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USGS2005

Integrated fire science in the Rocky Mountains

Fire is an important ecological process that has helped shape western landscapes. Wildfire suppression and other management practices may have altered historic fire regimes in ecosystems adapted to frequent, low-severity fires. Compounding this problem is the encroachment of homes into fire-prone areas. Fire affects a number of abiotic and biotic components of ecosystems, and had many economic and social ramifications. The full range of consequences, however, remains poorly understood. To implement sound fire management, managers require improved understanding of fire effects on public lands. Although the importance of fire to ecosystem function is widely recognized, wildfire science has not been fully integrated into management actions. An interdisciplinary approach is essential to integrate and evaluate tradeoffs among fire management policies and practices.

Rocky Mountains↗

USGS2021

A more representative community of ecologists

Ecologists play a crucial role in providing solutions to the challenges facing the world. For most of the history of the field, however, the science of ecology has been pursued by white men, and increasingly, by white women. This lack of diversity is untenable today, not only because it is socially unjust, but also because solving environmental problems requires diversity. Ecology as a science is an extremely rewarding and fun career choice for many, but how can the field recruit a more diverse workforce to do this important and gratifying work? Attracting and retaining future ecologists of color is the focus of this Forum. How do young people choose a career in ecology and environmental sciences? For many ecologists, environmental scientists and managers, and future natural resource professionals, an early field experience provides a crucial introduction and gateway. A sojourn at a field station, an extended field trip, or field expedition has introduced many of today’s professionals to their fields, but at the same time, a growing literature documents problematic behavior, discrimination, and other forms of harassment that have been far too frequently reported, and little attention has been given to conscious or implicit exclusion of students from diverse backgrounds. In their lead article, Bowser and Cid, two leading researchers and long-time champions of diversity in ecology, build on experience in long-running programs as well as the literature to diagnose challenges facing diverse youth, and present approaches to encourage, rather than discourage, further engagement. They describe affirmative and creative measures that foster a sense of inclusion and community among young scholars; this sense of belonging and empowerment allows many to advance to studies and careers in ecology and environmental science. In the subsequent six papers, authors explore topics either responding to, or inspired by, the lead paper. They explore alternatives to a field experience as a gateway to a career in ecology or environmental sciences through, for example, data science or the social sciences. Other comment papers describe challenges faced in the next phases of an academic career, barriers faced by specific cultural groups and the approaches, challenges, and outcomes of programs aiming to increase the diversity of the environmental STEM workforce. All responses sound a clarion call for change to hear and value different voices and perspectives to be heard and valued. These include (1) structural and cultural change to our institutions and reward structures; (2) developing and nurturing personal relationships among students and their mentors, within teams and in internships; (3) making entry to ecology inviting and making advancement in ecology free from systemic barriers; and (4) broadening our vision of ecology, and the ways we learn about the world’s ecosystems. The Ecological Society of America, the home for Ecological Applications , is committed to the diversity, equity and inclusion needed to tackle environmental challenges in unity (https://www.esa.org/esablog/2020/09/24/time-for-action-esa-initiates-a-diversity-equity-inclusion-and-justice-deij-task-force/). The world needs all available talent and perspectives to meet environmental challenges today. Ecological Applications has long published occasional papers on the profession of ecology and never ones more important or timely than these. The editorial team is proud to provide an outlet for the voices of our field, in all its current, if inadequate, diversity and honored to host the passionate and committed views of our authors.

Ecological Applications↗

USGS2010

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

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

Data Series↗

USGS2012

U.S. Geological Survey, National Wildlife Health Center, 2011 report of selected wildlife diseases

The National Wildlife Health Center (NWHC) was founded in 1975 to provide technical assistance in identifying, controlling, and preventing wildlife losses from diseases, conduct research to understand the impact of diseases on wildlife populations, and devise methods to more effectively manage these disease threats. The impetus behind the creation of the NWHC was, in part, the catastrophic loss of tens of thousands of waterfowl as a result of an outbreak of duck plague at the Lake Andes National Wildlife Refuge in South Dakota during January 1973. In 1996, the NWHC, along with other Department of Interior research functions, was transferred from the U.S. Fish and Wildlife Service to the U.S. Geological Survey (USGS), where we remain one of many entities that provide the independent science that forms the bases of the sound management of the Nation’s natural resources. Our mission is to provide national leadership to safeguard wildlife and ecosystem health through dynamic partnerships and exceptional science. The main campus of the NWHC is located in Madison, Wis., where we maintain biological safety level 3 (BSL–3) diagnostic and research facilities purposefully designed for work with wildlife species. The NWHC provides research and technical assistance on wildlife health issues to State, Federal, and international agencies. In addition, since 1992 we have maintained a field station in Hawaii, the Honolulu Field Station, which focuses on marine and terrestrial natural resources throughout the Pacific region. The NWHC conducts diagnostic investigations of unusual wildlife morbidity and mortality events nationwide to detect the presence of wildlife pathogens and determine the cause of death. This is also an important activity for detecting new, emerging and resurging diseases. The NWHC provides this crucial information on the presence of wildlife diseases to wildlife managers to support sound management decisions. The data and information generated also allows for further indepth analyses for determining the biological and ecological significance of disease events, detecting disease trends over time and space, as well as detecting any significant changes to how diseases manifest in the field. Moreover, this information allows us to gain insight into the significance of future wildlife disease events. The purpose of this report is to provide a sample of NWHC data that are available from our Laboratory Information Management System (LIMS). These data are presented in summary format with minimal statistical analysis and interpretation. The goal is to share these data with wildlife managers and other stakeholders, promote the use of NHWC data, and encourage the sharing of wildlife disease data to improve temporal and geographic surveillance coverage. Continued national surveillance for wildlife diseases is essential for providing early detection and warning of events that have the potential to result in harm to human health, economic losses, declines in wildlife populations, and subsequent ecological disturbances. Increased collaboration, coordination, and sharing of surveillance data will enhance this Nation’s ability to detect and respond to wildlife disease threats.

Scientific Investigations Report↗

USGS2016

Panarchy use in environmental science for risk and resilience planning

Environmental sciences have an important role in informing sustainable management of built environments by providing insights about the drivers and potentially negative impacts of global environmental change. Here, we discuss panarchy theory, a multi-scale hierarchical concept that accounts for the dynamism of complex socio-ecological systems, especially for those systems with strong cross-scale feedbacks. The idea of panarchy underlies much of system resilience, focusing on how systems respond to known and unknown threats. Panarchy theory can provide a framework for qualitative and quantitative research and application in the environmental sciences, which can in turn inform the ongoing efforts in socio-technical resilience thinking and adaptive and transformative approaches to management.

Environment Systems and Decisions↗

USGS2019

Integration of social and ecological sciences for natural resource decision making: Challenges and opportunities

The last 25 years have witnessed growing recognition that natural resource management decisions depend as much on understanding humans and their social interactions as on understanding the interactions between non-human organisms and their environment. Decision science provides a framework for integrating ecological and social factors into a decision, but challenges to integration remain. The decision-analytic framework elicits values and preferences to help articulate objectives, and then evaluates the outcomes of alternative management actions to achieve these objectives. Integrating social science into these steps can be hindered by failing to include social scientists as more than stakeholder-process facilitators, assuming that specific decision-analytic skills are commonplace for social scientists, misperceptions of social data as inherently qualitative, timescale mismatches for iterating through decision analysis and collecting relevant social data, difficulties in predicting human behavior, and failures of institutions to recognize the importance of this integration. We engage these challenges, and suggest solutions to them, helping move forward the integration of social and biological/ecological knowledge and considerations in decision-making.

Environmental Management↗

USGS2007

Proceedings of the U.S. Geological Survey 2004 Mercury Workshop - Mercury research and its relation to Department of the Interior resource management

Introduction As part of the Department of the Interior (DOI) program Science on the DOI Landscape Initiative, the U.S. Geological Survey (USGS), Eastern Region, held a workshop during August 17–18, 2004, in Reston, VA, on mercury in the environment as it relates to DOI resource management. DOI bureaus manage millions of acres of land and offshore resources subject to mercury deposition and to the effects of mercury on ecosystems and human health. The goals of the workshop were to (1) summarize information on mercury sources and cycling on DOI lands in the eastern United States, (2) learn the perspectives of the DOI bureaus regarding mercury on DOI lands, (3) provide information to DOI land managers about monitoring mercury and minimizing mercury accumulation in wildlife and humans, and (4) consider future directions for mercury monitoring and research on DOI lands. The workshop focused on mercury research as it relates to DOI resource-management issues primarily in the eastern part of the United States (east of the Mississippi River). Topics included the influence of ecosystem setting on mercury biogeochemical transformation, land- and air-management practices as they affect mercury in the environment, mercury source issues, and effects of mercury on humans and wildlife. Mercury research topics were addressed by 24 invited oral presentations and 30 contributed posters. The perspectives of the DOI bureaus and land managers were addressed through a panel of scientists from the DOI resource-management bureaus and a Chippewa Indian Tribe of Minnesota. Discussion at the conclusion of the workshop was directed toward goals and long-term strategies for mercury research that will benefit DOI resource management. The panel, presentations, and discussions were videotaped and are available at the following URL, along with the slides presented: http://www.usgs.gov/mercury/2004workshop/ Abstracts from the presentations and posters are included in this report, together with summaries of each presentation session. The abstracts in this volume that were written by U.S. Geological Survey authors were reviewed and approved for publication by the Survey. Abstracts submitted by researchers from academia and from state and other federal agencies are published as part of these proceedings, but do not necessarily reflect the Survey’s policies and views. The use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Open-File Report↗

USGS2017

U.S. Geological Survey sage-grouse and sagebrush ecosystem research annual report for 2017

The sagebrush ( Artemisia spp.) ecosystem extends across a large portion of the Western United States, and the greater sage-grouse ( Centrocercus urophasianus ) is one of the iconic species of this ecosystem. Greater sage-grouse populations occur in 11 States and are dependent on relatively large expanses of sagebrush-dominated habitat. Sage-grouse populations have been experiencing long-term declines owing to multiple stressors, including interactions among fire, exotic plant invasions, and human land uses, which have resulted in significant loss, fragmentation, and degradation of landscapes once dominated by sagebrush. In addition to the sage-grouse, over 350 species of plants and animals are dependent on the sagebrush ecosystem. Increasing knowledge about how these species and the sagebrush ecosystem respond to these stressors and to management actions can inform and improve strategies to maintain existing areas of intact sagebrush and restore degraded landscapes. The U.S. Geological Survey (USGS) has a broad research program focused on providing the science needed to inform these strate-gies and to help land and resource managers at the Federal, State, Tribal, and local levels as they work towards sustainable sage-grouse populations and restored landscapes for the broad range of uses critical to stakeholders in the Western United States. USGS science has provided a foundation for major land and resource management decisions including those that precluded the need to list the greater sage-grouse under the Endangered Species Act. The USGS is continuing to build on that foundation to inform science-based decisions to help support local economies and the continued conservation, management, and restoration of the sagebrush ecosystem. This report contains descriptions of USGS sage-grouse and sagebrush ecosystem research projects that are ongoing or were active during 2017 and is organized into five thematic areas: Fire, Invasive Species, Restoration, Sagebrush and Sage-Grouse, and Climate and Weather.

Circular↗

USGS2023

Grassland management priorities for the North Central Region

Executive Summary Understanding how climate change and variability will impact grassland ecosystems is crucial for successful grassland management in the 21st century. In 2020, the U.S. Geological Survey North Central Climate Adaptation Science Center (USGS NC CASC) began a project to establish a baseline of information to best serve grassland managers (that is, those who develop grassland management plans or implement those plans on the ground) at Federal, State, and Tribal agen-cies and nongovernmental organizations to help meet regional grassland management goals. This project “A Synthesis of Climate Impacts, Stakeholder Needs, and Adaptation in Northern Great Plains Grassland Ecosystems” (hereafter, the Grasslands Synthesis Project), had two primary goals: (1) to synthesize management goals and challenges for grassland managers across the region and (2) to assess the state-of-the-science and identify knowledge gaps for addressing the goals and challenges within the context of climate change. The findings from the Grasslands Syn-thesis Project are described in two volumes. This report serves several purposes, including providing (1) a synthesis of regional grassland management goals and challenges, (2) identification of information needs relevant to grassland management in a changing climate, and (3) summaries of grassland management issues by ecoregion and management organization or agency.

Colorado, Kansas, Montana, Nebraska, Noth Dakota, ↗

USGS2010

EAARL coastal topography and imagery-Fire Island National Seashore, New York, 2009

These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived bare-earth (BE) and 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 Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the Fire Island National Seashore in New York, acquired on July 9 and August 3, 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 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 was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗

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↗

USGS2022

2021 assessment of the Joint Fire Science Program’s Fire Science Exchange Network

The U.S. Geological Survey (USGS), on behalf of the Joint Fire Science Program (JFSP), conducted an evaluation of the Fire Science Exchange Network (FSEN), which connects wildland fire scientists and practitioners through 15 individual exchanges across the United States to help address complex wildfire needs and challenges. The study was divided into two phases: The first phase was a literature review and synthesis from materials provided by the JFSP Board. Phase two, informed by the JFSP review, was an online survey sent to more than 16,000 exchange network users compiled from the electronic mailing lists for each exchange. Respondents were asked their opinions on the importance, quality, and delivery of information for 16 key fire science topics, the prioritization of FSEN objectives, and from where and to what extent respondents are gathering information on key topics. Overall, respondents believed that sharing information and building relationships are the most important objectives of the FSEN. Respondents believed the exchange network is successful in delivering information for many of the key science topics (for example, fire behavior, prescribed fire, firefighter safety, and incident management); gaps were identified in scientific resources available for some topics (for example, economic impacts, social science and human dimensions, Indigenous knowledge). Most respondents participated in one to two exchanges and relied heavily on their respondent location (the exchange in which they primarily live and [or] work) for information. Respondents also often relied on external sources outside of the exchange network. Regional patterns emerged in information gathering whereby respondents from exchanges in the western United States (for example, Northern Rockies, Southern Rockies, and Northwest) and respondents from exchanges in the eastern United States (for example, Southern, Oak Woodlands, and Tallgrass) frequently gathered information from each other.

Scientific Investigations Report↗

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↗

USGS2008

Some guidelines for helping natural resources adapt to climate change

The changes occurring in mountain regions are an epitome of climate change. The dramatic shrinkage of major glaciers over the past century – and especially in the last 30 years – is one of several iconic images that have come to symbolize climate change. Climate creates the context for ecosystems, and climate variables strongly influence the structure, composition, and processes that characterize distinct ecosystems. Climate change, therefore, is having direct and indirect effects on species attributes, ecological interactions, and ecosystem processes. Because changes in the climate system will continue regardless of emissions mitigation, management strategies to enhance the resilience of ecosystems will become increasingly important. It is essential that management responses to climate change proceed using the best available science despite uncertainties associated with the future path of climate change, the response of ecosystems to climate effects, and the effects of management. Given these uncertainties, management adaptation will require flexibility to reflect our growing understanding of climate change impacts and management effectiveness.

IHDP Update↗

USGS2010

EAARL Coastal Topography-Fire Island National Seashore, New York, Post-Nor'Ida, 2009

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the Fire Island National Seashore in New York, acquired post-Nor'Ida (November 2009 nor'easter) on December 4, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗

USGS2010

EAARL Coastal Topography and Imagery-Naval Live Oaks Area, Gulf Islands National Seashore, Florida, 2007

These remotely sensed, geographically referenced color-infrared (CIR) imagery and elevation measurements of lidar-derived bare-earth (BE) topography, first-surface (FS) topography, and canopy-height (CH) datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Science Center, St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Naval Live Oaks Area in Florida's Gulf Islands National Seashore, acquired June 30, 2007. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral 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 and Imagery-Assateague Island National Seashore, Maryland and Virginia, Post-Nor'Ida, 2009

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

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USGS2023

Colorado River Basin Actionable and Strategic Integrated Science and Technology Project—Science strategy

The U.S. Geological Survey (USGS) conducts a wide variety of science that improves understanding of droughts and their effects on ecosystems and society. This work includes data collection and monitoring of aquatic and terrestrial systems; assessment and analysis of patterns, trends, drivers, and impacts of drought; development and application of predictive models; and delivery of information and decision-making tools to stakeholders. Stakeholders, which include Federal, Tribal, State, and local agencies, nongovernmental organizations, and others, use this information to anticipate, assess, react to, and mitigate drought conditions and impacts. There is no obvious near-term solution to reduce the frequency and severity of droughts or to mitigate drought impacts. Multidecadal drought is a “grand challenge” that benefits from integration of existing technologies, data, knowledge, and models across related and disparate disciplines, facilitated by new science and technology. In response, the USGS initiated a new integrated-science approach in the Colorado River Basin in 2020. The Colorado River Basin was specifically selected because of concerns about future drought and its consequences for the region. This document explains how the Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST) project extends and enhances the science supported by USGS Mission Areas and Programs and articulates scientific gaps and stakeholder needs to identify and reduce drought risks. The approach seeks to answer complex Earth science questions developed in partnership with stakeholders about severe long-term drought. An integrated approach is required to tackle these complex questions, which any single science discipline cannot answer on its own. In addition to increased understanding of drought and drought effects in complex systems, the Colorado River Basin ASIST project was designed to improve efficiencies through rapid location of a broad array of data sources, assembly of model-ready multidisciplinary data, and delivery of actionable science to stakeholders at the speeds and scales needed for decision making. The project team identified the following actions needed for USGS to implement and advance an integrated science approach in the Colorado River Basin: (1) engage with stakeholders to document their needs and iteratively co-produce science and science delivery tools to address these needs, (2) integrate monitoring and observation systems developed by USGS and other agencies that track droughts and their effects, (3) collect and provide analysis-ready data to support integrated applications, (4) integrate data and model connections to predict multiple drought impacts, (5) conduct multidisciplinary coordination to improve interpretations, (6) leverage the knowledge base across USGS to enhance decision making, and (7) support the development of new integrated science approaches and technologies that provide analysis and management tools that can be used to adapt to the effects of drought in the Colorado River Basin. Proposals for initial short-term use-case projects were solicited, a subset of which was selected for funding to test implementation of these actions. Additionally, the project organized and convened a series of science and technology collaboration workshops in the USGS focused on challenges that were identified and prioritized by the short-term use-case projects and during the initial stakeholder analysis. These workshops were designed to bring together diverse perspectives to discuss science and technology challenges, stakeholder needs, capabilities, and knowledge gaps, with the goal of determining how the USGS can address challenges, identify future opportunities for continued engagement between participants, and inform the next steps for the Colorado River Basin ASIST project. Continuing to collaboratively engage with a wide range of stakeholders using an integrated approach will provide a suitable foundation of data and tools to formulate actionable intelligence for predicting droughts and informing adaptation to the effects of long-term drought in a holistic, timely, and effective manner.

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