65 magnetotelluric (MT) stations collected in 2015 near Mountain Pass, California. The U.S. Geological Survey acquired these data to create a regional conductivity model near the Mountain Pass mine. This work is in support of characterizing mineral deposits.
This dataset consists of 65 magnetotelluric (MT) stations collected in 2015 near Mountain Pass, California. The U.S. Geological Survey acquired these data to create a regional conductivity model near the Mountain Pass mine. This work is in support of characterizing mineral deposits.
This dataset consists of 65 magnetotelluric (MT) stations collected in 2015 near Mountain Pass, California. The U.S. Geological Survey acquired these data to create a regional conductivity model near the Mountain Pass mine. This work is in support of characterizing mineral deposits.
This dataset consists of 42 magnetotelluric (MT) stations collected in 2017 in the Northwest Geysers, CA. The U.S. Geological Survey acquired these data as part of a project to image the heat source in the Northwest Geysers. Support was from the U.S. Geological Survey's Volcano Hazards Program.
This dataset consists of 42 magnetotelluric (MT) stations collected in 2017 in the Northwest Geysers, CA. The U.S. Geological Survey acquired these data as part of a project to image the heat source in the Northwest Geysers. Support was from the U.S. Geological Survey's Volcano Hazards Program.
This dataset consists of 14 magnetotelluric (MT) stations collected in 2015 near San Pablo Bay, California along a east-northeast profile. The U.S. Geological Survey acquired these data to understand the fault geometry of the Hayward Fault and the Rodgers Creek Fault.
This dataset consists of 24 magnetotelluric (MT) stations collected in 2017 in Gabbs Valley, Nevada. The U.S. Geological Survey acquired these data as part of Phase 2 of the Nevada Play Fairway Analysis Project led by the University of Nevada at Reno and funded by the Department of Energy (grant number DE-EE0006731) with support from the U.S. Geological Survey's Energy Program.
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