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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Evaluating the effectiveness of M-AMBI with other biotic indexes in a temperate estuary

Need for a scalable and widely applicable index has been increasingly important. This study evaluates the applicability of the M-AMBI, a potential comprehensive index, at small spatial scales. M-AMBI was compared to regional indices (EMAP-E and GOM B-IBI), assessing response to natural environmental gradients and low oxygen stress. Results indicate poor agreement between indices with M-AMBI and GOM B-IBI showing positive correlation but significant disagreement in habitat condition. EMAP-E had no agreement. Indices showed similar patterns of better habitat scores in higher salinities. M-AMBI also showed a negative relationship with sediment organic matter and total nitrogen. DO influenced all indices with M-AMBI the most sensitive. However, mismatches between DO and index score were observed further calibration may be needed before adoption into programs. Altogether, the M-AMBI demonstrates potential at smaller, local scales, but additional studies are needed to validate its performance in different coastal environments and under different conditions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

Integration of socioeconomic data and remotely sensed imagery for land use applications

The Image Based Information System (IBIS) uses techniques of digital image processing to interface geocoded data sets, information management systems, thematic maps, and remotely sensed imagery. For two cases IBIS has been used to integrate remotely sensed imagery and socioeconomic data. In the first case thematically classified Landsat imagery covering Orange County, California is combined with census tracts and municipalities. In the second case, thematically classified Landsat imagery over Los Angeles, California is combined with census tracts.

Bryant, N. A.↗
NASA NTRS1979

Using population statistics for a first look at the utility of Landsat data for urban areas

The paper reviews the Image Based Information System (IBIS), developed at the Jet Propulsion Laboratory (JPL) which provided the city of Los Angeles with Landsat land use data in a format compatible with the city's land use and population files. Landsat data are compared to other land use files and the comparisons are discussed as an attempt to establish a level of validity. Relationships between population and Landsat data are investigated and reveal the strengths and weaknesses of the use of such data for urban areas. Finally, it is noted that the project verified the flexibility of IBIS for reducing and delivering Landsat data to users lacking the ability to process raw satellite data tapes and points to the system as a model for a potential national census of land use.

Landini, A. J.↗
NASA NTRS1981

Application of digital image processing techniques and information systems to water quality monitoring of Lake Tahoe

The Tahoe basin occupies over 500 square miles of territory located in a graben straddling the boundary between California and Nevada. Lake Tahoe contains 126 million acre-feet of water. Since the 1950's the basin has experienced an ever increasing demand for land development at the expense of the natural watershed. Discharge of sediment to the lake has greatly increased owing to accelerated human interference, and alterations to the natural drainage patterns are evident in some areas. In connection with an investigation of the utility of a comprehensive system that takes into account the causes as well as the effects of lake eutrophication, it has been attempted to construct an integrated and workable data base, comprised of currently available data sources for the Lake Tahoe region. Attention is given to the image based information system (IBIS), the construction of the Lake Tahoe basin data base, and the application of the IBIS concept to the Lake Tahoe basin.

Smith, A. Y.↗
NASA NTRS1987

Spatial data software integration - Merging CAD/CAM/mapping with GIS and image processing

The integration of CAD/CAM/mapping with image processing using geographic information systems (GISs) as the interface is examined. Particular emphasis is given to the development of software interfaces between JPL's Video Image Communication and Retrieval (VICAR)/Imaged Based Information System (IBIS) raster-based GIS and the CAD/CAM/mapping system. The design and functions of the VICAR and IBIS are described. Vector data capture and editing are studied. Various software programs for interfacing between the VICAR/IBIS and CAD/CAM/mapping are presented and analyzed.

Logan, Thomas L.↗
NASA NTRS2011

When A Standard Candle Flickers

The Crab Nebula is the only hard X-ray source in the sky that is both bright enough and steady enough to be easily used as a standard candle. As a result, it has been used as a normalization standard by most X-ray/gamma ray telescopes. Although small-scale variations in the nebula are well-known, since the start of science operations of the Fermi Gamma-ray Burst Monitor (GBM) in August 2008 a 7% (70 mcrab) decline has been observed in the overall Crab Nebula flux in the 15-50 keV band, measured with the Earth occultation technique. This decline is independently confirmed in the 15-50 keV band with three other instruments: the Swift Burst Alert Telescope (Swift/BAT), the Rossi X-ray Timing Explorer Proportional Counter Array (RXTE/PCA), and the INTErnational Gamma-Ray Astrophysics Laboratory Imager on Board INTEGRAL (IBIS). A similar decline is also observed in the 3 - 15 keV data from the RXTE/PCA and in the 50 - 100 keV band with GBM, Swift/BAT, and INTEGRAL/IBIS. The change in the pulsed flux measured with RXTE/PCA since 1999 is consistent with the pulsar spin-down, indicating that the observed changes are nebular. Correlated variations in the Crab Nebula flux on a 3 year timescale are also seen independently with the PCA, BAT, and IBIS from 2005 to 2008, with a flux minimum in April 2007. As of August 2010, the current flux has declined below the 2007 minimum.

Wilson-Hodge, Colleen A.↗
NASA NTRS2012

IGR J12319-0749: Evidence for Another Extreme Blazar Found with INTEGRAL

We report on the identification of a new soft gamma-ray source, IGR J12319 C0749, detected with the IBIS imager on board the INTEGRAL satellite. The source, which has an observed 20 C100 keV flux of 8.3 10.12 erg cm.2 s.1, is spatially coincident with an AGN at redshift z = 3.12. The broad-band continuum, obtained by combining XRT and IBIS data, is flat ( =1.3) with evidence for a spectral break around 25 keV (100 keV in the source rest frame). X-ray observations indicate flux variability which is further supported by a comparison with a previous ROSAT measurement. IGR J12319 C0749 is also a radio emitting object likely characterized by a flat spectrum and high radio loudness; optically it is a broad-line emitting object with a massive black hole (2.8 109 solar masses) at its center. The source Spectral Energy Distribution is similar to another high redshift blazar, 225155+2217 at z = 3.668: both objects are bright, with a large accretion disk luminosity and a Compton peak located in the hard X-ray/soft gamma-ray band. IGR J12319 C0749 is likely the second most distant blazar detected so far by INTEGRAL.

Bassani, L.↗
NASA NTRS2012

IGR J12319-0749: Evidence for Another Extreme Blazar Found with INTEGRAL

We report on the identification of a new soft gamma-ray source, IGR J12319-0749, detected with the IBIS imager on board the INTEGRAL satellite. The source, which has an observed 20−100 keV flux of approx 8.3 × 10(exp -12) erg/sq. cm/ s, is spatially coincident with an active galactic nucleus (AGN) at redshift z = 3.12. The broad-band continuum, obtained by combining XRT and IBIS data, is flat (Gamma = 1.3) with evidence for a spectral break around 25 keV (100 keV in the source restframe). X-ray observations indicate flux variability, which is also supported by a comparison with a previous ROSAT measurement. IGR J12319-0749 is also a radio-emitting object likely characterised by a flat spectrum and high radio loudness; optically it is a broad-line emitting object with a massive black hole (2.8 × 10(exp 9) solar masses) at its centre. The source spectral energy distribution is similar to another high-redshift blazar, 225155+2217 at z = 3.668: both objects are bright, with a high accretion disk luminosity and a Compton peak located in the hard X-ray/soft gamma-ray band. IGR J12319-0749 is likely the second-most distant blazar detected so far by INTEGRAL.

IGRJ12319-0749↗
NASA NTRS2023

Assessing the Performance of the South American Land Data Assimilation System Version 2 (SALDAS-2) Energy Balance across Diverse Biomes

Understanding the exchange of energy between the surface and the atmosphere is important in view of the climate scenario. However, it becomes a challenging task due to a sparse network of observations. This study aims to improve the energy balance estimates for the Amazon, Cerrado, and Pampa biomes located in South America using the radiation and precipitation forcing obtained from the Clouds and the Earth’s Radiant Energy System (CERES) and the precipitation CPTEC/MERGE datasets. We employed three surface models—Noah-MP, Community Land Model (CLSM), and Integrated Biosphere Simulator (IBIS)—and conducted modeling experiments, termed South America Land Data Assimilation System (SALDAS-2). The results showed that SALDAS-2 radiation estimates had the smallest errors. Moreover, SALDAS-2 precipitation estimates were better than the Global Land Data Assimilation System (GLDAS) in the Cerrado (MBE = −0.16) and Pampa (MBE = −0.19). Noah-MP presented improvements compared with CLSM and IBIS in 100% of towers located in the Amazon. CLSM tends to overestimate the latent heat flux and underestimate the sensible heat flux in the Amazon. Noah-MP and Ensemble outperformed GLDAS in terms latent and sensible heat fluxes. The potential of SALDAS-2 should be emphasized to provide more accurate estimates of surface energy balance.

modeling↗
DOE OSTI2022

Agroecosystem model simulations reveal spatial variability in relative productivity in biomass sorghum and maize in Iowa, USA

Biomass sorghum (Sorghum bicolor L. Moench) is an annual C 4 grass that has emerged as a candidate bioenergy crop but has not been widely grown in the United States. Corn (Zea mays L.), another annual C 4 grass, has been produced on a large scale in the United States for biofuels. Iowa leads the nation in both corn and ethanol production. The high productivity of corn in Iowa creates the research question: could biomass sorghum be as or more productive than corn in the state in terms of bioenergy? Efforts to use crop models to fill the gaps left by field experimentation on biomass sorghum have also been limited thus far. To address our research question, we collected biophysical data on biomass sorghum grown in Iowa for two growing seasons, used them to develop a biomass sorghum module in an agroecosystem model (Agro-IBIS), and predict the potential performance of biomass sorghum across Iowa compared to maize. Despite dry conditions in 2019 and 2020, average biomass sorghum yields were 17.20 Mg ha –1 . By comparison, average corn aboveground biomass was higher in 2020 (22.02 Mg ha –1 ). Soil cores indicated average belowground biomass of 1.46 Mg ha –1 , with roots concentrated near the surface (73% of biomass above 50 cm in a 1 m core). When biomass sorghum model parameters were calibrated with measured values, model output was in close agreement with measured biomass (slope = 0.932, R 2 = 0.91) and evapotranspiration (slope = 0.757, R 2 = 0.64). Subsequent regional simulations revealed a notable latitudinal gradient in biomass sorghum yield, with a strong linear relationship between yield and seasonal growing degree-days (R 2 = 0.89). When these yields were compared to simulated corn aboveground biomass yields, only 3.4% of the state had biomass sorghum yields that were significantly higher than corn. This number was reduced to 0.3% when comparing the crops in terms of energy ethanol yield. Thus, we conclude biomass sorghum must be improved to be competitive with corn as an annual biofuel crop in Iowa. This study provides a baseline against which to compare advancements in sorghum breeding for biomass and stress tolerance in Iowa.

Agro-IBIS↗
DOE OSTI2023

Field‐scale analysis of miscanthus production indicates climate change may increase the opportunity for water quality improvement in a key Iowa watershed

Abstract The Raccoon River Basin is the primary source for drinking water in Iowa's largest city and plays a major role in the Mississippi River Basin's high nutrient exports. Future climate change may have major impacts on the biological, physiological, and agronomic processes imposing a threat to ecosystem services. Efforts to reduce nitrogen (N) loads within this basin have included local litigation and the implementation of the Iowa Nutrient Reduction Strategy, which suggest incorporating bioenergy crops (i.e., miscanthus) within the current corn–soybean landscape to reach a 41% reduction in nitrate loads. This study focuses on simulating N export for historical and future land use scenarios by using an agroecosystem model (Agro‐IBIS) and a hydrology model (THMB) at the 500‐m resolution, similar to the scale of agricultural fields. Model simulations are driven by CMIP5 climate data for historical, mid‐century, and late‐century under the RCP 4.5 and 8.5 warming projections. Using recent crop profit analyses for the state of Iowa, profitability maps were generated and nitrogen leaching thresholds were used to determine where miscanthus should replace corn–soybean area to maximize reductions in N pollution. Our results show that miscanthus inclusion on low profit and high N leaching areas can result in a 4% reduction of N loss under current climate conditions and may reduce N loss by 21%–26% under future climate conditions, implying that water quality has the potential continue to improve under future climate conditions when strategically implemented conservation practices are included in future farm management plans.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Plug Load Management System Field Study

In 2018, NREL performed a demonstration of the IBIS InteliNetwork(TM) plug load management system, which includes: intelligent socket devices, which plug into existing electrical outlets and collect energy usage information; a gateway, which manages communication between the intelligent sockets and the PLM cloud service; and a PLM network, which is a cloud-based measurement and control network for the entire system. Two retail stores served as the field study sites. The PLM system was found to be effective at reducing plug load energy use, with a projected annual plug load reduction of 11% and 18% at the test locations. Retail staff reported that the hardware was easy to use, but no one used the online data management system, intended to analyze and control the hardware. This PLM solution shows promise as an effective means to monitor, control, and reduce plug load energy use, but the economics of the system need to be improved.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Moving With Parasites: Relationships Between Animal Movement and Infectious Disease Across Systems and Scales

Animal movement patterns are important for ecological processes such as population dynamics and infectious disease transmission. Because animals move in response to environmental cues like temperature and precipitation, changes to the environment – whether they are seasonal, interannual, or long-term – can change these processes, leading to changes in population sizes or infectious disease prevalence across space and time. My work uses a combination of simulation modeling and data analysis at multiple spatial and temporal scales to understand the environment-movement-disease connection in diverse animal taxa and environments. In this seminar, I will highlight the diverse ways that the environment can influence infectious disease dynamics via changes to animal movement patterns, including through a global study of migration in ungulate populations, a study of American White Ibis adapting to urban environments in South Florida, and examples of avian influenza prevalence in wild waterfowl. Together, these examples highlight that understanding environment-movement interactions can help predict how infectious disease dynamics might change in the future, as changes to climate, land use, and habitats alter animal movement patterns.

Animal movement↗
DOE OSTI2018

Plug Load Management System Field Study: Wireless Meter and Controls

This presentation offers background on GSA's Green Proving Ground (GPG) and DOE's High Impact Technology (HIT) Catalyst work, and a field study that assessed a plug load management (PLM) system in two commercial building applications. The Ibis InteliNetwork (TM) PLM system enables users to measure and analyze device energy use and identify opportunities for reduction of plug load energy use, and set times for individual devices (or groups of devices) to turn off when not in use. The presentation gives an overview of the PLM demonstration project, its results, and lessons learned.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

A machine learning approach to water quality forecasts and sensor network expansion: Case study in the Wabash River Basin, United States

Abstract Midwestern cities require forecasts of surface nitrate loads to bring additional treatment processes online or activate alternative water supplies. Concurrently, networks of nitrate monitoring stations are being deployed in river basins, co‐locating water quality observations with established stream gauges. However, tools to evaluate the future value of expanded networks to improve water quality forecasts remains challenging. Here, we construct a synthetic data set of stream discharge and nitrate for the Wabash River Basin—one of the United States’ most nutrient polluted basins—using the established Agro‐IBIS and THMB models. Synthetic data enables rapid, unbiased and low‐cost assessment of potential sensor placements to support management objectives, such as near‐term forecasting. Using the synthetic data, we established baseline 1‐day forecasts for surface water nitrate at 12 cities in the basin using support vector machine regression (SVMR; RMSE 0.48–3.3 ppm). Next, we used the SVMRs to evaluate the improvement in forecast performance associated with deployment of additional nitrate sensors. We identified the optimal sensor placement to improve forecasts at each city, and the relative value of sensors at each candidate location. Finally, we assessed the co‐benefit realized by other cities when a sensor is deployed to optimize a forecast at one city, finding significant positive externalities in all cases. Ultimately, our study explores the potential for machine learning to make near‐term predictions and critically evaluate the improvement realized by expanding a monitoring network. While we use nitrate pollution in the Wabash River Basin as a case study, this approach could be readily applied to any problem where the future value of sensors and network design are being evaluated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Soybean rust‐resistant and tolerant varieties identified through the Pan‐African Trial Network

Abstract BACKGROUND The global demand for soybeans is increasing rapidly, with projections indicating an escalation of 70–80 million metric tons over the next decade. Sub‐Saharan Africa (SSA) contributes significantly to this growth, with soybean production increasing by 6.8% per year, outpacing the global average increase of 4.7%. Despite the expansion, soybean productivity in Africa remains less than half of the global average. This yield gap is largely due to diseases and pests, such as soybean rust, which can be particularly severe. Effective management of soybean rust depends on several factors, including resistant cultivars. However, there has been limited information on the rust‐resistance levels of African cultivars. To address this gap, the Pan‐African Trial network conducted soybean varietal trials across diverse locations. RESULT Analyzing data from 370 individual trials conducted between 2015–2022, the network identified 81 cultivars with sufficient rust‐resistance data. Six cultivars including, Black Hawk, Dundee, Egret, Heron, Ibis, and Peka 06 were found to be resistant, and 12 were classified as tolerant. CONCLUSION This research is a significant step forward in improving soybean productivity in Africa, and further assessments are being undertaken to address other crop production challenges in the region. © 2025 Society of Chemical Industry.

Favoretto, Vitor Rampazzo [Cenex Harvest States (C↗
DOE OSTI2024

Development of a coarse-grained molecular dynamics model for poly(dimethyl- co -diphenyl)siloxane

Polydimethylsiloxane is an important polymeric material with a wide range of applications. However, environmental effects like low temperature can induce crystallization in this material with resulting changes in its structural and dynamic properties. The incorporation of phenyl-siloxane components, e.g., as in a poly(dimethyl-co-diphenyl)siloxane random copolymer, is known to suppress such crystallization. Molecular dynamics (MD) simulations can be a powerful tool to understand such effects in atomistic detail. Unfortunately, all-atomistic molecular dynamics (AAMD) is limited in both spatial dimensions and simulation times it can probe. Here, to overcome such constraints and to extend to more useful length- and time-scales, we systematically develop a coarse-grained molecular dynamics (CGMD) model for the poly(dimethyl-co-diphenyl)siloxane system with bonded and non-bonded interactions determined from all-atomistic simulations by the iterative Boltzmann inversion (IBI) method. Additionally, we propose a lever rule that can be useful to generate non-bonded potentials for such systems without reference to the all-atomistic ground truth. Our model captures the structural and dynamic properties of the copolymer material with quantitative accuracy and is useful to study long-time dynamics of highly-entangled systems, sequence-dependent properties, phase behaviour, etc.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Clustering analysis of medium-band selected high-redshift galaxies

Next-generation large-scale structure spectroscopic surveys will probe cosmology at high redshifts (2.3 < z < 3.5), relying on abundant galaxy tracers such as Lyα emitters (LAEs) and Lyman break galaxies (LBGs). Medium-band photometry has emerged as a potential technique for efficiently selecting these high-redshift galaxies. In this work, we present clustering analysis of medium-band selected galaxies at high redshift, utilizing photometric data from the Intermediate Band Imaging Survey (IBIS) and spectroscopic data from the Dark Energy Spectroscopic Instrument (DESI). We interpret the clustering of such samples using both Halo Occupation Distribution (HOD) modeling and a perturbation theory description of large-scale structure. Our modeling indicates that the current target sample is composed from an overlapping mixture of LAEs and LBGs with emission lines. Despite differences in target selection, we find that the clustering properties are consistent with previous studies, with correlation lengths r 0 ≃ 3-4 h -1 Mpc and a linear bias of b ∼ 1.8-2.5. Finally, we discuss the simulation requirements implied by these measurements and demonstrate that the properties of the samples would make them excellent targets to enhance our understanding of the high-z universe.

79 ASTRONOMY AND ASTROPHYSICS↗