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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Quantum dot lightning detection and warning system and method

A quantum dot (QD) lightning detection and warning (LDW) system and method. This LDW system and method find broader applicability to spark and other transient optical event detection as well. The QDs are operable for receiving ultraviolet (UV), infrared (IR), visible, x-ray, and/or gamma ray radiation emanating from lightning or the like and generating visible radiation that may be detected and utilized to generate topological event information, such that property, human life, and the like may be safeguarded.

Bahritdinov, Farhod↗
NASA NTRS2007

Potential of VIIRS Time Series Data for Aiding the USDA Forest Service Early Warning System for Forest Health Threats: A Gypsy Moth Defoliation Case Study

This report details one of three experiments performed during FY 2007 for the NASA RPC (Rapid Prototyping Capability) at Stennis Space Center. This RPC experiment assesses the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) and MODIS (Moderate Resolution Imaging Spectroradiometer) data for detecting and monitoring forest defoliation from the non-native Eurasian gypsy moth (Lymantria dispar). The intent of the RPC experiment was to assess the degree to which VIIRS data can provide forest disturbance monitoring information as an input to a forest threat EWS (Early Warning System) as compared to the level of information that can be obtained from MODIS data. The USDA Forest Service (USFS) plans to use MODIS products for generating broad-scaled, regional monitoring products as input to an EWS for forest health threat assessment. NASA SSC is helping the USFS to evaluate and integrate currently available satellite remote sensing technologies and data products for the EWS, including the use of MODIS products for regional monitoring of forest disturbance. Gypsy moth defoliation of the mid-Appalachian highland region was selected as a case study. Gypsy moth is one of eight major forest insect threats listed in the Healthy Forest Restoration Act (HFRA) of 2003; the gypsy moth threatens eastern U.S. hardwood forests, which are also a concern highlighted in the HFRA of 2003. This region was selected for the project because extensive gypsy moth defoliation occurred there over multiple years during the MODIS operational period. This RPC experiment is relevant to several nationally important mapping applications, including agricultural efficiency, coastal management, ecological forecasting, disaster management, and carbon management. In this experiment, MODIS data and VIIRS data simulated from MODIS were assessed for their ability to contribute broad, regional geospatial information on gypsy moth defoliation. Landsat and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data were used to assess the quality of gypsy moth defoliation mapping products derived from MODIS data and from simulated VIIRS data. The project focused on use of data from MODIS Terra as opposed to MODIS Aqua mainly because only MODIS Terra data was collected during 2000 and 2001-years with comparatively high amounts of gypsy moth defoliation within the study area. The project assessed the quality of VIIRS data simulation products. Hyperion data was employed to assess the quality of MODIS-based VIIRS simulation datasets using image correlation analysis techniques. The ART (Application Research Toolbox) software was used for data simulation. Correlation analysis between MODIS-simulated VIIRS data and Hyperion-simulated VIIRS data for red, NIR (near-infrared), and NDVI (Normalized Difference Vegetation Index) image data products collectively indicate that useful, effective VIIRS simulations can be produced using Hyperion and MODIS data sources. The r(exp 2) for red, NIR, and NDVI products were 0.56, 0.63, and 0.62, respectively, indicating a moderately high correlation between the 2 data sources. Temporal decorrelation from different data acquisition times and image misregistration may have lowered correlation results. The RPC experiment also generated MODIS-based time series data products using the TSPT (Time Series Product Tool) software. Time series of simulated VIIRS NDVI products were produced at approximately 400-meter resolution GSD (Ground Sampling Distance) at nadir for comparison to MODIS NDVI products at either 250- or 500-meter GSD. The project also computed MODIS (MOD02) NDMI (Normalized Difference Moisture Index) products at 500-meter GSD for comparison to NDVI-based products. For each year during 2000-2006, MODIS and VIIRS (simulated from MOD02) time series were computed during the peak gypsy moth defoliation time frame in the study area (approximately June 10 through July 27). Gypsy moth defoliation mapping products from simated VIIRS and MOD02 time series were produced using multiple methods, including image classification and change detection via image differencing. The latter enabled an automated defoliation detection product computed using percent change in maximum NDVI for a peak defoliation period during 2001 compared to maximum NDVI across the entire 2000-2006 time frame. Final gypsy moth defoliation mapping products were assessed for accuracy using randomly sampled locations found on available geospatial reference data (Landsat and ASTER data in conjunction with defoliation map data from the USFS). Extensive gypsy moth defoliation patches were evident on screen displays of multitemporal color composites derived from MODIS data and from simulated VIIRS vegetation index data. Such defoliation was particularly evident for 2001, although widespread denuded forests were also seen for 2000 and 2003. These visualizations were validated using aforementioned reference data. Defoliation patches were visible on displays of MODIS-based NDVI and NDMI data. The viewing of apparent defoliation patches on all of these products necessitated adoption of a specialized temporal data processing method (e.g., maximum NDVI during the peak defoliation time frame). The frequency of cloud cover necessitated this approach. Multitemporal simulated VIIRS and MODIS Terra data both produced effective general classifications of defoliated forest versus other land cover. For 2001, the MOD02-simulated VIIRS 400-meter NDVI classification produced a similar yet slightly lower overall accuracy (87.28 percent with 0.72 Kappa) than the MOD02 250-meter NDVI classification (88.44 percent with 0.75 Kappa). The MOD13 250-meter NDVI classification had a lower overall accuracy (79.13 percent) and a much lower Kappa (0.46). The report discusses accuracy assessment results in much more detail, comparing overall classification and individual class accuracy statistics for simulated VIIRS 400-meter NDVI, MOD02 250-meter NDVI, MOD02-500 meter NDVI, MOD13 250-meter NDVI, and MOD02 500-meter NDMI classifications. Automated defoliation detection products from simulated VIIRS and MOD02 data for 2001 also yielded similar, relatively high overall classification accuracy (85.55 percent for the VIIRS 400-meter NDVI versus 87.28 percent for the MOD02 250-meter NDVI). In contrast, the USFS aerial sketch map of gypsy moth defoliation showed a lower overall classification accuracy at 73.64 percent. The overall classification Kappa values were also similar for the VIIRS (approximately 0.67 Kappa) versus the MOD02 (approximately 0.72 Kappa) automated defoliation detection product, which were much higher than the values exhibited by the USFS sketch map product (overall Kappa of approximately 0.47). The report provides additional details on the accuracy of automated gypsy moth defoliation detection products compared with USFS sketch maps. The results suggest that VIIRS data can be effectively simulated from MODIS data and that VIIRS data will produce gypsy moth defoliation mapping products that are similar to MODIS-based products. The results of the RPC experiment indicate that VIIRS and MODIS data products have good potential for integration into the forest threat EWS. The accuracy assessment was performed only for 2001 because of time constraints and a relative scarcity of cloud-free Landsat and ASTER data for the peak defoliation period of the other years in the 2000-2006 time series. Additional work should be performed to assess the accuracy of gypsy moth defoliation detection products for additional years.The study area (mid-Appalachian highlands) and application (gypsy moth forest defoliation) are not necessarily representative of all forested regions and of all forest threat disturbance agents. Additional work should be performed on other inland and coastal regions as well as for other major forest threats.

Spruce, Joseph P.↗
NASA NTRS2013

Monitoring Regional Forest Disturbances across the US with Near Real Time MODIS NDVI Products included in the ForWarn Forest Threat Early Warning System

U.S. forests occupy approx.1/3 of total land area (approx. 304 million ha). Since 2000, a growing number of regionally evident forest disturbances have occurred due to abiotic and biotic agents. Regional forest disturbances can threaten human life and property, bio-diversity and water supplies. Timely regional forest disturbance monitoring products are needed to aid forest health management work. Near Real Time (NRT) twice daily MODIS NDVI data provide a means to monitor U.S. regional forest disturbances every 8 days. Since 2010, these NRT forest change products have been produced and posted on the US Forest Service ForWarn Early Warning System for Forest Threats.

Spruce, Joseph↗
NASA NTRS2012

Role of MODIS Vegetation Phenology Products in the U.S. for Warn Early Warning System for Forest Threats

U.S. forests occupy approx 751 million acres (approx 1/3 of total land). Several abiotic and biotic damage agents disturb, damage, kill, and/or threaten these forests. Regionally extensive forest disturbances can also threaten human life and property, bio-diversity and water supplies. timely regional forest disturbance monitoring products are needed to aid forest health management work at finer scales. daily MODIS data provide a means to monitor regional forest disturbances on a weekly basis, leveraging vegetation phenology. In response, the USFS and NASA began collaborating in 2006 to develop a Near Real Time (NRT) forest monitoring capability, based on MODIS NDVI data, as part of a national forest threat Early Warning System (EWS).

Spruce, Joseph↗
NASA NTRS2011

Contribution of Near Real Time MODIS-Based Forest Disturbance Detection Products to a National Forest Threat Early Warning System

U.S. forests occupy approx. 751 million acres (approx. 1/3 of total land). These forests are exposed to multiple biotic and abiotic threats that collectively damage extensive acreages each year. Hazardous forest disturbances can threaten human life and property, bio-diversity and water supplies. Timely regional forest monitoring products are needed to aid forest management and decision making by the US Forest Service and its state and private partners. Daily MODIS data products provide a means to monitor regional forest disturbances on a weekly basis. In response, we began work in 2006 to develop a Near Real Time (NRT) forest monitoring capability, based on MODIS NDVI data, as part of a national forest threat early warning system (EWS)

Spruce, Joseph↗
DOE OSTI2021

SNEWS 2.0: a next-generation supernova early warning system for multi-messenger astronomy

The next core-collapse supernova in the Milky Way or its satellites will represent a once-in-a-generation opportunity to obtain detailed information about the explosion of a star and provide significant scientific insight for a variety of fields because of the extreme conditions found within. Supernovae in our galaxy are not only rare on a human timescale but also happen at unscheduled times, so it is crucial to be ready and use all available instruments to capture all possible information from the event. The first indication of a potential stellar explosion will be the arrival of a bright burst of neutrinos. Its observation by multiple detectors worldwide can provide an early warning for the subsequent electromagnetic fireworks, as well as signal to other detectors with significant backgrounds so they can store their recent data. The supernova early warning system (SNEWS) has been operating as a simple coincidence between neutrino experiments in automated mode since 2005. In the current era of multi-messenger astronomy there are new opportunities for SNEWS to optimize sensitivity to science from the next galactic supernova beyond the simple early alert. This document is the product of a workshop in June 2019 towards design of SNEWS 2.0, an upgraded SNEWS with enhanced capabilities exploiting the unique advantages of prompt neutrino detection to maximize the science gained from such a valuable event.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1983

Voice interactive electronic warning systems (VIEWS) - An applied approach to voice technology in the helicopter cockpit

The cockpit has been one of the most rapidly changing areas of new aircraft design over the past thirty years. In connection with these developments, a pilot can now be considered a decision maker/system manager as well as a vehicle controller. There is, however, a trend towards an information overload in the cockpit, and information processing problems begin to occur for the rotorcraft pilot. One approach to overcome the arising difficulties is based on the utilization of voice technology to improve the information transfer rate in the cockpit with respect to both input and output. Attention is given to the background of speech technology, the application of speech technology within the cockpit, voice interactive electronic warning system (VIEWS) simulation, and methodology. Information subsystems are considered along with a dynamic simulation study, and data collection.

Voorhees, J. W.↗
NASA NTRSDate not supplied

Assessing the Viability of Using GEOS-Forecast Product for Landslides Forecasting: A Step Toward Early Warning System

Landslides across the globe are mostly triggered by extreme rainfall events affecting infrastructure, transportation and livelihoods. The risks are rarely quantified due to lack of data, analytical skills and limited modeling techniques. Knowledge of local to global scale landslide risks provides communities and national agencies the ability to adapt disaster management practices to mitigate and recover from these hazards. In order to minimize the risks and improve characterization of community resilience to landslides, it is vital to have reliable information about the factors triggering landslides such as rainfall, well ahead in time. Forecasting potential landslide activity and impacts can be achieved through reliable precipitation forecast models. However, it is challenging because of the temporal and spatial variability of precipitation, an important factor in triggering landslides. Evaluation of the precipitation field, associated errors, and sampling uncertainties is integral for development of efficient and reliable landslide forecasting and early warning system. This study develops a methodology to assess the viability of using a precipitation field provided by a global model and its potential integration in the landslide forecasting system. The study focuses on the comparison between the IMERG (Integrated Multi-satellitE Retrievals for Global Precipitation Mission) and GEOS (NASA Goddard Earth Observing System)-Forecast product over contiguous United States (CONUS). GEOS model assimilates new observations every 6 hours, at 00, 06, 12, and 18 UTC. The framework is tested on the GEOS-Forecast Model initialized at 00 UTC using daily IMERG early product as reference using both categorical and continuous statistics. The categorical statistics includes the probability of detection (POD), success ratio (SR), critical success index (CSI), and the hit bias. Continuous statistics such as correlation, normalized standard deviation, and root-mean-square error are also evaluated. Overall, GEOS-Forecast precipitation field over the analysis period (~1 year) show underestimation with respect to IMERG early for the daily accumulated rainfall. However, the probability distribution function and cumulative distribution function of both show similar patterns. In terms of correlations, POD, SR, CSI, hit bias, the performance varies with respect to the rainfall threshold used.

Sana Khan↗
NASA NTRS1978

Ray tracing of gravity waves as a possible warning system for tornadic storms and hurricanes

Gravity waves with wave periods of 13 to 15 min and horizontal phase velocities of 90 to 220 m/sec were present in ground-based observations of the upper atmosphere during time periods when tornadoes were occurring and gravity waves with wave periods of 20 to 25 min and horizontal phase velocities of 100 to 200 m/sec were detected when a hurricane was present. Combinations of available neutral atmosphere data and model parameter values were used with a group ray tracing technique in an attempt to locate the sources of these waves. Computed sources of the waves with periods of 13 to 15 min were located within 50 km of the locations where tornadoes touched down from 2 to 4 h later. In the case of the waves with periods of 20 to 25 min it was found that the computed location of the source was roughly where the hurricane would be located 3 h after the waves were excited. The applicability of the present study to a tornado and hurricane warning system is noted.

Hung, R. J.↗
NASA NTRS1977

A survey of the status of and philosophies relating to cockpit warning systems

A survey was taken to study current cockpit caution and warning (c/w) systems, and to examine industry philosophies regarding c/w system design including current efforts to improve them. Guidelines currently in use were outlined and those which appear to have general acceptance, those which are considered ineffective or erroneous, and those with which there is broad disagreement as to validity, were delineated. Major airplane manufacturerd were surveyed and a manufacturer dealing specifically with aircraft instrumentation was consulted.

Cooper, G. E.↗
NASA NTRS2011

The Effect of Sonic Booms on Earthquake Warning Systems

Several aerospace companies are designing quiet supersonic business jets for service over the United States. These aircraft have the potential to increase the occurrence of mild sonic booms across the country. This leads to interest among earthquake warning (EQW) developers and the general seismological community in characterizing the effect of sonic booms on seismic sensors in the field, their potential impact on EQW systems, and means of discriminating their signatures from those of earthquakes. The SonicBREWS project (Sonic Boom Resistant Earthquake Warning Systems) is a collaborative effort between Seismic Warning Systems, Inc. (SWS) and NASA Dryden Flight Research Center. This project aims to evaluate the effects of sonic booms on EQW sensors. The study consists of exposing high-sample-rate (1000 sps) triaxial accelerometers to sonic booms with overpressures ranging from 10 to 600 Pa in the free field and the built environment. The accelerometers record the coupling of the sonic boom to the ground and surrounding structures, while microphones record the acoustic wave above ground near the sensor. Sonic booms are broadband signals with more high-frequency content than earthquakes. Even a 1000 sps accelerometer will produce a significantly aliased record. Thus the observed peak ground velocity is strongly dependent on the sampling rate, and increases as the sampling rate is reduced. At 1000 sps we observe ground velocities that exceed those of P-waves from M L 3 earthquakes at local distances, suggesting that sonic booms are not negligible for EQW applications. We present the results of several experiments conducted under SonicBREWS showing the effects of typical-case low amplitude sonic booms and worst-case high amplitude booms. We show the effects of various sensor placements and sensor array geometries. Finally, we suggest possible avenues for discriminating sonic booms from earthquakes for the purposes of EQW.

Wurman, Gilead↗
NASA NTRS1980

A study of the comparative performance of six lightning warning systems

An analysis of mining explosive accident reports indicates a need for clear and ample warning of approaching electrical storms to reduce injuries/fatalities due to lightning induced premature detonation. Six lightning warning devices were comparatively evaluated at three test sites. The devices tested were: (1) flash counter, (2) corona point, (3) radioactive probe, (4) field mill, (5) azimuth/range locator, and (6) triangulation locator. The test sites were chosen to provide system evaluation under varied thunderstorm conditions. The devices were tested at San Antonio, Texas, Kennedy Space Center, Florida and Langmuir Laboratory, New Mexico. Comparative performance is reviewed in terms of alarm reliability, false alarm, and failure to alarm probabilities. Lightning warning system requirements and methods of relating warning criteria to explosive hazard are discussed.

Johnson, R. L.↗
NASA NTRS1998

LDAR, A Three-Dimensional Lightning Warning System: Its Development and Use by the Government, and Transition to Public Availability

NASA, at the John F. Kennedy Space Center (KSC), developed and operates a unique high precision lightning location system to provide lightning related weather warnings. These warnings are used to stop lightning-sensitive operations such as space vehicle launches and ground operations where equipment and personnel are at risk. The data is provided to the Range Weather Operations [45th Weather Squadron, U. S. Air Force (USAF)] where it is used with other meteorological data to issue weather advisories and warnings for Cape Canaveral Air Station (CCAS) and KSC operations. This system, called Lightning Detection and Ranging (LDAR), provides users with a graphical display in three dimensions of 66 MHz radio frequency events generated by lightning processes. The locations of these events provide a sound basis for the prediction of lightning hazards. NASA and Global Atmospherics, Inc. are developing a new system that will replace the unique LDAR components with commercially available and maintainable components having improved capabilities. These components will be phased in to ensure full continuity and access to this important warning technology. These LDAR systems are expected to eventually be available for installation and use by the public at specialized facilities, such as airports, and for general weather warnings via the National Weather Service (NWS) or television broadcast. The NWS in Melbourne has had access to real-time LDAR data since 1993 on an experimental basis. This use of LDAR has shown promise for the improvement of aviation forecasts and severe weather warnings. More so, it has opened the door to investigate the feasibility of issuing lightning-related public advisories. The success of its early use suggests that this technology may improve safety and potentially save lives, therefore constituting a significant benefit to the public. This paper describes the LDR system, the plans and progress of these upgrades, and the potential benefits of its use.

Starr, Stan↗
NASA NTRS2020

Kenya Food Security & Agriculture II: Utilizing NASA Earth Observations to Enhance Drought Warning Systems and Develop Capacity to Use the RHEAS Model in Kenya

Twenty-three counties in Kenya experience frequent drought, which damages agricultural productivity and threatens the health and well being of millions. NASA DEVELOP partnered with NASA SERVIR, the Regional Centre for Mapping of Resources for Development (RCMRD) and Kenya’s National Drought Management Authority (NDMA) to enhance drought-detection capacity using NASA Earth observations. Currently, the NDMA publishes monthly Early Warning Bulletins with drought conditions for each arid or semi-arid county in Kenya. These bulletins utilize the Vegetation Condition Index (VCI) from the Moderate Resolution ImagingSpectroradiometer (MODIS) as well as a variety of biophysical, social and economic drought indicators, but do not allow for advanced forecasting. To improve drought-monitoring capabilities, the team created a Combined Drought Indicator (CDI) using the Regional Hydrologic Extremes Assessment System (RHEAS) model and data from Aqua and Terra MODIS and the National Centers for Environmental Prediction. The CDI combined precipitation anomalies, soil moisture anomalies, evaporative stress, and VCI according to weights determined by principal component analysis. To evaluate the performance of the CDI across Kenya, the team compiled a dataset of drought events from historical reports and the NDMA’s records. Results suggested that the CDI detected drought earlier thanVCI alone. However, more validation is needed to ensure that the CDI accurately and consistently detects drought earlier than current warning systems. In order to better understand the behavior of individual indices and the potential for earlier drought detection, the team also conducted a time-lag analysis. The team found that VCI responds to drought, on average, one month later than most other indices included in the CDI, suggesting that incorporating additional indices could improve early drought warning systems in Kenya.

Food Security & Agriculture↗
NASA NTRS2020

Kenya Food Security & Agriculture II: Utilizing NASA Earth Observations to Enhance Drought Warning Systems and Develop Capacity to Use the RHEAS Model in Kenya

Twenty-three counties in Kenya experience frequent drought, which damages agricultural productivity and threatens the health and well being of millions. NASA DEVELOP partnered with NASA SERVIR, the Regional Centre for Mapping of Resources for Development (RCMRD) and Kenya’s National Drought Management Authority (NDMA) to enhance drought-detection capacity using NASA Earth observations. Currently, the NDMA publishes monthly Early Warning Bulletins with drought conditions for each arid or semi-arid county in Kenya. These bulletins utilize the Vegetation Condition Index (VCI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) as well as a variety of biophysical, social and economic drought indicators, but do not allow for advanced forecasting. To improve drought-monitoring capabilities, the team created a Combined Drought Indicator (CDI) using the Regional Hydrologic Extremes Assessment System (RHEAS) model and data from Aqua and Terra MODIS and the National Centers for Environmental Prediction.The CDI combined precipitation anomalies, soil moisture anomalies, evaporative stress, and VCI according to weights determined by principal component analysis. To evaluate the performance of the CDI across Kenya, the team compiled a dataset of drought events from historical reports and the NDMA’s records. Results suggested that the CDI detected drought earlier than VCI alone. However, more validation is needed to ensure that the CDI accurately and consistently detects drought earlier than current warning systems. In order to better understand the behavior of individual indices and the potential for earlier drought detection, the team also conducted a time-lag analysis. The team found that VCI responds to drought, on average, one month later than most other indices included in the CDI, suggesting that incorporating additional indices could improve early drought warning systems in Kenya.

Food Security & Agriculture↗
NASA NTRS1991

An airborne FLIR detection and warning system for low altitude wind shear

It is shown through some preliminary flight measurement research that a forward looking infrared radiometer (FLIR) system can be used to successfully detect the cool downdraft of downbursts (microbusts/macrobursts) and thunderstorm gust front outflows that are responsible for most of the low altitude wind shear (LAWS) events. The FLIR system provides a much greater safety margin for the pilot than that provided by reactive designs such as inertial air speed systems. Preliminary results indicate that an advanced airborne FLIR system could provide the pilot with remote indication of microburst (MB) hazards along the flight path ahead of the aircraft. Results of a flight test of a prototype FLIR system show that a minimum warning time of one to four minutes (5 to 10 km), depending on aircraft speed, is available to the pilot prior to the microburst encounter.

Sinclair, Peter C.↗
NASA NTRS2003

Airborne Turbulence Warning System Development

This viewgraph presentation provides information on the development of a system by which aircraft pilots will be warned of turbulence. This networked system of in situ sensors will be mounted on various aircraft all of which are linked through a ground based parabolic antenna. As its end result, this system will attempt to reduce the number of accidents arising from turbulence.

Bogue, Rod↗
NASA NTRS1994

The Global Emergency Observation and Warning System

Based on an extensive characterization of natural hazards, and an evaluation of their impacts on humanity, a set of functional technical requirements for a global warning and relief system was developed. Since no technological breakthroughs are required to implement a global system capable of performing the functions required to provide sufficient information for prevention, preparedness, warning, and relief from natural disaster effects, a system is proposed which would combine the elements of remote sensing, data processing, information distribution, and communications support on a global scale for disaster mitigation.

Bukley, Angelia P.↗