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Results for “Science of Surveying and Mapping”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 739 records · Page 41Linked to original sources
USGS2009

ATM Coastal Topography-Alabama 2001

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced collaboratively by 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. This project provides highly detailed and accurate datasets of the Alabama coastline, acquired October 3-4, 2001. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative scanning Lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning Lidar system that measures high-resolution topography of the land surface, and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM 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.

Alabama↗
USGS2009

ATM Coastal Topography-Florida 2001: Eastern Panhandle

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced collaboratively by 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. This project provides highly detailed and accurate datasets of the eastern Florida panhandle coastline, acquired October 2, 2001. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative scanning Lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning Lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM 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 routinely used to create maps that represent submerged or first surface topography.

Florida↗
USGS2024

Coastal Science Navigator companion guide—Discover the U.S. Geological Survey coastal science products you need

The Coastal Science Navigator is an online gateway to a wide variety of U.S. Geological Survey (USGS) coastal change hazards-related information, data, and tools relevant to stakeholders’ scientific and decision-making needs. The products within the Coastal Science Navigator provide data related to past, present, and future threats to our coastlines. The filter search allows users to see all available products and identify relevant options by time scale, geographic scope, coastal hazard theme, and other filters. The guided search suggests products based on users’ answers to a short series of questions. A comprehensive summary is available for each product. The idea for the Coastal Science Navigator arose in 2020 in response to stakeholder feedback identifying the need for a central source for USGS coastal science information. It was published in July 2023 and initially included 55 products. Regular updates are planned to integrate other existing and new products. This guide introduces some of the many coastal change hazards-related products available through the USGS. In it, we showcase the products included in the Coastal Science Navigator’s initial publication in July 2023. While it is not representative of all the information, tools, and data available, we hope it serves as a compelling snapshot of what the USGS has to offer and encourages you to explore the Coastal Science Navigator to discover more of the products you need. To navigate this guide, the products have been organized by the time scale they are best suited for—past, present, or future—although many products cover multiple time scales. An additional section features software, one of the many product types available as filters within the Coastal Science Navigator. Other products include downloadable data, websites, and geonarratives (web pages that combine text, images, and interactive maps into narratives you can scroll through). Featured geographic scopes are also highlighted within this guide, detailing some of the many regions in which the USGS conducts research and illustrating another way to filter products within the Coastal Science Navigator.

Circular↗
USGS2012

Three-dimensional sensitivity distribution and sample volume of low-induction-number electromagnetic-induction instruments

There is an ongoing effort to improve the understanding of the correlation of soil properties with apparent soil electrical conductivity as measured by low‐induction‐number electromagnetic‐induction (LIN FEM) instruments. At a minimum, the dimensions of LIN FEM instruments' sample volume, the spatial distribution of sensitivity within that volume, and implications for surveying and analyses must be clearly defined and discussed. Therefore, a series of numerical simulations was done in which a conductive perturbation was moved systematically through homogeneous soil to elucidate the three‐dimensional sample volume of LIN FEM instruments. For a small perturbation with electrical conductivity similar to that of the soil, instrument response is a measure of local sensitivity (LS). Our results indicate that LS depends strongly on the orientation of the instrument's transmitter and receiver coils and includes regions of both positive and negative LS. Integration of the absolute value of LS from highest to lowest was used to contour cumulative sensitivity (CS). The 90% CS contour was used to define the sample volume. For both horizontal and vertical coplanar coil orientations, the longest dimension of the sample volume was at the surface along the main instrument axis with a length of about four times the intercoil spacing (s) with maximum thicknesses of about 1 and 0.3 s, respectively. The imaged distribution of spatial sensitivity within the sample volume is highly complex and should be considered in conjunction with the expected scale of heterogeneity before the use and interpretation of LIN FEM for mapping and profiling.

Soil Science Society of America Journal↗
USGS2009

ATM coastal topography-Florida 2001: Western Panhandle

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced collaboratively by 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. This project provides highly detailed and accurate datasets of the western Florida panhandle coastline, acquired October 2-4 and 7-10, 2001. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative scanning Lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning Lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM 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 routinely used to create maps that represent submerged or first surface topography.

Florida↗
USGS2009

ATM Coastal Topography-Mississippi, 2001

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by 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. This project provides highly detailed and accurate datasets of the Mississippi coastline, from Lakeshore to Petit Bois Island, acquired September 9-10, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.

Mississippi↗
USGS2012

User’s guide and metada for the PICES Nonindigenous Species Information System

Introduction Welcome to the PICES Nonindigenous Species Information System, a Microsoft Access database that displays the biogeographic distributions, invasion status, vectors, and key life history attributes of the approximately 740 reported nonindigenous species (NIS) in the estuarine and near-coastal habitats of the North Pacific and Hawaii. This database was developed by the U.S. Environmental Protection Agency and the U.S. Geological Survey under the auspices of Working Group 21 (Invasive Species) of the North Pacific Marine Science Organization (PCIES). The PICES database contains the data used to generate the “Atlas of Nonindigenous Marine and Estuarine Species in the North Pacific” (Lee and Reusser, 2012; herein referred to as the “Atlas”). The User’s Guide provides instructions on how to use the PICES database as well as metadata for the database and the Atlas. We note that for most users, the Atlas provides a simpler approach to accessing key information on NIS in the PICES countries than the database, though the database does provide additional information on species and sources as well as allowing users to extract information on specific taxa and/or locations (see Section 4). The PICES database also includes species reported from the PICES Rapid Assessment Surveys (RAS). PICES sponsored four rapid assessment surveys with the objective of quickly characterizing the native, non-native, and cryptogenic species present in different locations. Surveys were sponsored in Dalian, China in 2008, Jeju, Korea in 2009, Newport, Oregon, USA in 2010, and Peter the Great Bay, near Vladivostok and Nakhodka, Russia in 2011 ( http://www.pices.int/publications/pices_press/volume19/v19_n1/pp_30-31_Kobe-WS_f.pdf , http://www.pices.int/publications/pices_press/volume20/v20_n1/pp_26-29_RAS-2011.pdf ). The PICES database contains the RAS species that were made available in time for inclusion. Thus, the database does not capture all the species found in these surveys. In addition, much of the information on the RAS species was provided by the experts conducting the survey, and their distributions, environmental requirements, and life history attributes were not evaluated to the same level of detail by the PICES authors as the North Pacific NIS. In lieu of the more extensive review as conduced with the Atlas species, the information on the RAS species needs to be considered preliminary. Additionally, it is important to use the “Map All Distributions” option (see Section 3.6.6) when mapping their distribution or conducting a query. The general reference for the RAS surveys in the PICES database is “PICES Working Group 21, YEAR SURVEY”. The overall goal of both the database and Atlas was to simplify and standardize the dissemination of distributional, habitat, and life history characteristics of near-coastal and estuarine nonindigenous species. This database provides a means of querying these data and displaying the information in a consistent format. The specific classes of information the database captures include: Regional and global ranges of native and nonindigenous near-coastal and estuarine species at different hierarchical spatial scales. Habitat and physiological requirements of near-coastal and estuarine species. Life history characteristics of near-coastal and estuarine species. Invasion history and vectors for nonindigenous species. This standardized and synthesized data in the database and the Atlas provide the basic information needed to address a number of managerial and scientific needs. Thus, users will be able to: Create a baseline on the extent of invasion by region in order to assess new invasions. Use existing geographical patterns of invasion to gain some insights into potential new invaders. Use existing geographical patters of invasion to gain some insights into mechanisms affecting relative invasibility of different areas. Use life history attributes and environmental requirements of the reported nonindigenous species to evaluate traits of invaders. Understand the potential spread of invaders based on their habitat and environmental requirements. Understand importance of different vectors of introduction of nonindigenous species by region. The data in the Atlas of Nonindigenous Marine and Estuarine Species in the North Pacific (Lee and Reusser, 2012) are up-to-date as of June 2012. Updates to the PICES database were made in September 2012.

Report↗
USGS2002

Influence of fluvial processes on the quaternary geologic framework of the continental shelf, North Carolina, USA

Digital, single-channel, high-resolution seismic reflection profiles were acquired from the insular continental shelf of North Carolina, USA along a data grid extending from Oregon Inlet northward 48 km to Duck, North Carolina and from the nearshore zone seaward approximately 28 km (total surveyed area= 1334 km2). These data were processed and interpreted to delineate principal reflecting horizons and develop a three-dimensional seismic stratigraphic framework for the continental shelf that was compared to stratigraphic data from the shoreward back-barrier (estuarine) and barrier island system. Six principal reflecting horizons (designated R0 through R5) were present within the upper 60 m of the shelf stratigraphic succession. Three-dimensional mapping of reflector R1 demonstrated its origin from fluvial incision of the continental shelf during an episode (or episodes) of lowered sea-level. Fluvial processes during development of reflector R1 were responsible for extensive reworking and re-deposition of sediment throughout most of the northern half of the study area. Five seismic stratigraphic units (designated S1 through S5) were tentatively correlated with depositional sequences previously identified from the North Carolina back-barrier (estuarine) and barrier island system. These five stratigraphic units span the Quaternary Period (S1 = early Holocene; S2 = 51-78 ka; S3 = 330-530 ka; S4 = 1.1-1.8 Ma; S5 = earliest Pleistocene). Unit S1 is composed of fine-grained fluvial/estuarine sediment that back-filled incised streams during early Holocene sea-level rise. The four other stratigraphic units (S2-S5) display tabular depositional geometries, low total relief, and thicken toward the east-southeast as their basal reflectors dip gently between 0.41 m km-1 (0.02??) and 0.54 m km-1 (0.03??). Knowledge of the three-dimensional subsurface stratigraphic architecture of the continental shelf enhances understanding of the development of shelf depositional successions and provides a framework for development of better Quaternary sea-level data, especially offshore North Carolina where such data are sparse. ?? 2002 Elsevier Science B.V. All rights reserved.

Marine Geology↗
USGS2009

ATM Coastal Topography-Texas, 2001: UTM Zone 14

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by 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. This project provides highly detailed and accurate datasets of a portion of the Texas coastline within UTM zone 14, acquired October 12-13, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.

Texas↗
USGS2014

ARkStorm@Tahoe: Stakeholder perspectives on vulnerabilities and preparedness for an extreme storm event in the greater Lake Tahoe, Reno, and Carson City region

Atmospheric rivers (ARs) are strongly linked to extreme winter precipitation events in the Western U.S., accounting for 80 percent of extreme floods in the Sierra Nevada and surrounding lowlands. In 2010, the U.S. Geological Survey developed the ARkStorm extreme storm scenario for California to quantify risks from extreme winter storms and to allow stakeholders to better explore and mitigate potential impacts. To explore impacts on natural resources and communities in montane and adjacent environments, we downscaled the scenario to the greater Lake Tahoe, Reno and Carson City region of northern Nevada and California. This ArkStorm@Tahoe scenario was presented at six stakeholder meetings, each with a different geographic and subject matter focus. Discussions were facilitated by the ARkStorm@Tahoe team to identify social and ecological vulnerabilities to extreme winter storms, science and information needs, and proactive measures that might minimize impacts from this type of event. Information collected in these meetings was used to develop a tabletop emergency response exercise and set of recommendations for increasing resilience to extreme winter storm events in both Tahoe and the downstream communities of Northern Nevada. Over 300 individuals participated in ARkStorm@Tahoe stakeholder meetings and the emergency response exercise, including representatives from emergency response, natural resource and ecosystem management, health and human services, public utilities, and businesses. Interruption of transportation, communications, and lack of power and backup fuel supplies were identified as the most likely and primary points of failure across multiple sectors and geographies, as these interruptions have cascading effects on natural and human systems by impeding emergency response efforts. Other key issues that arose in discussions included contamination risks to water supplies and aquatic ecosystems, especially in the Tahoe Basin and Pyramid Lake, interagency coordination, credentialing, flood management, and coordination of health and human services during such an event. Mitigation options were identified for each of the key issues. Several science needs were identified, particularly the need for improved flood inundation maps. Finally, key lessons learned were identified and may help to increase preparedness, response and recovery from extreme storms in the future.

Report↗
USGS2009

ATM Coastal Topography-Texas, 2001: UTM Zone 15

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by 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. This project provides highly detailed and accurate datasets of a portion of the Texas coastline within UTM zone 15, from Matagorda Peninsula to Galveston Island, acquired October 12-13, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.

Texas↗
USGS2010

ATM Coastal Topography-Louisiana, 2001: UTM Zone 15 (Part 1 of 2)

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by 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. This project provides highly detailed and accurate datasets of a portion of the Louisiana coastline beach face within UTM Zone 15, from Isles Dernieres to Grand Isle, acquired September 7 and 10, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.

Louisiana↗
USGS2024

Remote sensing large-wood storage downstream of reservoirs during and after dam removal: Elwha River, Washington, USA

Large wood is an integral part of many rivers, often defining river-corridor morphology and habitat, but its occurrence, magnitude, and evolution in a river system are much less well understood than the sedimentary and hydraulic components, and due to methodological limitations, have seldom previously been mapped in substantial detail. We present a new method for this, representing a substantial advance in automated deep-learning-based image segmentation. From these maps, we measured large wood and sediment deposits from high-resolution orthoimages to explore the dynamics of large wood in two reaches of the Elwha River, Washington, USA, between 2012 and 2017 as it adjusted to upstream dam removals. The data set consists of a time series of orthoimages (12.5-cm resolution) constructed using Structure-from-Motion photogrammetry on imagery from 14 aerial surveys. Model training was optimized to yield maximum accuracy for estimated wood areas, compared to manually digitized wood, therefore model development and intended application were coupled. These fully reproducible methods and model resulted in a maximum of 15% error between observed and estimated total wood areas and wood deposit size-distributions over the full spatio-temporal extent of the data. Areal extent of wood in the channel margin approximately doubled in the years following dam removal, with greatest increases in large wood in wider, lower-gradient sections. Large-wood deposition increased between the start of dam removal (2011) and winter 2013, then plateaued. Sediment bars continued to grow up until 2016/17, assisted by a partially static wood framework deposited predominantly during the period up to winter 2013.

Washington↗
USGS2009

ATM Coastal Topography - Louisiana, 2001: UTM Zone 16 (Part 2 of 2)

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by 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. This project provides highly detailed and accurate datasets of a portion of the Louisiana coastline beach face within UTM Zone 16, from Grand Isle to the Chandeleur Islands, acquired September 7 and 9, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft. Elevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.

Louisiana↗
USGS2017

The U.S. Geological Survey Peak-Flow File Data Verification Project, 2008–16

Annual peak streamflow (peak flow) at a streamgage is defined as the maximum instantaneous flow in a water year. A water year begins on October 1 and continues through September 30 of the following year; for example, water year 2015 extends from October 1, 2014, through September 30, 2015. The accuracy, characterization, and completeness of the peak streamflow data are critical in determining flood-frequency estimates that are used daily to design water and transportation infrastructure, delineate flood-plain boundaries, and regulate development and utilization of lands throughout the United States and are essential to understanding the implications of climate and land-use change on flooding and high-flow conditions. As of November 14, 2016, peak-flow data existed for 27,240 unique streamgages in the United States and its territories. The data, collectively referred to as the “peak-flow file,” are available as part of the U.S. Geological Survey (USGS) public web interface, the National Water Information System, at https://nwis.waterdata.usgs.gov/usa/nwis/peak . Although the data have been routinely subjected to periodic review by the USGS Office of Surface Water and screening at the USGS Water Science Center level, these data were not reviewed in a national, systematic manner until 2008 when automated scripts were developed and applied to detect potential errors in peak-flow values and their associated dates, gage heights, and peak-flow qualification codes, as well as qualification codes associated with the gage heights. USGS scientists and hydrographers studied the resulting output, accessed basic records and field notes, and corrected observed errors or, more commonly, confirmed existing data as correct. This report summarizes the changes in peak-flow file data at a national level, illustrates their nature and causation, and identifies the streamgages affected by these changes. Specifically, the peak-flow data were compared for streamgages with peak flow measured as of November 19, 2008 (before the automated scripts were widely applied) and on November 14, 2016 (after several rounds of corrections). There were 659,332 peak-flow values in the 2008 dataset and 731,965 peak-flow values in the 2016 dataset. When compared to the 2016 dataset, 5,179 (0.79 percent) peak-flow values had changed; 36,506 (5.54 percent) of the peak-flow qualification codes had changed; 1,938 (0.29 percent) peak-flow dates had changed; 18,599 (2.82 percent) of the peak-flow gage heights had changed; and 20,683 (3.14 percent) of the gage-height qualification codes had changed—most as a direct result of the peak-flow file data verification effort led by USGS personnel. The various types of changes are summarized and mapped in this report. In addition to this report, a corresponding USGS data release is provided to identify changes in peak flows at individual streamgages. The data release and the procedures to access the data release are described in this report.

Scientific Investigations Report↗
USGS2014

User's manual for the upper Delaware River riverine environmental flow decision support system (REFDSS), Version 1.1.2

Between 2002 and 2006, the Fort Collins Science Center (FORT) at the U.S. Geological Survey (USGS) conducted field surveys, organized workshops, and performed analysis of habitat for trout and shad in the Upper Delaware River Basin. This work culminated in the development of decision support system software (the Delaware River DSS–DRDSS, Bovee and others, 2007) that works in conjunction with the Delaware River Basin Commission’s reservoir operations model, OASIS, to facilitate comparison of the habitat and water-delivery effects of alternative operating scenarios for the Basin. This original DRDSS application was developed in Microsoft Excel and is available to all interested parties through the FORT web site ( http://www.fort.usgs.gov/Products/Software/DRDSS/ ). Initial user feedback on the original Excel-based DSS highlighted the need for a more user-friendly and powerful interface to effectively deliver the complex data and analyses encapsulated in the DSS. In order to meet this need, the USGS FORT and Northern Appalachian Research Branch (NARB) developed an entirely new graphical user interface (GUI) application. Support for this research was through the DOI WaterSmart program ( http://www.doi.gov/watersmart/html/index.php ) of which the USGS component is the National Water Census ( http://water.usgs.gov/watercensus/WaterSMART.html ). The content and methodology of the new GUI interface emulates those of the original DSS with a few exceptions listed below. Refer to Bovee and others (2007) for the original information. Significant alterations to the original DSS include: • We moved from Excel-based data storage and processing to a more powerful database back end powered by SQLite. The most notable effect of this is that the previous maximum temporal extent of 10 years has been replaced by a dynamic extent that can now cover the entire period of record for which we have data (1928–2000). • We incorporated interactive geographic information system (GIS) visualization and dynamic data processing. Previous habitat maps were generated outside of the DSS in an ad hoc process that the end user could not update or investigate. • The original bathymetric data collected in 2005 at the three main stem reaches was augmented with a higher resolution dataset collected in 2010. This new dataset was collected in order to conduct higher resolution (finer pixel size) two-dimensional (2D) hydrodynamic modeling for evaluating dwarf wedgemussel (DWM, Alasmidonta heterodon ) habitat. • Results charts are now substantially more interactive, dynamic, and accessible, which allows users to more easily focus on their particular topics of interest as well as drill down to the source data used to calculate given results.

Open-File Report↗
USGS2025

Ten more years of the golden pheasant (Chrysolophus pictus) on Maui, Hawaiian Islands

Since the introduction of the Golden Pheasant ( Chrysolophus pictus ) to Haleakalā volcano, Maui, three decades ago, subsequent reports have hinted at an expansion of this nascent population. We draw from a variety of data sources to learn about this pheasant's present status on Maui. First, forest bird surveys conducted every five years revealed that the frequency of Golden Pheasant detections has greatly increased, and the bird has both maintained its former distribution and expanded eastward into Haleakalā National Park (NP). Second, reports to eBird from The Nature Conservancy's Waikamoi Preserve, where Golden Pheasants first appeared on Maui, demonstrate that the frequency of observations has increased and is strongly seasonal, predominantly in the spring. Third, autonomous recording units monitoring endangered forest birds recorded pheasants too, adding new locations. Finally, trail cameras set to monitor mammals picked up pheasants as well, showing males of two color morphs: original “wild-type” and “dark-throated.” Trail cameras also documented a small juvenile at Waikamoi Preserve and both females and males in Haleakalā NP. By “connecting the dots” of mapped occurrences, we traced the pheasant's progression through a narrow band of subalpine cloud forest with open understory, extending from Waikamoi Preserve eastward to upper Kīpahulu Valley, a distance of 14 km. In summary, this body of evidence supports the claim that the Golden Pheasant has established a self-sustaining population on Maui, and we propose that the species' success there may be attributed to the minimal influence of predators and the absence of competing gallinaceous birds in its preferred habitat.

Hawaii↗
USGS2022

Bedrock depth influences spatial patterns of summer baseflow, temperature and flow disconnection for mountainous headwater streams

In mountain headwater streams, the quality and resilience of summer cold-water habitat is generally regulated by stream discharge, longitudinal stream channel connectivity and groundwater exchange. These critical hydrologic processes are thought to be influenced by the stream corridor bedrock contact depth (sediment thickness), a parameter often inferred from sparse hillslope borehole information, piezometer refusal and remotely sensed data. To investigate how local bedrock depth might control summer stream temperature and channel disconnection (dewatering) patterns, we measured stream corridor bedrock depth by collecting and interpreting 191 passive seismic datasets along eight headwater streams in Shenandoah National Park (Virginia, USA). In addition, we used multi-year stream temperature and streamflow records to calculate several baseflow-related metrics along and among the study streams. Finally, comprehensive visual surveys of stream channel dewatering were conducted in 2016, 2019 and 2021 during summer low flow conditions (124 total km of stream length). We found that measured bedrock depths along the study streams were not well-characterized by soils maps or an existing global-scale geologic dataset where the latter overpredicted measured depths by 12.2 m (mean) or approximately four times the average bedrock depth of 2.9 m. Half of the eight study stream corridors had an average bedrock depth of less than 2 m. Of the eight study streams, Staunton River had the deepest average bedrock depth (3.4 m), the coldest summer temperature profiles and substantially higher summer baseflow indices compared to the other study steams. Staunton River also exhibited paired air and water annual temperature signals suggesting deeper groundwater influence, and the stream channel did not dewater in lower sections during any baseflow survey. In contrast, Paine Run and Piney River did show pronounced, patchy channel dewatering, with Paine Run having dozens of discrete dry channel sections ranging from 1 to greater than 300 m in length. Stream dewatering patterns were apparently influenced by a combination of discrete deep bedrock (20+ m) features and more subtle sediment thickness variation (1–4 m) depending on local stream valley hydrogeology. In combination, these unique datasets show the first large-scale empirical support for existing conceptual models of headwater stream disconnection based on spatially variable underflow capacity and shallow groundwater supply.

Virginia↗