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

EAARL Coastal Topography-Eastern Louisiana Barrier Islands, Post-Hurricane Gustav, 2008: First Surface

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the eastern Louisiana barrier islands, acquired post-Hurricane Gustav (September 2008 hurricane) on September 6 and 7, 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 multispectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗
USGS2010

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

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

Data Series↗
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↗
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↗
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↗
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↗
USGS2013

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

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

Louisiana↗
USGS2020

Aeolian remobilisation of volcanic ash: Outcomes of a workshop in the Argentinian Patagonia

During explosive volcanic eruptions, large quantities of tephra can be dispersed and deposited over wide areas. Following deposition, subsequent aeolian remobilisation of ash can potentially exacerbate primary impacts on timescales of months to millennia. Recent ash remobilisation events (e.g., following eruptions of Cordón Caulle 2011; Chile, and Eyjafjallajökull 2010, Iceland) have highlighted this to be a recurring phenomenon with consequences for human health, economic sectors, and critical infrastructure. Consequently, scientists from observatories and Volcanic Ash Advisory Centers (VAACs), as well as researchers from fields including volcanology, aeolian processes and soil sciences, convened at the San Carlos de Bariloche headquarters of the Argentinian National Institute of Agricultural Technology to discuss the “state of the art” for field studies of remobilised deposits as well as monitoring, modeling and understanding ash remobilisation. In this article, we identify practices for field characterisation of deposits and active processes, including mapping, particle characterisation and sediment traps. Furthermore, since forecast models currently rely on poorly-constrained dust emission schemes, we call for laboratory and field measurements to better parameterise the flux of volcanic ash as a function of friction velocity. While source area location and extent are currently the primary inputs for dispersion models, once emission schemes become more sophisticated and better constrained, other parameters will also become important (e.g., source material volume and properties, effective precipitation, type and distribution of vegetation cover, friction velocity). Thus, aeolian ash remobilisation hazard and associated impact assessment require systematic monitoring, including the development of a regularly-updated spatial database of resuspension source areas.

Frontiers in Earth Science↗
USGS2008

EAARL coastal topography - Northern Gulf of Mexico

These remotely sensed, geographically referenced elevation measurements of Lidar-derived coastal topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. One objective of this research is to create techniques to survey areas for the purposes of geomorphic change studies following major storm events. The USGS Coastal and Marine Geology Program's National Assessment of Coastal Change Hazards project is a multi-year undertaking to identify and quantify the vulnerability of U.S. shorelines to coastal change hazards such as effects of severe storms, sea-level rise, and shoreline erosion and retreat. Airborne Lidar surveys conducted during periods of calm weather are compared to surveys collected following extreme storms in order to quantify the resulting coastal change. Other applications of high-resolution topography include habitat mapping, ecological monitoring, volumetric change detection, and event assessment. The purpose of this project is to provide highly detailed and accurate datasets of the northern Gulf of Mexico coastal areas, acquired on September 19, 2004, immediately following Hurricane Ivan. 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 Airborne Advanced 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 RGB (red-green-blue) 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 on September 19, 2004. The survey resulted in the acquisition of 3.2 gigabytes of data. The data were 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 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, Florida, Mississippi↗
USGS2014

Trouble in the aquatic world: How wildlife professionals are battling amphibian declines

A parasitic fungus, similar to the one that caused the extinction of numerous tropical frog and toad species, is killing salamanders in Europe. Scientists first identified the fungus, Batrachochytrium salamandrivorans, in 2013 as the culprit behind the death of fire salamanders ( Salamandr a salamandra ) in the Netherlands ( Martel et al. 2013 ) and are now exploring its potential impact to other species. Although the fungus, which kills the amphibians by infecting their skin, has not yet spread to the United States, researchers believe it’s only a matter of time before it does and, when that happens, the impact on salamander populations could be devastating ( Martel et al. 2014 ). Reports of worldwide declines of amphibians began a quarter of a century ago ( Blaustein & Wake 1990 ). Globally, some amphibian population declines occurred in the late 1950s and early 1960s, and declining trends continued in North America ( Houlahan et al. 2000 ). In the earlier years, population declines were attributed primarily to overharvest due to unregulated supply of species such as the northern leopard frog ( Lithobate s pipiens ) for educational use ( Dodd 2013 ). In later years, however, causes of declines were less evident. In 1989, herpetologists at the First World Congress of Herpetology traded alarming stories of losses across continents and in seemingly protected landscapes, making it clear that amphibian population declines were a “global phenomenon.” In response to these reports, in 1991, the International Union for Conservation of Nature (IUCN) established the Declining Amphibian Populations Task Force to better understand the scale and scope of global amphibian declines. Unfortunately, the absence of long-term monitoring data and targeted studies made it difficult for the task force to compile information. Today, according to AmphibiaWeb.org, there are 7,342 amphibian species in the world — double the number since the first alerts of declines — making the situation appear deceptively less dire. In fact, our understanding of genetic diversity significantly raises the stakes, and we are at risk of losing far more species than we believed only a few years ago. According to the IUCN, amphibians now lead the list of vertebrate taxa affected by the larger “biodiversity crisis” and sixth major mass- extinction event on Earth ( Keith et al. 2014 , Wake and Vredenburg 2008 ).

The Wildlife Professional↗
USGS2019

Advancing barrier island habitat mapping using landscape position information

Barrier islands are dynamic ecosystems that change gradually from coastal processes, including currents and tides, and rapidly from episodic events, such as storms. These islands provide many important ecosystem services, including storm protection and erosion control to the mainland, habitat for fish and wildlife, and tourism. Habitat maps, developed by scientists, provide a critical tool for monitoring changes to these dynamic ecosystems. Barrier island monitoring often requires custom habitat maps due to several factors, including island size and the classification of unique geomorphology-based habitats, such as beach, dune, and barrier flats. In this study, we reviewed barrier-island-specific habitat mapping efforts and highlighted common habitat class types, source data, and mapping approaches. We also developed a framework for mapping geomorphology-based barrier island habitats using a rule-based, geographic object-based image analysis approach, which included the use of field data, tide data, high-resolution orthophotography, and lidar data. This framework integrates several barrier island mapping advancements with regard to the use of landscape position information for automated dune extraction and the use of Monte Carlo analyses for the treatment of elevation uncertainty for elevation-dependent habitats. Specifically, we used the uncertainty analyses to refine automated dune delineation based on elevation relative to extreme storm water levels and to increase the accuracy of intertidal and supratidal/upland habitat delineation. We found that dune extraction results were enhanced when elevation relative to storm water levels and visual interpretation were also applied. This framework could also be applied to beach–dune systems found along a mainland.

Alabama↗
USGS2025

Late Quaternary environmental change in eastern Beringia

Eastern Beringia (Alaska and western Yukon) is an extensive, high-latitude region of North America that remained largely unglaciated throughout the Quaternary. Consequently, its sedimentary deposits preserve long-term environmental records that have intrigued scientists for nearly a century. Recent advances in palaeoecological proxies and dating methods have proved critical in addressing long-standing questions about regional late Quaternary environmental change. At the same time, they have led to new and sometimes controversial hypotheses. This review covers recent discoveries and unresolved questions focused on the period 57,000–10,000 calendar years before C.E. 1950 (cal yr BP). The middle Wisconsin interstadial (57,000–30,000 cal yr BP) was a period of relative warmth in eastern Beringia, compared with the late Wisconsin (30,000–14,000 cal yr BP). Early in the interstadial occasional Picea woodland was present amongst widespread shrub tundra. Palaeoecological, sedimentary and isotopic data indicate that climate was cooler and drier than the Holocene, with high rates of aeolian activity. Megafauna typically associated with the ‘mammoth steppe’ ecosystem (woolly mammoth [ Mammuthus primigenius ], horse [ Equus ] and steppe-bison [ Bison priscus ]) were present in some abundance. The transition towards late Wisconsin cold-stage conditions (35,000–30,000 cal yr BP) coincided with the establishment of the Bering Land Bridge and featured expansion of spatially varied, herbaceous vegetation, sometimes associated with deep active layers. Sedimentary DNA ( seda DNA) and macrofossil evidence show vegetation was not a prairie-like grassland, and the term “steppe-tundra” is a better descriptor. Permafrost pore-ice isotopic (δ 18 O) records suggest a step change in one or more climate drivers ca. 30,000 cal yr BP, by which time steppe-tundra was established across eastern Beringia. It remains uncertain whether Picea survived cold-stage conditions within isolated refugia, or whether it recolonized from south of the Laurentide-Cordilleran ice sheets. Genetic data suggest that Picea probably survived in situ ; however, there is no definitive fossil evidence to support this. The end-Pleistocene transition from steppe-tundra to shrub tundra began ca. 15,000 cal yr BP and took place within decades at local scales. The expansion of woody taxa coincided with rising sea levels, reduced sea-ice extent and an abrupt shift in atmospheric circulation that enhanced precipitation. During this time, Earth's orbital configuration caused high early-summer temperatures and strong seasonality, creating growing conditions very different from today. The vegetation consisted of Salix and Betula shrub tundra with open areas of herbs and graminoids. During the deglacial warming trend, the Younger Dryas oscillation (12,800–11,700 cal yr BP) was variably expressed. It is generally evident in records affected by adjacent oceans but can be absent at sites in continental areas. These past conditions and paleoenvironmental changes have implications for contemporary issues: hypotheses about Pleistocene mammalian extinction; sensitivity of eastern Beringia to major oceanic reorganizations and high-frequency climate variability; the nature of woody plant expansion with climate warming; grazing, hydroclimate and fire as controls over ecosystems; the efficacy of “Pleistocene rewilding” for carbon capture.

Beringia↗
USGS1995

U.S. Geological Survey Subsidence Interest Group conference, Edwards Air Force Base, Antelope Valley, California, November 18-19, 1992; Abstracts and summary

Land subsidence, the loss of surface elevation as a result of the removal of subsurface support, affects every state in the United States. More than 17,000 mi 2 of land in the United States has been lowered by the various processes that produce land subsidence with annual costs from resulting flooding and structural damage that exceed $125 million. It is estimated that an additional $400 million is spent nationwide in attempts to control subsidence. Common causes of land subsidence include the removal of oil, gas, and water from underground reservoirs; dissolution of limestone aquifers (sinkholes); underground mining activities; drainage of organic soils; and hydrocompaction (the initial wetting of dry soils). Overdrafting of aquifers is the major cause of areally extensive land subsidence, and as ground-water pumping increases, land subsidence also will increase. Land subsidence and its effects on engineering structures have been recognized for centuries, but it was not until this century that the processes that produce land subsidence were identified and understood. In 1928, while working with field data from a test of the Dakota Sandstone aquifer, O.E. Meinzer of the U.S. Geological Survey recognized the compressibility of aquifers. Around the same time, Karl Terzaghi, a soil scientist working at Harvard University, developed the one-dimensional consolidation theory that provided a quantitative means of predicting soil compaction resulting from the drainage of compressible soils. Thus, with the recognition of the compressibility of aquifers (Meinzer), and the development of a quantitative means of predicting soil compaction as a consequence of the reduction of intergranular pore pressure (Terzaghi), the theory of aquifer-system compaction was formed. With the widespread availability of electric power in rural areas, and the advent of the deep turbine pump, ground-water withdrawals increased dramatically throughout the country in the 1940's and 1950's. Along with this unprecedented increase in pumpage, substantial amounts of land subsidence were observed in several areas of the United States, most notably in Arizona, California, and Texas. Beginning in 1955, under the direction of Joseph Poland, the Geological Survey began the "Mechanics of Aquifers Project," which focused largely on the processes that resulted in land subsidence due to the withdrawal of ground water. This research team gained international renown as they advanced the scientific understanding of aquifer mechanics and land-subsidence theory. The results of field studies by members of this research group not only verified the validity of the application of Terzaghi's consolidation theory to compressible aquifers, but they also provided definitions, methods of quantification, and confirmation of the interrelation among hydraulic head declines, aquifer-system compaction, and land subsidence. In addition to conducting pioneering research, this group also formed a "center of expertise," providing a focal point within the Geological Survey for the dissemination of technology and scientific understanding in aquifer mechanics. However, when the "Mechanics of Aquifers Project" was phased out in 1984, the focal point for technology transfer no longer existed. Interest among various state and local agencies in land subsidence has persisted, and the Geological Survey has continued to participate in a broad spectrum of cooperative and Federally funded projects in aquifer mechanics and land subsidence. These projects are designed to identify and monitor areas with the potential for land subsidence, to conduct basic research in the processes that control land subsidence and the development of earth fissures, as well as to develop new quantitative tools to predict aquifer-system deformation. In 1989 an ad hoc "Aquifer Mechanics and Subsidence Interest Group" (referred to herein as the "Subsidence Interest Group") was formed

California↗
USGS1998

Geospatial Technology Applications and Infrastructure in the Biological Resources Division

Executive Summary -- Automated spatial processing technology such as geographic information systems (GIS), telemetry, and satellite-based remote sensing are some of the more recent developments in the long history of geographic inquiry. For millennia, humankind has endeavored to map the Earth's surface and identify spatial relationships. But the precision with which we can locate geographic features has increased exponentially with satellite positioning systems. Remote sensing, GIS, thematic mapping, telemetry, and satellite positioning systems such as the Global Positioning System (GPS) are tools that greatly enhance the quality and rapidity of analysis of biological resources. These technologies allow researchers, planners, and managers to more quickly and accurately determine appropriate strategies and actions. Researchers and managers can view information from new and varying perspectives using GIS and remote sensing, and GPS receivers allow the researcher or manager to identify the exact location of interest. These geospatial technologies support the mission of the U.S. Geological Survey (USGS) Biological Resources Division (BRD) and the Strategic Science Plan (BRD 1996) by providing a cost-effective and efficient method for collection, analysis, and display of information. The BRD mission is 'to work with others to provide the scientific understanding and technologies needed to support the sound management and conservation of our Nation's biological resources.' A major responsibility of the BRD is to develop and employ advanced technologies needed to synthesize, analyze, and disseminate biological and ecological information. As the Strategic Science Plan (BRD 1996) states, 'fulfilling this mission depends on effectively balancing the immediate need for information to guide management of biological resources with the need for technical assistance and long-range, strategic information to understand and predict emerging patterns and trends in ecological systems.' Information sharing plays a key role in nearly everything BRD does. The Strategic Science Plan discusses the need to (1) develop tools and standards for information transfer, (2) disseminate information, and (3) facilitate effective use of information. This effort centers around the National Biological Information Infrastructure (NBII) and the National Spatial Data Infrastructure (NSDI), components of the National Information Infrastructure. The NBII and NSDI are distributed electronic networks of biological and geographical data and information, as well as tools to help users around the world easily find and retrieve the biological and geographical data and information they need. The BRD is responsible for developing scientifically and statistically reliable methods and protocols to assess the status and trends of the Nation's biological resources. Scientists also conduct important inventory and monitoring studies to maintain baseline information on these same resources. Research on those species for which the Department of the Interior (DOI) has trust responsibilities (including endangered species and migratory species) involves laboratory and field studies of individual animals and the environments in which they live. Researchboth tactical and strategicis conducted at the BRD's 17 science centers and 81 field stations, 54 Cooperative Fish and Wildlife Research Units in 40 states, and at 11 former Cooperative Park Study Units. Studies encompass fish, birds, mammals, and plants, as well as their ecosystems and the surrounding landscape. Biological Resources Division researchers use a variety of scientific tools in their endeavors to understand the causes of biological and ecological trends. Research results are used by managers to predict environmental changes and to help them take appropriate measures to manage resources effectively. The BRD Geospatial Technology Program facilitates the collection, analysis, and dissemination of data and informat

Information and Technology Report↗
USGS2016

Assessing the socioeconomic impact and value of open geospatial information

The production and accessibility of geospatial information including Earth observation is changing greatly both technically and in terms of human participation. Advances in technology have changed the way that geospatial data are produced and accessed, resulting in more efficient processes and greater accessibility than ever before. Improved technology has also created opportunities for increased participation in the gathering and interpretation of data through crowdsourcing and citizen science efforts. Increased accessibility has resulted in greater participation in the use of data as prices for Government-produced data have fallen and barriers to access have been reduced. The increase in participation in the production and in the use of data, defined as data democracy for this workshop, are having great impacts on economics and more generally on society. There is also a strong drive by governments around the world, as shown by the G8 Declaration in June 2013, to make public sector information and scientific data more widely accessible. These are respectively termed “open data” and “open research data.” This report summarizes discussion at the Workshop on Assessing the Impact and Value of Open Geospatial Information held at George Washington University in Washington, D.C. in October 2014. Workshop participants examined the consequences of expanding data democracy with a focus on its socioeconomic impacts. Evaluations were presented of state-of-the-art methods to assess these socioeconomic impacts, which included position papers and remarks by discussants. The workshop included discussions about the following topics: (1) increased and expanded information sources; (2) societal impacts, including approaches to economics assessments; (3) constraints to open access, including the demands for return on investment, specifications of intellectual property rights, and privacy issues; and (4) learning from the experiences of other data-rich domains, such as environmental management, internet businesses, health, and transportation. The workshop was a working meeting with strong participant engagement, leading to recommendations for action. The meeting included five topic-driven sessions and keynote presentations. Precirculated position papers for each panel session facilitated preparation and remarks by discussants. After the position papers are updated following the discussants’ remarks, it is planned to submit them for publication. The workshop included 68 participants coming from international organizations, the U.S. public and private sectors, nongovernmental organizations, and academia. Participants included policy makers and analysts, financial analysts, economists, information scientists, geospatial practitioners, and other discipline experts.

Open-File Report↗
USGS2022

On the documentation, independence, and stability of widely used seismological data products

Earthquake scientists have traditionally relied on relatively small data sets recorded on small numbers of instruments. With advances in both instrumentation and computational resources, the big-data era, including an established norm of open data-sharing, allows seismologists to explore important issues using data volumes that would have been unimaginable in earlier decades. Alongside with these developments, the community has moved towards routine production of interpreted data products such as seismic moment tensor catalogs that have provided an additional boon to earthquake science. As these products have become increasingly familiar and useful, it is important to bear in mind that they are not data, but rather interpreted data products. As such, they differ from data in ways that can be important, but not always appreciated. Important - and sometimes surprising - issues can arise if methodology is not fully described, data from multiple sources are included, or data products are not versioned (time-stamped). The line between data and data products is sometimes blurred, leading to an underappreciation of issues that affect data products. This note illustrates examples from two widely used data products: moment tensor catalogs and Did You Feel It? (DYFI) macroseismic intensity values. These examples show that increasing a data product’s documentation, independence, and stability can make it even more useful. To ensure the reproducibility of studies using data products, time-stamped products should be preserved, for example as electronic supplements to published papers, or, ideally, a more permanent repository.

Frontiers in Earth Science↗