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At least 181 records · Page 10Linked to original sources
USGS2001

Geologic map of the Riverside West 7.5' quadrangle, Riverside County, California

Open-File Report 01-451 contains a digital geologic map database of the Riverside West 7.5’ quadrangle, Riverside County, California that includes: ARC/INFO (Environmental Systems Research Institute, http://www.esri.com) version 7.2.1 coverages of the various elements of the geologic map. A PostScript file to plot the geologic map on a topographic base, containing a Correlation of Map Units diagram (CMU), a Description of Map Units (DMU), and an index map. Portable Document Format (.pdf) files of: a. This Readme; includes in Appendix I, data contained in rsw_met.txt b. The same graphic as plotted in 2 above. Test plots have not produced 1:24,000-scale map sheets. Adobe Acrobat page size setting influences map scale. The Correlation of Map Units and Description of Map Units is in the editorial format of USGS Geologic Investigations Series (I-series) maps but has not been edited to comply with I-map standards. Within the geologic map data package, map units are identified by standard geologic map criteria such as formation-name, age, and lithology. Where known, grain size is indicated on the map by a subscripted letter or letters following the unit symbols as follows: lg, large boulders; b, boulder; g, gravel; a, arenaceous; s, silt; c, clay; e.g. Qyfa is a predominantly young alluvial fan deposit that is arenaceous. Multiple letters are used for more specific identification or for mixed units, e.g., Qfysa is a silty sand. In some cases, mixed units are indicated by a compound symbol; e.g., Qyf2sc. Marine deposits are in part overlain by local, mostly alluvial fan, deposits and are labeled Qomf. Grain size follows f.Even though this is an Open-File Report and includes the standard USGS Open-File disclaimer, the report closely adheres to the stratigraphic nomenclature of the U.S. Geological Survey. Descriptions of units can be obtained by viewing or plotting the .pdf file (3b above) or plotting the postscript file (2 above).

California↗
USGS2001

Geologic map of the Riverside East 7.5' quadrangle, Riverside County, California

Open-File Report 01-452 contains a digital geologic map database of the Riverside East 7.5’ quadrangle, Riverside County, California that includes: ARC/INFO Environmental Systems Research Institute (http://www.esri.com) version 7.2.1 coverages of the various elements of the geologic map. A Postscript file to plot the geologic map on a topographic base, containing a Correlation of Map Units diagram (CMU), a Description of Map Units (DMU), and an index map. Portable Document Format (.pdf) files of: a. This Readme; includes in Appendix I, data contained in rse_met.txt b. The same graphic as plotted in 2 above. Test plots have not produced 1:24,000-scale map sheets. Adobe Acrobat page size setting influences map scale. The Correlation of Map Units and Description of Map Units is in the editorial format of USGS Geologic Investigations Series (I-series) maps but has not been edited to comply with I-map standards. Within the geologic map data package, map units are identified by standard geologic map criteria such as formation-name, age, and lithology. Where known, grain size is indicated on the map by a subscripted letter or letters following the unit symbols as follows: lg, large boulders; b, boulder; g, gravel; a, arenaceous; s, silt; c, clay; e.g. Qyfa is a predominantly young alluvial fan deposit that is arenaceous. Multiple letters are used for more specific identification or for mixed units, e.g., Qfysa is a silty sand. In some cases, mixed units are indicated by a compound symbol; e.g., Qyf2sc. Marine deposits are in part overlain by local, mostly alluvial fan, deposits and are labeled Qomf. Grain size follows f. Even though this is an Open-File Report and includes the standard USGS Open-File disclaimer, the report closely adheres to the stratigraphic nomenclature of the U.S. Geological Survey. Descriptions of units can be obtained by viewing or plotting the .pdf file (3b above) or plotting the postscript file (2 above).

California↗
USGS2014

EAARL-B coastal topography: Fire Island, New York, pre-Hurricane Sandy, 2012: seamless (bare earth and submerged)

These remotely sensed, geographically referenced elevation measurements of lidar-derived seamless (bare-earth and submerged) 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 part of Fire Island, New York, acquired pre-Hurricane Sandy on October 27, 2012. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar, 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 near-shore 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 originally in a NASA-USGS collaboration. The exploration and processing of lidar data in an interactive or batch mode is supported using ALPS. 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. The Airborne Lidar Processing System (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 York↗
USGS2001

Geologic map of the Steele Peak 7.5' quadrangle, Riverside County, California

Open-File Report 01-449 contains a digital geologic map database of the Steele Peak 7.5’ quadrangle, Riverside County, California that includes: ARC/INFO (Environmental Systems Research Institute, http://www.esri.com) version 7.2.1 coverages of the various elements of the geologic map. A Postscript file to plot the geologic map on a topographic base, and containing a Correlation of Map Units diagram (CMU), a Description of Map Units (DMU), and an index map. Portable Document Format (.pdf) files of: a. This Readme; includes in Appendix I, data contained in stp_met.txt b. The same graphic as plotted in 2 above. Test plots have not produced 1:24,000-scale map sheets. Adobe Acrobat page size setting influences map scale. The Correlation of Map Units and Description of Map Units is in the editorial format of USGS Geologic Investigations Series (I-series) maps but has not been edited to comply with I-map standards. Within the geologic map data package, map units are identified by standard geologic map criteria such as formation-name, age, and lithology. Where known, grain size is indicated on the map by a subscripted letter or letters following the unit symbols as follows: lg, large boulders; b, boulder; g, gravel; a, arenaceous; s, silt; c, clay; e.g. Qyfa is a predominantly young alluvial fan deposit that is arenaceous. Multiple letters are used for more specific identification or for mixed units, e.g., Qfysa is a silty sand. In some cases, mixed units are indicated by a compound symbol; e.g., Qyf2sc. Marine deposits are in part overlain by local, mostly alluvial fan, deposits and are labeled Qomf. Grain size follows f. Even though this is an Open-File Report and includes the standard USGS Open-File disclaimer, the report closely adheres to the stratigraphic nomenclature of the U.S. Geological Survey. Descriptions of units can be obtained by viewing or plotting the .pdf file (3b above) or plotting the postscript file (2 above).

California↗
USGS2001

Geologic map of the Sunnymead 7.5' quadrangle, Riverside County, California

Open-File Report 01-450 contains a digital geologic map database of the Sunnymead 7.5’ quadrangle, Riverside County, California that includes: ARC/INFO (Environmental Systems Research Institute, http:/www.esri.com) version 7.2.1 coverages of the various elements of the geologic map. A Postscript file to plot the geologic map on a topographic base, containing a Correlation of Map Units diagram (CMU), a Description of Map Units (DMU), and an index map. Portable Document Format (.pdf) files of: a. This Readme; includes in Appendix I, data contained in sun_met.txt b. The same graphic as plotted in 2 above. Test plots have not produced 1:24,000-scale map sheets. Adobe Acrobat page size setting influences map scale. The Correlation of Map Units and Description of Map Units is in the editorial format of USGS Geologic Investigations Series (I-series) maps but has not been edited to comply with I-map standards. Within the geologic map data package, map units are identified by standard geologic map criteria such as formation-name, age, and lithology. Where known, grain size is indicated on the map by a subscripted letter or letters following the unit symbols as follows: lg, large boulders; b, boulder; g, gravel; a, arenaceous; s, silt; c, clay; e.g. Qyfa is a predominantly young alluvial fan deposit that is arenaceous. Multiple letters are used for more specific identification or for mixed units, e.g., Qfysa is a silty sand. In some cases, mixed units are indicated by a compound symbol; e.g., Qyf2sc. Marine deposits are in part overlain by local, mostly alluvial fan, deposits and are labeled Qomf. Grain size follows f. Even though this is an Open-File Report and includes the standard USGS Open-File disclaimer, the report closely adheres to the stratigraphic nomenclature of the U.S. Geological Survey. Descriptions of units can be obtained by viewing or plotting the .pdf file (3b above) or plotting the postscript file (2 above).

California↗
USGS2002

Geologic map of the Corona North 7.5' quadrangle, Riverside and San Bernardino Counties, California

Open-File Report 02-22 contains a digital geologic map database of the Corona North 7.5’ quadrangle, Riverside and San Bernardino Counties, California that includes: ARC/INFO (Environmental Systems Research Institute, http://www.esri.com) version 7.2.1 coverages of the various elements of the geologic map. A Postscript file to plot the geologic map on a topographic base, and containing a Correlation of Map Units diagram (CMU), a Description of Map Units (DMU), and an index map. Portable Document Format (.pdf) files of: a. This Readme; includes in Appendix I, data contained in crn_met.txt b. The same graphic as plotted in 2 above. Test plots have not produced precise 1:24,000- scale map sheets. Adobe Acrobat page size setting influences map scale. The Correlation of Map Units and Description of Map Units is in the editorial format of USGS Geologic Investigations Series (I-series) maps but has not been edited to comply with I-map standards. Within the geologic map data package, map units are identified by standard geologic map criteria such as formation name, age, and lithology. Where known, grain size is indicated on the map by a subscripted letter or letters following the unit symbols as follows: lg, large boulders; b, boulder; g, gravel; a, arenaceous; s, silt; c, clay; e.g. Qyfa is a predominantly young alluvial fan deposit that is arenaceous. Multiple letters are used for more specific identification or for mixed units, e.g., Qfysa is a silty sand. In some cases, mixed units are indicated by a compound symbol; e.g., Qyf2sc. Marine deposits are in part overlain by local, mostly alluvial fan, deposits and are labeled Qomf. Grain size follows f. Even though this is an Open-File Report and includes the standard USGS Open-File disclaimer, the report closely adheres to the stratigraphic nomenclature of the U.S. Geological Survey. Descriptions of units can be obtained by viewing or plotting the .pdf file (3b above) or plotting the postscript file (2 above).

California↗
USGS2002

Geologic map of the Corona South 7.5' quadrangle, Riverside and Orange counties, California

Open-File Report 01-021 contains a digital geologic map database of the Corona South 7.5’ quadrangle, Riverside County, California that includes: 1. ARC/INFO (Environmental Systems Research Institute, http://www.esri.com) version 7.2.1 coverages of the various elements of the geologic map. 2. A Postscript file to plot the geologic map on a topographic base, and containing a Correlation of Map Units diagram (CMU), a Description of Map Units (DMU), and an index map. 3. Portable Document Format (.pdf) files of: a. A Readme file; includes in Appendix I, data contained in crs_met.txt b. The same graphic as plotted in 2 above. Test plots have not produced 1:24,000-scale map sheets. Adobe Acrobat page size setting influences map scale. The Correlation of Map Units and Description of Map Units is in the editorial format of USGS Geologic Investigations Series (I-series) maps but has not been edited to comply with I-map standards. Within the geologic map data package, map units are identified by standard geologic map criteria such as formation-name, age, and lithology. Where known, grain size is indicated on the map by a subscripted letter or letters following the unit symbols as follows: lg, large boulders; b, boulder; g, gravel; a, arenaceous; s, silt; c, clay; e.g. Qyfa is a predominantly young alluvial fan deposit that is arenaceous. Multiple letters are used for more specific identification or for mixed units, e.g., Qfysa is a silty sand. In some cases, mixed units are indicated by a compound symbol; e.g., Qyf2sc. Marine deposits are in part overlain by local, mostly alluvial fan, deposits and are labeled Qomf. Grain size follows f. Even though this is an Open-File Report and includes the standard USGS Open-File disclaimer, the report closely adheres to the stratigraphic nomenclature of the U.S. Geological Survey. Descriptions of units can be obtained by viewing or plotting the .pdf file (3b above) or plotting the postscript file (2 above).

California↗
USGS2005

Biogeochemical controls on diel cycling of stable isotopes of dissolved 02 and dissolved inorganic carbon in the Big Hole River, Montana

Rivers with high biological productivity typically show substantial increases in pH and dissolved oxygen (DO) concentration during the day and decreases at night, in response to changes in the relative rates of aquatic photosynthesis and respiration. These changes, coupled with temperature variations, may impart diel (24-h) fluctuations in the concentration of trace metals, nutrients, and other chemical species. A better understanding of diel processes in rivers is needed and will lead to improved methods of data collection for both monitoring and research purposes. Previous studies have used stable isotopes of dissolved oxygen (DO) and dissolved inorganic carbon (DIC) as tracers of geochemical and biological processes in streams, lakes, and marine systems. Although seasonal variation in δ 18 O of DO in rivers and lakes has been documented, no study has investigated diel changes in this parameter. Here, we demonstrate large (up to 13‰) cycles in δ 18 O-DO for two late summer sampling periods in the Big Hole River of southwest Montana and illustrate that these changes are correlated to variations in the DO concentration, the C-isotopic composition of DIC, and the primary productivity of the system. The magnitude of the diel cycle in δ 18 O-DO was greater in August versus September because of the longer photoperiod and warmer water temperatures. This study provides another biogeochemical tool for investigating the O 2 and C budgets in rivers and may also be applicable to lake and groundwater systems.

Montana↗
USGS2014

EAARL-B submerged topography: Barnegat Bay, New Jersey, pre-Hurricane Sandy, 2012

These remotely sensed, geographically referenced elevation measurements of lidar-derived submerged 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 part of Barnegat Bay, New Jersey, acquired pre-Hurricane Sandy on October 18, 22, 23, and 26, 2012. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar, 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 near-shore 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 originally in a NASA-USGS collaboration. The exploration and processing of lidar data in an interactive or batch mode is supported using ALPS. 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. The Airborne Lidar Processing System (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↗
USGS2008

Correlation of the Deccan and Rajahmundry Trap lavas: Are these the longest and largest lava flows on Earth?

We propose that the Rajahmundry Trap lavas, found near the east coast of peninsular India , are remnants of the longest lava flows yet recognized on Earth (∼ 1000 km long). These outlying Deccan-like lavas are shown to belong to the main Deccan Traps. Several previous studies have already suggested this correlation, but have not demonstrated it categorically. The exposed Rajahmundry lavas are interpreted to be the distal parts of two very-large-volume pāhoehoe flow fields, one each from the Ambenali and Mahabaleshwar Formations of the Wai Sub-group in the Deccan Basalt Group. Eruptive conditions required to emplace such long flows are met by plausible values for cooling and eruption rates, and this is shown by applying a model for the formation of inflated pāhoehoe sheet flow lobes. The model predicts flow lobe thicknesses similar to those observed in the Rajahmundry lavas. For the last 400 km of flow, the lava flows were confined to the pre-existing Krishna valley drainage system that existed in the basement beyond the edge of the gradually expanding Deccan lava field, allowing the flows to extend across the subcontinent to the eastern margin where they were emplaced into a littoral and/or shallow marine environment. These lavas and other individual flow fields in the Wai Sub-group may exceed eruptive volumes of 5000 km 3 , which would place them amongst the largest magnitude effusive eruptive units yet known. We suggest that the length of flood basalt lava flows on Earth is restricted mainly by the size of land masses and topography. In the case of the Rajahmundry lavas, the flows reached estuaries and the sea, where their advance was perhaps effectively terminated by cooling and/or disruption. However, it is only during large igneous province basaltic volcanism that such huge volumes of lava are erupted in single events, and when the magma supply rate is sufficiently high and maintained to allow the formation of very long lava flows. The Rajahmundry lava fields were emplaced around 65 Ma during the later times of Deccan volcanism, probably just after the K/T environmental crisis. However, many lava-forming eruptions of similar magnitude and style straddled the K/T boundary.

Rajahmundry Trap↗
USGS2024

The use of conceptual ecological models to identify critical data and uncertainties to support numerical modeling: The northern Gulf of Mexico eastern oyster Crassostrea virginica example

Objective Increasing reliance on numerical simulation models to help inform management and restoration choices benefits from careful consideration of critical early steps in model development. Along the northern coast of the Gulf of Mexico, the eastern oyster Crassostrea virginica fulfills important ecological and economic roles. Using the eastern oyster as an example, we draw on several recent frameworks outlining best practices for model development and application for restoration, conservation, and management. Methods We identify priority model questions, outline a conceptual ecological model (CEM) to guide numerical model development, and use this framework to identify uncertainties and research needs. Result The CEM uses a nested design, identifying explicit vital rates, processes, attributes, and outcomes for the species (oysters), population, and metapopulation (i.e., network of populations) levels in response to drivers of species, population, and metapopulation changes and changing environmental factors. Most management actions related to oyster restoration and harvest affect population attributes directly, but many coastal management actions and changes (i.e., climate change and coastal and water resource engineering) impact environmental factors that alter vital rates and attributes of oysters, populations, and metapopulations. Conclusion Investment in studies targeting individual oyster‐ and population‐level multi‐stressor responses (filtration, respiration, growth, and reproduction) and improving hydrodynamic and environmental models targeting drivers that influence metapopulation vital rates and attributes (i.e., connectivity and substrate persistence) would contribute to reducing uncertainties. Development of numerical models covering the entire oyster life cycle and connectivity of populations using hydrodynamic models of current and predicted conditions to provide key abiotic and biotic factors influencing larval movement, recruitment, and on‐reef oyster vital rates would assist in balancing the goals of conservation, restoration, and fisheries management of this foundational estuarine species.

Marine and Coastal Fisheries: Dynamics, Management↗
USGS2005

The seasonal cycle of diabatic heat storage in the Pacific Ocean

This study quantifies uncertainties in closing the seasonal cycle of diabatic heat storage (DHS) over the Pacific Ocean from 20??S to 60??N through the synthesis of World Ocean Circulation Experiment (WOCE) reanalysis products from 1993 to 1999. These products are DHS from Scripps Institution of Oceanography (SIO); near-surface geostrophic and Ekman currents from Earth and Space Research (ESR); and air-sea heat fluxes from Comprehensive Ocean-Atmosphere Data Set (COADS), National Centers for Environmental Prediction (NCEP), and European Center for Mid-Range Weather Forecasts (ECMWF). With these products, we compute residual heat budget components by differencing long-term monthly means from the long-term annual mean. This allows the seasonal cycle of the DHS tendency to be modeled. Everywhere latent heat flux residuals dominate sensible heat flux residuals, shortwave heat flux residuals dominate longwave heat flux residuals, and residual Ekman heat advection dominates residual geostrophic heat advection, with residual dissipation significant only in the Kuroshio-Oyashio current extension. The root-mean-square (RMS) of the differences between observed and model residual DHS tendencies (averaged over 10??latitude-by-20??longitude boxes) is <20 W m-2 in the interior ocean and <100 W m-2 in the Kuroshio-Oyashio current extension. This reveals that the residual DHS tendency is driven everywhere by some mix of residual latent heat flux, shortwave heat flux, and Ekman heat advection. Suppressing bias errors in residual air-sea turbulent heat fluxes and Ekman heat advection through minimization of the RMS differences reduces the latter to <10 W m-2 over the interior ocean and <25 W m -2 in the Kuroshio-Oyashio current extension. This reveals air-sea temperature and specific humidity differences from in situ surface marine weather observations to be a principal source of bias error, overestimated over most of ocean but underestimated near the Intertropical Convergence Zone. ?? 2005 Elsevier Ltd. All rights reserved.

Progress in Oceanography↗
USGS2021

Marine distribution and foraging habitat highlight potential threats at sea for Endangered Bermuda Petrel Pterodroma cahow

Marine spatial planning relies on detailed spatial information of marine areas to ensure effective conservation of species. To enhance our understanding of marine habitat use by the highly pelagic Bermuda petrel Pterodroma cahow , we deployed GPS tags on 6 chick-rearing adults in April 2019 and constructed a habitat suitability model using locations classified as foraging to explore functional responses to a selection of marine environmental variables. We defined 15 trips for 5 individuals, ranging from 1-6 trips per bird, that included both short and long foraging excursions indicative of a dual foraging strategy that optimizes chick feeding and self maintenance. The maximum distance birds flew from Bermuda during foraging trips ranged from 61 to 2513 km (total trip lengths: 186-14051 km). Behaviourally deduced foraging habitat was best predicted at shorter distances from the colony, under warmer sea surface temperature, greater sea surface height, and in deeper water compared to transiting locations; our model results indicated that suitable foraging habitat exists beyond the core home range of the population, as far north as the highly productive Gulf Stream frontal system, and within the territorial waters of both the USA and Canada. Our results are crucial to inform management decisions and international conservation efforts by better identifying potential threats encountered at sea by this globally rare seabird and highlighting jurisdictions potentially responsible for mitigating those threats.

Nonsuch Island, Horn Rock↗
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↗
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↗
USGS2010

EAARL Coastal Topography-Chandeleur Islands, Louisiana, 2010: Bare Earth

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and submerged 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 Chandeleur Islands, acquired March 3, 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 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↗
USGS2014

EAARL-B submerged topography: Barnegat Bay, New Jersey, post-Hurricane Sandy, 2012-2013

These remotely sensed, geographically referenced elevation measurements of lidar-derived submerged 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 part of Barnegat Bay, New Jersey, acquired post-Hurricane Sandy on November 1, 5, 16, 20, and 30, 2012; December 5, 6, and 21, 2012; and January 10, 2013. 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 originally in a NASA-USGS collaboration. The exploration and processing of lidar data in an interactive or batch mode is supported using ALPS. 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. The Airborne Lidar Processing System (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↗