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USGS2009

EAARL Coastal Topography - Northern Gulf of Mexico, 2007: First surface

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) elevation data were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. The project provides highly detailed and accurate datasets of select barrier islands and peninsular regions of Louisiana, Mississippi, Alabama, and Florida, acquired June 27-30, 2007. 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 multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit which provide for submeter 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.

Alabama, Mississippi↗
USGS2009

EAARL Coastal Topography-Pearl River Delta 2008: Bare Earth

These remotely sensed, geographically referenced elevation measurements of Lidar-derived bare earth (BE) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the University of New Orleans (UNO), Pontchartrain Institute for Environmental Sciences (PIES), New Orleans, LA; 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 Pearl River Delta in Louisiana and Mississippi, acquired March 9-11, 2008. 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 multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter 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 first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

Data Series↗
USGS2008

EAARL coastal topography — Fire Island National Seashore 2007

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) and bare earth (BE) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of Fire Island National Seashore in New York, acquired on April 29-30 and May 15-16, 2007. 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 multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers and an integrated miniature digital inertial measurement unit, which provide for submeter 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 pre-survey 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 routinely used to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

New York↗
USGS2008

EAARL coastal topography — Sandy Hook 2007

These remotely sensed, geographically referenced elevation measurements of Lidar-derived topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of Gateway National Recreation Area's Sandy Hook Unit in New Jersey, acquired on May 16, 2007. 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 multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers and an integrated miniature digital inertial measurement unit, which provide for submeter 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 pre-survey 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 routinely used to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

New York↗
USGS2009

EAARL Coastal Topography-Pearl River Delta 2008: First Surface

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the University of New Orleans (UNO), Pontchartrain Institute for Environmental Sciences (PIES), New Orleans, LA; 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 Pearl River Delta in Louisiana and Mississippi, acquired March 9-11, 2008. 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 multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter 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 first surface 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--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↗
USGS2022

Development of projected depth-duration frequency curves (2050–89) for south Florida

Planning stormwater projects requires estimates of current and future extreme precipitation depths for events with specified return periods and durations. In this study, precipitation data from four downscaled climate datasets are used to determine changes in precipitation depth-duration-frequency curves from the period 1966–2005 to the period 2050–89 primarily on the basis of Representative Concentration Pathways 4.5 and 8.5 emission scenarios from the Coupled Model Intercomparison Project Phase 5. The four downscaled climate datasets are (1) the Coordinated Regional Downscaling Experiment (CORDEX) dataset, (2) the Localized Constructed Analogs (LOCA) dataset, (3) the Multivariate Adaptive Constructed Analogs (MACA) dataset, and (4) the Jupiter Intelligence Weather Research and Forecasting Model (JupiterWRF) dataset. Change factors—multiplicative changes in expected extreme precipitation magnitude from current to future period—were computed for grid cells from the downscaled climate datasets containing National Oceanic and Atmospheric Administration Atlas 14 stations in central and south Florida. Change factors for specific durations and return periods may be used to scale the National Oceanic and Atmospheric Administration Atlas 14 historical depth-duration-frequency values to the period 2050–89 on the basis of changes in extreme precipitation derived from downscaled climate datasets. Model culling was implemented to select downscaled climate models that best captured observed historical patterns of precipitation extremes in central and south Florida. Overall, a large variation in change factors across downscaled climate datasets was found, with change factors generally greater than one and increasing with return period. In general, median change factors were higher for the south-central Florida climate region (1.05–1.55 depending on downscaled climate dataset, duration, and return period) than for the south Florida climate region (1–1.4 depending on downscaled climate dataset, duration, and return period) when considering best performing models for both areas, indicating a projected overall increase in future extreme precipitation events.

Florida↗
USGS2011

EAARL Coastal Topography-Cape Hatteras National Seashore, North Carolina, Post-Nor'Ida, 2009: Bare Earth

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) 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 Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the National Park Service Southeast Coast Network's Cape Hatteras National Seashore in North Carolina, acquired post-Nor'Ida (November 2009 nor'easter) on November 27 and 29 and December 1, 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↗
USGS2012

EAARL coastal topography--Alligator Point, Louisiana, 2010

This project provides highly detailed and accurate datasets of a portion of Alligator Point, Louisiana, acquired on March 5 and 6, 2010. 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 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.

Louisiana↗
USGS2021

Optimization of salt marsh management at the Moosehorn National Wildlife Refuge, Maine, through use of structured decision making

Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Moosehorn National Wildlife Refuge in Maine. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of four marsh management units within the refuge, totaling about 13 hectares, and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to $ 1,000, and may continue to increase at a lower rate with further expenditures. Potential management actions in optimal portfolios at total costs less than or equal to $ 1,000 included improving nesting habitat for Ammodramus nelsoni (Nelson’s sparrow) or restoring hydrologic connections to the upper marsh in one marsh management unit (Hobart Stream West). The potential management benefits were derived from expected increases in the density of nekton and of spiders (as an indicator of trophic health). The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Moosehorn National Wildlife Refuge that can be updated for implementation as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuge.

Maine↗
USGS1988

Fracture characterization and fracture-permeability estimation at the underground research laboratory in southeastern Manitoba, Canada

Various conventional geophysical well logs were obtained in conjunction with acoustic tube-wave amplitude and experimental heat-pulse flowmeter measurements in two deep boreholes in granitic rocks on the Canadian shield in southeastern Manitoba. The objective of this study is the development of measurement techniques and data processing methods for characterization of rock volumes that might be suitable for hosting a nuclear waste repository. One borehole, WRA1, intersected several major fracture zones, and was suitable for testing quantitative permeability estimation methods. The other borehole, URL13, appeared to intersect almost no permeable fractures; it was suitable for testing methods for the characterization of rocks of very small permeability and uniform thermo-mechanical properties in a potential repository horizon. Epithermal neutron , acoustic transit time, and single-point resistance logs provided useful, qualitative indications of fractures in the extensively fractured borehole, WRA1. A single-point log indicates both weathering and the degree of opening of a fracture-borehole intersection. All logs indicate the large intervals of mechanically and geochemically uniform, unfractured granite below depths of 300 m in the relatively unfractured borehole, URL13. Some indications of minor fracturing were identified in that borehole, with one possible fracture at a depth of about 914 m, producing a major acoustic waveform anomaly. Comparison of acoustic tube-wave attenuation with models of tube-wave attenuation in infinite fractures of given aperture provide permeability estimates ranging from equivalent single-fractured apertures of less than 0.01 mm to apertures of > 0.5 mm. One possible fracture anomaly in borehole URL13 at a depth of about 914 m corresponds with a thin mafic dike on the core where unusually large acoustic contrast may have produced the observed waveform anomaly. No indications of naturally occurring flow existed in borehole URL13; however, flowmeter measurements indicated flow at < 0.05 L/min from the upper fracture zones in borehole WRA1 to deeper fractures at depths below 800 m. (Author 's abstract)

Water-Resources Investigations Report↗
USGS2010

Cartographic Production for the FLaSH Map Study: Generation of Rugosity Grids, 2008

Project Summary This series of raster data is a U.S. Geological Survey (USGS) Data Series release from the Florida Shelf Habitat Project (FLaSH). This disc contains two raster images in Environmental Systems Research Institute, Inc. (ESRI) raster grid format, jpeg image format, and Geo-referenced Tagged Image File Format (GeoTIFF). Data is also provided in non-image ASCII format. Rugosity grids at two resolutions (250 m and 1000 m) were generated for West Florida shelf waters to 250 m using a custom algorithm that follows the methods of Valentine and others (2004). The Methods portion of this document describes the specific steps used to generate the raster images. Rugosity, also referred to as roughness, ruggedness, or the surface-area ratio (Riley and others, 1999; Wilson and others, 2007), is a visual and quantitative measurement of terrain complexity, a common variable in ecological habitat studies. The rugosity of an area can affect biota by influencing habitat, providing shelter from elements, determining the quantity and type of living space, influencing the type and quantity of flora, affecting predator-prey relationships by providing cover and concealment, and, as an expression of vertical relief, can influence local environmental conditions such as temperature and moisture. In the marine environment rugosity can furthermore influence current flow rate and direction, increase the residence time of water in an area through eddying and current deflection, influence local water conditions such as chemistry, turbidity, and temperature, and influence the rate and nature of sedimentary deposition. State-of-the-art computer-mapping techniques and data-processing tools were used to develop shelf-wide raster and vector data layers. Florida Shelf Habitat (FLaSH) Mapping Project (http://coastal.er.usgs.gov/flash) endeavors to locate available data, identify data gaps, synthesize existing information, and expand our understanding of geologic processes in our dynamic coastal and marine systems.

Data Series↗
USGS2002

Documentation and analysis of a geographic information system application for combining data layers, using nonpoint-source pollution as an example

A geographical information system application has been developed that allows scientists to combine multiple data layers into a single data layer. This application provides an effective tool for identifying areas where the potential effect of the combination of data layers may be greater than any single data layer. Such a tool is useful in studying an activity that cannot be measured directly. Scientists wanting to identify areas where an activity may have the greatest effect can identify factors that directly or indirectly reflect the effect of the activity being studied. When combined, these factors would identify areas where the potential for the activity to have an effect are greatest. The data layers used to develop the single data layer determine the activity addressed by the application?the application was developed to identify areas where the potential for nonpoint-source pollution to affect areas of Indiana is greater relative to other areas in Indiana. To evaluate the potential in other states or areas, data layers for those states or areas would be used. To address a different activity, even activities not related to water resources, data layers that directly or indirectly reflect the effects of the activity being studied would be used in the application. The application was developed using Environmental System Research Institute's ArcView geographical information system and the ArcView extension, Spatial Analyst. To use the application, the user selects data layers related to the activity being studied, describes the variability of a data element between geographic areas on each data layer, assigns a relative importance factor to each data layer, and focuses the output by identifying a watershed of interest. The application then assigns a rank value to the features within each data layer on the basis of the spatial variation of the data layer. The data layers are converted to grids. The values of the grid cells are the product of the rank values and the importance factors. The cells for each data layer are combined to form a single grid. The combination is summarized to describe the spatial variation for the watershed of interest. The combined data layer does not show the actual potential effect of the selected factors but rather the relative difference in the potential effect among areas when all data layers are considered. An analysis of the application indicates that the selected data layers to be combined should be at the greatest spatial resolution possible; however, all data layers do not have to be at the same spatial resolution. The spatial variation of the data layers should be adequately defined. The size of each grid cell should be small enough to maintain the spatial definition of smaller features within the data layers. The most accurate results are shown to occur when the values for the grid cells representing the individual data layers are summed and the mean of the summed grid-cell values is used to describe the watershed of interest.

Indiana↗
USGS2021

Optimization of salt marsh management at the Long Island National Wildlife Refuge Complex, New York, through use of structured decision making

Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Long Island National Wildlife Refuge Complex in New York. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of five marsh management units within the refuge complex and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge-complex scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to about $24,000 , but that further expenditures may yield diminishing return on investment. Potential management actions in optimal portfolios at total costs less than $24,000 consistently included approaches for increasing drainage from the marsh surface within the marsh management units. The potential management benefits were derived from expected improvements in surface-water drainage and capacity for marsh elevation to keep pace with sea-level rise, and presumed increases in numbers of spiders (as an indicator of trophic health) and tidal marsh obligate birds. The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Long Island National Wildlife Refuge Complex that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.

New York↗
USGS2003

Methods of analysis by the U.S. Geological Survey National Water Quality Laboratory-Evaluation of alkaline persulfate digestion as an alternative to Kjeldahl digestion for determination of total and dissolved nitrogen and phosphorus in water

Alkaline persulfate digestion was evaluated and validated as a more sensitive, accurate, and less toxic alternative to Kjeldahl digestion for routine determination of nitrogen and phosphorus in surface- and ground-water samples in a large-scale and geographically diverse study conducted by U.S. Geological Survey (USGS) between October 1, 2001, and September 30, 2002. Data for this study were obtained from about 2,100 surface- and ground-water samples that were analyzed for Kjeldahl nitrogen and Kjeldahl phosphorus in the course of routine operations at the USGS National Water Quality Laboratory (NWQL). These samples were analyzed independently for total nitrogen and total phosphorus using an alkaline persulfate digestion method developed by the NWQL Methods Research and Development Program. About half of these samples were collected during nominally high-flow (April-June) conditions and the other half were collected during nominally low-flow (August-September) conditions. The number of filtered and whole-water samples analyzed from each flow regime was about equal.By operational definition, Kjeldahl nitrogen (ammonium + organic nitrogen) and alkaline persulfate digestion total nitrogen (ammonium + nitrite + nitrate + organic nitrogen) are not equivalent. It was necessary, therefore, to reconcile this operational difference by subtracting nitrate + nitrite concentra-tions from alkaline persulfate dissolved and total nitrogen concentrations prior to graphical and statistical comparisons with dissolved and total Kjeldahl nitrogen concentrations. On the basis of two-population paired t-test statistics, the means of all nitrate-corrected alkaline persulfate nitrogen and Kjeldahl nitrogen concentrations (2,066 paired results) were significantly different from zero at the p = 0.05 level. Statistically, the means of Kjeldahl nitrogen concentrations were greater than those of nitrate-corrected alkaline persulfate nitrogen concentrations. Experimental evidence strongly suggests, however, that this apparent low bias resulted from nitrate interference in the Kjeldahl digestion method rather than low nitrogen recovery by the alkaline persulfate digestion method. Typically, differences between means of Kjeldahl nitrogen and nitrate-corrected alkaline persulfate nitrogen in low-nitrate concentration (< 0.1 milligram nitrate nitrogen per liter) subsets of filtered surface- and ground-water samples were statistically equivalent to zero at the p =level.Paired analytical results for dissolved and total phosphorus in Kjeldahl and alkaline persulfate digests were directly comparable because both digestion methods convert all forms of phosphorus in water samples to orthophosphate. On the basis of two-population paired t-test statistics, the means of all Kjeldahl phosphorus and alkaline persulfate phosphorus concentrations (2,093 paired results) were not significantly different from zero at the p = 0.05 level. For some subsets of these data, which were grouped according to water type and flow conditions at the time of sample collection, differences between means of Kjeldahl phosphorus and alkaline persulfate phosphorus concentrations were not equivalent to zero at the p = 0.05 level. Differences between means of these subsets, however, were less than the method detection limit for phosphorus (0.007 milligram phosphorus per liter) by the alkaline persulfate digestion method, and were therefore analytically insignificant.This report provides details of the alkaline persulfate digestion procedure, interference studies, recovery of various nitrogen- and phosphorus-containing compounds, and other analytical figures of merit. The automated air-segmented continuous flow methods developed to determine nitrate and orthophosphate in the alkaline persulfate digests also are described. About 125 microliters of digested sample are required to determine nitrogen and phosphorus in parallel at a rate of about 100 samples per hour with less than 1-percent sample in

Water-Resources Investigations Report↗
USGS2013

Great Lakes rivermouths: a primer for managers

Between the North American Great Lakes and their tributaries are the places where the confluence of river and lake waters creates a distinct ecosystem: the rivermouth ecosystem. Human development has often centered around these rivermouths, in part, because they provide a rich array of ecosystem services. Not surprisingly, centuries of intense human activity have led to substantial pressures on, and alterations to, these ecosystems, often diminishing or degrading their ecological functions and associated ecological services. Many Great Lakes rivermouths are the focus of intense restoration efforts. For example, 36 of the active Great Lakes Areas of Concern (AOCs) are rivermouths or areas that include one or more rivermouths. Historically, research of rivermouth ecosystems has been piecemeal, focused on the Great Lakes proper or on the upper reaches of tributaries, with little direct study of the rivermouth itself. Researchers have been divided among disciplines, agencies and institutions; and they often work independently and use disparate venues to communicate their work. Management has also been fragmented with a focus on smaller, localized, sub-habitat units and socio-political or economic elements, rather than system-level consideration. This Primer presents the case for a more holistic approach to rivermouth science and management that can enable restoration of ecosystem services with multiple benefits to humans and the Great Lakes ecosystem. A conceptual model is presented with supporting text that describes the structures and processes common to all rivermouths, substantiating the case for treating these ecosystems as an identifiable class. 1 Ecological services provided by rivermouths and changes in how humans value those services over time are illustrated through case studies of two Great Lakes rivermouths—the St. Louis River and the Maumee River. Specific ecosystem services are identified in italics throughout this Primer and follow definitions described by the Millennium Ecosystem Assessment (Table1). Collectively, this primer synthesizes existing information in a new way that aims to support management of rivermouths as distinct and important ecosystems. The development and management decisions made around rivermouths today will shape the future of these ecosystems, and the human communities within them, well into the future. 1 The information presented in this paper was derived from discussions and draft documents of the Great Lakes Rivermouth Collaboratory. The Great Lakes Rivermouth Collaboratory was established by the U.S. Geological Survey's Great Lakes Science Center (USGS-GLSC) in collaboration with the Great Lakes Commission to engage the Great Lakes scientific community in sharing and documenting knowledge about freshwater rivermouth ecosystems. For more information, see http://www.glc.org/habitat/Rivermouth-Collaboratory.html.

Great Lakes↗
USGS2009

EAARL Coastal Topography-Assateague Island National Seashore, 2008: First Surface

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Assateague Island National Seashore in Maryland and Virginia, acquired March 24-25, 2008. 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 multi-spectral 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 pre-survey 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↗
USGS2009

EAARL Coastal Topography-Assateague Island National Seashore, 2008: Bare Earth

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Assateague Island National Seashore in Maryland and Virginia, acquired March 24-25, 2008. 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 multi-spectral 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 pre-survey 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↗