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E. Terrence Slonecker

Publications and source records attributed to E. Terrence Slonecker.

At least 19 recordsLinked to original sources

Demonstration, validation, and application of hyperspectral microscopy for the collection of cyanobacterial spectral signatures

Cyanobacterial and other algal blooms are an environmental concern in waterbodies worldwide. While these blooms are a nuisance for recreational activities, they can also be harmful to human and wildlife health when the algae produce and release toxins. Algal community composition can be monitored and analyzed by acquiring hyperspectral images that provide information on various photosynthetic and accessory pigments. Validated, traceable measurements are needed to compare data collected by different hyperspectral instruments. In this proof-of-concept study, we detail the development and validation of a custom hyperspectral microscopy imaging system and assess whether this technology can differentiate between cyanobacteria genera based on differences in their reflectance characteristics. As not all cyanobacteria produce toxins, the ability to distinguish among taxa could be used to identify potential toxin-producers and guide field sampling and further research. Spectral characterization of these taxa contributes to remote sensing efforts to characterize and identify cyanobacterial genera at larger spatial scales.

Oregon

Interdisciplinary science approach for harmful algal blooms (HABs) and algal toxins—A strategic science vision for the U.S. Geological Survey

Executive Summary Algal blooms in water, soils, dusts, and the environment have captured national attention because of concerns associated with exposure to algal toxins for humans and animals. Algal blooms naturally occur in all surface-water types and are important primary producers for aquatic ecosystems. However, excessive algae growth can be associated with many harmful effects ranging from aesthetic to toxicity concerns, so this excessive growth is commonly called a harmful algal bloom (HAB). Ecological imbalances that can lead to excessive algal growth, such as increased nutrient availability to waterbodies from natural and anthropogenic sources, are well documented in scientific literature. On the other hand, fundamental scientific understandings of environmental causes and controls leading to algal toxin production, environmental exposures, and adverse health outcomes for humans and animals could benefit from more attention by U.S. Geological Survey (USGS) scientists. Understanding when, why, and how the toxin is produced by individual algal cells or communities and why the toxin is released to the surrounding waterbody requires fundamental research to determine a toxin’s role, whether it provides competitive advantage or if other potential reasons exist for toxin production and release, such as secretions from otherwise benign biological processes. This research will require groundbreaking scientific discovery about underlying biologic and abiotic (non-living) processes commonly complicated by local variation in land use, microbial species composition, and ecosystem structure of the surrounding watershed. Although underlying processes by which HABs form may be similar from one waterbody to another, individual waterbodies may be controlled by local factors for HAB development and toxin production that are unique to the watershed. Consequently, many fundamental science gaps exist that prevent informed mitigation and prevention of toxic HAB events. There are also gaps in understanding local conditions that control algal growth unique to specific watersheds. Addressing these science gaps is needed to inform evidence-based decisions that protect human and animal health and that reduce recreational and socioeconomic losses.

Circular

Using Global Fiducials Library high-resolution imagery, commercial satellite imagery, Landsat and Sentinel satellite imagery, and aerial photography to monitor change at East Timbalier Island, Louisiana, 1953–2021

This report documents morphological changes between 1953 and 2021 at East Timbalier Island, Louisiana, a Gulf of Mexico barrier island. East Timbalier Island, which was located west of the Mississippi River Delta at the front of Timbalier Bay, was one of the most rapidly changing barrier islands on Earth. Since aerial photographs were initially taken in 1953, the Island steadily lost length and area, finally eroding away by early summer 2021. After major storm events, sediment eroded from the Island and migrated hundreds of meters north. In August 1992, Hurricane Andrew breached the Island in several places, resulting in increased erosion and land loss. Until it completely eroded away, the Island underwent a cycle of washovers, vegetation removal, breaching, and erosion with sediment transport to the north. Satellite imagery shows that three such cycles occurred between 1992 and 2017, despite the partial restoration of the Island between 1998 and 2000. Each cycle increased the distance between the Island and the mainland to the east, reducing both the sediment supply from the east and the protection that Timbalier Bay and the adjacent coastal lands received from the barrier island. Previously, the U.S. Geological Survey (USGS) National Civil Applications Center used 1-meter resolution imagery archived at the USGS Global Fiducials Library (GFL), collected between 2000 and 2010 by U.S. National Imaging Systems, to monitor the changes at the Island. New research expands this study retrospectively and prospectively using aerial photography collected from 1953 to 2012 and in 2020; declassified imagery collected in 1962, 1972, and 1975; DigitalGlobe satellite imagery collected since 2004; Landsat satellite imagery collected since 1972; Sentinel–2 satellite imagery collected since 2015; and GFL imagery collected from 1991 to 2020.

Louisiana

Spectral mixture analysis for surveillance of harmful algal blooms (SMASH): A field-, laboratory-, and satellite-based approach to identifying cyanobacteria genera from remotely sensed data

Algal blooms around the world are increasing in frequency and severity, often with the possibility of adverse effects on human and ecosystem health. The health and economic impacts associated with harmful algal blooms, or HABs, provide compelling rationale for developing new methods for monitoring these events via remote sensing. Although concentrations of chlorophyll- a and key pigments like phycocyanin are routinely estimated from satellite images and used to infer algal or cyanobacterial cell counts, current methods are unable to provide information on the taxonomic composition of a bloom. This study introduced a new approach capable of differentiating among genera based on their reflectance characteristics: Spectral Mixture Analysis for Surveillance of HABs, or SMASH. The foundation of SMASH is a multiple endmember spectral mixture analysis (MESMA) algorithm that takes a library of cyanobacteria endmembers and a hyperspectral image as input and estimates the fractional abundance of each genus, plus water, on a per-pixel basis. Importantly, we assume that the water column consists of only pure water and cyanobacteria, implying that our linear spectral unmixing models do not account for other optically active constituents such as suspended sediment and colored dissolved organic matter (CDOM). We used reflectance spectra for 12 genera measured under a microscope to populate an algal spectral library and applied the SMASH workflow to satellite images from four waterbodies across the United States. Normalized spectral separability scores indicated that the 12 genera were distinct from one another and the MESMA algorithm reproduced known input fractions for simulated mixtures that included all pairwise combinations of genera and water. We used Upper Klamath Lake as an example to illustrate data products generated via SMASH: maps of the normalized difference chlorophyll index and cyanobacterial index, a MESMA-based classification of algal genera, fraction images for each endmember, and a root mean square error (RMSE) image that summarizes uncertainty. For Upper Klamath Lake, these outputs highlighted a complex algal bloom featuring several genera, primarily Aphanizomenon , and intricate spatial patterns associated with gyres. The maximum RMSE constraint imposed on the MESMA algorithm provided a means of avoiding false positive detection of genera not present in a waterbody but must not be set so low as to leave much of an image unclassified in cases where genera included in the library are present. Comparison of endmember fractions with relative biovolumes calculated from field samples indicated that taxonomic information from SMASH was consistent with field observations. For example, the algorithm successfully identified Microcystis in Owasco Lake but avoided misclassifying Asterionella , a genus not yet included in our library, in Detroit Lake. This proof-of-concept investigation demonstrates the potential of SMASH to enhance our understanding of algal blooms, particularly with respect to their spatial and temporal dynamics.

New York, Oregon, Texas

A comparison of hydrocarbon-related landscape disturbance patterns along the New York-Pennsylvania border, 2004–2013

Executive Summary The New York-Pennsylvania area has a long history of hydrocarbon extraction, and the addition of shale gas extraction methods contributes to landscape disturbance borne by previously developed oil and non-shale gas resources. The main unconventional extraction method used to extract shale gas from the Marcellus Shale located in New York and Pennsylvania is hydraulic fracturing, or “fracking,” although other conventional methods are used extensively. All forms of hydrocarbon extraction disturb the surrounding landscape to some extent, primarily in the form of land clearance and degradation, road construction, and pipeline development, although the effects of these disturbances are not fully understood. In this study, landscape-change metrics and indicators are used to analyze change in a 10-county region along the New York-Pennsylvania border—the New York counties of Allegany, Steuben, Chemung, Tioga, and Broome, and the Pennsylvania counties of McKean, Potter, Tioga, Bradford, and Susquehanna. This 10-county region was selected due to the differences in policies between the States of New York and Pennsylvania. While fracking occurred extensively in Pennsylvania over the past 10 years or more, the State of New York issued a temporary moratorium against hydraulic fracturing in 2010—citing repercussions that might affect air quality, water quality, and public health—and officially banned hydraulic fracturing in June 2015. The quantification of landscape disturbance due to hydrocarbon extraction activities is presented in this report as land-use and land-cover (LULC) change between 2004 and 2013 and defined using specific disturbance categories (including well sites, roads, and pipelines) to compare the disturbances and changes, by county, on both sides of the New York-Pennsylvania border. The quantification was accomplished by gathering the signatures of disturbance from high-resolution aerial images, comparing the derived totals of disturbance, and then computing landscape metrics in a geographic information system (GIS) environment. The collected data represent a summation of landscape disturbance from oil and gas development, as some of the data represented were established decades earlier. The Analytical Tools Interface for Landscape Assessments (ATtILA) software was used to calculate land-cover area and landscape metrics for each shale gas, non-shale gas, oil, and other infrastructure types associated with hydrocarbons across each county and both five-county regions in the study area. The three primary metrics used to describe changes in forest structure were (1)forest area, (2) interior forest area, and (3) forest edge area. The changes in metrics were subsequently evaluated using the Pearson correlation coefficient. Overall, the disturbed-area footprint in the Pennsylvania region is considerably larger than the disturbed-area footprint in the New York region (13,687.9 hectares [ha] in Pennsylvania; 3,840.5 ha in New York). Disturbance per site is similar, with 1.2 disturbed ha per site in New York and 1.6 disturbed ha per site in Pennsylvania. In the New York-Pennsylvania 10-county region, hydrocarbon-development and extraction disturbance strongly correlate with a reduction in the percentage of forest for the entire region. This observation also appears to be true in the New York five-county region for forest area. This form of disturbance in the New York five-county region shows significantly correlated changes in forest metrics (–0.4 percent total forest area), particularly in the percentage of interior forest (–1.2 percent total area) and forest edge (+0.7 percent total area). On the other hand, gas and hydrocarbon-development and extraction disturbance (1.0 percent total area) in the Pennsylvania five-county region strongly correlates with a total decline in forest area and agricultural land area (–0.8 percent combined total area) but not with either land-cover class separately.

New York, Pennsylvania

Optical characterization of two cyanobacteria genera, Aphanizomenon and Microcystis, with hyperspectral microscopy.

Cyanobacterial blooms are a nuisance and a potential hazard in freshwater systems worldwide. Remote sensing has been used to detect cyanobacterial blooms, but few studies have distinguished between genera of cyanobacteria. Because some genera are more likely to be toxic than others, this is a useful distinction.In this study, hyperspectral imaging reflectance microscopy was used to examine cyanobacteria from Upper Klamath Lake, Oregon, USA, at high spatial and spectral resolution to determine if two species found commonly in the lake, Aphanizomenon flos-aquae and Microcystis aeruginosa, can be separated spectrally. Of the analytical methods applied, a spectral shape algorithm applied to the derivative was found to be most successful in classifying these species in microscope scenes. Further work is required to determine if the spectral characterization of cyanobacterial genera can be scaled up to other remote sensing applications.

Oregon

A preliminary assessment of hyperspectral remote sensing technology for mapping submerged aquatic vegetation in the Upper Delaware River National Parks

Hyperspectral remote sensing of submerged aquatic vegetation is a complex and difficult process that is affected by unique constraints on the energy flow profile near and below the water surface. In addition, shallow, winding, lotic systems, such as the Upper Delaware River, present additional remote sensing problems in the form of specular reflectance, variable depth and constituents in the water column and sometimes extremely weak signal strength due to absorption and scattering in the water column that can be statistically overwhelmed by the reflectance from upland vegetation in any individual image scene. Here we test hyperspectral imagery from the Civil Air Patrol’s (CAP), Airborne Real-time Cueing Hyperspectral Enhanced Recon (ARCHER) system in the scenic waters of two National Parks on the Upper Delaware River. A number of unique image processing problems were encountered, including specular reflectance from winding lotic systems, variable depth and flow dynamics of the riverine environment, and disproportionate signal strength from surface reflectance in this riverine environment. This were solved by applying a specular reflectance removal algorithm, applying field data collections to classification results and masking upland vegetation so as to not statistically overwhelm the weak reflectance signal from surface and near-surface water. Much was learned about conducting imaging spectroscopy in such difficult conditions. Significant results include successful mapping of SAV presenece/absence, advantages of upland masking of the reflectance signal, and a numkber of processing approaches that are unique to this environment. In this paper we summarize our results and identify unique issues that must be addressed in this environment

New Jersey, New York, Pennsylvania

Canopy volume removal from oil and gas development activity in the upper Susquehanna River basin in Pennsylvania and New York (USA): An assessment using lidar data

Oil and gas development is changing the landscape in many regions of the United States and globally. However, the nature, extent, and magnitude of landscape change and development, and precisely how this development compares to other ongoing land conversion (e.g. urban/sub-urban development, timber harvest) is not well understood. In this study, we examine land conversion from oil and gas infrastructure development in the upper Susquehanna River basin in Pennsylvania and New York, an area that has experienced much oil and gas development over the past 10 years. We quantified land conversion in terms of forest canopy geometric volume loss in contrast to previous studies that considered only areal impacts. For the first time in a study of this type, we use fine-scale lidar forest canopy geometric models to assess the volumetric change due to forest clearing from oil and gas development and contrast this land change to clear cut forest harvesting, and urban and suburban development. Results show that oil and gas infrastructure development removed a large volume of forest canopy from 2006 to 2013, and this removal spread over a large portion of the study area. Timber operations (clear cutting) on Pennsylvania State Forest lands removed a larger total volume of forest canopy during the same time period, but this canopy removal was concentrated in a smaller area. Results of our study point to the need to consider volumetric impacts of oil and gas development on ecosystems, and to place potential impacts in context with other ongoing land conversions.

New York, Pennsylvania

A detailed risk assessment of shale gas development on headwater streams in the Pennsylvania portion of the Upper Susquehanna River Basin, U.S.A.

The development of unconventional oil and gas (UOG) involves infrastructure development (well pads, roads and pipelines), well drilling and stimulation (hydraulic fracturing), and production; all of which have the potential to affect stream ecosystems. Here, we developed a fine-scaled (1:24,000) catchment-level disturbance intensity index (DII) that included 17 measures of UOG capturing all steps in the development process (infrastructure, water withdrawals, probabilistic spills) that could affect headwater streams (< 200 km 2 in upstream catchment) in the Upper Susquehanna River Basin in Pennsylvania, U.S.A. The DII ranged from 0 (no UOG disturbance) to 100 (the catchment with the highest UOG disturbance in the study area) and it was most sensitive to removal of pipeline cover, road cover and well pad cover metrics. We related this DII to three measures of high quality streams: Pennsylvania State Exceptional Value (EV) streams, Class A brook trout streams and Eastern Brook Trout Joint Venture brook trout patches. Overall only 3.8% of all catchments and 2.7% of EV stream length, 1.9% of Class A streams and 1.2% of patches were classified as having medium to high level DII scores (> 50). Well density, often used as a proxy for development, only correlated strongly with well pad coverage and produced materials, and therefore may miss potential effects associated with roads and pipelines, water withdrawals and spills. When analyzed with a future development scenario, 91.1% of EV stream length, 68.7% of Class A streams and 80.0% of patches were in catchments with a moderate to high probability of development. Our method incorporated the cumulative effects of UOG on streams and can be used to identify catchments and reaches at risk to existing stressors or future development.

Pennsylvania

Brook trout distributional response to unconventional oil and gas development: Landscape context matters

We conducted a large-scale assessment of unconventional oil and gas (UOG) development effects on brook trout ( Salvelinus fontinalis ) distribution. We compiled 2231 brook trout collection records from the Upper Susquehanna River Watershed, USA. We used boosted regression tree (BRT) analysis to predict occurrence probability at the 1:24,000 stream-segment scale as a function of natural and anthropogenic landscape and climatic attributes. We then evaluated the importance of landscape context (i.e., pre-existing natural habitat quality and anthropogenic degradation) in modulating the effects of UOG on brook trout distribution under UOG development scenarios. BRT made use of 5 anthropogenic (28% relative influence) and 7 natural (72% relative influence) variables to model occurrence with a high degree of accuracy [Area Under the Receiver Operating Curve (AUC) = 0.85 and cross-validated AUC = 0.81]. UOG development impacted 11% ( n = 2784) of streams and resulted in a loss of predicted occurrence in 126 (4%). Most streams impacted by UOG had unsuitable underlying natural habitat quality ( n = 1220; 44%). Brook trout were predicted to be absent from an additional 26% ( n = 733) of streams due to pre-existing non-UOG land uses (i.e., agriculture, residential and commercial development, or historic mining). Streams with a predicted and observed (via existing pre- and post-disturbance fish sampling records) loss of occurrence due to UOG tended to have intermediate natural habitat quality and/or intermediate levels of non-UOG stress. Simulated development of permitted but undeveloped UOG wells ( n = 943) resulted in a loss of predicted occurrence in 27 additional streams. Loss of occurrence was strongly dependent upon landscape context, suggesting effects of current and future UOG development are likely most relevant in streams near the probability threshold due to pre-existing habitat degradation.

New York, Pennsylvania

Full-range, solar-reflected hyperspectral microscopy to support earth remote sensing research

Over the past 20 years, hyperspectral microscopy has grown into a robust field of analysis for a number of applications. The visible to near-infrared (VNIR; 400 to 1000 nm) region of the spectrum has demonstrated utility for the characterization of healthy and diseased tissue and of biomolecular indicators at the cellular level. Here, we describe the development of a hyperspectral imaging (HSI) microscope that is aimed at material characterization to complement traditional stand-off, earth remote sensing with hyperspectral sensors. We combine commercial off the shelf technology to build an HSI microscope to collect spectral data with illumination provided by a tunable laser. Hyperspectral imaging microscopy (HIM) facilitates detailed examination of target materials at the subcentimeter spatial scale. The custom-built, laser illumination HSI microscope covers the NIR to shortwave infrared (NIR/SWIR; 900 to 2500 nm) solar-reflected spectral range. It is combined with a separate VNIR sensor (400 to 900 nm) that utilizes quartz–tungsten–halogen lamps for illumination. The combined sensors provide a means to collect <10,000 s of spectra in the full VNIR/SWIR spectral range from both pure substances and precisely engineered linear and nonlinear mixtures. The large abundance of spectra allows for a more detailed understanding of the variability and multivariate probability distributions of spectral signatures. This additional information aids in understanding the variability observed in ground truth spectra collected from portable spectrometers, and it greatly enhances sample description and metadata content. In addition, HIM data cubes can serve as proxies, as “microscenes,” for systems engineering applications such as trade studies for HSI acquired by air- and space-borne sensors.

Journal of Applied Remote Sensing

Forest cover changes due to hydrocarbon extraction disturbance in central Pennsylvania (2004–2010)

The state of Pennsylvania has a long history of oil and gas extraction. In recent years with advances in technology such as hydraulic fracturing, hydrocarbon sources that were not profitable in the past are now being exploited. Here, we present an assessment of the cumulative impact of oil and gas extraction activities on the forests of 35 counties in Pennsylvania and their intersecting sub-watersheds between 2004 and 2010. The assessment categorizes counties and sub-watersheds based on the estimated amount of change to forest cover in the area. From the data collected we recognize that although forest cover has not been greatly impacted (with an average loss of percent forest coverage of 0.16% at the county level), landscape structure is affected. Increase in edge forest and decrease in interior forest is evident in many of the counties and sub-watersheds examined. These changes can have a detrimental effect on forest biodiversity and dynamics.

Pennsylvania

Towards establishing compact imaging spectrometer standards

Remote sensing science is currently undergoing a tremendous expansion in the area of hyperspectral imaging (HSI) technology. Spurred largely by the explosive growth of Unmanned Aerial Vehicles (UAV), sometimes called Unmanned Aircraft Systems (UAS), or drones, HSI capabilities that once required access to one of only a handful of very specialized and expensive sensor systems are now miniaturized and widely available commercially. Small compact imaging spectrometers (CIS) now on the market offer a number of hyperspectral imaging capabilities in terms of spectral range and sampling. The potential uses of HSI/CIS on UAVs/UASs seem limitless. However, the rapid expansion of unmanned aircraft and small hyperspectral sensor capabilities has created a number of questions related to technological, legal, and operational capabilities. Lightweight sensor systems suitable for UAV platforms are being advertised in the trade literature at an ever-expanding rate with no standardization of system performance specifications or terms of reference. To address this issue, both the U.S. Geological Survey and the National Institute of Standards and Technology are eveloping draft standards to meet these issues. This paper presents the outline of a combined USGS/NIST cooperative strategy to develop and test a characterization methodology to meet the needs of a new and expanding UAV/CIS/HSI user community.

International Journal of Experimental Spectroscopi

The new Landsat 8 potential for remote sensing of colored dissolved organic matter (CDOM)

Due to a combination of factors, such as a new coastal/aerosol band and improved radiometric sensitivity of the Operational Land Imager aboard Landsat 8, the atmospherically-corrected Surface Reflectance product for Landsat data, and the growing availability of corrected fDOM data from U.S. Geological Survey gaging stations, moderate-resolution remote sensing of fDOM may now be achievable. This paper explores the background of previous efforts and shows preliminary examples of the remote sensing and data relationships between corrected fDOM and Landsat 8 reflectance values. Although preliminary results before and after Hurricane Sandy are encouraging, more research is needed to explore the full potential of Landsat 8 to continuously map fDOM in a number of water profiles.

Marine Pollution Bulletin

Best practices in passive remote sensing VNIR hyperspectral system hardware calibrations

Hyperspectral imaging (HSI) is an exciting and rapidly expanding area of instruments and technology in passive remote sensing. Due to quickly changing applications, the instruments are evolving to suit new uses and there is a need for consistent definition, testing, characterization and calibration. This paper seeks to outline a broad prescription and recommendations for basic specification, testing and characterization that must be done on Visible Near Infra-Red grating-based sensors in order to provide calibrated absolute output and performance or at least relative performance that will suit the user’s task. The primary goal of this paper is to provide awareness of the issues with performance of this technology and make recommendations towards standards and protocols that could be used for further efforts in emerging procedures for national laboratory and standards groups.

Conference Paper

An evaluation of remote sensing technologies for the detection of fugitive contamination at selected Superfund hazardous waste sites in Pennsylvania

This evaluation was conducted to assess the potential for using both traditional remote sensing, such as aerial imagery, and emerging remote sensing technology, such as hyperspectral imaging, as tools for postclosure monitoring of selected hazardous waste sites. Sixteen deleted Superfund (SF) National Priorities List (NPL) sites in Pennsylvania were imaged with a Civil Air Patrol (CAP) Airborne Real-Time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) sensor between 2009 and 2012. Deleted sites are those sites that have been remediated and removed from the NPL. The imagery was processed to radiance and atmospherically corrected to relative reflectance with standard software routines using the Environment for Visualizing Imagery (ENVI, ITT–VIS, Boulder, Colorado) software. Standard routines for anomaly detection, endmember collection, vegetation stress, and spectral analysis were applied.

Pennsylvania

An evaluation of remote sensing technologies for the detection of residual contamination at ready-for-anticipated use sites

Operational problems with site access and information, XRF instrument operation, and imagery collections hampered the effective data collection and analysis process. Of the 24 sites imaged and analyzed, 17 appeared to be relatively clean with no discernible metal contamination, hydrocarbons, or asbestos in the soil. None of the samples for the sites in Louisiana had any result exceeding the appropriate industrial or residential standard for arsenic or lead. One site in South Carolina (North Street Dump) had two samples that exceeded the residential standard for lead. One site in Texas (Cadiz Street), and four sites in Florida (210 North 12th Street, Encore Retail Site, Clearwater Auto, and 22nd Street Mixed Use) were found to have some level of residual metal contamination above the applicable residential or commercial Risk-Based Concentration (RBC) standard. Three of the Florida sites showing metal contamination also showed a pattern of vegetation stress based on standard vegetation analysis techniques.

Florida, Louisiana, South Carolina, Texas