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At least 289 records · Page 16

The Evolution of Icelandic Volcano Emissions, as Observed From Space in the Era of NASA's Earth Observing System (EOS)

Volcanoes are natural phenomena that have global environmental impacts. Satellite remote sensing can help classify volcanic eruptions and track the dispersion of emissions. We assess multiple volcanic eruptions in Iceland (Eyjafjallajökull 2010, Grímsvötn 2011 and Holuhraun 2014-2015), using space-borne observations to infer information about the geological dynamics of each volcano and the properties and evolution of plume particles. We derive qualitative constraints on plume particle size, shape and light-absorption characteristics from Multi-angle Imaging SpectroRadiometer (MISR) space-borne imagery. With the MISR Research Algorithm (RA), we distinguish sulfate/water-dominated volcanic plumes from Holuhraun and ash-dominated plumes from Eyjafjallajökull and Grímsvötn, and even identify subtler changes in ash particle size and light-absorption within plumes. Additionally, plume heights are retrieved geometrically from MISR. These are combined with surface thermal anomalies from the MODerate resolution Imaging Spectroradiometer (MODIS) and SO2 concentrations derived from the Ozone Monitoring Instrument (OMI) to synthesize eruption remote-sensing chronologies. Signals related to differences in particle properties are identified and linked to evolving magma composition at Eyjafjallajökull. The results illustrate the potential to distinguish qualitative differences in eruptive magma composition based on particle light absorption and plume profile from remote-sensing. For the sulfate-rich Holuhraun plumes, the influence of aerosol hygroscopic growth during transport is inferred from such data. Three processes appear to dominate plume evolution in Iceland: downwind aerosol formation; particle hydration; and particle deposition. This work demonstrates enhanced MISR capabilities, and more generally, remote-sensing analysis that can be applied globally, especially where suborbital volcano observations are limited or entirely absent.

remote sensting↗

Canadian and Alaskan Wildfire Smoke Particle Properties, Their Evolution and Controlling Factors, From Satellite Observations

The optical and chemical properties of biomass burning (BB) smoke particles greatly affect the impact that wildfires have on climate and air quality. Previous work has demonstrated some links between smoke properties and factors such as fuel type and meteorology. However, the factors controlling BB particle speciation at emission are not adequately understood nor are the factors driving particle aging during atmospheric transport. As such, modeling wildfire smoke impacts on climate and air quality remains challenging. The potential to provide robust, statistical characterizations of BB particles based on ecosystem type and ambient environmental conditions with remote sensing data is investigated here. Space-based Multi-angle Imaging SpectroRadiometer (MISR) observations, combined with the MISR Research Aerosol (RA) algorithm and the MISR Interactive Explorer (MINX) tool, are used to retrieve smoke plume aerosol optical depth (AOD) and to provide constraints on plume vertical extent; smoke age; and particle size, shape, light-absorption properties, and absorption spectral dependence. These tools are applied to numerous wildfire plumes in Canada and Alaska, across a range of conditions, to create a regional inventory of BB particle-type temporal and spatial distribution. We then statistically compare these results with satellite measurements of fire radiative power (FRP) and land cover characteristics, as well as short-term climate, meteorological, and drought information from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) reanalysis and the North American Drought Monitor. We find statistically significant differences in the retrieved smoke properties based on land cover type, with fires in forests producing the thickest plumes containing the largest, brightest particles and fires in savannas and grasslands exhibiting the opposite. Additionally, the inferred dominant aging mechanisms and the timescales over which they occur vary systematically between land types. This work demonstrates the potential of remote sensing to constrain BB particle properties and the mechanisms governing their evolution over entire ecosystems. It also begins to realize this potential, as a means of improving regional and global climate and air quality modeling in a rapidly changing world.

Katherine T. Junghenn Noyes↗

Lunar Payloads to Constrain Exospheric Water through the NASA M-STAR program

Our understanding of water cycles on the Moon has significantly enhanced recent observations by Chang E-5, Lunar Prospector, and Chandrayaan-1 missions indicating the existence of an active water cycle on the Moon. In a new partnership between Delaware State University (DSU) and NASA Goddard Space Flight Center, enabled through the NASA’s M-STAR (MUREP Space Technology Artemis Research) program, we are developing low mass and power lunar rover payloads to enable long-duration human exploration missions. Payload technologies include wavelength modulation absorption spectroscopy to simultaneously detect water (H16OH) and isotopes (H16OD) in the (6700 nm) mid-infrared region using a closed path in compact Herriot cell optical design and wavelength modulation spectroscopy, and (2) Laser-induced breakdown spectroscopy (LIBS) to simultaneously detect and correlate water isotopes with characteristics elemental composition of lunar regolith. Due to the airless atmosphere of the Moon, we will utilize Artificial intelligence (AI) and Machine learning (ML) approaches to discriminate spectral interference with instrument drifts and correlate mid-IR trace gas profile with LIBS spectral information. This partnership will initiate a STEM engagement space program, e.g., Lander and CubeSat payload technology development for students and the next-generation NASA workforce for future lunar and Mars missions. DSU, a Historically Black University, prides itself in its proven excellence in teaching and research. It enrolls a diverse population of students (~5000) traditionally underrepresented in STEM disciplines. DSU has established itself at the forefront of optics and photonics research that transcends multidisciplinary fields of earth sciences, environmental, defense, and biomedical sensing applications.

water cycles↗

A Computer Learning Center for Environmental Sciences

In the fall of 1998, MacMillan Hall opened at Brown University to students. In MacMillan Hall was the new Computer Learning Center, since named the EarthLab which was outfitted with high-end workstations and peripherals primarily focused on the use of remotely sensed and other spatial data in the environmental sciences. The NASA grant we received as part of the "Centers of Excellence in Applications of Remote Sensing to Regional and Global Integrated Environmental Assessments" was the primary source of funds to outfit this learning and research center. Since opening, we have expanded the range of learning and research opportunities and integrated a cross-campus network of disciplines who have come together to learn and use spatial data of all kinds. The EarthLab also forms a core of undergraduate, graduate, and faculty research on environmental problems that draw upon the unique perspective of remotely sensed data. Over the last two years, the Earthlab has been a center for research on the environmental impact of water resource use in and regions, impact of the green revolution on forest cover in India, the design of forest preserves in Vietnam, and detailed assessments of the utility of thermal and hyperspectral data for water quality analysis. It has also been used extensively for local environmental activities, in particular studies on the impact of lead on the health of urban children in Rhode Island. Finally, the EarthLab has also served as a key educational and analysis center for activities related to the Brown University Affiliated Research Center that is devoted to transferring university research to the private sector.

Mustard, John F.↗

Implementing Spatio-Temporal 3D-Convolution Neural Networks and UAV Time Series Imagery to Better Predict Lodging Damage in Sorghum

Unmanned aerial vehicle (UAV)-based remote sensing is gaining momentum in a variety of agricultural and environmental applications. Very-high-resolution remote sensing image sets collected repeatedly throughout a crop growing season are becoming increasingly common. Analytical methods able to learn from both spatial and time dimensions of the data may allow for an improved estimation of crop traits, as well as the effects of genetics and the environment on these traits. Multispectral and geometric time series imagery was collected by UAV on 11 dates, along with ground-truth data, in a field trial of 866 genetically diverse biomass sorghum accessions. We compared the performance of Convolution Neural Network (CNN) architectures that used image data from single dates (two spatial dimensions, 2D) versus multiple dates (two spatial dimensions + temporal dimension, 3D) to estimate lodging detection and severity. Lodging was detected with 3D-CNN analysis of time series imagery with 0.88 accuracy, 0.92 Precision, and 0.83 Recall. This outperformed the best 2D-CNN on a single date with 0.85 accuracy, 0.84 Precision, and 0.76 Recall. The variation in lodging severity was estimated by the best 3D-CNN analysis with 9.4% mean absolute error (MAE), 11.9% root mean square error (RMSE), and goodness-of-fit (R2) of 0.76. This was a significant improvement over the best 2D-CNN analysis with 11.84% MAE, 14.91% RMSE, and 0.63 R2. The success of the improved 3D-CNN analysis approach depended on the inclusion of “before and after” data, i.e., images collected on dates before and after the lodging event. The integration of geometric and spectral features with 3D-CNN architecture was also key to the improved assessment of lodging severity, which is an important and difficult-to-assess phenomenon in bioenergy feedstocks such as biomass sorghum. This demonstrates that spatio-temporal CNN architectures based on UAV time series imagery have significant potential to enhance plant phenotyping capabilities in crop breeding and Precision agriculture applications.

3D-convolution neural networks↗

Importance of atmospheric scattering in remote sensing, or everything you've always wanted to know about atmospheric scattering but were afraid to ask.

Discussion of the effects of atmospheric scattering and/or absorption on discrimination between target and background materials in environmental or natural science remote sensing applications. The spectral region considered lies between 0.4 and 3 microns. The results are presented parametrically and include an interesting effect that neighboring materials have on the spectral character of a target as a result of aerosol scattering by atmospheric haze.

Turner, R. E.↗

Impacts and Conclusions of NASA DEVELOP’s Environmental Justice Landscape Analyses and Feasibility Studies

The NASA DEVELOP National Program builds dual capacity in their partner organizations and participants (students and early or transitioning career professionals) to apply Earth science and remote sensing for decision making about environmental and policy issues. The first iteration of projects at DEVELOP’s Environmental Justice (EJ) node conducted landscape analyses to identify geospatial understandings and needs of organizations working at the intersection of EJ and disasters and air quality. Their findings about collaboration, community engagement, networking, and holistic approaches to justice informed the planning and structures of the EJ node’s successive feasibility projects, which leverage NASA Earth observations and sociodemographic and economic data to provide geospatial analyses tailored to partner concerns. This poster provides an overview of DEVELOP’s approach to conducting EJ feasibility projects, use of Earth observations, end products, project outcomes, challenges, and impacts.

Julianne Bo-Heen Liu↗

Prediction of health levels by remote sensing

Measures of the environment derived from remote sensing were compared to census population/housing measures in their ability to discriminate among health status areas in two urban communities. Three hypotheses were developed to explore the relationships between environmental and health data. Univariate and multiple step-wise linear regression analyses were performed on data from two sample areas in Houston and Galveston, Texas. Environmental data gathered by remote sensing were found to equal or surpass census data in predicting rates of health outcomes. Remote sensing offers the advantages of data collection for any chosen area or time interval, flexibilities not allowed by the decennial census.

Rush, M.↗

The SrrAB two-component system regulates Staphylococcus aureus pathogenicity through redox sensitive cysteines

Staphylococcus aureus infections can lead to diseases that range from localized skin abscess to life-threatening toxic shock syndrome. The SrrAB two-component system (TCS) is a global regulator of S. aureus virulence and critical for survival under environmental conditions such as hypoxic, oxidative, and nitrosative stress found at sites of infection. Despite the critical role of SrrAB in S. aureus pathogenicity, the mechanism by which the SrrAB TCS senses and responds to these environmental signals remains unknown. Bioinformatics analysis showed that the SrrB histidine kinase contains several domains, including an extracellular Cache domain and a cytoplasmic HAMP-PAS-DHp-CA region. In this work, we show that the PAS domain regulates both kinase and phosphatase enzyme activity of SrrB and present the structure of the DHp-CA catalytic core. Importantly, this structure shows a unique intramolecular cysteine disulfide bond in the ATP-binding domain that significantly affects autophosphorylation kinetics. In vitro data show that the redox state of the disulfide bond affects S. aureus biofilm formation and toxic shock syndrome toxin-1 production. Moreover, with the use of the rabbit infective endocarditis model, we demonstrate that the disulfide bond is a critical regulatory element of SrrB function during S. aureus infection. Our data support a model whereby the disulfide bond and PAS domain of SrrB sense and respond to the cellular redox environment to regulate S. aureus survival and pathogenesis.

59 BASIC BIOLOGICAL SCIENCES↗

Mapping Environmental Contaminants at Ray Mine, AZ

Airborne Visible and InfraRed Imaging Spectrometer (AVIRIS) data was collected over Ray Mine as part of a demonstration project for the Environmental Protection Agency (EPA) through the Advanced Measurement Initiative (AMI). The overall goal of AMI is to accelerate adoption and application of advanced measurement technologies for cost effective environmental monitoring. The site was selected to demonstrate the benefit to EPA in using advanced remote sensing technologies for the detection of environmental contaminants due to the mineral extraction industry. The role of the Jet Propulsion Laboratory in this pilot study is to provide data as well as performing calibration, data analysis, and validation of the AVIRIS results. EPA is also interested in developing protocols that use commercial software to perform such work on other high priority EPA sites. Reflectance retrieval was performed using outputs generated by the MODTRAN radiative transfer model and field spectra collected for the purpose of calibration. We are presenting advanced applications of the ENVI software package using n-Dimensional Partial Unmixing to identify image-derived endmembers that best match target materials reference spectra from multiple spectral libraries. Upon identification of the image endmembers the Mixture Tuned Match Filter algorithm was applied to map the endmembers within each scene. Using this technique it was possible to map four different mineral classes that are associated with mine generated acid waste.

McCubbin, Ian↗

Electronic and Optical Properties of NV Center in Diamonds for Sensing Applications: Experimental and First Principles Density Functional Theory Approach

The nitrogen-vacancy (NV) center in a nanodiamond (ND) crystal is one of the best candidate materials for quantum sensing and metrology applications at elevated environmental conditions. The NV center can be used to achieve an unprecedented level of sensitivity for sensing applications at high temperatures and pressures. The NV center is also proven to be useful for magnetic field sensing. Furthermore, it can be used for applications in the sensing of valuable minerals such as rare earth elements (REEs) from the crude and waste subsurface materials. This work presents computational and experimental studies on electronic and optical properties of bulk diamond with N and NV defects. ND in MOF/polymer materials will be experimentally encapsulated. The transverse spin relaxation time of the NV center will be measured in bare and encapsulated ND. Different doping elements will be introduced on the surfaces and present surface electronic properties to study the surfaces with shallow NV center for quantum sensing applications.

Paudel, Hari P.↗

Development of remote sensing technology in New Zealand, part 1. Mapping land use and environmental studies in New Zealand, part 2. Indigenous forest assessment, part 3. Seismotectonic, structural, volcanologic and geomorphic study of New Zealand, part 4

The author has identified the following significant results. As part of the tape reformatting process, a simple coded picture output program was developed. This represents Pixel's radiance level by one of a 47 character set on a nonoverprinting line printer. It not only has aided in locating areas for the reformatting process, but has also formed the foundation for a supervised clustering package. This in turn has led to a simplistic but effective thematic mapping package.

Probine, M. C.↗

Environmental Public Health Surveillance for Exposure to Respiratory Health Hazards: A Joint NASA/CDC Project to Use Remote Sensing Data for Estimating Airborne Particulate Matter Over the Atlanta, Georgia Metropolitan Area

As part of the National Environmental Public Health Tracking Network (EPHTN) the National Center for Environmental Health (NCEH) at the Centers for Disease Control and Prevention (CDC) is leading a project called Health and Environment Linked for Information Exchange (HELiX-Atlanta). The goal of developing the National Environmental Public Health Tracking Network is to improve the health of communities. Currently, few systems exist at the state or national level to concurrently track many of the exposures and health effects that might be associated with environmental hazards. An additional challenge is estimating exposure to environmental hazards such as particulate matter whose aerodynamic diameter is less than or equal to 2.5 micrometers (PM2.5). HELIX-Atlanta's goal is to examine the feasibility of building an integrated electronic health and environmental data network in five counties of Metropolitan Atlanta, GA. NASA Marshall Space Flight Center (NASA/MSFC) is collaborating with CDC to combine NASA earth science satellite observations related to air quality and environmental monitoring data to model surface estimates of PM2.5 concentrations that can be linked with clinic visits for asthma. While use of the Air Quality System (AQS) PM2.5 data alone could meet HELIX-Atlanta specifications, there are only five AQS sites in the Atlanta area, thus the spatial coverage is not ideal. We are using NASA Moderate Resolution Imaging Spectroradiometer (MODIS) satellite Aerosol Optical Depth (AOD) data for estimating daily ground level PM2.5 at 10 km resolution over the metropolitan Atlanta area supplementing the AQS ground observations and filling their spatial and temporal gaps.

Quattrochi, Dale A.↗

Sensor Domain of Histidine Kinase VxrA of Vibrio cholerae : Hairpin-Swapped Dimer and Its Conformational Change

VxrA and VxrB are cognate histidine kinase (HK)-response regulator (RR) pairs of a two-component signaling system (TCS) found in Vibrio cholerae, a bacterial pathogen that causes cholera. The VxrAB TCS positively regulates virulence, the type VI secretion system, biofilm formation, and cell wall homeostasis in V. cholerae, providing protection from environmental stresses and contributing to the transmission and virulence of the pathogen. The VxrA HK has a unique periplasmic sensor domain (SD) and, remarkably, lacks a cytoplasmic linker domain between the second transmembrane helix and the dimerization and histidine phosphotransfer (DHp) domain, indicating that this system may utilize a potentially unique signal sensing and transmission TCS mechanism. Here, we have determined several crystal structures of VxrA-SD and its mutants. These structures reveal a novel structural fold forming an unusual β hairpin-swapped dimer. A conformational change caused by relative rotation of the two monomers in a VxrA-SD dimer could potentially change the association of transmembrane helices and, subsequently, the pairing of cytoplasmic DHp domains. Based on the structural observation, we propose a putative scissor-like closing regulation mechanism for the VxrA HK. IMPORTANCE V. cholerae has a dynamic life cycle, which requires rapid adaptation to changing external conditions. Two-component signal transduction (TCS) systems allow V. cholerae to sense and respond to these environmental changes. The VxrAB TCS positively regulates a number of important V. cholerae phenotypes, including virulence, the type six secretion system, biofilm formation, and cell wall homeostasis. Here, we provide the crystal structures of the VxrA sensor histidine kinase sensing domain and propose a mechanism for signal transduction. The cognate signal for VxrAB remains unknown; however, in this work we couple our structural analysis with functional assessments of key residues to further our understanding of this important TCS.

59 BASIC BIOLOGICAL SCIENCES↗

Satellite sensing capabilities for surface temperature and meteorological parameters over the ocean

Remote meteorological measurements over the oceans have been used extensively for weather forecasting, ship safety, and global-scale studies of climate and sea conditions. A review is conducted regarding the satellite-sensing capabilities for sea-surface temperature and tropospheric marine meteorological mesurements. The tropospheric measurements are concerned with vertical temperature profiles, integrated water vapor and liquid water, rain, aerosols and surface winds. Attention is also given to several environmental-monitoring applications where satellite sensed synoptic data might be combined with ground and airborne chemical measurements to provide improved assessments of regional and global ennvironmental quality and climatology. Special emphasis is given to current satellite measurement accuracies (errors) and to programs involving U.S. technology. Aspects of sea-surface temperature are treated in detail in connection with extensive studies concentrated in this area.

Darnell, W. L.↗

Geospatial Analysis and Remote Sensing from Airplanes and Satellites for Cultural Resources Management

Cultural resource management consists of research to identify, evaluate, document and assess cultural resources, planning to assist in decision-making, and stewardship to implement the preservation, protection and interpretation of these decisions and plans. One technique that may be useful in cultural resource management archaeology is remote sensing. It is the acquisition of data and derivative information about objects or materials (targets) located on the Earth's surface or in its atmosphere by using sensor mounted on platforms located at a distance from the targets to make measurements on interactions between the targets and electromagnetic radiation. Included in this definition are systems that acquire imagery by photographic methods and digital multispectral sensors. Data collected by digital multispectral sensors on aircraft and satellite platforms play a prominent role in many earth science applications, including land cover mapping, geology, soil science, agriculture, forestry, water resource management, urban and regional planning, and environmental assessments. Inherent in the analysis of remotely sensed data is the use of computer-based image processing techniques. Geographical information systems (GIS), designed for collecting, managing, and analyzing spatial information, are also useful in the analysis of remotely sensed data. A GIS can be used to integrate diverse types of spatially referenced digital data, including remotely sensed and map data. In archaeology, these tools have been used in various ways to aid in cultural resource projects. For example, they have been used to predict the presence of archaeological resources using modern environmental indicators. Remote sensing techniques have also been used to directly detect the presence of unknown sites based on the impact of past occupation on the Earth's surface. Additionally, remote sensing has been used as a mapping tool aimed at delineating the boundaries of a site or mapping previously unknown features. All of these applications are pertinent to the goals of site discovery and assessment in cultural resource management.

Giardino, Marco J.↗