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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Investigating the Impact of UV Radiation on High-Altitude Shallow Lake Habitats, Life Diversity, and Life Survival Strategies: Clues for Mars' Past Habitability Potential?

We present data and results from an ongoing project of astrobiological high-altitude expeditions investigating the highest and least explored perennial lakes on Earth in the Bolivian and Chilean Andes, including several volcanic crater lakes nearing and beyond 6,000 m in elevation. In the next five years, they will provide the first integrated long-term astrobiological characterization and monitoring of lacustrine environments and their biology for such altitude. These extreme lakes are natural laboratories. They provide the field data missing beyond 4,000 m to complete our understanding of terrestrial lakes and biota. Research on the effects of UV has been performed in lower altitude lakes and models of UV flux over time are being developed. Lakes showing a high content of dissolved organic material (DOM) shield organisms from UV. DOM acts as a natural sunscreen as it influences the water transparency, therefore is a determinant of photic zone depth. In sparsely vegetated alpine areas, lakes are clearer and offer less protection from UV to organisms living in the water. Transparent water and high UV irradiance may maximize the penetration and effect of UV radiation. Shallow-water communities in these lakes are particularly sensitive to UV radiation. The periphyton can live on various susbtrates. While on rocks, it includes immobile species that cannot seek low UV refuges unlike sediment-dwelling periphyton or alpine phytoflagellates which undergo vertical migration. Inhibition of algal photosynthesis by UV radiation has been documented in laboratory and showed that phytoplankton production is reduced by formation of nucleic acid lesions or production of peroxides and free oxygen radicals. of peroxides and free oxygen radicals. Our project is providing the field data that is missing from natural laboratories beyond 4,000 m and will complement the vision of the effects of UV on life and its adaptation modes (or lack thereof).

Cabrol, A.↗
NASA NTRS2010

Evaluating Failures and near Misses in Human Spaceflight History for Lessons for Future Human Spaceflight

Studies done in the past have drawn on lessons learned with regard to human loss-of-life events. However, an examination of near-fatal accidents can be equally useful, not only in detecting causes, both proximate and systemic, but also for determining what factors averted disaster, what design decisions and/or operator actions prevented catastrophe. Binary pass/fail launch history is often used for risk, but this also has limitations. A program with a number of near misses can look more reliable than a consistently healthy program with a single out-of-family failure. Augmenting reliability evaluations with this near miss data can provide insight and expand on the limitations of a strictly pass/fail evaluation. This paper intends to show how near-miss lessons learned can provide crucial data for any new human spaceflight programs that are interested in sending man into space

Barr, Stephanie↗
DOE OSTI2019

Proteomic studies of bone and skeletal health outcomes

Proteins are an essential part of essentially all biological processes, and there is enormous variation in protein forms and concentrations that is not reflected in DNA or RNA. Recently there have been rapid advances in the ability to measure protein sequence, modification and concentration, particularly with methods based in mass spectrometry. Global measures of proteins in tissues or in the circulation provide a broad assessment of the proteome that can be extremely useful for discovery, and targeted proteomic measures can yield specific and sensitive assessments of specific peptides and proteins. While most proteomic measures are directed at the detection of consensus peptide sequences, mass spectrometry based proteomic methods also allow a detailed examination of the peptide sequence differences that result from genetic variants and that may have important effects on protein function. In evaluating proteomic data, a number of analytical considerations are important, including an understanding of missing data, the challenge of multiple testing and replication, and the use of rapidly evolving methods in systems biology. While proteomics has not yet had a major impact in skeletal research, interesting recent research has used these approaches in the study of bone cell biology and the discovery of biomarkers of skeletal disorders. Proteomics can be expected to have an increasing influence in the study of bone biology and pathophysiology

Proteomic, Bone↗
DOE OSTI2019

Accelerating full waveform inversion via source stacking and cross-correlations

SUMMARY Accurate synthetic seismic wavefields can now be computed in 3-D earth models using the spectral element method (SEM), which helps improve resolution in full waveform global tomography. However, computational costs are still a challenge. These costs can be reduced by implementing a source stacking method, in which multiple earthquake sources are simultaneously triggered in only one teleseismic SEM simulation. One drawback of this approach is the perceived loss of resolution at depth, in particular because high-amplitude fundamental mode surface waves dominate the summed waveforms, without the possibility of windowing and weighting as in conventional waveform tomography. This can be addressed by redefining the cost-function and computing the cross-correlation wavefield between pairs of stations before each inversion iteration. While the Green’s function between the two stations is not reconstructed as well as in the case of ambient noise tomography, where sources are distributed more uniformly around the globe, this is not a drawback, since the same processing is applied to the 3-D synthetics and to the data, and the source parameters are known to a good approximation. By doing so, we can separate time windows with large energy arrivals corresponding to fundamental mode surface waves. This opens the possibility of designing a weighting scheme to bring out the contribution of overtones and body waves. It also makes it possible to balance the contributions of frequently sampled paths versus rarely sampled ones, as in more conventional tomography. Here we present the results of proof of concept testing of such an approach for a synthetic 3-component long period waveform data set (periods longer than 60 s), computed for 273 globally distributed events in a simple toy 3-D radially anisotropic upper mantle model which contains shear wave anomalies at different scales. We compare the results of inversion of 10 000 s long stacked time-series, starting from a 1-D model, using source stacked waveforms and station-pair cross-correlations of these stacked waveforms in the definition of the cost function. We compute the gradient and the Hessian using normal mode perturbation theory, which avoids the problem of cross-talk encountered when forming the gradient using an adjoint approach. We perform inversions with and without realistic noise added and show that the model can be recovered equally well using one or the other cost function. The proposed approach is computationally very efficient. While application to more realistic synthetic data sets is beyond the scope of this paper, as well as to real data, since that requires additional steps to account for such issues as missing data, we illustrate how this methodology can help inform first order questions such as model resolution in the presence of noise, and trade-offs between different physical parameters (anisotropy, attenuation, crustal structure, etc.) that would be computationally very costly to address adequately, when using conventional full waveform tomography based on single-event wavefield computations.

Romanowicz, Barbara↗
DOE OSTI2016

SU-F-T-78: Minimum Data Set of Measurements for TG 71 Based Electron Monitor-Unit Calculations

Purpose: Building up a TG-71 based electron monitor-unit (MU) calculation protocol usually involves massive measurements. This work investigates a minimum data set of measurements and its calculation accuracy and measurement time. Methods: For 6, 9, 12, 16, and 20 MeV of our Varian Clinac-Series linear accelerators, the complete measurements were performed at different depth using 5 square applicators (6, 10, 15, 20 and 25 cm) with different cutouts (2, 3, 4, 6, 10, 15 and 20 cm up to applicator size) for 5 different SSD’s. For each energy, there were 8 PDD scans and 150 point measurements for applicator factors, cutout factors and effective SSDs that were then converted to air-gap factors for SSD 99–110cm. The dependence of each dosimetric quantity on field size and SSD was examined to determine the minimum data set of measurements as a subset of the complete measurements. The “missing” data excluded in the minimum data set were approximated by linear or polynomial fitting functions based on the included data. The total measurement time and the calculated electron MU using the minimum and the complete data sets were compared. Results: The minimum data set includes 4 or 5 PDD’s and 51 to 66 point measurements for each electron energy, and more PDD’s and fewer point measurements are generally needed as energy increases. Using only <50% of complete measurement time, the minimum data set generates acceptable MU calculation results compared to those with the complete data set. The PDD difference is within 1 mm and the calculated MU difference is less than 1.5%. Conclusion: Data set measurement for TG-71 electron MU calculations can be minimized based on the knowledge of how each dosimetric quantity depends on various setup parameters. The suggested minimum data set allows acceptable MU calculation accuracy and shortens measurement time by a few hours.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2019

Relativistic large scale CI calculations of energies, transition rates and lifetimes in Ca-like ions between Co VIII and Zn XI

Energies, E1, E2 and M1 transition rates and lifetimes are reported for the lowest 134 fine-structure levels of the 3p{sup 6}3d{sup 2}, 3p{sup 6}3d4s, 3p{sup 5}3d{sup 3} and 3p{sup 6}3d4p configurations in all Ca-like ions between Co VIII and Zn XI. The calculations have been performed using the multiconfiguration Dirac–Hartree–Fock (MCDHF) and relativistic configuration interaction (RCI) methods. Important core–valance and core–core electron correlation effects are systematically accounted with large scale configuration interaction expansion. The Breit interaction and leading quantum-electrodynamical (QED) contributions such as the vacuum polarization and self-energy corrections are also included in the RCI calculations. The results are compared with the compiled data from the NIST ASD and other calculations to evaluate the accuracy of the present calculations. Our results have good agreement with previous relativistic many-body perturbation theory (RMBPT) calculations and the data from the NIST ASD, except for Zn XI. Present calculations provide some missing data, especially for Cu X and Zn XI, in the NIST ASD.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

WE-EF-207-09: Single-Scan Dual-Energy CT Using Primary Modulation

Purpose: Compared with conventional CT, dual energy CT (DECT) provides better material differentiation but requires projection data with two different effective x-ray spectra. Current DECT scanners use either a two-scan setting or costly imaging components, which are not feasible or available on open-gantry cone-beam CT systems. We propose a hardware-based method which utilizes primary modulation to enable single-scan DECT on a conventional CT scanner. The CT imaging geometry of primary modulation is identical to that used in our previous method for scatter removal, making it possible for future combination with effective scatter correction on the same CT scanner. Methods: We insert an attenuation sheet with a spatially-varying pattern - primary modulator-between the x-ray source and the imaged object. During the CT scan, the modulator selectively hardens the x-ray beam at specific detector locations. Thus, the proposed method simultaneously acquires high and low energy data. High and low energy CT images are then reconstructed from projections with missing data via an iterative CT reconstruction algorithm with gradient weighting. Proof-of-concept studies are performed using a copper modulator on a cone-beam CT system. Results: Our preliminary results on the Catphan(c) 600 phantom indicate that the proposed method for single-scan DECT is able to successfully generate high-quality high and low energy CT images and distinguish different materials through basis material decomposition. By applying correction algorithms and using all of the acquired projection data, we can reconstruct a single CT image of comparable image quality to conventional CT images, i.e., without primary modulation. Conclusion: This work shows great promise in using a primary modulator to perform high-quality single-scan DECT imaging. Future studies will test method performance on anthropomorphic phantoms and perform quantitative analyses on image qualities and DECT decomposition accuracy. We will use simulations to optimize the modulator material and geometry parameters.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Single-frame far-field diffractive imaging with randomized illumination

We introduce a single-frame diffractive imaging method called randomized probe imaging (RPI). In RPI, a sample is illuminated by a structured probe field containing speckles smaller than the sample’s typical feature size. Quantitative amplitude and phase images are then reconstructed from the resulting far-field diffraction pattern. The experimental geometry of RPI is straightforward to implement, requires no near-field optics, and is applicable to extended samples. When the resulting data are analyzed with a complimentary algorithm, reliable reconstructions which are robust to missing data are achieved. To realize these benefits, a resolution limit associated with the numerical aperture of the probe-forming optics is imposed. RPI therefore offers an attractive modality for quantitative X-ray phase imaging when temporal resolution and reliability are critical but spatial resolution in the tens of nanometers is sufficient. We discuss the method, introduce a reconstruction algorithm, and present two proof-of-concept experiments: one using visible light, and one using soft X-rays.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS1997

Monitoring Earth's Ecosystems

Partnered with Goddard Space Flight Center, Sensit Technologies Inc. developed a third-generation Portable Apparatus for Rapid Acquisitions of Bidirectional Observations of Land and Atmosphere, or PARABOLA III for short. Now commercially available, PARABOLA III is designed to measure the reflected signature of a variety of Earth surface types, from rangeland vegetation to ice and snow. It can rapidly acquire data for almost the complete sky and ground-looking hemispheres, with no missing data and sufficient dynamic range to measure direct solar radiance. The instrument was actively used in the Boreal Ecosystem- Atmosphere Study which provided useful information in designing a Multi-angle Imaging SpectroRadiometer, a small satellite being built by the Jet Propulsion Laboratory that will measure sunlight reflected by the Earth into space.

Source record↗
DOE OSTI2017

Atmospheric Radiation Measurement Climate Research Facility Operations Quarterly Report April 1-June 30, 2017

Individual datastreams from instrumentation at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility fixed and mobile research observatories (sites) are collected and routed to the ARM Data Center (ADC). The Data Management Facility (DMF), a component of the ADC, executes datastream processing in near-real time. Processed data are then delivered approximately daily to the ARM Data Archive, also a component of the ADC, where they are made freely available to the research community. For each instrument, ARM calculates the ratio of the actual number of processed data records received daily at the ARM Data Archive to the expected number of data records. DOE requires national user facilities to report time-based operating data. The requirements involve: Actual hours of operation (ACTUAL)—24 hours per day, 91 days or 2184 hours for this quarter Estimated maximum operation or uptime target (TARGET) Variance (VARIANCE), which is equal to (1–[ACTUAL/TARGET]) TARGET and VARIANCE numbers account for unplanned downtime. Differences in TARGET performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure TARGET for each instrument or datastream. Data availability reported here refers to the average of the individual, continuous datastreams received by the ARM Data Archive. Therefore, data availability is directly related to individual instrument uptime expressed in hours. Data not at the ARM Data Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Missing data caused by scheduled downtime are not included in the metrics. Thus, the average percentage of data in the ARM Data Archive represents the average percentage of the time the instruments were operating for the quarter.

Aerosol↗
DOE OSTI2017

Atmospheric Radiation Measurement Climate Research Facility Operations Quarterly Report January 1-March 31, 2017

Individual datastreams from instrumentation at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility fixed and mobile research observatories (sites) are collected and routed to the ARM Data Center (ADC). The Data Management Facility (DMF), a component of the ADC, executes datastream processing in near-real time. Processed data are then delivered approximately daily to the ARM Data Archive, also a component of the ADC, where they are made freely available to the research community. For each instrument, ARM calculates the ratio of the actual number of processed data records received daily at the ARM Data Archive to the expected number of data records. DOE requires national user facilities to report time-based operating data. The requirements involve: Actual hours of operation (ACTUAL)—24 hours per day, 90 days or 2160 hours for this quarter Estimated maximum operation or uptime target (TARGET) Variance (VARIANCE), which is equal to (1–[ACTUAL/TARGET]) TARGET and VARIANCE numbers account for unplanned downtime. Differences in TARGET performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure TARGET for each instrument or datastream. Data availability reported here refers to the average of the individual, continuous datastreams received by the ARM Data Archive. Therefore, data availability is directly related to individual instrument uptime expressed in hours. Data not at the ARM Data Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Missing data caused by scheduled downtime are not included in the metrics. Thus, the average percentage of data in the ARM Data Archive represents the average percentage of the time the instruments were operating for the quarter.

Eastern North Atlantic, Southern Great Plains, Nor↗
DOE OSTI2017

Atmospheric Radiation Measurement Climate Research Facility Operations Quarterly Report July 1-September 30, 2016

Individual datastreams from instrumentation at the Atmospheric Radiation Measurement (ARM) Climate Research Facility fixed and mobile research sites are collected and routed to the Data Management Facility (DMF) for processing in near-real time. Instrument and processed data are then delivered approximately daily to the ARM Data Archive, where they are made freely available to the research community. For each instrument, ARM calculates the ratio of the actual number of processed data records received daily at the ARM Data Archive to the expected number of data records. The results are tabulated by 1) individual datastream, site, and month for the current year, and 2) site and fiscal year dating back to 1998. The U.S. Department of Energy requires national user facilities to report time-based operating data. The requirements involve the: Actual hours of operation (ACTUAL) – 24 hours per day, 92 days or 2208 hours for this quarter Estimated maximum operation or uptime target (TARGET) Variance (VARIANCE), which is equal to (1 – [ACTUAL/TARGET]) TARGET and VARIANCE numbers account for unplanned downtime. Differences in TARGET performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure TARGET for each instrument or datastream. Data availability reported here refers to the average of the individual, continuous datastreams received by the ARM Data Archive. Therefore, data availability is directly related to individual instrument uptime expressed in hours. Data not at the ARM Data Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Missing data caused by scheduled downtime are not included in the metrics. Thus, the average percentage of data in the ARM Data Archive represents the average percentage of the time the instruments were operating for the quarter.

Southern Great Plains, North Slope of Alaska, East↗
DOE OSTI2016

Atmospheric Radiation Measurement Climate Research Facility Operations Quarterly Report April 1-June 30, 2016

Individual datastreams from instrumentation at the Atmospheric Radiation Measurement (ARM) Climate Research Facility fixed and mobile research sites are collected and routed to the Data Management Facility (DMF) for processing in near-real time. Instrument and processed data are then delivered approximately daily to the ARM Data Archive, where they are made freely available to the research community. For each instrument, ARM calculates the ratio of the actual number of processed data records received daily at the ARM Data Archive to the expected number of data records. The results are tabulated by 1) individual datastream, site, and month for the current year, and 2) site and fiscal year dating back to 1998. The U.S. Department of Energy requires national user facilities to report time-based operating data. The requirements involve the: Actual hours of operation (ACTUAL) – 24 hours per day, 91 days or 2184 hours for this quarter Estimated maximum operation or uptime target (TARGET) Variance (VARIANCE), which is equal to (1 – [ACTUAL/TARGET]) TARGET and VARIANCE numbers account for unplanned downtime. Differences in TARGET performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure TARGET for each instrument or datastream. Data availability reported here refers to the average of the individual, continuous datastreams received by the ARM Data Archive. Therefore, data availability is directly related to individual instrument uptime expressed in hours. Data not at the ARM Data Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Missing data caused by scheduled downtime are not included in the metrics. Thus, the average percentage of data in the ARM Data Archive represents the average percentage of the time the instruments were operating for the quarter.

North Slope of Alaska, Eastern North Atlantic, Sou↗
DOE OSTI2018

Preliminary Long-term Safety Assessment for the Planned LLW Disposal Facility at Al-Tuwaitha, Iraq - 18142

Before 1991, Iraq had a significant nuclear program which encompassed ten nuclear sites spread out across the country. The largest nuclear site was located at the Al-Tuwaitha site near Baghdad where 18 nuclear facilities were concentrated. During the first Gulf War in 1991, all sites suffered significant damage from bombing and subsequent looting. Currently, the Ministry of Science and Technology is responsible for the ten heavily damaged nuclear sites and for the management of radioactive waste in Iraq in general. The task of decommissioning the damaged nuclear facilities and managing the resulting waste is being supported by the International Atomic Energy Agency (IAEA), the European Commission (EC), and the United States (US). In the framework of its Instrument for Nuclear Safety Cooperation (INSC), the EC has launched a cooperation project to support the planned construction of an engineered repository for short-lived low- and intermediate level waste for the safe disposal of radioactive waste resulting from the decommissioning activities, as well as for waste from the continuing use of radioisotopes in medicine and the oil and gas industry in the country. The main objectives of this project, which was awarded to a Consortium led by NUKEM Technologies Engineering Services GmbH and joined by DBE Technology GmbH of Germany and JAVYS a.s. of Slovakia, are the development of an initial conceptual level basic design and preliminary safety assessment report (PSAR) and the subsequent detailed engineering design and supporting pre-construction safety assessment report (PCSAR). The current paper focuses on the development of the PSAR. Special focus is given to the long-term calculations and difficulties associated with the limited data base in regard to site characterization as well as the expected inventory for the future repository. Because of the ongoing security concerns in Iraq, the Ministry of Science and Technology had already selected the Al-Tuwaitha Site as the best suited location for the planned surface repository at the start of the project. Although some site characterization work had already been carried out prior to the start of the project, certain data for modelling the geology and hydrology of the site are still lacking. Missing data have been compensated by conservative assumptions and the assessment of alternative scenarios. Consequently, for the development of the simplified GoldSim{sup R} computer model used to carry out the long-term calculations supporting the PSAR, existing site information was used and, as appropriate, amended or replaced by conservative assumptions. Due to the nature of the waste, data on the expected inventory are associated with large uncertainties. Although certain estimates related to the future volume of the waste exist, little to no information is available on the expected radionuclide vector and respective activities. Therefore, the long-term calculations were carried out for a generic inventory including a broad range of radionuclides that are to be expected as being important considering the kind of waste to be disposed of in the facility. Based on the results of these calculations, the maximum total capacity of the facility was estimated and converted into activity limits for individual radionuclides that will be integrated into the existing general WAC for the facility. Compliance with these WAC will then guarantee the safety of the repository in regard to potential radionuclide releases via the groundwater pathway. In parallel to the determination of activity limits for the WAC, long-term calculations were carried using different estimates for the expected total activity to determine the general suitability of the proposed technical solution of the repository for receiving the total amount of Iraqi radioactive waste principally acceptable for surface disposal. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

A Scalable Multi-Modal Framework for High-Fidelity Distributed Human Mobility Simulations

The development of data-driven models for human mobility in urban settings requires access to substantial and diverse real-world data. However, existing historical data often presents challenges such as limited volume, variety, and veracity, as well as missing data and privacy preservation concerns. Also, urban mobility modeling is inherently time-variant, complex, and multi-modal, encompassing everything from individual walking and running to private road travel and large-scale public transportation. These challenges call for innovative solutions to overcome data limitations and compute needs to model mobility behaviors accurately. To address these challenges, we propose a distributed, co-simulation-based architecture DURMOSim that integrates real-world data with scalable, high-fidelity simulations, demonstrating distributed co-simulation feasibility with existing mobility models. DURMOSim underpins a modular integration that would enable using any available mobility simulators for greater extensibility and scalability in performing various urban scenarios. In this paper, we present the design, implementation, and performance evaluation of DURMOSim, highlighting its capability to model population-scale mobility patterns. Our initial results show its ability to dynamically synchronize multiple simulation models at runtime with negligible computational overhead. We believe DURMOSim could be a robust tool for advancing urban mobility research and intelligent transportation systems.

Yoginath, Srikanth [ORNL] (ORCID:0000000184236050)↗
DOE OSTI2022

Nuclide Inventory Benchmark for BWR Spent Nuclear Fuel: Challenges in Evaluation of Modeling Data Assumptions and Uncertainties

This work discusses challenges and approaches to uncertainty analyses associated with the development of a nuclide inventory benchmark for fuel irradiated in a boiling water reactor. The benchmark under consideration is being developed based on experimental data from the SFCOMPO international database. The focus herein is on how to address missing data in fuel design and operating conditions that are important for adequately simulating the time-dependent changes in fuel during irradiation in the reactor. The effects of modeling assumptions and uncertainties in modeling parameters on the calculated nuclide inventory were analyzed and quantified through computational models developed using capabilities in the SCALE code system. Particular attention was given to the impact of the power history and water coolant density on the calculated nuclide inventory, as well as to the effect of geometry modeling considerations not usually addressed in a nuclide inventory benchmark. These considerations include gap closure, channel bow, and channel corner radius, which do not usually apply to regular reactor operation but are relevant for assessing impacts of potential anomalous operating scenarios.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

A Dynamic Landsat Derived Normalized Difference Vegetation Index (NDVI) Product for the Conterminous United States

Satellite derived vegetation indices (VIs) are broadly used in ecological research, ecosystem modeling, and land surface monitoring. The Normalized Difference Vegetation Index (NDVI), perhaps the most utilized VI, has countless applications across ecology, forestry, agriculture, wildlife, biodiversity, and other disciplines. Calculating satellite derived NDVI is not always straight-forward, however, as satellite remote sensing datasets are inherently noisy due to cloud and atmospheric contamination, data processing failures, and instrument malfunction. Readily available NDVI products that account for these complexities are generally at coarse resolution; high resolution NDVI datasets are not conveniently accessible and developing them often presents numerous technical and methodological challenges. Here, we address this deficiency by producing a Landsat derived, high resolution (30 m), long-term (30+ years) NDVI dataset for the conterminous United States. We use Google Earth Engine, a planetary-scale cloud-based geospatial analysis platform, for processing the Landsat data and distributing the final dataset. We use a climatology driven approach to fill missing data and validate the dataset with established remote sensing products at multiple scales. We provide access to the composites through a simple web application, allowing users to customize key parameters appropriate for their application, question, and region of interest.

42 ENGINEERING↗
NASA NTRS2017

Informal Statistics Help Desk

Back by popular demand, the JSC Biostatistics Laboratory and LSAH statisticians are offering an opportunity to discuss your statistical challenges and needs. Take the opportunity to meet the individuals offering expert statistical support to the JSC community. Join us for an informal conversation about any questions you may have encountered with issues of experimental design, analysis, or data visualization. Get answers to common questions about sample size, repeated measures, statistical assumptions, missing data, multiple testing, time-to-event data, and when to trust the results of your analyses.

Young, M.↗