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At least 433 records · Page 24Linked to original sources
USGS2010

Oblique Aerial Photography of the Arctic Coast of Alaska, Cape Sabine to Milne Point, July 16-19, 2009

The Arctic Coastal Plain of northern Alaska, an area of strategic economic importance to the United States, is home to remote Native American communities and encompasses unique habitats of global significance. Coastal erosion along the Arctic coast is chronic and widespread; recent evidence suggests that erosion rates are among the highest in the world (as high as ~16 m/yr) and may be accelerating. Coastal erosion adversely impacts energy-related infrastructure, natural shoreline habitats, and Native American communities. Climate change is thought to be a key component of recent environmental changes in the Arctic. Reduced sea-ice cover in the Arctic Ocean is one of the probable mechanisms responsible for increasing coastal exposure to wave attack and the resulting increase in erosion. Extended periods of permafrost melting and associated decreases in bluff cohesion and stability are another possible source of the increase in erosion. Several studies of selected areas on the Alaska coast document past shoreline positions and coastal change, but none have examined the entire North coast systematically. Results from these studies indicate high rates of coastal retreat that vary spatially along the coast. To address the need for a comprehensive and regionally consistent evaluation of shoreline change along the North coast of Alaska, the U.S. Geological Survey (USGS), as part of their Coastal and Marine Geology Program's (CMGP) National Assessment of Shoreline Change Study, is evaluating shoreline change from Peard Bay to the United States/Canadian border, using historical maps and photography and a standardized methodology that is consistent with other shoreline-change studies along the Nation's coastlines (see, for example, http://coastal.er.usgs.gov/shoreline-change/, last accessed February 12, 2010). This is the second in a series of publications containing photographs collected during reconnaissance surveys conducted in support of the National Assessment of Shoreline Change Study. An accompanying ESRI ArcGIS shape file (and plaintext copy) indicates the position of the aircraft and time when each photograph was taken. The USGS-CMGP Field Activity ID for the survey is A-5-09-AK, and more information on the survey and how to view the photographs using Google Earth software is available online at http://walrus.wr.usgs.gov/infobank/a/a509ak/html/a-5-09-ak.photos.kmz (last accessed February 12, 2010). The initial report ?Oblique aerial photography of the Arctic coast of Alaska, Nulavik to Demarcation Point, August 7-10, 2006? is available online at http://pubs.usgs.gov/ds/436/, and the associated Google Earth .kmz file is available at http://walrus.wr.usgs.gov/infobank/a/a106ak/html/a-1-06-ak.photos.kmz (last accessed February 12, 2010).

Data Series↗
USGS2010

EAARL Coastal Topography-Eastern Florida, Post-Hurricane Jeanne, 2004: First Surface

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the eastern Florida coastline beachface, acquired post-Hurricane Jeanne (September 2004 hurricane) on October 1, 2004. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗
USGS2010

EAARL Coastal Topography-Maryland and Delaware, Post-Nor'Ida, 2009

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL. This project provides highly detailed and accurate datasets of a portion of the eastern Maryland and Delaware coastline beachface, acquired post-Nor'Ida (November 2009 nor'easter) on November 28 and 30, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗
USGS2011

EAARL Coastal Topography--Cape Canaveral, Florida, 2009: First Surface

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Kennedy Space Center, FL. This project provides highly detailed and accurate datasets of a portion of the eastern Florida coastline beachface, acquired on May 28, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations.

Data Series↗
USGS2011

EAARL coastal topography-Virginia, post-Nor'Ida, 2009

This DVD contains lidar-derived first-surface (FS) and bare-earth (BE) topography GIS datasets of a portion of the Virginia coastline beachface. These datasets were acquired post-Nor'Ida on November 27, 2009, November 29, 2009, and December 1, 2009.

Post-no'ida↗
USGS2001

Coastal vulnerability to sea-level rise: a preliminary database for the U.S. Atlantic, Pacific, and Gulf of Mexico coasts

The prediction of coastal evolution is not straightforward. There is no standard methodology, and even the kind of data required to make such predictions are the subject of much scientific debate. Since a viable, quantitative predictive model for coastal evolution is not available. The relative susceptibility of the Nation's coastline to sea-level rise is quantified here at a regional to national scale using basic information on coastal geomorphology, rate of sea-level rise, past shoreline evolution and other factors. This approach combines the coastal system's susceptibility to change with its natural ability to adapt to changing environmental and conditions, and yields a relative measure of the system's natural vulnerability to the effects of sea-level rise. This information has immediate application to many of the decisions our society will be making regarding coastal development in both the short- and long-term.

Data Series↗
USGS2012

A seamless, high-resolution digital elevation model (DEM) of the north-central California coast

A seamless, 2-meter resolution digital elevation model (DEM) of the north-central California coast has been created from the most recent high-resolution bathymetric and topographic datasets available. The DEM extends approximately 150 kilometers along the California coastline, from Half Moon Bay north to Bodega Head. Coverage extends inland to an elevation of +20 meters and offshore to at least the 3 nautical mile limit of state waters. This report describes the procedures of DEM construction, details the input data sources, and provides the DEM for download in both ESRI Arc ASCII and GeoTIFF file formats with accompanying metadata.

California↗
USGS2014

National Assessment of Oil and Gas Project: geologic assessment of undiscovered gas hydrate resources on the North Slope, Alaska

Scientists with the U.S. Geological Survey have completed the first assessment of the undiscovered, technically recoverable gas hydrate resources beneath the North Slope of Alaska. This assessment indicates the existence of technically recoverable gas hydrate resources—that is, resources that can be discovered, developed, and produced using current technology. The approach used in this assessment followed standard geology-based USGS methodologies developed to assess conventional oil and gas resources. In order to use the USGS conventional assessment approach on gas hydrate resources, three-dimensional industry-acquired seismic data were analyzed. The analyses indicated that the gas hydrates on the North Slope occupy limited, discrete volumes of rock bounded by faults and downdip water contacts. This assessment approach also assumes that the resource can be produced by existing conventional technology, on the basis of limited field testing and numerical production models of gas hydrate-bearing reservoirs. The area assessed in northern Alaska extends from the National Petroleum Reserve in Alaska on the west through the Arctic National Wildlife Refuge on the east and from the Brooks Range northward to the State-Federal offshore boundary (located 3 miles north of the coastline). This area consists mostly of Federal, State, and Native lands covering 55,894 square miles. Using the standard geology-based assessment methodology, the USGS estimated that the total undiscovered technically recoverable natural-gas resources in gas hydrates in northern Alaska range between 25.2 and 157.8 trillion cubic feet, representing 95 percent and 5 percent probabilities of greater than these amounts, respectively, with a mean estimate of 85.4 trillion cubic feet.

Alaska↗
USGS2013

EAARL coastal topography and imagery–Western Louisiana, post-Hurricane Rita, 2005: First surface

These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived first-surface (FS) topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, Virginia. This project provides highly detailed and accurate datasets of a portion of the Louisiana coastline beachface, acquired post-Hurricane Rita on September 27-28 and October 2, 2005. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the National Aeronautics and Space Administration (NASA) Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Lidar for Science and Resource Management Website.

Louisiana↗
USGS2012

Archive of single-beam bathymetry data collected during USGS cruise 07CCT01 nearshore of Fort Massachusetts and within Camille Cut, West and East Ship Islands, Gulf Islands National Seashore, Mississippi, July 2007

The Gulf Islands National Seashore (GUIS) is composed of a series of barrier islands along the Mississippi - Alabama coastline. Historically these islands have undergone long-term shoreline change. The devastation of Hurricane Katrina in 2005 prompted questions about the stability of the barrier islands and their potential response to future storm impacts. Additionally, there was concern from the National Park Service (NPS) about the preservation of the historical Fort Massachusetts, located on West Ship Island. During the early 1900s, Ship Island was an individual island. In 1969 Hurricane Camille breached Ship Island, widening the cut and splitting it into what is now known as West Ship Island and East Ship Island. In July of 2007, the U.S. Geological Survey (USGS) was able to provide the NPS with a small bathymetric survey of Camille Cut using high-resolution single-beam bathymetry. This provided GUIS with a post-Katrina assessment of the bathymetry in Camille Cut and along the northern shoreline directly in front of Fort Massachusetts. Ultimately, this survey became an initial bathymetry dataset toward a larger USGS effort included in the Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility Project ( http://ngom.usgs.gov/gomsc/mscip/ ). This report serves as an archive of the processed single-beam bathymetry. Data products herein include gridded and interpolated digital depth surfaces and x,y,z data products. Additional files include trackline maps, navigation files, geographic information system (GIS) files, Field Activity Collection System (FACS) logs, and formal Federal Geographic Data Committee (FGDC) metadata. Scanned images of the handwritten FACS logs and digital FACS logs are also provided as PDF files. Refer to the Acronyms page for description of acronyms and abbreviations used in this report or hold the cursor over an acronym for a pop-up explanation. The USGS St. Petersburg Coastal and Marine Science Center assigns a unique identifier to each cruise or field activity. For example, 07CCT01 tells us the data were collected in 2007 for the Coastal Change and Transport (CCT) study and the data were collected during the first (01) field activity for that project in that calendar year. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the field activity ID. Data were collected using a 26-foot (ft) Glacier Bay catamaran. The single-beam transducers were sled mounted on a rail attached between the catamaran hulls. Navigation was acquired using HYPACK, Inc., Hypack version 4.3a.7.1 and differentially corrected using land-based GPS stations. See the digital FACS equipment log for details about the acquisition equipment used. Raw datasets were stored digitally and processed systematically using NovAtel's Waypoint GrafNav version 7.6, SANDS version 3.7, and ESRI ArcGIS version 9.3.1. For more information on processing refer to the Equipment and Processing page.

Mississippi↗
USGS2014

EAARL-B coastal topography: eastern New Jersey, Hurricane Sandy, 2012: first surface

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida. This project provides highly detailed and accurate datasets for a portion of the New Jersey coastline beachface, acquired pre-Hurricane Sandy on October 26, and post-Hurricane Sandy on November 1 and November 5, 2012. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar system, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nm) lidar designed to map nearshore bathymetry, topography, and vegetation structure simultaneously. The EAARL-B sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, down-looking red-green-blue (RGB) and infrared (IR) digital cameras, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL-B platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL-B system. The resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Lidar for Science and Resource Management Web site.

New Jersey↗
USGS2015

Chemical and ancillary data associated with bed sediment, young of year Bluefish ( Pomatomus saltatrix ) tissue, and mussel ( Mytilus edulis and Geukensia demissa ) tissue collected after Hurricane Sandy in bays and estuaries of New Jersey and New York, 2013–14

This report describes the methods and data associated with a reconnaissance study of young of year bluefish and mussel tissue samples as well as bed sediment collected as bluefish habitat indicators during August 2013–April 2014 in New Jersey and New York following Hurricane Sandy in October 2012. This study was funded by the Disaster Relief Appropriations Act of 2013 (PL 113-2) and was conducted by the U.S. Geological Survey (USGS) in cooperation with the National Oceanic and Atmospheric Administration (NOAA). Young of year Pomatomus saltatrix (bluefish) were collected from nine sites in New Jersey (N.J.) and New York (N.Y.) including Barnegat Bay, N.J., Sandy Hook Bay, N.J., Jamaica Bay, N.Y., and Great South Bay, N.Y., and analyzed for indicators of health and chemical contamination. At each bluefish sampling location, bed sediment was also collected and analyzed for a suite of contaminants. Resident mussels, Mytilus edulis (blue mussels) and (or) Geukensia demissa (ribbed mussels), were collected from 11 historic NOAA Mussel Watch Program sites along the N.J. and N.Y. coastlines in the winter/spring of 2014 and analyzed for contaminants. Individual age of a subset of the mussels sampled was also determined at each site. Bed sediment samples were analyzed for a suite of organic contaminants including 34 polychlorinated biphenyl (PCB) congeners, 28 polybrominated diphenyl ether (PBDE) congeners, 24 organochlorine pesticides (OCPs), 53 polycyclic aromatic hydrocarbons (PAHs) and alkylated PAHs, 33 aliphatic hydrocarbons (AHs), and 10 petroleum biomarkers (steranes and hopanes). Bed sediment collected from the Navesink River (Sandy Hook, N.J.), Metedeconk River (Barnegat Bay, N.J.), and Toms River (Barnegat Bay, N.J.) had the highest concentrations of contaminants compared to the other sites. Bluefish and mussel tissue collected throughout the study area was analyzed for 34 PCB congeners, 28 PBDE congeners, and 24 OCPs. Thirty-three PCB congeners, 22 PBDE congeners, and 24 OCPs were detected in the bluefish analyzed. The highest median concentrations of total PCBs were present in tissue from Jamaica Bay, N.Y., whereas the highest median concentrations of total PBDEs and total OCPs were present in tissue from Sandy Hook Bay. Of the OCPs detected, p,p’ -DDE was found in 99 percent (%) of the tissue samples and at the highest median concentrations compared to the other OCPs. Fish health assessments were conducted on 20 fish from the 4 bays. Results indicate that the sex ratio and the mean total length varied by site. Physical fish damage, such as lesions and parasites, was observed in fish from all four bays. The most common parasite observed visually was the presence of Livoneca redmanii , an ectoparasitic gill isopod, which can cause localized gill erosion. The prevalence of the gill isopod infestation ranged from 20% at Great South Bay, N.Y., to 35% at Jamaica Bay, N.Y. Twenty three PCB congeners, 9 PBDE congeners, and 20 OCPs were detected in composite mussel samples collected throughout the study area. The co-eluting PCB congeners 153 and 132, PBDE 47, 99, and 100, and p,p’ -DDE were detected in samples from each site. The highest median concentrations of PCBs and PBDEs were present in mussels from Raritan Bay, N.Y., whereas the highest median concentrations of OCPs were present in mussels from Fire Island Inlet, N.Y., and Shark River, N.J. Mytilus edulis (blue mussels) and Geukensia demissa (ribbed mussels) were thin-sectioned and aged. The blue mussels collected ranged in age from 4 to 13 years, and the ribbed mussels ranged in age from 3 to 12 years.

New Jersey, New York↗
USGS2015

Archive of bathymetry data collected at Cape Canaveral, Florida, 2014

Remotely sensed, geographically referenced elevation measurements of the sea floor, acquired by boat- and aircraft-based survey systems, were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida, for the area at Cape Canaveral. The work was conducted as part of a study to describe an updated bathymetric dataset collected in 2014 and compare it to previous data sets. The updated data focus on the bathymetric features and sediment transport pathways that connect the offshore regions to the shoreline and, therefore, are related to the protection of other portions of the coastal environment, such as dunes, that support infrastructure and ecosystems. Cape Canaveral Coastal System (CCCS) is a prominent feature along the Southeast U.S. coastline and is the only large cape south of Cape Fear, North Carolina. Most of the CCCS lies within the Merritt Island National Wildlife Refuge and included within its boundaries are the Cape Canaveral Air Force Station (CCAFS), NASA’s Kennedy Space Center (KSC), and a large portion of Canaveral National Seashore. The actual promontory of the modern cape falls within the jurisdictional boundaries of the CCAFS. Hydrographic survey data were collected August 18-20, 2014 ( USGS Field Activity Number 2014-324-FA ). The study covered a 20 kilometer (km) section of shoreline extending from Port Canaveral, Fla., to the northern end of the KSC property, and from the shoreline to about 2.5 km offshore. Data were acquired using both sound navigation and ranging (sonar) and light detection and ranging (lidar) systems. Two jet skis and a 17-foot (ft) outboard motor boat equipped with the USGS SANDS (System for Accurate Nearshore Depth Surveying) hydrographic system collected precision sonar data. The USGS airborne EAARL-B mapping system flown in a twin engine airplane was used to collect lidar data. The missions were synchronized so that there was temporal and spatial overlap between the sonar and lidar operations. Additional data were collected to evaluate water clarity to verify the ability of lidar to receive bathymetric returns. Both systems used differential Global Positioning System GPS and utilized the National Oceanic and Atmospheric Administration/National Geodetic Survey (NOAA/NGS) Continuously Operating Reference Station (CORS) station located at CCAFS was used as the reference station. This data series serves as an archive of processed single-beam sonar and lidar bathymetry data. Graphical Information System (GIS) data products include XYZ point bathymetry data files, a color coded bathymetry map, and interpolated bathymetry grid surface. Additional information includes an error analysis and formal Federal Geographic Data Committee (FGDC) metadata. For more information about similar projects, please visit the Barrier Island Evolution Web site.

Florida↗
USGS2015

Land-cover types, shoreline positions, and sand extents derived From Landsat satellite imagery, Assateague Island to Metompkin Island, Maryland and Virginia, 1984 to 2014

The U.S. Geological Survey has a long history of responding to and documenting the impacts of storms along the Nation’s coasts and incorporating these data into storm impact and coastal change vulnerability assessments. These studies, however, have traditionally focused on sandy shorelines and sandy barrier-island systems, without consideration of impacts to coastal wetlands. The goal of the Barrier Island and Estuarine Wetland Physical Change Assessment project is to integrate a wetland-change assessment with existing coastal-change assessments for the adjacent sandy dunes and beaches, initially focusing on Assateague Island along the Maryland and Virginia coastline. Assateague Island was impacted by waves and storm surge associated with the passage of Hurricane Sandy in October 2012, including erosion and overwash along the ocean-facing sandy shoreline as well as erosion and overwash deposition in the back-barrier and estuarine bay environments. This report serves as an archive of data that were derived from Landsat 5 and Landsat 8 imagery from 1984 to 2014, including wetland and terrestrial habitat extents; open-ocean, back-barrier, and estuarine mainland shoreline positions; and sand-line positions along the estuarine mainland and barrier shorelines from Assateague Island, Maryland to Metompkin Island, Virginia. The geographic information system data files with accompanying formal Federal Geographic Data Committee metadata can be downloaded from the Data Downloads page.

Maryland, Virginia↗
USGS2016

Sedimentologic characteristics of recent washover deposits from Assateague Island, Maryland

The U.S. Geological Survey has a long history of responding to and documenting the impacts of storms along the Nation’s coasts and incorporating these data into storm impact and coastal change vulnerability assessments. Although physical changes caused by tropical and extratropical storms to the sandy beaches and dunes fronting barrier islands are generally well documented, the interaction between sandy shoreline erosion and overwash with the back-barrier wetland and estuarine environments is poorly constrained. The goal of the Barrier Island and Estuarine Wetland Physical Change Assessment project is to integrate a wetland-change assessment with existing coastal-change assessments for the adjacent sandy dunes and beaches, initially focusing on Assateague Island along the Maryland and Virginia coastline. Assateague Island was impacted by waves and storm surge associated with the passage of Hurricane Sandy in October 2012, causing erosion and overwash along the ocean-facing sandy shoreline as well as erosion and overwash deposition in the back-barrier and estuarine bay environments. This report describes sediment data collected using sand augers in active overwash zones on Assateague Island in Maryland. Samples were collected by the U.S. Geological Survey (USGS) during two surveys in March/April and October 2014 (USGS Field Activity Numbers [FAN] 2014-301-FA and 2014-322-FA, respectively). The physical characteristics (for example, sediment texture or bedding structure) of and spatial differences among these deposits will provide information about overwash processes and sediment transport from the sandy barrier-island reaches to the back-barrier environments. Metrics derived from these data, such as mean grain size or deposit thicknesses, can be used to ground-truth remote sensing and geophysical data and can also be incorporated into sediment transport models. Data products, including sample location tables, descriptive core logs, core photographs and x-radiographs, the results of sediment grain-size analyses, and Geographic Information System (GIS) data files with accompanying formal Federal Geographic Data Committee (FGDC) metadata can be downloaded from the Data Downloads page.

Maryland↗
USGS2003

Effects of hydrology on red mangrove recruits

Coastal wetlands along the Gulf of Mexico have been experiencing significant shifts in hydrology and salinity levels over the past century as a result of changes in sea level and freshwater drainage patterns. Local land management in coastal zones has also impacted the hydrologic regimes of salt marshes and mangrove areas. Parks and refuges in south Florida that contain mangrove forests have, in some cases, been ditched or impounded to control mosquito outbreaks and to foster wildlife use. And while mangroves dominate the subtropical coastlines of Florida and thrive in saltwater environments, little is known about how they respond to changes in hydrology under managed or variable tidal conditions. USGS researchers designed a study to evaluate the basic hydrological requirements of mangroves so that their health and survival may be more effectively managed in controlled impoundments and restored wetlands. Mangroves are commonly found in the intertidal zone (between low and high tides) in a rather broad spectrum of hydrologic settings. Because they thrive at the interface of land and sea, mangroves are subject to changes in freshwater flow (flow rate, nutrients, pollutants) and to marine influences (sea-level rise, salinity). Salinity has long been recognized as a controlling factor that determines the health and distribution of mangrove forests. Field and experimental observations indicate that most mangrove species achieve their highest growth potential under brackish conditions (modest salinity) between 10 and 20 parts per thousand (ppt). Yet, if provided with available propagules, successful regeneration, and limited competition from other plants, then mangroves can survive and thrive in freshwater systems as well. Because little is known about the growthand survival patterns of mangrove species relative to changing hydrology, USGS scientists conducted greenhouse and field experiments to determine how flooded or drained patterns of hydrology would influence growth of the red mangrove, Rhizophora mangle (fig. 1). Red mangrove propagules (recruits) of select sizes and genotypes (i.e., genetically similar groups) were planted both in greenhouses and in the field. Seedling growth was monitored in both studies on a quarterly basis for over a year; measurements included shoot growth, seedling height, and a final harvest of plant biomass.

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