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This Data Release accompanies the publication "State of stress in areas of active unconventional oil and gas development in North America" by J.-E. Lund Snee (now J.-E. Lundstern) and M.D. Zoback (2022) in the AAPG Bulletin. This dataset provides maximum horizontal stress (SHmax) orientation and relative stress magnitude (faulting regime) information that comprise a new-generation crustal stress map for North America. Relative stress magnitudes are presented using the Aϕ (A_phi) parameter, a single scalar that represents the ratio of the three principal stress magnitudes. Data were collected between 2015 and 2022. Data points for SHmax orientations, relative stress magnitudes, and the earthquake focal mechanisms...
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This dataset consists of short-term (~33 years) shoreline change rates for the north coast of Alaska between the Colville River and Point Barrow. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1979 and 2012. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to calculate short-term rates.
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This dataset has been superseded. The most current data for this data release are available here: https://www.sciencebase.gov/catalog/item/663a5123d34e77890839b03f This dataset consists of long-term (~63 years) shoreline change rates for the north coast of Alaska between the Hulahula River and the Colville River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2010. A reference baseline was used as the originating point for the orthogonal transects...
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This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the exposed north coast of Alaska coastal region between the Colville River and Point Barrow for the time period 1947 to 2012. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.
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This dataset consists of short-term (~33 years) shoreline change rates for the north coast of Alaska between Point Barrow and Icy Cape. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using an end point rate-of-change method based on available shoreline data between 1979 and 2012. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. Transects intersect each shoreline establishing measurement points, which are then used to calculate short-term rates.
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This dataset has been superseded. The most current data for this data release are available here: https://www.sciencebase.gov/catalog/item/663a5822d34e77890839b073 This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the exposed north coast of Alaska coastal region between the U.S. Canadian Border to the Hulahula River for the time period 1947 to 2010. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.
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This part of DS 781 presents data for the habitat map of the seafloor of the Offshore of Aptos map area, California. The vector data file is included in "Habitat_OffshoreAptos.zip," which is accessible from https://doi.org/10.5066/F7K35RQB. These data accompany the pamphlet and map sheets of Cochrane, G.R., Johnson, S.Y., Dartnell, P., Greene, H.G., Erdey, M.D, Dieter, B.E., Golden, N.E., Hartwell, S.R., Ritchie, A.C., Kvitek, r.G., Maier, K.L., Endris, C.A., Davenport, C.W., Watt, J.T., Sliter, R.W., Finlayson, D.P., and Krigsman, L.M., (G.R. Cochrane and S.A. Cochran, eds.), 2016, California State Waters Map Series—Offshore of Aptos, California: U.S. Geological Survey Open-File Report 2016–1025, 43 p., 10 sheets,...
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The U.S. National Seismic Hazard Model (NSHM) relies on deformation models to assign slip rates along active faults used in the earthquake rupture forecast. Here, we present the geologic deformation model results in tabular form. We provide model outputs in multiple file formats, as well as the polygons used in analyses throughout the geologic deformation model process.The data presented herein are in support of the following interprative manuscript: Hatem, A.E., Reitman, N.G., Briggs, R.W., Gold, R.D., Thompson Jobe, J.A., Burgette, R.J., (2022) ­­­Western U.S. geologic deformation model for use in the U.S. National Seismic Hazard Model 2023, Seismological Research Letters.
This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the shorelines near Barter Island, Alaska for the time period 1947 to 2020. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.
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The 2018 lower East Rift Zone eruption of Kīlauea Volcano began in the late afternoon of 3 May, with fissure 1 opening and erupting lava onto Mohala Street in the Leilani Estates subdivision, part of the lower Puna District of the Island of Hawaiʻi. For the first week of the eruption, relatively viscous lava flowed only within a kilometer (0.6 miles) of the fissures within Leilani Estates, before activity shifted downrift (east-northeast) and out of the subdivision during mid-May. Around 18 May, activity along the lower East Rift Zone intensified, and fluid lava erupting at higher effusion rates from the downrift fissures reached the ocean within two days. Near the end of May, this more vigorous activity shifted...
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Introduction This data release is a compilation of known landslides, debris flows, lahars, and outburst floods that generated seismic signals observable on existing seismic networks. The data release includes basic information about each event such as location, volume, area, and runout distances as well as information about seismic detections and the location of seismic data, photos, maps, GIS files, and links to papers, websites, and media reports about the event. Not all record types exist for each event, and the quality of the information varies from event to event. While the SQLite3 database (lsseis.db) is the native format of this database and preserves its relational structure, for the convenience of users,...
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Introduction This data release is a compilation of known mass movements that generated seismic signals recorded by seismic networks. It represents a major update of a previous data release (Allstadt and others, 2017) available at https://doi.org/10.5066/F7251H3W. This update includes all events published in the previous data release along with more instances of landslides, debris flows, snow avalanches, outburst floods, and lahars, as well as new event types including mine collapses, a submarine landslide, a volcanic flank collapse, and a pyroclastic density current. The 2017 release included only mass movements in the western United States and Canada. The current data release adds new events in North America, and...
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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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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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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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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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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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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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Unvegetated to vegetated marsh ratio (UVVR) in the Assateague Island National Seashore and Chincoteague Bay is computed based on conceptual marsh units defined by Defne and Ganju (2018). UVVR was calculated based on U.S. Department of Agriculture National Agriculture Imagery Program (NAIP) 1-meter resolution imagery. Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands, including the Assateague Island National Seashore and Chincoteague Bay salt marshes, with the intent of providing Federal, State, and local managers with tools to estimate the vulnerability and...
map background search result map search result map Habitat--Offshore of Aptos, California Offshore baseline for the exposed East Beaufort Sea, Alaska coastal region (U.S. Canadian Border to the Hulahula River) generated to calculate shoreline change rates Offshore baseline for the exposed West Beaufort Sea, Alaska coastal region (Colville River to Point Barrow) generated to calculate shoreline change rates Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Sheltered Central Beaufort Sea coast of Alaska between the Hulahula River and the Colville River Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term Linear Regression Rate Calculations for the Sheltered West Beaufort Sea coast of Alaska between the Colville River and Point Barrow Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term End Point Rate Calculations for the Sheltered East Chukchi Sea coast of Alaska between Point Barrow and Icy Cape Seismogenic Landslides, Debris Flows, and Outburst Floods in the Western United States and Canada from 1977 to 2017 Unvegetated to vegetated marsh ratio in Assateague Island National Seashore and Chincoteague Bay, Maryland and Virginia DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Cape Hatteras, NC, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cape Hatteras, NC, 2014 Development: Development delineation: Rhode Island National Wildlife Refuge, RI, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Rhode Island National Wildlife Refuge, RI, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Metompkin Island, VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Ship Shoal Island, VA, 2014 Footprints and producers of source data used to create northern portion of the high-resolution (1 m) San Francisco Bay, California, digital elevation model (DEM) Geospatial database of the 2018 lower East Rift Zone eruption of Kīlauea Volcano, Hawaiʻi Offshore baseline generated to calculate shoreline change rates near Barter Island, Alaska Western U.S. geologic deformation model for use in the U.S. National Seismic Hazard Model 2023, version 1.0 Seismogenic Landslides and other Mass Movements (ver. 2.0, December 2023) Maximum horizontal stress orientation and relative stress magnitude (faulting regime) data throughout North America (COPY) DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Ship Shoal Island, VA, 2014 DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Metompkin Island, VA, 2014 Offshore baseline generated to calculate shoreline change rates near Barter Island, Alaska Habitat--Offshore of Aptos, California Geospatial database of the 2018 lower East Rift Zone eruption of Kīlauea Volcano, Hawaiʻi Footprints and producers of source data used to create northern portion of the high-resolution (1 m) San Francisco Bay, California, digital elevation model (DEM) Development: Development delineation: Rhode Island National Wildlife Refuge, RI, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Rhode Island National Wildlife Refuge, RI, 2014 Unvegetated to vegetated marsh ratio in Assateague Island National Seashore and Chincoteague Bay, Maryland and Virginia DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Cape Hatteras, NC, 2014 shoreline, inletLines: Shoreline polygons and tidal inlet delineations: Cape Hatteras, NC, 2014 Offshore baseline for the exposed East Beaufort Sea, Alaska coastal region (U.S. Canadian Border to the Hulahula River) generated to calculate shoreline change rates Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term Linear Regression Rate Calculations for the Sheltered West Beaufort Sea coast of Alaska between the Colville River and Point Barrow Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Short-Term End Point Rate Calculations for the Sheltered East Chukchi Sea coast of Alaska between Point Barrow and Icy Cape Digital Shoreline Analysis System (DSAS) version 4.3 Transects with Long-Term Linear Regression Rate Calculations for the Sheltered Central Beaufort Sea coast of Alaska between the Hulahula River and the Colville River Offshore baseline for the exposed West Beaufort Sea, Alaska coastal region (Colville River to Point Barrow) generated to calculate shoreline change rates Western U.S. geologic deformation model for use in the U.S. National Seismic Hazard Model 2023, version 1.0 Seismogenic Landslides, Debris Flows, and Outburst Floods in the Western United States and Canada from 1977 to 2017 Seismogenic Landslides and other Mass Movements (ver. 2.0, December 2023) Maximum horizontal stress orientation and relative stress magnitude (faulting regime) data throughout North America (COPY)