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Found 908 dataset(s) matching "Raster Grid".
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The U.S. Geological Survey (USGS), in cooperation with the Puerto Rico Environmental Quality Board, has compiled a series of geospatial datasets for Puerto Rico to be implemented into the USGS...
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This data set is derived from the original 2005 data collected over the southern San Andreas and San Jacinto fault zones in southern California, USA. These data have provided a fundamental...
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Global 3-Year Running Mean Ground-Level Nitrogen Dioxide (NO2) Grids from GOME, SCIAMACHY and GOME-2
The Global 3-Year Running Mean Ground-Level Nitrogen Dioxide (NO2) Grids from GOME, SCIAMACHY and GOME-2 represent a series of three-year running mean grids (1996-2012) of ground level NO2 that...
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In December 2024, the Lower Mississippi-Gulf Water Science Center (LMGWSC) conducted comprehensive field surveys of Lake Pushmataha, a central Mississippi reservoir owned by the Mississippi Band...
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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...
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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...
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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...
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This raster dataset represents approximately 49,581 square kilometers of Simrad EM122 multibeam backscatter-intensity data collected in the Bering Sea during U.S. Geological Survey (USGS) cruise...
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This 1-kilometer raster (grid) dataset for the conterminous United States was created by i nterpolating base-flow index (BFI) values estimated at U.S. Geological Survey (USGS) streamgages. Base...
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Groundwater is a vital resource in the Mississippi embayment of the central United States. An innovative approach using machine learning (ML) was employed to predict groundwater salinity—including...
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Groundwater is a vital resource to the Mississippi embayment region of the central United States. Regional and integrated assessments of water availability that link physical flow models and water...
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Groundwater is a vital resource in the Mississippi embayment physiographic region (Mississippi embayment) of the central United States and can be limited in some areas by high concentrations of...
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Groundwater is a vital resource in the Mississippi embayment physiographic region (Mississippi embayment) of the central United States and can be limited in some areas by high concentrations of...
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Groundwater is a vital resource in the Mississippi embayment physiographic region (Mississippi embayment) of the central United States and can be limited in some areas by high concentrations of...
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Groundwater is a vital resource in the Mississippi embayment of the central United States. An innovative approach using machine learning (ML) was employed to predict groundwater salinity—including...
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Groundwater is a vital resource in the Mississippi embayment of the central United States. An innovative approach using machine learning (ML) was employed to predict groundwater salinity—including...
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Groundwater is a vital resource in the Mississippi embayment of the central United States. An innovative approach using machine learning (ML) was employed to predict groundwater salinity—including...
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Groundwater is a vital resource in the Mississippi embayment of the central United States. An innovative approach using machine learning (ML) was employed to predict groundwater salinity—including...
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Groundwater is a vital resource to the Mississippi embayment region of the central United States. Regional and integrated assessments of water availability that link physical flow models and water...
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Groundwater is a vital resource in the Mississippi embayment physiographic region (Mississippi embayment) of the central United States and can be limited in some areas by high concentrations of...
