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USGS Topo Map Vector Data (Vector) 6749 California, Michigan 20200707 for 7.5 x 7.5 minute Shapefile
Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
Types: Citation;
Tags: 7.5 x 7.5 minute,
7.5 x 7.5 minute,
Branch County,
Combined Vector,
Combined Vector,
![]() Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
Types: Citation;
Tags: 7.5 x 7.5 minute,
7.5 x 7.5 minute,
Combined Vector,
Combined Vector,
Combined Vector,
![]() Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
Types: Citation;
Tags: 7.5 x 7.5 minute,
7.5 x 7.5 minute,
Combined Vector,
Combined Vector,
Combined Vector,
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....
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....
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....
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....
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....
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....
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....
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....
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....
![]() Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
Types: Citation;
Tags: 7.5 x 7.5 minute,
7.5 x 7.5 minute,
Combined Vector,
Combined Vector,
Combined Vector,
Field spikes were prepared at 207 stream and river sites as part of the U.S. Geological Survey (USGS) National Water Quality Assessment (NAWQA) project between December, 2012, and September, 2015. At the field site, a depth-and width-integrated environmental sample was collected, and one subsample of the environmental sample was spiked with a known amount of a spike mixture. Both the spiked subsample ("spike sample") and another subsample ("environmental sample") of the original water sample were analyzed for pesticides at the USGS National Water Quality Laboratory (NWQL) by direct injection liquid chromatography with tandem mass spectrometry (LC-MS/MS), and were used to calculate the spike recovery of each analyte....
The glacial aquifer system of the United States encompasses all or parts of 25 states and is the most widely used supply of drinking water in the Nation (Maupin and Barber, 2005; Maupin and Arnold, 2010). A series of seven raster data sets were derived from a database of water-well drillers' records that was compiled in partial fulfillment of the goals of the U.S. Geological Survey’s Groundwater Availability and Use assessment program (U.S. Geological Survey, 2002). They contain hydrogeologic information for areas of the U.S. that are north of the southern limit of Pleistocene glaciation, including the total thickness of glacial deposits, thickness of coarse-grained sediment within the glacial deposits, specific-capacity...
This data release contains tabular digital data describing calculated hourly back trajectory position coordinates for air masses contributing to five selected precipitation-mercury deposition episodes at National Atmospheric Deposition Program monitoring site IN21 (National Atmospheric Deposition Program, 2017) in southeastern Indiana during 2009‒2015. The air pollution transport and dispersion modeling system HYSPLIT (Stein et. al, 2015) was used to calculate the back trajectory position coordinates during 48 hours preceding the start of each episode. The 40-km gridded input data to HYSPLIT were from National Oceanic and Atmospheric Administration (2017). Continuous, digital precipitation depth data were recorded...
Categories: Data;
Tags: Indiana,
USGS Science Data Catalog (SDC),
air pollution,
atmospheric deposition,
dispersion model,
These data are bathymetry (river bottom elevation) in XYZ format, generated from the March 29-30, 2017 and April 13, 2017, bathymetric survey of the East Fork White River at Columbus, Indiana. The bathymetry was collected from approximately the confluence of Driftwood and Flatrock rivers, downstream to the confluence of Haw Creek. Hydrographic data were collected using an acoustic Doppler current profiler (ADCP) with integrated Differential Global Positioning System (DGPS). Data were collected as the surveying vessel traversed the river, approximately perpendicular to the velocity vectors at 55 cross sections which were spaced 200 feet apart along the river. Additional cross sections were collected upstream and...
![]() This map layer consists of federally owned or administered lands of the United States, Puerto Rico, and the U.S. Virgin Islands. For the most part, only areas of 320 acres or more are included; some smaller areas deemed to be important or significant are also included. There may be private inholdings within the boundaries of Federal lands in this map layer. Some established Federal lands which are larger than 320 acres are not included in this map layer, because their boundaries were not available from the owning or administering agency.
![]() Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
Types: Citation;
Tags: 7.5 x 7.5 minute,
7.5 x 7.5 minute,
Combined Vector,
Combined Vector,
Combined Vector,
This data set includes WRTDS nutrient flux trend results and the values of daily streamflow trend results displayed in the Quantile-Kendall plots. For 1995-2015 nutrient trends, the method of generalized flow normalization (FNG) was used which explicitly addresses non-stationary streamflow conditions. For 2005-2015 nutrient trends, the WRTDS trend analyses used the method of stationary flow normalization (FNS) because streamflow nonstationarity is difficult to assess over this shorter duration time frame. The 1995-2015 annual nutrient trends were determined for all five nutrient parameters (TP, SRP, TN, NO23, TKN), and monthly trends were evaluated only for SRP. The 2005-2015 annual nutrient trends were determined...
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