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At least 325 records · Page 18Linked to original sources

USGS2026

A methods framework for evaluating measurement consistency across spectrometers for multispectral uncrewed aerial system vegetation mapping applications

The U.S. Geological Survey collects remote sensing data to support national scientific assessments of natural resources, hazards, and landscape change. Spectrometers and spectroradiometers are essential for gathering point-based spectral measurements used in applications such as uncrewed aerial systems (UAS) multispectral image calibration, validation, and analysis. Evaluating how different instruments perform in laboratory and field environments helps determine whether they provide consistent, interoperable measurements. Such verification can expand access to spectral ground data during UAS operations by allowing scientists to use alternative instruments when budgets, logistics, or field conditions limit options. We propose and test a methodological framework for evaluating spectrometers for measurement consistency during UAS multispectral vegetation mapping applications. There are three central evaluation components to the framework: laboratory, field, and relative to UAS multispectral imagery. By evaluating the instruments in both relatively controlled and uncontrolled environments, we thoroughly examine measurement consistency and when/why measurements may differ. We opportunistically selected two instruments for a case study in a coastal marsh setting: a compact laboratory spectrometer we modified for field use and a field-ready spectroradiometer. The instruments produced consistent measurements in both environments. We found differences between the field spectra and UAS spectra that likely reflect the perspectives of ground vs. aerial data and indicate that further radiometric calibration may be needed.

Massachusetts↗

USGS2021

Field methods, quality-assurance, and data management plan for water-quality activities and water-level measurements, Idaho National Laboratory, Idaho

Introduction Water-quality activities and water-level measurements conducted by the U.S. Geological Survey (USGS) Idaho National Laboratory (INL) Project Office coincide with the USGS mission of appraising the quantity and quality of the Nation’s water resources. The activities are conducted in cooperation with the U.S. Department of Energy’s (DOE) Idaho Operations Office. Results of water-quality and hydraulic head investigations are presented in various USGS publications or in refereed scientific journals, and the data are stored in the National Water Information System (NWIS) database. The results of the studies are used by researchers, regulatory and managerial agencies, and civic groups. In its broadest sense, “quality assurance” refers to doing the job right the first time. It includes the functions of planning for products, review and acceptance of the products, and an audit designed to evaluate the system that produces the products. Quality control and quality assurance differ in that quality control ensures that things are done correctly given the “state-of-the-art” technology, and quality assurance ensures that quality control is maintained within specified limits.

Idaho↗

USGS2006

National Geomagnetism Program: Current Status & Five-Year Plan, 2006-2010

Executive Summary: The U.S. Geological Survey's Geomagnetism Program serves the scientific community and the broader public by collecting and distributing magnetometer data from an array of ground-based observatories and by conducting scientific analysis on those data. Preliminary, variational time-series can be collected and distributed in near-real time, while fully calibrated, absolute time-series are distributed after processing. The data are used by the civilian and military parts of the Federal Government, by private industry, and by academia, for a wide variety of purposes of both immediately practical importance and long-term scientific interest, including space-weather diagnosis and related hazard mitigation, mapping of the magnetic field and measurement of its activity, and research on the nature of the Earth's interior and the near-Earth space environment. This document reviews the current status of the Program, in terms of its situation within the Government and within the scientific community; summarizes the Program's operations, its staffing situation, and its facilities; describes the diversity of uses of Program magnetometer data; and presents a plan for the next 5 years for enhancing the Program's data-based services, developing products, and conducting scientific research.

Open-File Report↗

USGS2021

Can Landsat 7 preserve its science capability with a drifting orbit?

Since 2017, the orbit of Landsat 7 has drifted outside its nominal mission requirement toward an earlier acquisition time because of limited onboard fuel resources. This makes quantitative analyses from Landsat 7 data potentially unreliable for many scientific studies. To comprehensively understand the effect of ongoing (2018–2020) orbit drift on Landsat 7 data, we compared surface reflectance and Top-Of-Atmosphere (TOA) reflectance of growing season observations (July 1 ± 30 days) from Landsat 7 with orbit drift and Landsat 8 with nominal orbit using a total of 10,000 randomly selected Northern Hemisphere (0–75 0 N) terrestrial pixels. To evaluate the future (2021–2023) effect of Landsat 7's orbit drift, we analyzed the historical Northern Hemisphere terrestrial growing season Earth Observing-1 (EO-1) TOA reflectance images, which shared a similar orbit drift as Landsat 7 but occurred much earlier. Results suggest that Landsat 7's orbit drift has already led to a general decrease in surface reflectance and TOA reflectance in 2019 and 2020, with a limited impact (overall reflectance changes less than 0.007). The influence of orbit drift is more substantial for the two shortwave infrared (SWIR) bands and the near infrared (NIR) band, but less for the three visible bands (i.e., Red, Green, and Blue). The Normalized Difference Vegetation Index (NDVI), derived from either surface reflectance or TOA reflectance, increased less than 0.003 in 2020. According to the historical EO-1 TOA reflectance data, we estimate that the effect of Landsat 7's orbit drift will be much more dramatic in the future (e.g., the NIR and SWIR bands will decrease more than 0.015 since July 1, 2021), and for different land cover types, the effects of orbit drift are also quite different. To reduce this influence, we examined the c-factor Bidirectional Reflectance Distribution Function (BRDF) normalization approach to correct the orbit drift impact for Landsat 7 surface reflectance data collected between 2019 and 2020. We found that the c-factor BRDF can reduce the data difference substantially, but how this approach works after Landsat 7's orbit drifts further still requires more investigation. Therefore, we determined that Landsat 7 can preserve its science capability until 2020, but will be less reliable for remote sensing applications that need accurate absolute radiometric values after 2020. Correction methods such as c-factor BRDF could be a potential viable approach to maintain its science capability going forward.

Science of Remote Sensing↗

USGS2019

Fluvial sedimentary history of Arlington Canyon, Channel Islands National Park, California

Arlington Canyon, in the northwest part of Santa Rosa Island, Channel Islands National Park, California, has been the setting for important scientific discoveries over the past half century, including the oldest human remains in North America, several vertebrate fossil sites, and purported evidence of a catastrophic extinction event at the end of the Pleistocene. The canyon is filled with alluvial sediments that date to between 16.4 and 1.1 ka (thousands of calibrated years before present), representing accumulation that occurred primarily in response to rising sea levels during the late Pleistocene and Holocene. The deposits are laterally discontinuous, exhibit a high degree of sedimentary complexity, and contain evidence of past climates and environments, including fossil bones, burned plant macrofossils, and invertebrate microfossils. Here, we show that it is critical to view the observations, data, and conclusions of scientific studies conducted in the canyon within this larger context so that localized facets of the spatially and temporally extensive alluvial deposits are not misinterpreted or misrepresented. By improving the baseline understanding of processes and drivers of sediment accumulation in Arlington Canyon, we hope to offer a solid foundation and better underpinning for future archeological, paleontological, and geochemical studies here and throughout the northern Channel Islands.

California↗

USGS2022

Asking nicely: Best practices for requesting data

Compiling disparate datasets into publicly available composite databases helps natural resource communities explore ecological trends and effectively manage across spatiotemporal scales. Though some studies have reported on the database construction phase, fewer have evaluated the data acquisition and distribution process. To facilitate future data sharing collaborations, Louisiana State University surveyed data providers and requestors to understand the characteristics of effective data requests and sharing. Data providers were largely U.S. natural resource agency personnel, and they reported that unclear data requests, privacy issues, and rigid timelines and formats were the greatest barriers toward providing data, but that they were motivated by improving science and collaboration. Data requestors identified challenges such as evolving needs, standardization issues, and insufficient resources (time and funding) as barriers to compiling data for these types of efforts. In a time of big data, open access, and collaboration, significant scientific advances can be made with effective requests and inclusion of data sets into larger and more powerful databases.

Ecological Indicators↗

USGS2022

Contaminants of emerging concern in the Great Lakes: Science to inform management practices for protecting the health and integrity of wildlife populations from adverse effects: GLRI action plan I, focus area 1, goal 5

Executive Summary: Under Action Plan I (2010-2014) of the Great Lakes Restoration Initiative (GLRI), Federal and Academic partners began an investigation of the presence and distribution of contaminants of emerging concern (CECs) in the Great Lakes and potential impacts on fish and wildlife. The term CECs is applied to a broad range of chemicals that are currently in use but for which we currently lack good understanding of whether fish, wildlife, or humans are being exposed and/or whether negative health or environmental effects are expected if exposure occurs. Pharmaceuticals, personal care products, flame retardants, many current use pesticides, and poly- and perfluorinated chemicals are some well-known groups of CECs, but there is no definitive or comprehensive list that can be used to support the management of CECs to reduce impacts on the Great Lakes ecosystem. Four overarching goals were identified for this collaborative investigation: 1. Evaluate the sources, occurrence, and distribution of CECs across the Great Lakes Basin. 2. Examine associations between the distribution of CECs and land-use patterns. 3. Review both scientific literature and field-generated data to determine the potential for CECs to cause adverse effects on Great Lakes fish and wildlife populations. 4. Develop efficient strategies to survey and/or monitor for threats that CECs may pose in order to take effective management actions before those threats evolve into large scale impacts on Great Lakes ecosystems or the services they provide. Achievement of these goals ensures progress towards Focus Area 1: Toxic Substances and Areas of Concern from GLRI Action Plan I, Goal 5: “ The health and integrity of wildlife populations and habitat are protected from adverse chemical and biological effects associated with the presence of toxic substances in the Great Lakes Basin ”. This large-scale research effort was comprised of individual and collaborative projects from multiple federal agencies and academic institutions, involving over 85 investigators, and overseen by the U.S. Environmental Protection Agency (EPA) Region 5, Great Lakes National Program Office. Partners include the United States Geological Survey, the National Oceanic and Atmospheric Administration, U.S. Fish and Wildlife Service, Saint Cloud State University, the U.S. EPA Office of Research and Development, and the U.S. Army Corps of Engineers. Key findings: 1. Contaminants of emerging concern were found throughout the monitored Great Lakes tributaries, but types and concentrations vary in association with regional land use. CECs were detected in nearly all samples collected. The type and concentration of the specific contaminants detected varied considerably among field sites and in association with land use type, such as urban, agricultural, wetland, 2 or forest. Contaminants were detected in the water column, sediment, and tissues of all species surveyed in the current work (mussels, aquatic insects, fish, and insect-eating birds). 2. There were over 20 contaminants for which CEC concentrations approached or exceeded those reported to cause toxicity in laboratory experiments. This was based on detection in water, sediments and or biota at one or more field sites. These contaminants represent compounds that warrant further investigation and monitoring with respect to potential impacts in certain areas of the Great Lakes basin. Based on the present investigation, compounds of greatest concern include: polycyclic aromatic hydrocarbons, associated with oil-based products and combustion of organic matter; atrazine, an herbicide; dichlorvos, an insecticide; and ibuprofen and venlafaxine, both pharmaceuticals. 3. Results suggest that mixtures of CECs presently found in most Great Lakes tributary locations surveyed may elicit subtle biological effects, but likely are not, alone, causing obvious detriment to current communities of fish and wildlife. CECs detected in the Great Lakes were associated with subtle biological effects like changes in gene expression, altered circulating glucose, etc. in both wild-caught and laboratory-reared organisms. These effects were generally not indicative of reproductive failure or mortality. However, the effects may have more serious implications when combined with other sources of stress like habitat degradation, changing climate conditions, and competition with invasive species. Due to limited historical data, it is unknown whether severe CEC-related impacts have already affected aquatic communities in waterbodies that have received long-term inputs of these contaminants. Likewise, under Action Plan I, biological effects were not necessarily evaluated at the sites where CEC concentrations exceeding laboratory toxicity thresholds were detected. As a result, strategic, ongoing surveillance and monitoring of CECs is warranted. This collaborative investigation resulted in new tools, approaches, and data that can be used to inform and support the management of CECs to reduce their impacts on Great Lakes natural resources. The following products of this research effort are available through https://communities.geoplatform.gov/glri/ or by contacting the investigators (see technical chapters found in Appendices A-F): 1. Database of CEC occurrence and concentrations in US tributary streams. The database includes CEC detections in water, sediment, and fish and wildlife tissues, and represents the most comprehensive survey of CECs in the Great Lakes Region. 2. Synopses of results and key findings. Integrated summaries of results, conclusions, and management implications of the CEC research are available through reports, topical fact sheets, and presentations. 3. Technical publications: This collaborative research effort has resulted in over 50 peer-reviewed publications, agency reports, and data releases that can be of use to resource managers, the scientific community, and members of the public. 4. Innovative tools. Innovative monitoring devices, sampling equipment, conceptual frameworks, and software applications were developed over the course of this 3 research. These tools are transferable to stakeholders via internet accessibility or via specifications, instructions, and demonstration detailed in technical publications. Hypotheses to guide CECs research under Action Plan II. Findings from 2010-2014 were used to guide further research in 2015-2018 for basin-wide surveillance of CECs and for sites warranting further study of potential biological impacts of CECs. Additional surveillance included both evaluation of additional classes of contaminants and expanded lists for chemical classes shown to be of greatest concern. Mixtures of some of the most frequently detected contaminants were also tested in laboratory studies to understand whether long term exposures to multiple contaminants may result in effects not evident from uncontrolled, short-term field experiments.

Great Lakes↗

USGS2025

Methodology for compilation of previously published contour data showing the altitude of the base of Dakota Sandstone on the Colorado Plateau, Arizona, Colorado, New Mexico, and Utah

Structure contours and other geologic information from numerous published geologic maps were digitized and compiled into a digital dataset showing the configuration of a single stratigraphic datum, the base of the Dakota Sandstone and its equivalents across the Colorado Plateau. The principal maps compiled in digital form are a series of 1:250,000-scale 1 degree (°) × 2° quadrangle maps published by the U.S. Geological Survey, augmented by other geologic maps published at various map scales. The compiled digital dataset contains geologic map polygons of the Dakota Sandstone and regional stratigraphic equivalents, the location of faults and fold axes, structure contour lines that define the altitude of the base of the unit and bedding orientation data computed from the structure contour lines. This report provides the scientific rationale for compilation of these data and describes the compilation methodology for each of the data elements. This report provides an extended description of the data compilation in a companion U.S. Geological Survey digital data release of spatial data and attributes associated with the contoured surface and associated geologic data layers.

Arizona, Colorado, New Mexico, Utah↗

USGS2017

Capturing change: the duality of time-lapse imagery to acquire data and depict ecological dynamics

We investigate the scientific and communicative value of time-lapse imagery by exploring applications for data collection and visualization. Time-lapse imagery has a myriad of possible applications to study and depict ecosystems and can operate at unique temporal and spatial scales to bridge the gap between large-scale satellite imagery projects and observational field research. Time-lapse data sequences, linking time-lapse imagery with data visualization, have the ability to make data come alive for a wider audience by connecting abstract numbers to images that root data in time and place. Utilizing imagery from the Platte Basin Timelapse Project, water inundation and vegetation phenology metrics are quantified via image analysis and then paired with passive monitoring data, including streamflow and water chemistry. Dynamic and interactive time-lapse data sequences elucidate the visible and invisible ecological dynamics of a significantly altered yet internationally important river system in central Nebraska.

Nebraska↗

USGS1979

Compilation of strong-motion records from the August 6, 1979 Coyote Lake earthquake

This report represents a joint effort by the OSMS, CDMG and the U.S. Geological Survey (USGS). The report summarizes all strong-motion accelerograph records recovered from the August 6, 1979 Coyote Lake earthquake. The majority of accelerograms were recorded at stations operated by the OSMS-CDMG and USGS; the latter organization operates a network of instruments that belong to various federal agencies. Documentation of strong-motion data for the Coyote Lake earthquake best serves the scientific community if presented as a single data set. Reasonable precautions have been taken to ensure the accuracy of the material presented; however, the preliminary nature of the report makes it subject to change upon further verification. Measurements and scalings of the accelerograms are not recommended for use in detailed studies because of possible photo copy distortions during reproduction. A report on the processed data from close-in stations is in preparation and will be issued in the near future.

California↗

USGS2011

Making United States Integrated Ocean Observing System (U.S. IOOS) inclusive of marine biological resources

An important Data Management and Communication (DMAC) goal is to enable a multi-disciplinary view of the ocean environment by facilitating discovery and integration of data from various sources, projects and scientific domains. United States Integrated Ocean Observing System (U.S. IOOS) DMAC functional requirements are based upon guidelines for standardized data access services, data formats, metadata, controlled vocabularies, and other conventions. So far, the data integration effort has focused on geophysical U.S. IOOS core variables such as temperature, salinity, ocean currents, etc. The IOOS Biological Observations Project is addressing the DMAC requirements that pertain to biological observations standards and interoperability applicable to U.S. IOOS and to various observing systems. Biological observations are highly heterogeneous and the variety of formats, logical structures, and sampling methods create significant challenges. Here we describe an informatics framework for biological observing data (e.g. species presence/absence and abundance data) that will expand information content and reconcile standards for the representation and integration of these biological observations for users to maximize the value of these observing data. We further propose that the approach described can be applied to other datasets generated in scientific observing surveys and will provide a vehicle for wider dissemination of biological observing data. We propose to employ data definition conventions that are well understood in U.S. IOOS and to combine these with ratified terminologies, policies and guidelines.

Conference Paper↗

USGS2012

Maximizing the utility of monitoring to the adaptive management of natural resources

Data collection is an important step in any investigation about the structure or processes related to a natural system. In a purely scientific investigation (experiments, quasi-experiments, observational studies), data collection is part of the scientific method, preceded by the identification of hypotheses and the design of any manipulations of the system to test those hypotheses. Data collection and the manipulations that precede it are ideally designed to maximize the information that is derived from the study. That is, such investigations should be designed for maximum power to evaluate the relative validity of the hypotheses posed. When data collection is intended to inform the management of ecological systems, we call it monitoring. Note that our definition of monitoring encompasses a broader range of data-collection efforts than some alternative definitions – e.g. Chapter 3. The purpose of monitoring as we use the term can vary, from surveillance or “thumb on the pulse” monitoring (see Nichols and Williams 2006), intended to detect changes in a system due to any non-specified source (e.g. the North American Breeding Bird Survey), to very specific and targeted monitoring of the results of specific management actions (e.g. banding and aerial survey efforts related to North American waterfowl harvest management). Although a role of surveillance monitoring is to detect unanticipated changes in a system, the same result is possible from a collection of targeted monitoring programs distributed across the same spatial range (Box 4.1). In the face of limited budgets and many specific management questions, tying monitoring as closely as possible to management needs is warranted (Nichols and Williams 2006). Adaptive resource management (ARM; Walters 1986, Williams 1997, Kendall 2001, Moore and Conroy 2006, McCarthy and Possingham 2007, Conroy et al. 2008a) provides a context and specific purpose for monitoring: to evaluate decisions with respect to achievement of specific management objectives; and to evaluate the relative validity of predictive system models. This latter purpose is analogous to the role of data collection within the scientific method, in a research context.

Book chapter↗

USGS2022

U.S. Geological Survey Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST)—Information Management Technology Plan

Introduction More than 840 publications, 575 data releases, and 330 project web pages from the U.S. Geological Survey (USGS) pertain to the Colorado River Basin. Limited interconnections between Colorado River Basin publications, data, and web pages restrict the ability to synthesize and interpret scientific resources. Currently, these pieces are spread across multiple isolated locations, internal systems, data repositories, and local offices. The increasing size, complexity, and diversity of Colorado River Basin data creates additional need for integration. These different data types—including discrete, continuous, aerial, remote sensing, geophysical, geospatial, and other types in varied formats—are collected over numerous time and space scales and require data-intensive science and technology to integrate. Information management technology (IMT) resources are enterprise capabilities that the USGS workforce can leverage at multiple scales with consistent interoperable solutions to better facilitate integrated science. The USGS 21st Century Science Strategy directs the USGS to establish enterprise IMT capabilities that support integrated work through interoperable software and database solutions at multiple scales. This Information Management Technology Plan identifies nine steps to leverage new and existing technologies, data, models, and scientific knowledge to support integrated science projects conducted across the Colorado River Basin. These steps are transferable to integrated-science studies in other locations.

Arizona, Colorado, Nevada, New Mexico, Utah, Wyomi↗

USGS2007

Observatories, program in USA

The Geomagnetism Program of the US Geological Survey has, for over a century now, monitored the Earth's magnetic field through a network of magnetic observatories and conducted scientific analysis on the data collected. The program traces its origins to the Reorganization Act of 1843, in which Congress authorized the creation of a coastal survey agency, as part of the Treasury Department, that was responsible for, among other things, geomagnetic surveys. The 19th century saw the establishment of relatively short‐lived magnetic stations, as well as the production of declination maps for the United States and territories. With the purchase of Alaska, coastal surveys became an increasingly higher priority, and in 1889 the Coast and Geodetic Survey, with a Division of Terrestrial Magnetism, was established. The first essentially permanent geomagnetic observatories were established under the Division's leadership of Dr. Louis A. Bauer and Dr. John A. Fleming: Cheltenham Maryland Observatory was established in 1900, subsequently moved to the Fredericksburg site in 1956; Sitka Alaska Observatory was established in 1901 and that of Honolulu Hawaii in 1902. Soon after these observatories became operational, it was found that the Sitka and Honolulu magnetometers were also sensitive to local earthquakes, and so seismometers were installed at the sites. In part, because of this colocation of instruments, the magnetic and seismological programs in the Coast and Geodetic Survey were united in 1925 under the Division of Geomagnetism and Seismology. Over the years, the Geomagnetism Program has evolved in response to the needs of the United States and in response to changes in the nation's various federal agencies. In 1903 the Coast and Geodetic Survey was transferred to the newly organized Department of Commerce, and in 1970 the survey became part of the National Oceanic and Atmospheric Administration (NOAA). In 1973, the US Geological Survey of the Department of the Interior assumed responsibility for the nation's Geomagnetism and Seismology programs.

Book chapter↗

USGS2022

Trends in volcano seismology: 2010 to 2020 and beyond

Volcano seismology has been fundamental to our current understanding of crustal magma migration and eruption. The increasing availability of portable seismic networks with the creative use of seismic sources and ambient noise has led to a better understanding of the volcanic structure of many volcanoes and is producing increasingly detailed images of the volcanic subsurface. The past decade (2010-2020) has seen advances in our understanding of seismic sources under and surrounding volcanoes through precise locations, and through analysis of source mechanisms from seismic signals that are more varied and smaller in magnitude, reaching beyond traditional techniques. In tandem with continued research on fundamental physics-based understanding of volcano-seismic sources, new advances in computational analyses including machine learning methods will push our understanding of volcanic processes into the future. Incorporation of multidisciplinary geophysical observations (especially infrasound) has become commonplace, and our understanding of infrasound propagation and sources will feed back into our ability to monitor ongoing eruptions and surficial mass movements. Open-source codes will permit widespread evaluation and adoption of new methodologies for volcano-seismic analysis and inversion. Combined with quantitative and conceptual source models using improved structural constraints, these new methodologies will better characterize the range of volcano-seismic signal evolution scenarios and hold promise for creating better short-term forecasts. Finally, permanent instrumentation is available on an expanding range of volcanoes, and open data policies are increasingly making these data available to the scientific community in near real time.

Bulletin of Volcanology↗

USGS1978

Mars synthetic topographic mapping

Topographic contour maps of Mars are compiled by the synthesis of data acquired from various scientific experiments of the Mariner 9 mission, including S-band radio-occulation, the ultraviolet spectrometer (UVS), the infrared radiometer (IRR), the infrared interferometer spectrometer (IRIS) and television imagery, as well as Earth-based radar information collected at Goldstone, Haystack, and Arecibo Observatories. The entire planet is mapped at scales of 1:25,000,000 and 1:25,000,000 using Mercator, Lambert, and polar stereographic map projections. For the computation of map projections, a biaxial spheroid figure is adopted. The semimajor and semiminor axes are 3393.4 and 3375.7 km, respectively, with a polar flattening of 0.0052. For the computation of elevations, a topographic datum is defined by a gravity field described in terms of spherical harmonics of fourth order and fourth degree combined with a 6.1-mbar occulation pressure surface. This areoid can be approximated by a triaxial ellipsoid with semimajor axes of A = 3394.6 km and B = 3393.3 km and a semiminor axis of C = 3376.3 km. The semimajor axis A intersects the Martian surface at longitude 105°W. The dynamic flattening of Mars is 0.00525. The contour intercal of the maps is 1 km. For some prominent features where overlapping pictures from Mariner 9 are available, local contour maps at relatively larger scales were also compiled by photogrammetric methods on stereo plotters.

Icarus↗

USGS2026

Revisiting chlorophyll a thresholds for San Francisco Bay: Insights from observations of phytoplankton molecular abundance

Harmful Algal Blooms (HABs) are a hazard for coastal environments worldwide; identifying screening thresholds of chlorophyll- a (chl- a) associated with increased risk of HABs is a management priority. Molecular surveillance of coastal phytoplankton and bivalve biotoxins could be used to link chl- a with HAB risk, but requires an understanding of whether the HAB risks increase uniformly as chl-a rises, or whether some taxa are disproportionately favored, and if these relationships vary by season. In this study, we present a novel use of molecular abundance data to investigate the scientific bases for estuarine chl- a thresholds protective against HABs. In San Francisco Bay (SFB), California, the relationship between molecular relative abundance (as measured by 18S metabarcoding) of nine different HAB taxa, absolute quantitative polymerase chain reaction (qPCR) abundance, and mussel toxin concentrations of a subset of the taxa were investigated for thresholds as a function of increasing chl- a . Our results show most HAB taxa did not increase in absolute or relative abundance during SFB’s spring bloom interval, when chl- a levels were highest (>10 µg/L) but the assemblage was dominated by non-harmful diatoms. However, several flagellated, mixotrophic taxa did increase above their molecular baseline in fall, and the combined probability of any HAB occurring above baseline was elevated when chl- a reached ∼4.6 µg/L in the fall. This work demonstrates the promise of molecular approaches in disentangling the seasonally complex interplay between stressors and phytoplankton/HAB community responses and has the potential to provide clearer, more cost-effective monitoring and mitigation strategies for managers.

California↗

USGS2011

A simple and effective method for filling gaps in Landsat ETM+ SLC-off images

The scan-line corrector (SLC) of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor failed in 2003, resulting in about 22% of the pixels per scene not being scanned. The SLC failure has seriously limited the scientific applications of ETM+ data. While there have been a number of methods developed to fill in the data gaps, each method has shortcomings, especially for heterogeneous landscapes. Based on the assumption that the same-class neighboring pixels around the un-scanned pixels have similar spectral characteristics, and that these neighboring and un-scanned pixels exhibit similar patterns of spectral differences between dates, we developed a simple and effective method to interpolate the values of the pixels within the gaps. We refer to this method as the Neighborhood Similar Pixel Interpolator (NSPI). Simulated and actual SLC-off ETM+ images were used to assess the performance of the NSPI. Results indicate that NSPI can restore the value of un-scanned pixels very accurately, and that it works especially well in heterogeneous regions. In addition, it can work well even if there is a relatively long time interval or significant spectral changes between the input and target image. The filled images appear reasonably spatially continuous without obvious striping patterns. Supervised classification using the maximum likelihood algorithm was done on both gap-filled simulated SLC-off data and the original "gap free" data set, and it was found that classification results, including accuracies, were very comparable. This indicates that gap-filled products generated by NSPI will have relevance to the user community for various land cover applications. In addition, the simple principle and high computational efficiency of NSPI will enable processing large volumes of SLC-off ETM+ data.

Remote Sensing of Environment↗