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This dataset consists of 127 wideband and 21 long-period magnetotelluric (MT) stations collected from 2016-2019 across parts of Missouri, Arkansas, Tennessee, Illinois, and Kentucky. The U.S. Geological Survey acquired these data as part of regional investigations into the geologic and tectonic framework of the area and to support mineral resource and geologic hazard investigations. These data have been used to generate a 3D regional conductivity model of the area. Files included in this publication include measured electric- and magnetic-field time series as well as estimated impedance and vertical-magnetic field transfer functions. The data included here are for MT station mrv013 in the Mississippi River Valley...
This dataset consists of 127 wideband and 21 long-period magnetotelluric (MT) stations collected from 2016-2019 across parts of Missouri, Arkansas, Tennessee, Illinois, and Kentucky. The U.S. Geological Survey (USGS) acquired these data as part of regional investigations into the geologic and tectonic framework of the area and to support mineral resource and geologic hazard investigations. These data have been used to generate a 3D regional conductivity model of the area. Files included in this publication include measured electric- and magnetic-field time series as well as estimated impedance and vertical-magnetic field transfer functions. The data included here are for MT station rfr202 in the Reelfoot Rift survey...
This dataset consists of 127 wideband and 21 long-period magnetotelluric (MT) stations collected from 2016-2019 across parts of Missouri, Arkansas, Tennessee, Illinois, and Kentucky. The U.S. Geological Survey (USGS) acquired these data as part of regional investigations into the geologic and tectonic framework of the area and to support mineral resource and geologic hazard investigations. These data have been used to generate a 3D regional conductivity model of the area. Files included in this publication include measured electric- and magnetic-field time series as well as estimated impedance and vertical-magnetic field transfer functions. The data included here are for MT station rfr301 in the Reelfoot Rift survey...
This dataset consists of 127 wideband and 21 long-period magnetotelluric (MT) stations collected from 2016-2019 across parts of Missouri, Arkansas, Tennessee, Illinois, and Kentucky. The U.S. Geological Survey (USGS) acquired these data as part of regional investigations into the geologic and tectonic framework of the area and to support mineral resource and geologic hazard investigations. These data have been used to generate a 3D regional conductivity model of the area. Files included in this publication include measured electric- and magnetic-field time series as well as estimated impedance and vertical-magnetic field transfer functions. The data included here are for MT station rfr113 in the Reelfoot Rift survey...
This dataset consists of 127 wideband and 21 long-period magnetotelluric (MT) stations collected from 2016-2019 across parts of Missouri, Arkansas, Tennessee, Illinois, and Kentucky. The U.S. Geological Survey (USGS) acquired these data as part of regional investigations into the geologic and tectonic framework of the area and to support mineral resource and geologic hazard investigations. These data have been used to generate a 3D regional conductivity model of the area. Files included in this publication include measured electric- and magnetic-field time series as well as estimated impedance and vertical-magnetic field transfer functions. The data included here are for MT station sfm052 in the Reelfoot Rift survey...
This dataset consists of 127 wideband and 21 long-period magnetotelluric (MT) stations collected from 2016-2019 across parts of Missouri, Arkansas, Tennessee, Illinois, and Kentucky. The U.S. Geological Survey (USGS) acquired these data as part of regional investigations into the geologic and tectonic framework of the area and to support mineral resource and geologic hazard investigations. These data have been used to generate a 3D regional conductivity model of the area. Files included in this publication include measured electric- and magnetic-field time series as well as estimated impedance and vertical-magnetic field transfer functions. The data included here are for MT station sfm020 in the Reelfoot Rift survey...
This dataset consists of 127 wideband and 21 long-period magnetotelluric (MT) stations collected from 2016-2019 across parts of Missouri, Arkansas, Tennessee, Illinois, and Kentucky. The U.S. Geological Survey (USGS) acquired these data as part of regional investigations into the geologic and tectonic framework of the area and to support mineral resource and geologic hazard investigations. These data have been used to generate a 3D regional conductivity model of the area. Files included in this publication include measured electric- and magnetic-field time series as well as estimated impedance and vertical-magnetic field transfer functions. The data included here are for MT station sfm018 in the Reelfoot Rift survey...
This dataset consists of 127 wideband and 21 long-period magnetotelluric (MT) stations collected from 2016-2019 across parts of Missouri, Arkansas, Tennessee, Illinois, and Kentucky. The U.S. Geological Survey (USGS) acquired these data as part of regional investigations into the geologic and tectonic framework of the area and to support mineral resource and geologic hazard investigations. These data have been used to generate a 3D regional conductivity model of the area. Files included in this publication include measured electric- and magnetic-field time series as well as estimated impedance and vertical-magnetic field transfer functions. The data included here are for MT station sfm002 in the Reelfoot Rift survey...
This dataset consists of 127 wideband and 21 long-period magnetotelluric (MT) stations collected from 2016-2019 across parts of Missouri, Arkansas, Tennessee, Illinois, and Kentucky. The U.S. Geological Survey (USGS) acquired these data as part of regional investigations into the geologic and tectonic framework of the area and to support mineral resource and geologic hazard investigations. These data have been used to generate a 3D regional conductivity model of the area. Files included in this publication include measured electric- and magnetic-field time series as well as estimated impedance and vertical-magnetic field transfer functions. The data included here are for MT station sfm015 in the Reelfoot Rift survey...
This dataset consists of 127 wideband and 21 long-period magnetotelluric (MT) stations collected from 2016-2019 across parts of Missouri, Arkansas, Tennessee, Illinois, and Kentucky. The U.S. Geological Survey (USGS) acquired these data as part of regional investigations into the geologic and tectonic framework of the area and to support mineral resource and geologic hazard investigations. These data have been used to generate a 3D regional conductivity model of the area. Files included in this publication include measured electric- and magnetic-field time series as well as estimated impedance and vertical-magnetic field transfer functions. The data included here are for MT station rfr304 in the Reelfoot Rift survey...
This dataset consists of 127 wideband and 21 long-period magnetotelluric (MT) stations collected from 2016-2019 across parts of Missouri, Arkansas, Tennessee, Illinois, and Kentucky. The U.S. Geological Survey (USGS) acquired these data as part of regional investigations into the geologic and tectonic framework of the area and to support mineral resource and geologic hazard investigations. These data have been used to generate a 3D regional conductivity model of the area. Files included in this publication include measured electric- and magnetic-field time series as well as estimated impedance and vertical-magnetic field transfer functions. The data included here are for MT station rfr118 in the Reelfoot Rift survey...
This dataset consists of 127 wideband and 21 long-period magnetotelluric (MT) stations collected from 2016-2019 across parts of Missouri, Arkansas, Tennessee, Illinois, and Kentucky. The U.S. Geological Survey (USGS) acquired these data as part of regional investigations into the geologic and tectonic framework of the area and to support mineral resource and geologic hazard investigations. These data have been used to generate a 3D regional conductivity model of the area. Files included in this publication include measured electric- and magnetic-field time series as well as estimated impedance and vertical-magnetic field transfer functions. The data included here are for MT station rfr114 in the Reelfoot Rift survey...
The Southern San Andreas fault (SSAF) poses one of the largest seismic risks in California. However, structural properties around Coachella Valley remain enigmatic. In 2019, we collected magnetotelluric soundings (MT) to help inform depth-dependent fault zone geometry, fluid content and porosity. This project was led by the Institute of Geophysics and Planetary Physics at the University of California San Diego in partnership with U.S. Geological Survey and funded in large part by the Southern California Earthquake Center (SCEC). The MT data were collected using Zonge International 32-bit ZEN data loggers with ANT-4 magnetic induction coils and Borin Ag-AgCl electrodes with 50 m dipoles. The ZEN was programmed to...
In the southwestern US, the meteorological phenomenon known as atmospheric rivers (ARs) has gained increasing attention due to its strong connections to floods, snowpacks and water supplies in the West Coast states. Relatively less is known about the ecological implications of ARs, particularly in the interior Southwest, where AR storms are less common. To address this gap, we compared a chronology of AR landfalls on the west coast between 1989-2011 and between 25-42.5ºN, to annual metrics of the Normalized Difference Vegetation Index (NDVI; an indicator of vegetation productivity) and daily-resolution precipitation data to assess influences of AR-fed winter precipitation on vegetation productivity across the southwestern...
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Tags: Arizona,
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The Southern San Andreas fault (SSAF) poses one of the largest seismic risks in California. However, structural properties around Coachella Valley remain enigmatic. In 2019, we collected magnetotelluric soundings (MT) to help inform depth-dependent fault zone geometry, fluid content and porosity. This project was led by the Institute of Geophysics and Planetary Physics at the University of California San Diego in partnership with U.S. Geological Survey and funded in large part by the Southern California Earthquake Center (SCEC). The MT data were collected using Zonge International 32-bit ZEN data loggers with ANT-4 magnetic induction coils and Borin Ag-AgCl electrodes with 50 m dipoles. The ZEN was programmed to...
The Southern San Andreas fault (SSAF) poses one of the largest seismic risks in California. However, structural properties around Coachella Valley remain enigmatic. In 2019, we collected magnetotelluric soundings (MT) to help inform depth-dependent fault zone geometry, fluid content and porosity. This project was led by the Institute of Geophysics and Planetary Physics at the University of California San Diego in partnership with U.S. Geological Survey and funded in large part by the Southern California Earthquake Center (SCEC). The MT data were collected using Zonge International 32-bit ZEN data loggers with ANT-4 magnetic induction coils and Borin Ag-AgCl electrodes with 50 m dipoles. The ZEN was programmed to...
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using Landsat imagery from 1985-2023. The RCMAP product suite consists of ten fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, tree, and shrub height in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, high-resolution training was revised using an improved neural-net classifier and modelling approach. These data serve as foundation to the RCMAP approach. The training database was...
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using Landsat imagery from 1985-2023. The RCMAP product suite consists of ten fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, tree, and shrub height in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, high-resolution training was revised using an improved neural-net classifier and modelling approach. These data serve as foundation to the RCMAP approach. The training database was...
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas...
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2020. The RCMAP product suite consists of eight fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub and rule-based error maps including the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. We used an updated version of the 2016 base training data, with a more aggressive forest mask and reduced shrub and sagebrush cover bias in pinyon-juniper woodlands. We pooled training data in areas...
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