Search USGS⌕ Search

SEARCH · Search USGS

Results for “Science of Remote Sensing”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15Linked to original sources
USGS2014

EAARL-B coastal topography: eastern New Jersey, Hurricane Sandy, 2012: first surface

These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida. This project provides highly detailed and accurate datasets for a portion of the New Jersey coastline beachface, acquired pre-Hurricane Sandy on October 26, and post-Hurricane Sandy on November 1 and November 5, 2012. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar system, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nm) lidar designed to map nearshore bathymetry, topography, and vegetation structure simultaneously. The EAARL-B sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, down-looking red-green-blue (RGB) and infrared (IR) digital cameras, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL-B platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL-B system. The resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Lidar for Science and Resource Management Web site.

New Jersey↗
USGS2013

Landsat surface reflectance quality assurance extraction (version 1.7)

The U.S. Geological Survey (USGS) Land Remote Sensing Program is developing an operational capability to produce Climate Data Records (CDRs) and Essential Climate Variables (ECVs) from the Landsat Archive to support a wide variety of science and resource management activities from regional to global scale. The USGS Earth Resources Observation and Science (EROS) Center is charged with prototyping systems and software to generate these high-level data products. Various USGS Geographic Science Centers are charged with particular ECV algorithm development and (or) selection as well as the evaluation and application demonstration of various USGS CDRs and ECVs. Because it is a foundation for many other ECVs, the first CDR in development is the Landsat Surface Reflectance Product (LSRP). The LSRP incorporates data quality information in a bit-packed structure that is not readily accessible without postprocessing services performed by the user. This document describes two general methods of LSRP quality-data extraction for use in image processing systems. Helpful hints for the installation and use of software originally developed for manipulation of Hierarchical Data Format (HDF) produced through the National Aeronautics and Space Administration (NASA) Earth Observing System are first provided for users who wish to extract quality data into separate HDF files. Next, steps follow to incorporate these extracted data into an image processing system. Finally, an alternative example is illustrated in which the data are extracted within a particular image processing system.

Techniques and Methods↗
USGS2016

Perspectives on bay-delta science and policy

The State of Bay–Delta Science 2008 highlighted seven emerging perspectives on science and management of the Delta. These perspectives had important effects on policy and legislation concerning management of the Delta ecosystem and water exports. From the collection of papers that make up the State of Bay–Delta Science 2016, we derive another seven perspectives that augment those published in 2008. The new perspectives address nutrient and contaminant concentrations in Delta waters, the failure of the Delta food web to support native species, the role of multiple stressors in driving species toward extinction, and the emerging importance of extreme events in driving change in the ecosystem and the water supply. The scientific advances that underpin these new perspectives were made possible by new measurement and analytic tools. We briefly discuss some of these, including miniaturized acoustic fish tags, sensors for monitoring of water quality, analytic techniques for disaggregating complex contaminant mixtures, remote sensing to assess levee vulnerability, and multidimensional hydrodynamic modeling. Despite these new tools and scientific insights, species conservation objectives for the Delta are not being met. We believe that this lack of progress stems in part from the fact that science and policy do not incorporate sufficiently long-term perspectives. Looking forward half a century was central to the Delta Visioning process, but science and policy have not embraced this conceptual breadth. We are also concerned that protection and enhancement of the unique cultural, recreational, natural resource, and agricultural values of the Delta as an evolving place, as required by the Delta Reform Act, has received no critical study and analysis. Adopting wider and longer science and policy perspectives immediately encourages recognition of the need for evaluation, analysis, and public discourse on novel conservation approaches. These longer and wider perspectives also encourage more attention to the opportunities provided by heavily invaded ecosystems. It is past time to turn scientific and policy attention to these issues.

California↗
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↗
USGS2010

EAARL coastal topography-Cape Hatteras National Seashore, North Carolina, post-Nor'Ida, 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 Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the National Park Service Southeast Coast Network's Cape Hatteras National Seashore in North Carolina, acquired post-Nor'Ida (November 2009 nor'easter) on November 27 and 29 and December 1, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website.

Data Series↗
USGS2011

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

These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI. This project provides highly detailed and accurate datasets of a portion of the National Park Service Southeast Coast Network's Cape Hatteras National Seashore in North Carolina, acquired post-Nor'Ida (November 2009 nor'easter) on November 27 and 29 and December 1, 2009. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

Data Series↗
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↗
USGS2013

Data management challenges in species distribution modeling

An important component in the fields of ecology and conservation biology is understanding the environmental conditions and geographic areas that are suitable for a given species to inhabit. A common tool in determining such areas is species distribution modeling which uses computer algorithms to determine the spatial distribution of organisms. Most commonly the correlative relationships between the organism and environmental variables are the primary consideration. The data requirements for this type of modeling consist of known presence and possibly absence locations of the species as well as the values of environmental or climatic covariates thought to define the species habitat suitability at these locations. These covariate data are generally extracted from remotely sensed imagery, interpolated/gridded historical climate data, or downscaled climate model output. Traditionally, ecologists and biologists have constructed species distribution models using workflows and data that reside primarily on their local workstations or networks. This workflow is becoming challenging as scientists increasingly try to use these modeling techniques to inform management decisions under different climate change scenarios. This challenge stems from the fact that remote sensing products, gridded historical climate, and downscaled climate models are not only increasing in spatial and temporal resolution but proliferating as well. Any rigorous assessment of uncertainty requires a computationally intensive sensitivity analysis accounting for various sources of uncertainty. The scientists fitting these models generally do not have the background in computer science required to take advantage of recent advances in web-service based data acquisition, remote high-powered data processing, or scientific workflow systems. Ecologists in the field of modeling are in need of a tractable platform that abstracts the inherent computational complexity required to incorporate the burgeoning field of coupled climate and ecological response modeling. In this paper we describe the computational challenges in species distribution modeling and solutions using scientific workflow systems. We focus on the Software for Assisted Species Modeling (SAHM) a package within VisTrails, an open-source scientific workflow system.

Bulletin of the Technical Committee on Data Engine↗
USGS2014

High-resolution digital elevation model of Mount St. Helens crater and upper North Fork Toutle River basin, Washington, based on an airborne lidar survey of September 2009

The lateral blast, debris avalanche, and lahars of the May 18th, 1980, eruption of Mount St. Helens, Washington, dramatically altered the surrounding landscape. Lava domes were extruded during the subsequent eruptive periods of 1980–1986 and 2004–2008. More than three decades after the emplacement of the 1980 debris avalanche, high sediment production persists in the North Fork Toutle River basin, which drains the northern flank of the volcano. Because this sediment increases the risk of flooding to downstream communities on the Toutle and Cowlitz Rivers, the U.S. Army Corps of Engineers (USACE), under the direction of Congress to maintain an authorized level of flood protection, built a sediment retention structure on the North Fork Toutle River in 1989 to help reduce this risk and to prevent sediment from clogging the shipping channel of the Columbia River. From September 16–20, 2009, Watershed Sciences, Inc., under contract to USACE, collected high-precision airborne lidar (light detection and ranging) data that cover 214 square kilometers (83 square miles) of Mount St. Helens and the upper North Fork Toutle River basin from the sediment retention structure to the volcano's crater. These data provide a digital dataset of the ground surface, including beneath forest cover. Such remotely sensed data can be used to develop sediment budgets and models of sediment erosion, transport, and deposition. The U.S. Geological Survey (USGS) used these lidar data to develop digital elevation models (DEMs) of the study area. DEMs are fundamental to monitoring natural hazards and studying volcanic landforms, fluvial and glacial geomorphology, and surface geology. Watershed Sciences, Inc., provided files in the LASer (LAS) format containing laser returns that had been filtered, classified, and georeferenced. The USGS produced a hydro-flattened DEM from ground-classified points at Castle, Coldwater, and Spirit Lakes. Final results averaged about five laser last-return points per square meter. As reported by Watershed Sciences, Inc., vertical accuracy is 10 centimeters (cm) at the 95-percent confidence interval on bare road surfaces; however, over natural terrain, USGS found vertical accuracy to be 10–50 cm. This USGS data series contains the bare-earth lidar data as 1- and 10-meter (m) resolution Esri grid files. Digital-elevation data can be downloaded (1m_DEM.zip and 10m_DEM.zip), as well as a 1-m resolution hillshade image with pyramids (1m_hillshade.zip). These geospatial data files require geographic information system (GIS) software for viewing.

Washington↗
USGS2018

Climate-related variation in plant peak biomass and growth phenology across Pacific Northwest tidal marshes

The interannual variability of tidal marsh plant phenology is largely unknown and may have important ecological consequences. Marsh plants are critical to the biogeomorphic feedback processes that build estuarine soils, maintain marsh elevation relative to sea level, and sequester carbon. We calculated Tasseled Cap Greenness, a metric of plant biomass, using remotely sensed data available in the Landsat archive to assess how recent climate variation has affected biomass production and plant phenology across three maritime tidal marshes in the Pacific Northwest of the United States. First, we used clipped vegetation plots at one of our sites to confirm that tasseled cap greenness provided a useful measure of aboveground biomass (r 2 = 0.72). We then used multiple measures of biomass each growing season over 20–25 years per study site and developed models to test how peak biomass and the date of peak biomass varied with 94 climate and sea-level metrics using generalized linear models and Akaike Information Criterion (AIC) model selection. Peak biomass was positively related to total annual precipitation, while the best predictor for date of peak biomass was average growing season temperature, with the peak 7.2 days earlier per degree C. Our study provides insight into how plants in maritime tidal marshes respond to interannual climate variation and demonstrates the utility of time-series remote sensing data to assess ecological responses to climate stressors.

Oregon, Washington↗
USGS2021

Long-term ecosystem and biogeochemical research in Loch Vale watershed, Rocky Mountain National Park, Colorado

Loch Vale watershed was instrumented in 1983 with initial support from the National Acid Precipitation Assessment Program to ask whether ecosystems of Rocky Mountain National Park (RMNP) were affected by acidic atmospheric deposition. Research and monitoring activities were expanded in 1991 by the U.S. Geological Survey Water, Energy, and Biogeochemical Budgets program to understand the processes, and their interactions, controlling water, energy, and biogeochemical fluxes. With help from many collaborators we have characterized trends and patterns in atmospheric deposition, climate, and hydrology, including glaciers and other ice features. Instead of acidic deposition, we documented high atmospheric inputs of reactive nitrogen (Nr), and have studied the ecological consequences in soils, surface water, and vegetation. Using paleolimnology, we documented the onset of human-caused change to lake primary producers ca. 1950 in response to increased Nr deposition and warming. Our results provided the basis for the Colorado Nitrogen Deposition Reduction Plan, a state policy that aims to reduce Nr emissions to protect resources in RMNP by 2032. Carbon cycle research revealed mountain wetlands now release more carbon than they store, and respiration and methane flux occurs even during winter through deep snow packs. Trend analyses found export of Nr to be closely tied to atmospheric inputs, but can lag in response to drought. Current research explores consequences of the combination of warming, changes in precipitation dynamics, and atmospheric deposition of Nr and dust on stream and lake CO 2 dynamics, lake biology and trophic state, and soil carbon composition. Dramatic increases in park visitors have prompted studies on the effects of recreational use on water quality. New tools such as remote sensing and high frequency instream water quality sensors are being applied to lake and stream studies. Monitoring, combined with experiments, models, and spatial comparisons is an essential foundation for science-based resource management.

Colorado↗
USGS2021

Riverscape approaches in practice: Perspectives and applications

Landscape perspectives in riverine ecology have been undertaken increasingly in the last 30 years, leading aquatic ecologists to develop a diverse set of approaches for conceptualizing, mapping and understanding ‘riverscapes’. Spatiotemporally explicit perspectives of rivers and their biota nested within the socio-ecological landscape now provide guiding principles and approaches in inland fisheries and watershed management. During the last two decades, scientific literature on riverscapes has increased rapidly, indicating that the term and associated approaches are serving an important purpose in freshwater science and management. We trace the origins and theoretical foundations of riverscape perspectives and approaches and examine trends in the published literature to assess the state of the science and demonstrate how they are being applied to address recent challenges in the management of riverine ecosystems. We focus on approaches for studying and visualizing rivers and streams with remote sensing, modelling and sampling designs that enable pattern detection as seen from above (e.g. river channel, floodplain, and riparian areas) but also into the water itself (e.g. aquatic organisms and the aqueous environment). Key concepts from landscape ecology that are central to riverscape approaches are heterogeneity, scale (resolution, extent and scope) and connectivity (structural and functional), which underpin spatial and temporal aspects of study design, data collection and analysis. Mapping of physical and biological characteristics of rivers and floodplains with high-resolution, spatially intensive techniques improves understanding of the causes and ecological consequences of spatial patterns at multiple scales. This information is crucial for managing river ecosystems, especially for the successful implementation of conservation, restoration and monitoring programs. Recent advances in remote sensing, field-sampling approaches and geospatial technology are making it increasingly feasible to collect high-resolution data over larger scales in space and time. We highlight challenges and opportunities and discuss future avenues of research with emerging tools that can potentially help to overcome obstacles to collecting, analysing and displaying these data. This synthesis is intended to help researchers and resource managers understand and apply these concepts and approaches to address real-world problems in freshwater management.

Biological Reviews↗
USGS2014

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

These remotely sensed, geographically referenced elevation measurements of lidar-derived seamless (bare-earth and submerged) topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida. This project provides highly detailed and accurate datasets for part of Fire Island, New York, acquired pre-Hurricane Sandy on October 27, 2012. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nm) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL-B sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, down-looking red-green-blue (RGB) and infrared (IR) digital cameras, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL-B platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL-B system. The resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed originally in a NASA-USGS collaboration. The exploration and processing of lidar data in an interactive or batch mode is supported using ALPS. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. The Airborne Lidar Processing System (ALPS) is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations. For more information about similar projects, please visit the Lidar for Science and Resource Management Web site.

New York↗
USGS2015

High-resolution digital elevation model of lower Cowlitz and Toutle Rivers, adjacent to Mount St. Helens, Washington, based on an airborne lidar survey of October 2007

The lateral blast, debris avalanche, and lahars of the May 18th, 1980, eruption of Mount St. Helens, Washington, dramatically altered the surrounding landscape. Lava domes were extruded during the subsequent eruptive periods of 1980–1986 and 2004–2008. More than three decades after the emplacement of the 1980 debris avalanche, high sediment production persists in the Toutle River basin, which drains the northern and western flanks of the volcano. Because this sediment increases the risk of flooding to downstream communities on the Toutle and lower Cowlitz Rivers, the U.S. Army Corps of Engineers (USACE), under the direction of Congress to maintain an authorized level of flood protection, continues to monitor and mitigate excess sediment in North and South Fork Toutle River basins to help reduce this risk and to prevent sediment from clogging the shipping channel of the Columbia River. From October 22–27, 2007, Watershed Sciences, Inc., under contract to USACE, collected high-precision airborne lidar (light detection and ranging) data that cover 273 square kilometers (105 square miles) of lower Cowlitz and Toutle River tributaries from the Columbia River at Kelso, Washington, to upper North Fork Toutle River (below the volcano's edifice), including lower South Fork Toutle River. These data provide a digital dataset of the ground surface, including beneath forest cover. Such remotely sensed data can be used to develop sediment budgets and models of sediment erosion, transport, and deposition. The U.S. Geological Survey (USGS) used these lidar data to develop digital elevation models (DEMs) of the study area. DEMs are fundamental to monitoring natural hazards and studying volcanic landforms, fluvial and glacial geomorphology, and surface geology. Watershed Sciences, Inc., provided files in the LASer (LAS) format containing laser returns that had been filtered, classified, and georeferenced. The USGS produced a hydro-flattened DEM from ground-classified points at Castle and Coldwater Lakes. Final results averaged about two laser last-return points per square meter. As reported by Watershed Sciences, Inc., vertical accuracy is 10 centimeters (cm) at the 95-percent confidence interval on bare road surfaces; however, over natural terrain, USGS found vertical accuracy to be 10–50 cm. This USGS data series contains the bare-earth lidar data as 1- and 10-meter (m) resolution Esri grid files. Digital-elevation data can be downloaded (1m_DEM.zip and 10m_DEM.zip), as well as a 1-m resolution hillshade image with pyramids (1m_hillshade.zip). These geospatial data files require geographic information system (GIS) software for viewing.

Washington↗
USGS2008

EAARL topography: Jean Lafitte National Historical Park and Preserve 2006

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) and bare earth (BE) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), 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 Jean Lafitte National Historical Park and Preserve in Louisiana, acquired on September 22, 2006. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

Louisiana↗
USGS2008

EAARL coastal topography — Fire Island National Seashore 2007

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) and bare earth (BE) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Northeast Coastal and Barrier Network, Kingston, RI; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of Fire Island National Seashore in New York, acquired on April 29-30 and May 15-16, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL) was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for pre-survey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

New York↗
USGS2009

EAARL topography - George Washington Birthplace National Monument 2008

These remotely sensed, geographically referenced elevation measurements of Lidar-derived bare earth (BE) and 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 George Washington Birthplace National Monument in Virginia, acquired on March 26, 2008. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL) was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is 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.

Virginia↗