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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....
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This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs....


map background search result map search result map FSA 10:1 NAIP Imagery m_3511546_ne_11_h_20160420_20161004 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3511546_sw_11_h_20160420_20161004 3.75 x 3.75 minute JPEG2000 from The National Map USGS 1:62500-scale Quadrangle for Ivanpah, CA 1956 station mp104 station mp109 station mp113 station mp118 station mp203 station mp204 station mp207 station mp208 station mp323 station mp326 station mp331 station mp340 station mp341 station mp345 station mp353 station mp357 station mp358 FSA 10:1 NAIP Imagery m_3511546_ne_11_h_20160420_20161004 3.75 x 3.75 minute JPEG2000 from The National Map FSA 10:1 NAIP Imagery m_3511546_sw_11_h_20160420_20161004 3.75 x 3.75 minute JPEG2000 from The National Map USGS 1:62500-scale Quadrangle for Ivanpah, CA 1956