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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Modeling Malaria Transmission in Thailand and Indonesia

Malaria Modeling and Surveillance is a project in the NASA Applied Sciences Public Health Applications Program. The main objectives of this project are: 1) identification of the potential breeding sites for major vector species: 2) implementation of a malaria transmission model to identify they key factors that sustain or intensify malaria transmission; and 3) implementation of a risk algorithm to predict the occurrence of malaria and its transmission intensity. Remote sensing and GIs are the essential elements of this project. The NASA Earth science data sets used in this project include AVHRR Pathfinder, TRMM, MODIS, NSIPP and SIESIP. Textural-contextual classifications are used to identify small larval habitats. Neural network methods are used to model malaria cases as a function of precipitation, temperatures, humidity and vegetation. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Examples for spatio-temporal modeling of malaria transmissions in Southeast Asia are given. Discrete event simulations were used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results are in good agreement with mosquito vector and human malaria data acquired by Coleman et al. over 4.5 years in Kong Mong Tha, a remote village in western Thailand. Application of our models is not restricted to Southeast Asia. The model and techniques are equally applicable to other regions of the world, when appropriate epidemiological and vector ecological parameters are used as input.

Kiang, Richard↗
NASA NTRS1995

Assessment of climate variability of the Greenland ice sheet: Integration of in situ and satellite data

The proposed research involves the application of multispectral satellite data in combination with ground truth measurements to monitor surface properties of the Greenland ice sheet which are essential for describing the energy and mass of the ice sheet. Several key components of the energy balance are parameterized using satellite data and in situ measurements. The analysis will be done for a ten year time period in order to get statistics on the seasonal and interannual variations of the surface processes and the climatology. Our goal is to investigate to what accuracy and over what geographic areas large scale snow properties and radiative fluxes can be derived based upon a combination of available remote sensing and meterological data sets. Data analysis showed the following results: (1)cloud classification based on longwave sky radiation revealed that overcast sky occurred for 25% of the time in winter, and for 15% in spring and summer respectively (winter and summer both show the same occurrence of clear sky of approximately 26%); (2) comparison of aerodynamic profile method with eddy correlation method to derive sensible and latent heat flux showed good agreement in the diurnal cycle and the turbulent fluxes were underestimated with the aerodynamic method by 10 - 30% as compared to the in situ eddy flux method; (3) the katabatic wind shows a distinct diurnal cycle with a maximum in the morning (7-9 h solar time) and a minimum in the later afternoon (18 h solar time); (4) snow grain size was modeled with a surface energy balance model (SNTHERM) and compared with in situ measurements. Sharp decreases in the modeled snow grain size, caused by accumulation events such as precipitation and deposition, could be verified with observational data; (4) radiative transfer modeling of firn supports our beliefs that the observed trends in 18 and 19 GHz passive microwave brightness temperatures are attributable to accumulation rate changes (modeling also indicates the above relationship is detectable because of the presence of depth hoar; (5) snow melt can be detected by a distinct signal in the passive microwave cross-polarized gradient ratio (19h-37v)/(19h+37v) and has been used for wet/dry snow classification; (6) top of the atmosphere (TOA) broadband albedos were derived from AVHRR visible and near infrared reflectances for the entire ice sheet from May 1990 - June 1991, and the highest albedo values are found along the southeast coast of the ice sheet which is consistent with the summer peak of precipitation due to onshore flow loaded with high water vapor content (TOA albedo values dropped to around 40% along the south-western coast during July and August due to bare ice surfaces); and (7) the net all-wave radiation balance at the top of the atmosphere is negative over the entire ice sheet except for the summer months - June-July-August (in June, the net radiation balance is slightly positive over the dry snow areas--15 W/m2).

Steffen, K.↗
NASA NTRS1990

Classification of auroral precipitation fluxes by characteristic parameters and their effects on the coupling of the precipitation to the ambient ionosphere

The spectral shapes of the precipitating auroral electron flux spectra are quantified by an automated fitting procedure which represents each flux spectrum as a superposition of Maxwellian and Gaussian partial fluxes. This makes it possible to represent each spectrum by a set of characteristic parameters which describe the shape of that spectrum. A set of inverted-V events observed by the Low-Energy Plasma Instrument on Dynamics Explorer 2 near the fall 1981 equinox, has been analyzed. The distribution of the peak inverted-V energies in magnetic local time and invariant latitude (IL) has been obtained, and it is shown that by far the highest peak energies occur in the range of IL between 65 and 70 and MLT between 18 and 24 hrs. It is also shown how the difference in spectral characteristics of the precipitation fluxes between the cusp and the nighttime auroral zone determines the thermal coupling of the precipitation to the ambient ionosphere.

Fontheim, E. G.↗
NASA NTRS2020

Determination of Lidar Ratio for Major Aerosol Types over Western North Pacific Based on Long-Term MPLNET Data

East Asia is the most complex region in the world for aerosol studies, as it encounters a lot of varieties of aerosols, and aerosol classification can be a challenge in this region. In the present study, we focused on the relationship between aerosol types and aerosol optical properties. We analyzed the long-term (2005–2012) data of vertical profiles of aerosol extinction coefficients, lidar ratio (Sp), and other aerosol optical properties obtained from a NASA Micro-Pulse Lidar Network and Aerosol Robotic Network site in northern Taiwan, which frequently receives Asian continental outflows. Based on aerosol extinction vertical profiles, the profiles were classified into two types: type 1 (single-layer structure) and type 2 (two-layer structure). Fall season (October–November) was the prevailing season for the Type 1, whereas type 2 mainly happened in spring (March–April). In type 1, air masses normally originated from three regional sectors, i.e., Asia continental (AC), Pacific Ocean (PO), and Southeast Asia (SA). The mean Sp values were 39 ± 17 sr, 30 ± 12 sr, and 38 ± 18 sr for the AC, PO, and SA sectors, respectively. The Sp results suggested that aerosols from the AC sector contained dust and anthropogenic particles, and aerosols from the PO sector were most likely sea salts. We further combined the EPA dust event database and backward trajectory analysis for type 2. Results showed that Sp was 41 ± 14 sr and 53 ± 21 sr for dust storm and biomass-burning events, respectively. The Sp for biomass-burning events in type 2 showed two peaks patterns. The first peak occurred within range of 30–50 sr corresponding to urban pollutant, and the second peak occurred within range of 60–80 sr in relation to biomass burning. Finally, our study summarized the Sp values for four major aerosol types over northern Taiwan, viz., urban (42 ± 18 sr), dust (34 ± 6 sr), biomass-burning (69 ± 12 sr), and oceanic (30 ± 12 sr). Our findings provide useful references for aerosol classification and air pollution identification over the western North Pacific.

Sheng-Hsiang Wang↗
NASA NTRS2021

Flood Monitoring and Crop Damage Assessment

In recent years, the occurrence and impact of inland and coastal flood events have become more frequent and damaging, especially within agricultural fields, due to the global climate change and consistent sea level rise. Monitoring and measuring the magnitude of flood events in a timely manner and assessing the subsequent crop damages accurately are precursors in minimizing detrimental consequences that could potentially lead to a global food security crisis. Traditional gauge-based measurements with sophisticated hydrological models are capable of monitoring flood events precisely but limited within the smaller spatial extent, time-consuming, and costly. In recent decades, advancement in airborne- and satellite-based remote sensing technologies offering products at a daily global spatial extent with various spectral resolution helps address the shortcomings of the traditional in situ approaches in flood monitoring. Furthermore, the methods such as classification and band ratioing using remote sensing products are simple and effective in assessing flood-induced agricultural damages. The combination of remote sensing products and geographic information systems along with the current development in web mapping, users now can get near real-time flood monitoring and crop damage assessments, albeit dependent upon the quality of available data. A case study to quantify the impact of the 2011 Missouri Mississippi River flooding on the surrounding cornfield was performed through a regression model. The model was trained using historical daily NDVI and corn yield across Nebraska and Missouri, and the overall accuracy in estimating corn yield was about 90%. The method implemented in this localized case study could be extended at a larger geographical scale.

Flood monitoring↗
NASA NTRS1986

Distinguishing among tallgrass prairie cover types from measurements of multispectral reflectance

The heterogeneity in surface cover caused by management practices or natural events complicates monitoring the conditions of grasslands and assessing their productivity by remote sensing techniques. Statistical procedures were sought that would allow different grassland surface cover types (bare soil, senescent vegetation, and green vegetation) to be distinguished by using measurements of grassland multispectral reflectance. Two procedures, discriminant analysis and canonical discriminant analysis, were found suitable for achieving this objective. Linear classification functions and canonical variables were derived, which distinguish between the three cover types. A comparison between two sensor systems, a Barnes multiband radiometer and an Exotech radiometer that simulates the Landsat thematic mapper (TM) and multispectral scanner (MSS) bands, respectively, showed that the separability among the three cover types was substantially improved by the additional and improved spectral features of the Barnes radiometer.

Asrar, G.↗
NASA NTRS2004

GLAST Burst Monitor Trigger Classification Algorithm

The Gamma Ray Large Area Space Telescope (GLAST), currently set for launch in the first quarter of 2007, will consist of two instruments, the GLAST Burst Monitor (GBM) and the Large Area Telescope (LAT). One of the goals of the GBM is to identify and locate gamma-ray bursts using on-board software. The GLAST observatory can then be re-oriented to allow observations by the LAT. A Bayesian analysis will be used to distinguish gamma-ray bursts from other triggering events, such as solar flares, magnetospheric particle precipitation, soft gamma repeaters (SGRs), and Cygnus X-1 flaring. The trigger parameters used in the analysis are the burst celestial coordinates, angle from the Earth's horizon, spectral hardness, and the spacecraft geomagnetic latitude. The algorithm will be described and the results of testing will be presented.

Perrin, D. J.↗
NASA NTRS1977

Chemistry of Apollo 12 mare basalts - Magma types and fractionation processes

Major and trace element data for a large suite of petrographically diverse Apollo 12 mare basalts are presented, and magma types sampled at the Apollo 12 site are characterized. The data confirm earlier classifications of the basalts into olivine, pigeonite, ilmenite, and feldspathic basalts. The olivine and pigeonite basalts are shown to be comagnetic and related by olivine fractionation. The other types, which differ in trace element and isotopic characteristics, are derived from different sources within the lunar interior. The spatial relations between the main basalt types are discussed in terms of local cratering events, and it is suggested that the younger ilmenite basalts overlie the olivine-pigeonite basalts. The role of olivine-dominated near-surface crystal fractionation in causing chemical variation is examined, and a relation between inferred cooling rate and the position of a sample in the fractionation sequence is determined.

Rhodes, J. M.↗
NASA NTRS2007

On the Prompt Gamma-ray Emission Properties of Short GRBs

Short Gamma-Ray Bursts have been identified as a separate class of events with distinct spectral and temporal properties from their long (>2 seconds) counterparts. Although multi-wavelength transients and their host galaxies had been found for the latter, it was only after the launch of the Swift satellite that short GRB counterparts and hosts were discovered and studied in detail. Currently, over a dozen short events have been detected with less than half having a measured redshift. Since 199 1 , GRB durations were established using BATSE gamma-ray light-curves; it is becoming, however, gradually evident from the Swift/BAT data, that we now need to fold spectral dependence, in particular prompt gamma-ray emission spectral time lags, into a multi-parameter GRB classification scheme. I will discuss here the properties of the prompt gamma-rays of all Swift short GRBs, compare them to those detected with BATSE and other missions and comment on the implications of the different subclass population each mission is probing.

Kouveliotou, Chryssa↗
NASA NTRS2017

iPTF17cw: An Engine-Driven Supernova Candidate Discovered Independent of a Gamma-Ray Trigger

We present the discovery, classification, and radio-to-X-ray follow-up observations of iPTF17cw, a broad-lined (BL) type Ic supernova (SN) discovered by the intermediate Palomar Transient Factory (iPTF). Although it is unrelated to the gravitational wave trigger, this SN was discovered as a happy by-product of the extensive observational campaign dedicated to the follow-up of Advanced LIGO event GW 170104. The spectroscopic properties and inferred peak bolometric luminosity of iPTF17cw are most similar to the gamma-ray-burst (GRB)- associated SN, SN 1998bw, while the shape of the r-band light curve is most similar to that of the relativistic SN, SN 2009bb. Karl G. Jansky Very Large Array (VLA) observations of the iPTF17cw field reveal a radio counterpart approximately 10 times less luminous than SN 1998bw, and with a peak radio luminosity comparable to that of SN 2006aj/GRB 060218 and SN 2010bh/GRB 100316D. Our radio observations of iPTF17cw imply a relativistically expanding outflow. However, further late-time observations with the VLA in its most extended configuration are needed to confirm fading of the iPTF17cw radio counterpart at all frequencies. X-ray observations carried out with Chandra reveal the presence of an X-ray counterpart with a luminosity similar to that of SN 2010bh/GRB 100316D. Searching the Fermi catalog for possible gamma-rays reveals that GRB 161228B is spatially and temporally compatible with iPTF17cw. The similarity to SN 1998bw and SN 2009bb, the radio and X-ray detections, and the potential association with GRB 161228B all point to iPTF17cw being a new candidate member of the rare sample of optically discovered engine-driven BL-Ic SNe associated with relativistic ejecta.

Corsi, A.↗
NASA NTRS1988

Object oriented studies into artificial space debris

A prototype simulation is being developed under contract to the Royal Aerospace Establishment (RAE), Farnborough, England, to assist in the discrimination of artificial space objects/debris. The methodology undertaken has been to link Object Oriented programming, intelligent knowledge based system (IKBS) techniques and advanced computer technology with numeric analysis to provide a graphical, symbolic simulation. The objective is to provide an additional layer of understanding on top of conventional classification methods. Use is being made of object and rule based knowledge representation, multiple reasoning, truth maintenance and uncertainty. Software tools being used include Knowledge Engineering Environment (KEE) and SymTactics for knowledge representation. Hooks are being developed within the SymTactics framework to incorporate mathematical models describing orbital motion and fragmentation. Penetration and structural analysis can also be incorporated. SymTactics is an Object Oriented discrete event simulation tool built as a domain specific extension to the KEE environment. The tool provides facilities for building, debugging and monitoring dynamic (military) simulations.

Adamson, J. M.↗
NASA NTRS2011

Thermal Evolution of Solar Flares During the First Year of SDO as Seen by the EVE Instrument

It is very evident during the first year of the Solar Dynamics Observatory (SDO) that the Sun awoke from its prolonged minimum and is well into solar cycle 24. There has been tens of moderate M-class flares and a large X-class event (as of abstract submission), with more surely to come as the solar cycle activity increases. With SDO's 24/7 observations, every single flare has been observed through their entire evolution, providing new insights in the thermal evolution of every flare. It is evident that this evolution is extremely different for many of the flares, even for flares with similar X-ray magnitude classifications. Presented and discussed will be these different flares with their varying thermal evolution profiles as observed by the Extreme ultraviolet Variability Experiment (EVE) onboard the Solar Dynamics Observatory (SDO).

Chamberlin, Phillip C.↗
NASA NTRS2024

EdgeCortix SAKURA-I Machine-Learning, PCIe Accelerator SEE Heavy Ion Test Report

To enable autonomy in space, machine-learning and computer vision applications become invaluable for sensor processing. However, these algorithms are computationally complex and unfeasible for many embedded central processing units (CPUs) and usually require external coprocessors, such as graphics processing units (GPUs) or accelerators specific to the application, including application specific integrated circuits (ASICs). In power-constrained systems, GPUs tend to consume more power than is acceptable (>40W), so lower-power accelerators have shown promise to provide the performance needed under spacecraft constraints. For radiation engineers, developing methodologies that can properly test CPUs, GPUs, and accelerators, and enable comparisons between them remains a necessary complication to solve as the devices become more complex. The methodology in this test aims to be a start in developing a baseline single-event effect (SEE) test for client-device machine learning accelerators. This category of devices do not host their own operating system. This testing campaign is a continuation of a previous 200 MeV proton test performed in January 2024. This report covers two heavy ion tests of the SAKURA-I card: one in April 2024, and one in June 2024. Additional data was needed after the April test due to ion-range issues experienced at higher linear-energy transfers (LETs). These range issues are described in more detail in Section 8. This experiment characterizes SEEs and data error susceptibility of the EdgeCortix SAKURA-I machine-learning accelerator under heavy ions. The device was monitored for single event upsets (SEUs) and single event functional interrupts (SEFIs) at the Lawrence Berkeley National Laboratory’s 88-inch cyclotron. The SAKURA-I board accelerates machine-learning inference applications on a host computer through a PCIex16 connection. For the purposes of devising an end to end automated analysis workflow for this experiment, the YOLO-V5 and SSD300 objection-detection models, and the ResNet-50, EfficientNet, and MobileNetV2 image classification models were used as a representative suite of analytical machine-learning models.

Seth S Roffe↗
NASA NTRS2020

Assessment of Extremes in Global Precipitation Products: How Reliable Are They?

Global gridded precipitation products have proven essential for many applications ranging from hydrological modeling and climate model validation to natural hazard risk assessment. They provide a global picture of how precipitation varies across time and space, specifically in regions where ground-based observations are scarce. While the application of global precipitation products has become widespread, there is limited knowledge on how well these products represent the magnitude and frequency of extreme precipitation—the key features in triggering flood hazards. Here, five global precipitation datasets (MSWEP, CFSR, CPC, PERSIANN-CDR, and WFDEI) are compared to each other and to surface observations. The spatial variability of relatively high precipitation events (tail heaviness) and the resulting discrepancy among datasets in the predicted precipitation return levels were evaluated for the time period 1979–2017. The analysis shows that 1) these products do not provide a consistent representation of the behavior of extremes as quantified by the tail heaviness, 2) there is strong spatial variability in the tail index, 3) the spatial patterns of the tail heaviness generally match the Köppen–Geiger climate classification, and 4) the predicted return levels for 100 and 1000 years differ significantly among the gridded products. More generally, our findings reveal shortcomings of global precipitation products in representing extremes and highlight that there is no single global product that performs best for all regions and climates.

Risk assessment↗
NASA NTRS1976

Efficient detection, analysis and classification of lightning radiation fields

Modeling the large scale lightning flash structure is considered. Large scale flash data has been measured from strip charts of storms of August 5, August 26, and September 12, 1975. The data is being processed by a computer program called SASEV to estimate the large scale flash statistics. The program, experimental results, and conclusions for the large scale flash structure are described. The progress made in examining the internal flash structure consists mainly of developing the software required to process the NASA digital tape data. A FORTRAN program has been written for the statistical analysis of series of events. The statistics computed and tests performed are found to be particularly useful in the analysis of lightning data.

Harger, R. O.↗
NASA NTRS1974

Study of the characteristics of seismic signals generated by natural and cultural phenomena

Seismic data recorded at the Tonto Forest Seismological Observatory in Arizona and the Uinta Basin Seismological Observatory in Utah were used to compare the frequency of occurrence, severity, and spectral content of ground motions resulting from earthquakes, and other natural and man-made sources with the motions generated by sonic booms. A search of data recorded at the two observatories yielded a classification of over 180,000 earthquake phase arrivals on the basis of frequency of occurrence versus maximum ground velocity. The majority of the large ground velocities were produced by seismic surface waves from moderate to large earthquakes in the western United States, and particularly along the Pacific Coast of the United States and northern Mexico. A visual analysis of raw film seismogram data over a 3-year period indicates that local and regional seismic events, including quarry blasts, are frequent in occurrence, but do not produce ground motions at the observatories comparable to either the large western United States earthquakes or to sonic booms. Seismic data from the Nevada Test Site nuclear blasts were used to derive magnitude-distance-sonic boom overpressure relations.

Goforth, T. T.↗
NASA NTRS2022

Arizona Water Resources: Utilizing Aerial Imagery and NASA Earth Observations to Assess Pinyon-Juniper Tree Mortality in Flagstaff, AZ

Pinyon-juniper woodlands (PJW) are a vital habitat and food source for several wildlife species and a source of both utility and cultural importance for Indigenous groups. In 2021, amidst a decades-long drought, an extensive juniper mortality event occurred at Wupatki National Monument (WNM) in Arizona. In response, the National Park Service (NPS) is evaluating which land management practices will be beneficial. In partnership with the NPS, the NASA DEVELOP team used remote sensing data to map PJW mortality and analyze the relation of tree mortality to stand density, climate, and topography in north-central Arizona from 2015 to 2021. To identify the extent of PJW, the team performed an unsupervised classification using National Agricultural Imagery Program (NAIP) data with validation sources including NPS-created land cover maps, Landscape Fire and Resource Management Planning Tools (LANDFIRE), NPS and United States Forest Service (USFS) vegetation maps, and Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) data. Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG), Soil Moisture Active Passive (SMAP), Shuttle Radar Topography Mission (SRTM), and Landsat 8-derived Normalized Difference Vegetation Index (NDVI) and Normalized Difference Moisture Index (NDMI) were used to analyze factors contributing to pinyon-juniper mortality. Although no relationships were found in the broader study region, PJW mortality was weakly correlated to elevation, soil moisture, and land surface temperature within WNM. Results from this study can inform NPS vegetation management that best protects natural and cultural resources.

Margaret Jaenicke↗
NASA NTRS1972

A classification of magnetic field configurations associated with solar flares.

On the assumption that solar flares are due to instabilities which occur in current sheets in the sun's atmosphere, one may classify magnetic-field configurations associated with flares into two types. One is characterized by 'closed' current sheets, magnetic-field lines adjacent to these sheets beginning and ending at the sun's surface. The other is characterized by 'open' current sheets, magnetic-field lines adjacent to these sheets beginning at the sun's surface but extending out into interplanetary space. Flares associated with open current sheets can produce Type III radio bursts and high-energy-particle events, but flares associated with closed current sheets cannot. The flare of July 6, 1966 apparently consisted of one flare of each type.

Sturrock, P. A.↗