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The U.S. Geological Survey, in cooperation with the Massachusetts Office of Coastal Zone Management compiled Massachusetts vector shorelines into an updated dataset for the Office’s Shoreline Change Project. The Shoreline Change Project started in 1989 to identify erosion-prone areas of the Massachusetts coast by compiling a database of historical shoreline positions. Trends of shoreline position over long- and short-term timescales provide information to landowners, managers, and potential buyers about possible future changes to costal resources and infrastructure. This updated dataset strengthens the understanding of shoreline position change in Massachusetts. It includes U.S. Geological Survey vector shorelines...
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The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast by compiling a database of historical (mid 1800's-1989) shoreline positions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013, two oceanfront shorelines for Massachusetts were added using 2008-2009 color aerial orthoimagery and 2007 topographic lidar datasets obtained...
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The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using 2008-2009 color aerial orthoimagery and 2007 topographic lidar datasets obtained from NOAA's Ocean Service, Coastal...
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The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using 2008-2009 color aerial orthoimagery and 2007 topographic lidar datasets obtained from NOAA's Ocean Service, Coastal...
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During Hurricane Irma in September 2017, Florida and Georgia experienced significant impacts to beaches, dunes, barrier islands, and coral reefs. Extensive erosion and coral losses result in increased immediate and long-term hazards to shorelines that include densely populated regions. These hazards put critical infrastructure at risk to future flooding and erosion and may cause economic losses. The USGS Coastal and Marine Hazards Resources Program (CMHRP) is assessing hurricane-induced coastal erosion along the southeast US coastline and implications for vulnerability to future storms. Shoreline positions were compiled prior to and following Hurricane Irma along the sandy shorelines of the Gulf of Mexico and Atlantic...
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Cassiterite (SnO2), a main ore mineral in tin deposits, was collected by multiple Russian geologists or obtained from museum collections in both the USA and Russia and dated at the U.S. Geological Survey. The dated samples represent four different mining districts spanning the entire country from the village of Pitkäranta in the west (31° E Longitude) to the Merekskoe Deposit in the Russian Far East (134°E Longitude). The samples were recovered from a variety of host deposit types that range from the Proterozoic to Phanerozoic. Cassiterite (in the form of mounted loose grains) was prepared and analyzed for direct age dating on a laser ablation inductively coupled plasma mass spectrometer (LA-ICP-MS) system at the...
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This data release supports interpretations of field-observed root distributions within a shallow landslide headscarp (CB1) located below Mettman Ridge within the Oregon Coast Range, approximately 15 km northeast of Coos Bay, Oregon, USA. (Schmidt_2021_CB1_topo_far.png and Schmidt_2021_CB1_topo_close.png). Root species, diameter (greater than or equal to 1 mm), general orientation relative to the slide scarp, and depth below ground surface were characterized immediately following landsliding in response to large-magnitude precipitation in November 1996 which triggered thousands of landslides within the area (Montgomery and others, 2009). The enclosed data includes: (1) tests of root-thread failure as a function of...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for developing approaches that balance the needs of humans and native species. Given the magnitude of the threat posed by sea-level rise, and the urgency to better understand it, there is an increasing need to forecast sea-level rise effects on barrier islands. To address this problem, scientists in the U.S. Geological Survey (USGS) Coastal and Marine Geology program are developing Bayesian networks as a tool to evaluate and to forecast the effects of sea-level rise on shoreline change, barrier island geomorphology, and habitat availability for species such as the piping plover (Charadrius melodus)...
Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Assateague Island, Assateague Island, Assateague Island National Seashore, Assateague Island National Seashore, Atlantic Ocean, All tags...
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Shallow subsurface electrical conductivity was mapped at Stateline National Wildlife Refuge (NWR) in northeast Montana using the DUALEM421 electromagnetic sensor (Dualem, Inc., ON, Canada) in the winter of 2017. Data were acquired by towing the DUALEM421 sensor on a sled behind an all-terrain vehicle or snow machine, with the sensor at a nominal height of 0.3 meters (m) above ground surface. Approximately 3 line-kilometers (km) of data were acquired over an area of approximately .2 square-kilometers. Data were manually edited to remove sensor dropouts, lag corrected for apparent offsets between recorded GPS location and data locations for each coil pair, and averaged to a sounding distance of 1m along the survey...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
Categories: Data; Types: Downloadable, GeoTIFF, Map Service, OGC WFS Layer, OGC WMS Layer, Raster, Shapefile; Tags: Atlantic Ocean, Barrier Island, Bayesian Network, CMGP, Coastal Erosion, All tags...
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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
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To determine if invasive annual grasses increased around energy developments after the construction phase, we calculated an invasives index using Landsat TM and ETM+ imagery for a 34-year time period (1985-2018) and assessed trends for 1,755 wind turbines (from the U.S. Wind Turbine Database) installed between 1988 and 2013 in the southern California desert. The index uses the maximum normalized difference vegetation index (NDVI) for early season greenness (January-June), and mean NDVI (July-October) for the later dry season. We estimated the relative cover of invasive annuals each year at turbine locations and control sites and tested for changes before and after each turbine was installed. These data were used...
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This dataset contains absolute-gravity measurements made using an A-10 absolute gravity meter (Micro-g Lacoste, Inc.) in 2019 in Pinal County, Arizona. Measurements were made at a total of 19 different stations used by the Arizona Department of Water Resources (ADWR) to monitor aquifer-storage changes. Data are presented in tabular and spatial vector (point) form, including relevant parameters used for processing. Data were output by g software (Micro-g Lacoste, Inc.) version 9.12.04.23. A correction for laser-frequency drift was applied, based on regular calibration of the HeNe laser used in the A-10 against an iodine-stabilized laser.
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Areas of groundwater discharge are hydrologically and ecologically important, and yet are difficult to predict at the river network scale. Thermal infrared imagery can be used to identify areas of groundwater discharge based on an observed temperature anomaly (colder during the late summer or warmer during the late winter). The thermal images, direct temperature measurements (11 cm depth) and discharge zone (seep) location information in this data release were collected as part of a study to evaluate and improve predicted spatial patterns of groundwater discharge. The data were collected during the late summer / early fall of 2017 along selected river reaches in the Farmington River watershed (Connecticut and Massachusetts)....
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The Massachusetts Office of Coastal Zone Management launched the Shoreline Change Project in 1989 to identify erosion-prone areas of the coast and support local land-use decisions. Trends of shoreline position over long and short-term timescales provide information to landowners, managers, and potential buyers about possible future impacts to coastal resources and infrastructure. In 2001, a 1994 shoreline was added to calculate both long- and short-term shoreline change rates along ocean-facing sections of the Massachusetts coast. In 2013 two oceanfront shorelines for Massachusetts were added using 2008-2009 color aerial orthoimagery and 2007 topographic lidar datasets obtained from NOAA's Ocean Service, Coastal...
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Data on 17 metrics of shale gas development in the Pennsylvania portion of the Upper Susquehanna River basin that was collated from a variety of sources and summarized at the upstream catchment scale. Data were also standardized by upstream area and transformed into rank scores based on metric distribution and then summarized into a Disturbance Intensity Index (DII). See Maloney et al. 2018 for detailed descriptions of each data sets and limitations of data. (Maloney, K. O., J. A. Young, S. P. Faulkner, A. Hailegiorgis, E. T. Slonecker, and L. E. Milheim. 2018. A detailed risk assessment of shale gas development on headwater streams in the Pennsylvania portion of the Upper Susquehanna River Basin, U.S.A. Science...
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The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This data release includes two new mean high water (MHW) shorelines extracted from lidar data collected in 2010 and 2017-2018. Previously published historical shorelines for South Carolina (Kratzmann and others, 2017)...
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Shallow subsurface electrical conductivity was mapped at Beaver Lake National Wildlife Refuge (NWR) in northwest North Dakota using the DUALEM421 electromagnetic sensor (Dualem, Inc., ON, Canada) in the winter of 2018. Data were acquired by towing the DUALEM421 sensor on a sled behind an all-terrain vehicle or snow machine, with the sensor at a nominal height of 0.3 meters (m) above ground surface. Approximately 127 line-kilometers (km) of data were acquired over an area of approximately 8 square-kilometers. At this survey location, the 4m transmitter-receiver horizontal co-planar and perpendicular coil orientations did not function due to equipment malfunction. Data were manually edited to remove sensor dropouts,...
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During the spring and summer of 2022, the U.S. Geological Survey collected water-quality samples for nutrient analysis at 45 stations across the state of Connecticut and adjacent areas of New York and Rhode Island to better understand the groundwater discharge component of nitrogen loading to the Long Island Sound. The targeted stations were located in small drainage basins (less than 50 square kilometers) in the southern portion of the Long Island Sound watershed. Sites were selected randomly from groups based on expected drivers or controls on baseflow nitrogen loads. Factors used in the grouping included four metrics calculated for the upstream watershed: percent impervious cover, septic system density, percent...


map background search result map search result map Shale gas data used in development of the Disturbance Intensity Index for the Pennsylvania portion of the Upper Susquehanna River basin in Maloney et al. 2018 Development: Development delineation: Edwin B. Forsythe NWR, NJ, 2010 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2010 Thermal infrared images and direct temperature measurements of groundwater discharge zones throughout the Farmington River watershed (Connecticut and Massachusetts) Data supporting Landsat time series assessment of invasive annual grasses following energy development Absolute gravity data from Pinal County, Arizona, 2019 Stateline NWR, Montana, 2017 Beaver Lake NWR, North Dakota, 2018 Historical shoreline positions for the coast of MA, from 1844 - 2014 Intersects for the coastal region around Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1 Intersects for coastal region of Buzzards Bay, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1 Long-term and short-term shoreline change rates for the region of Buzzards Bay, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 Baselines for Outer Cape Cod, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1 Pb-Pb and U-Pb data of Proterozoic to Phanerozoic cassiterite deposits in Russia Root thread strength, landslide headscarp geometry, and observed root characteristics at the monitored CB1 landslide, Oregon, USA Intersects for the Florida east coast (FLec) coastal region generated to calculate short-term shoreline change rates using the Digital Shoreline Analysis System version 5 Seabeach Amaranth Presence-Absence Data, Assateague Island National Seashore, 2010 Long-term shoreline change rate transects for the South Carolina coastal region, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 Nitrogen Loads, Yields, and Associated Field Data Collected During Baseflow Conditions and Site Attributes for Small Basins Draining to Long Island Sound NSHM2025_EQGeoDB_PRVI_v1 shapefile Root thread strength, landslide headscarp geometry, and observed root characteristics at the monitored CB1 landslide, Oregon, USA Stateline NWR, Montana, 2017 Beaver Lake NWR, North Dakota, 2018 Intersects for the coastal region around Boston, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1 Development: Development delineation: Edwin B. Forsythe NWR, NJ, 2010 points, transects, beach width: Barrier island geomorphology and shorebird habitat metrics at 50-m alongshore transects and 5-m cross-shore points: Edwin B. Forsythe NWR, NJ, 2010 Intersects for coastal region of Buzzards Bay, Massachusetts, generated to calculate shoreline change rates using the Digital Shoreline Analysis System version 5.1 Long-term and short-term shoreline change rates for the region of Buzzards Bay, Massachusetts, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 Absolute gravity data from Pinal County, Arizona, 2019 Historical shoreline positions for the coast of MA, from 1844 - 2014 Nitrogen Loads, Yields, and Associated Field Data Collected During Baseflow Conditions and Site Attributes for Small Basins Draining to Long Island Sound Long-term shoreline change rate transects for the South Carolina coastal region, calculated with and without the proxy-datum bias using the Digital Shoreline Analysis System version 5.1 Intersects for the Florida east coast (FLec) coastal region generated to calculate short-term shoreline change rates using the Digital Shoreline Analysis System version 5 Shale gas data used in development of the Disturbance Intensity Index for the Pennsylvania portion of the Upper Susquehanna River basin in Maloney et al. 2018 Data supporting Landsat time series assessment of invasive annual grasses following energy development NSHM2025_EQGeoDB_PRVI_v1 shapefile Pb-Pb and U-Pb data of Proterozoic to Phanerozoic cassiterite deposits in Russia