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At least 325 records · Page 18Linked to original sources
USGS2020

Ecological interfaces between land and flowing water: Themes and trends in riparian research and management

This paper provides an overview of past, present and future themes for research and management of riparian zones, often relating to papers within this Wetlands Special Feature. Riparian research expanded in the United States around 1980 with themes that recognized (1) damage from excessive livestock, or (2) damage from river damming and diversion, and (3) the beneficial capacity of riparian buffers to intercept and assimilate nutrients and other water contaminants. Research expanded globally in the 1990s, with themes including (4) plant life history requirements and (5) reliance on fluvial geomorphic dynamics that enable riparian rejuvenation. Resource managers recognized that riparian areas provide (6) rich wildlife habitats (7) along with valued ecosystem services, (8) which encouraged conservation and restoration initiatives, (9) including environmental flow regimes. Floodplains are (10) vulnerable to invasive plants and management has included biocontrol such as for Tamarix in the American Southwest. Into the twenty-first century, (11) climate change is advancing, and riparian ecosystems may be especially impacted due to the compound challenges from increasing water demand and declining summer flows. As an emerging opportunity, (12) while reservoirs submerge floodplain vegetation, reservoir deltas may support compensatory riparian wetlands. (13) Studies increasingly utilize remote sensing tools including satellite imagery, LiDAR and unmanned aircraft systems, and (14) the coordination of large data sets invites digital ecology, including artificial intelligence and machine learning. Since riparian zones are centres for human activities, (15) there are opportunities for citizen science, social media and internet applications, which will increasingly democratize riparian research and management.

Wetlands↗
USGS2024

Observing systems, modeling, and forecasting

Predicting harmful algal blooms (HABs) requires integrating physical, chemical, and biological data collected from observing networks and then assimilating these data into models, which are used to generate forecasts. In 2005, the Harmful Algal Research and Response: A National Environmental Science Strategy 2005-2015 (HARRNESS, 2005) made recommendations on how to improve HAB modeling and forecasting over the next decade. Key HARRNESS recommendations related to sensing, networking, and modeling HABs included: ● Support the development and validation of new and improved technologies for remote cell and toxin detection, and for modeling and forecasting, ● Improve coordination of monitoring/ and modeling efforts, both at national and regional levels, ● Improve the use of networking technologies for monitoring and modeling efforts, ● Conduct sustained time series measurements of the biotic, chemical, and physical environments impacted by HABs, ● Develop food web models on the ecosystem fate and effects of toxins, ● Develop and improve species-specific models that link to physical-biological models. Here we review HAB observing, modeling, and forecasting advances and technologies and recommend research and management priorities for the next decade and beyond. Our report encompasses sensing technologies, sensor networking and data management, models and forecasts, and the paths to operationalize forecasts. Continued improvements of deployable sensors are foundational to improving early warning indicators, models, and forecasts, which are only as good as the underlying data. Sensing technology has advanced considerably in the last decade; for example, more capable fluorometric pigment sensors can track changes in bloom biomass in real-time. Additionally, automated imaging/classifying systems to identify and quantify key harmful algal (HA) taxa are being routinely deployed. However, deployable toxin sensors are available for only some HAB toxins and continue to be identified as a critical need by researchers and managers. As more and improved sensors and technologies become available, the data quality associated with each sensor needs to be assessed. Data quality encompasses the reliability, accuracy, and uncertainty associated with sensor-generated data. These data need to be of known quality so that researchers, managers, and end-users can reliably determine if the information is appropriate for their intended applications. Many of the data quality recommendations from HARRNESS (2005) are still relevant and have been reiterated within the management community. Understanding and documenting data quality, and when applicable, standardizing best practices for sensor use, continue to be recommended.

Report↗
USGS1987

Evaluating evaporation from field crops using airborne radiometry and ground-based meteorological data

Airborne measurements of reflected solar and emitted thermal radiation were combined with ground-based measurements of incoming solar radiation, air temperature, windspeed, and vapor pressure to calculate instantaneous evaporation (LE) rates using a form of the Penman equation. Estimates of evaporation over cotton, wheat, and alfalfa fields were obtained on 5 days during a one-year period. A Bowen ratio apparatus, employed simultaneously, provided ground-based measurements of evaporation. Comparison of the airborne and ground techniques showed good agreement, with the greatest difference being about 12% for the instantaneous values. Estimates of daily (24 h) evaporation were made from the instantaneous data. On three of the five days, the difference between the two techniques was less than 8%, with the greatest difference being 25%. The results demonstrate that airborne remote sensing techniques can be used to obtain spatially distributed values of evaporation over agricultural fields. ?? 1987 Springer-Verlag.

Irrigation Science↗
USGS2025

Predicting aquatic habitat connectivity across watershed boundaries: Implications for interbasin spread of nonindigenous aquatic species.

Understanding habitat connectivity is critical for managing nonindigenous aquatic species (NAS) spread. Dams and watershed boundaries can be impassable to NAS during typical conditions but may become temporarily passable during flooding. The goal of our project was to develop an approach for identifying locations of aquatic connectivity at a fine spatial scale along watershed boundaries using readily available data. To develop this approach, we focused on the potential for range expansion of invasive fish in the United States via possible cross-boundary habitat connections. First, we developed an index using metrics of elevation, watershed size, and geology at regular points along a watershed boundary to stratify points by likelihood of connectivity during high precipitation (>20 mm of precipitation in a 3-day period). We then used a subset of points across a gradient of connectivity likelihoods to gather Landsat-derived observed surface water data and developed a statistical model to predict surface water presence from landscape characteristics. We applied the model throughout the entire watershed boundary to identify locations of hydrologic connectivity during high-water events. The presence of surface water on watershed boundaries was predicted by the interactions between watershed boundary point elevation relative to the minimum adjacent HUC-12 elevations and watershed boundary point elevation relative to neighboring point elevations (marginal R 2 = 0.94). Our approach can be used to identify potential areas of surface water connectivity between watersheds quickly and easily at a fine spatial scale using readily available, remotely sensed data that can inform conservation and management actions across disciplines.

North Dakota, South Dakota↗
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↗
USGS2016

Dynamic reusable workflows for ocean science

Digital catalogs of ocean data have been available for decades, but advances in standardized services and software for catalog search and data access make it now possible to create catalog-driven workflows that automate — end-to-end — data search, analysis and visualization of data from multiple distributed sources. Further, these workflows may be shared, reused and adapted with ease. Here we describe a workflow developed within the US Integrated Ocean Observing System (IOOS) which automates the skill-assessment of water temperature forecasts from multiple ocean forecast models, allowing improved forecast products to be delivered for an open water swim event. A series of Jupyter Notebooks are used to capture and document the end-to-end workflow using a collection of Python tools that facilitate working with standardized catalog and data services. The workflow first searches a catalog of metadata using the Open Geospatial Consortium (OGC) Catalog Service for the Web (CSW), then accesses data service endpoints found in the metadata records using the OGC Sensor Observation Service (SOS) for in situ sensor data and OPeNDAP services for remotely-sensed and model data. Skill metrics are computed and time series comparisons of forecast model and observed data are displayed interactively, leveraging the capabilities of modern web browsers. The resulting workflow not only solves a challenging specific problem, but highlights the benefits of dynamic, reusable workflows in general. These workflows adapt as new data enters the data system, facilitate reproducible science, provide templates from which new scientific workflows can be developed, and encourage data providers to use standardized services. As applied to the ocean swim event, the workflow exposed problems with two of the ocean forecast products which led to improved regional forecasts once errors were corrected. While the example is specific, the approach is general, and we hope to see increased use of dynamic notebooks across the geoscience domains.

Journal of Marine Science and Engineering↗
USGS2022

Giant planet observations in NASA's Planetary Data System

While there have been far fewer missions to the outer Solar System than to the inner Solar System, spacecraft destined for the giant planets have conducted a wide range of fundamental investigations, returning data that continues to reshape our understanding of these complex systems, sometimes decades after the data were acquired. These data are preserved and accessible from national and international planetary science archives. For all NASA planetary missions and instruments the data are available from the science discipline nodes of the NASA Planetary Data System (PDS). Looking ahead, the PDS will be the primary repository for giant planets data from several upcoming missions and derived datasets, as well as supporting research conducted to aid in the interpretation of the remotely sensed giant planets data already archived in the PDS.

Remote Sensing↗
USGS1996

The imaging node for the Planetary Data System

The Planetary Data System Imaging Node maintains and distributes the archives of planetary image data acquired from NASA's flight projects with the primary goal of enabling the science community to perform image processing and analysis on the data. The Node provides direct and easy access to the digital image archives through wide distribution of the data on CD-ROM media and on-line remote-access tools by way of Internet services. The Node provides digital image processing tools and the expertise and guidance necessary to understand the image collections. The data collections, now approaching one terabyte in volume, provide a foundation for remote sensing studies for virtually all the planetary systems in our solar system (except for Pluto). The Node is responsible for restoring data sets from past missions in danger of being lost. The Node works with active flight projects to assist in the creation of their archive products and to ensure that their products and data catalogs become an integral part of the Node's data collections.

Planetary and Space Science↗
USGS2022

Paleoclimatology and paleoceanography perspectives on integrated, coordinated, open, networked (ICON) science

This article is composed of three independent commentaries about the state of Integrated, Coordinated, Open, Networked (ICON) principles (Goldman et al., 2021, https://doi.org/10.1002/essoar.10508554.1 ) in the AGU section paleoclimatology and paleoceanography (P&P), and a discussion on the opportunities and challenges of adopting them. Each commentary focuses on a different topic: (Section 2) Global collaboration, technology transfer and application, reproducibility, and data sharing and infrastructure; (Section 3) Local knowledge, global gain: improving interactions within the scientific community and with locals, indigenous communities, stakeholders, and the public; (Section 4) Field, experimental, remote sensing, and real-time data research and application. P&P projects can better include ICON principles by directly incorporating them into research proposals. A promising way to overcome the challenges of interdisciplinarity and integration is to foster networking, which will advance our research discipline through the application of ICON.

Earth and Space Science↗
USGS2013

Field calibration and validation of remote-sensing surveys

The Optical Collection Suite (OCS) is a ground-truth sampling system designed to perform in situ measurements that help calibrate and validate optical remote-sensing and swath-sonar surveys for mapping and monitoring coastal ecosystems and ocean planning. The OCS system enables researchers to collect underwater imagery with real-time feedback, measure the spectral response, and quantify the water clarity with simple and relatively inexpensive instruments that can be hand-deployed from a small vessel. This article reviews the design and performance of the system, based on operational and logistical considerations, as well as the data requirements to support a number of coastal science and management projects. The OCS system has been operational since 2009 and has been used in several ground-truth missions that overlapped with airborne lidar bathymetry (ALB), hyperspectral imagery (HSI), and swath-sonar bathymetric surveys in the Gulf of Maine, southwest Alaska, and the US Virgin Islands (USVI). Research projects that have used the system include a comparison of backscatter intensity derived from acoustic (multibeam/interferometric sonars) versus active optical (ALB) sensors, ALB bottom detection, and seafloor characterization using HSI and ALB.

Alaska↗
USGS2011

Examination of brine contamination risk to aquatic resources from petroleum development in the Williston Basin

U.S. Geological Survey scientists and cooperating partners are examining the potential risk to aquatic resources (for example, wetlands, streams) by contamination from saline waters (brine) produced by petroleum development in the Williston Basin of Montana, North Dakota, and South Dakota. The primary goals of this study are to provide a science-based approach to assess potential risk of brine contamination to aquatic systems and to help focus limited monitoring and mitigation resources on the areas of greatest need. These goals will be accomplished through field investigations that quantify brine movement and risk assessments using remotely-sensed and other spatial datasets.

Fact Sheet↗
USGS2026

Remote sensing enables basin-scale inventories of coal mine methane

Underground coal mines are important global sources of methane, but emission estimates are uncertain. We show that emission estimates for individual mines from aircraft remote-sensing surveys in the United States agree within 40% with direct measurements used for national emission reporting (IPCC Tier 3 estimate). Such direct measurements are unavailable in most countries, which rely on estimated emission factors (EFs) applied to coal-production rates. We find that EFs from IPCC Tier 1 and the Model for Calculating Coal Mine Methane (MC2M) methods overestimate U.S. emissions 3-fold due to incorrect dependence on mine depth. An IPCC Tier 2 method using measured basin-specific mine gas content agrees with direct emission measurements but does not account for gob well emissions and requires gas content data that are generally unavailable. We show that aircraft remote sensing for a small sample of mines can successfully estimate basin-specific EFs for ventilation shafts and gob wells, enabling estimates of basin- and national-scale emissions. We discuss how the method can be applied with satellite remote sensing to quantify coal emissions worldwide.

Alabama, Colorado, Kentucky, New Mexico, Ohio, Pen↗
USGS1971

Lunar Apennine-Hadley region: Geological implications of earth-based radar and infrared measurements

Recently completed high-resolution radar maps of the moon contain information on the decimeter-scale structure of the surface. When this information is combined with eclipse thermal-enhancement data and with high-resolution Lunar Orbiter photography, the surface morphology is revealed in some detail. A geological history for certain features and subareas can be developed, which provides one possible framework for the interpretation of the findings from the Apollo 15 landing. Frequency of decimeter- and meter-size blocks in and around lunar craters, given by the remote-sensed data, supports a multilayer structure in the Palus Putredinis mare region, as well as a great age for the bordering Apennine Mountains scarp.

Science↗
USGS2025

Prospectivity modeling of the NASA VIPER landing site at Mons Mouton near the Lunar South Pole

We use a high-resolution digital elevation model and a numerical thermal model to produce a variety of inputs for a water-ice prospectivity model for the Volatiles Investigating Polar Exploration Rover (VIPER) landing site. These input data are maps of topography, surface slope, surface aspect, surface curvature, maximum temperature, depth to ice stability, permanently shadowed regions (PSRs), distance to PSRs, and PSR density. This model predicts where water ice is most likely within the top meter of regolith, assuming plausible relationships between ice concentration and the various inputs. The model is designed to be adjusted in near-real time as data are collected during the VIPER mission. As such, it is a tool for both analyzing data from the mission as well as planning operations. Since the current model, at this point, relies only on orbital remote sensing, the final version will also be a tool to extrapolate the VIPER mission results across the lunar poles.

Planetary Science Journal↗
USGS2011

An approach to regional wetland digital elevation model development using a differential global positioning system and a custom-built helicopter-based surveying system

Accurate topographic data are critical to restoration science and planning for the Everglades region of South Florida, USA. They are needed to monitor and simulate water level, water depth and hydroperiod and are used in scientific research on hydrologic and biologic processes. Because large wetland environments and data acquisition challenge conventional ground-based and remotely sensed data collection methods, the United States Geological Survey (USGS) adapted a classical data collection instrument to global positioning system (GPS) and geographic information system (GIS) technologies. Data acquired with this instrument were processed using geostatistics to yield sub-water level elevation values with centimetre accuracy (±15 cm). The developed database framework, modelling philosophy and metadata protocol allow for continued, collaborative model revision and expansion, given additional elevation or other ancillary data.

Florida↗
USGS2015

Assessment of existing and potential landslide hazards resulting from the April 25, 2015 Gorkha, Nepal earthquake sequence

Introduction On April 25, 2015, a large ( M 7.8) earthquake shook much of central Nepal and was followed by a series of M >6 aftershocks, including a M 7.3 event on May 12, 2015. This earthquake and aftershocks, referred to as the “Gorkha earthquake sequence,” caused thousands of fatalities, damaged and destroyed entire villages, and displaced millions of residents. The earthquakes also triggered thousands of landslides in the exceedingly steep topography of Nepal; these landslides were responsible for hundreds of fatalities, and blocked vital roads and trails to affected villages (fig. 1). Landslides caused by the Gorkha earthquake sequence continue to pose both immediate and long-term hazards to villages and infrastructure within the affected region. Some landslides blocked rivers and thus created another potential concern for villages located downstream. With the support of the United States Agency for International Development (USAID), Office of Foreign Disaster Assistance (OFDA), and in collaboration with earthquake-hazard organizations from both the United States (for example, U.S. National Science Foundation Geoengineering Extreme Event Reconnaissance [GEER] Team) and Nepal (International Centre for Integrated Mountain Development [ICIMOD]), the U.S. Geological Survey (USGS) responded to this crisis by providing landslide-hazard expertise to Nepalese agencies and affected villages. In addition to collaborating with an international group of remote-sensing scientists to document the spatial distribution of landsliding in the first few weeks following the earthquake, the USGS conducted in-country landslide hazard assessments for 10 days beginning May 24, 2015. Much of the information obtained by the USGS during their time in Nepal was conveyed directly to affected villages and government agencies as opportunities arose. Upon return to the United States, data organization, interpretation, and synthesis began immediately to provide a rapid assessment of landslide hazards for use by Nepalese agencies during the 2015 summer monsoon (typically occurring from June through September). This report provides a detailed account of assessments performed in May and June 2015 and focuses on valley-blocking landslides because they have the potential to pose considerable hazard to many villages in Nepal. First, we provide a seismological background of Nepal and then detail the methods used for both external and in-country data collection and interpretation. Our results consist of an overview of landsliding extent, a characterization of all valley-blocking landslides identified during our work, and a description of video resources that provide high resolution coverage of approximately 1,000 kilometers (km) of river valleys and surrounding terrain affected by the Gorkha earthquake sequence. This is followed by a description of site-specific landslide-hazard assessments conducted while in Nepal and includes detailed descriptions of five noteworthy case studies. Finally, we assess the expectation for additional landslide hazards during the 2015 summer monsoon season.

Open-File Report↗
USGS2007

Survey report of NOAA Ship McArthur II cruises AR-04-04, AR-05-05 and AR-06-03: habitat classification of side scan sonar imagery in support of deep-sea coral/sponge explorations at the Olympic Coast National Marine Sanctuary

Habitat mapping and characterization has been defined as a high-priority management issue for the Olympic Coast National Marine Sanctuary (OCNMS), especially for poorly known deep-sea habitats that may be sensitive to anthropogenic disturbance. As a result, a team of scientists from OCNMS, National Centers for Coastal Ocean Science (NCCOS), and other partnering institutions initiated a series of surveys to assess the distribution of deep-sea coral/sponge assemblages within the sanctuary and to look for evidence of potential anthropogenic impacts in these critical habitats. Initial results indicated that remotely delineating areas of hard bottom substrate through acoustic sensing could be a useful tool to increase the efficiency and success of subsequent ROV-based surveys of the associated deep-sea fauna. Accordingly, side scan sonar surveys were conducted in May 2004, June 2005, and April 2006 aboard the NOAA Ship McArthur II to: (1) obtain additional imagery of the seafloor for broader habitat-mapping coverage of sanctuary waters, and (2) help delineate suitable deep-sea coral-sponge habitat, in areas of both high and low commercial-fishing activities, to serve as sites for surveying-in more detail using an ROV on subsequent cruises, Several regions of the sea floor throughout the OCNMS were surveyed and mosaicked at 1-meter pixel resolution. Imagery from the side scan sonar mapping efforts was integrated with other complementary data from a towed camera sled, ROVs, sedentary samples, and bathymetry records to describe geological and biological (where possible) aspects of habitat. Using a hierarchical deep-water marine benthic classification scheme (Greene et al. 1999), we created a preliminary map of various habitat polygon features for use in a geographical information system (GIS). This report provides a description of the mapping and groundtruthing efforts as well as results of the image classification procedure for each of the areas surveyed.

Washington↗
USGS2009

Use of land surface remotely sensed satellite and airborne data for environmental exposure assessment in cancer research

In recent years, geographic information systems (GIS) have increasingly been used for reconstructing individual-level exposures to environmental contaminants in epidemiological research. Remotely sensed data can be useful in creating space-time models of environmental measures. The primary advantage of using remotely sensed data is that it allows for study at the local scale (e.g., residential level) without requiring expensive, time-consuming monitoring campaigns. The purpose of our study was to identify how land surface remotely sensed data are currently being used to study the relationship between cancer and environmental contaminants, focusing primarily on agricultural chemical exposure assessment applications. We present the results of a comprehensive literature review of epidemiological research where remotely sensed imagery or land cover maps derived from remotely sensed imagery were applied. We also discuss the strengths and limitations of the most commonly used imagery data (aerial photographs and Landsat satellite imagery) and land cover maps.

Journal of Exposure Science and Environmental Epid↗