Cloud-based Web Services for Near-Real-Time Web access to NPP Satellite Imagery and other Data

NASA Astrophysics Data System (ADS)

Evans, J. D.; Valente, E. G.

2010-12-01

We are building a scalable, cloud computing-based infrastructure for Web access to near-real-time data products synthesized from the U.S. National Polar-Orbiting Environmental Satellite System (NPOESS) Preparatory Project (NPP) and other geospatial and meteorological data. Given recent and ongoing changes in the the NPP and NPOESS programs (now Joint Polar Satellite System), the need for timely delivery of NPP data is urgent. We propose an alternative to a traditional, centralized ground segment, using distributed Direct Broadcast facilities linked to industry-standard Web services by a streamlined processing chain running in a scalable cloud computing environment. Our processing chain, currently implemented on Amazon.com's Elastic Compute Cloud (EC2), retrieves raw data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and synthesizes data products such as Sea-Surface Temperature, Vegetation Indices, etc. The cloud computing approach lets us grow and shrink computing resources to meet large and rapid fluctuations (twice daily) in both end-user demand and data availability from polar-orbiting sensors. Early prototypes have delivered various data products to end-users with latencies between 6 and 32 minutes. We have begun to replicate machine instances in the cloud, so as to reduce latency and maintain near-real time data access regardless of increased data input rates or user demand -- all at quite moderate monthly costs. Our service-based approach (in which users invoke software processes on a Web-accessible server) facilitates access into datasets of arbitrary size and resolution, and allows users to request and receive tailored and composite (e.g., false-color multiband) products on demand. To facilitate broad impact and adoption of our technology, we have emphasized open, industry-standard software interfaces and open source software. Through our work, we envision the widespread establishment of similar, derived, or interoperable systems for

High-resolution near real-time drought monitoring in South Asia

NASA Astrophysics Data System (ADS)

Aadhar, Saran; Mishra, Vimal

2017-10-01

Drought in South Asia affect food and water security and pose challenges for millions of people. For policy-making, planning, and management of water resources at sub-basin or administrative levels, high-resolution datasets of precipitation and air temperature are required in near-real time. We develop a high-resolution (0.05°) bias-corrected precipitation and temperature data that can be used to monitor near real-time drought conditions over South Asia. Moreover, the dataset can be used to monitor climatic extremes (heat and cold waves, dry and wet anomalies) in South Asia. A distribution mapping method was applied to correct bias in precipitation and air temperature, which performed well compared to the other bias correction method based on linear scaling. Bias-corrected precipitation and temperature data were used to estimate Standardized precipitation index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) to assess the historical and current drought conditions in South Asia. We evaluated drought severity and extent against the satellite-based Normalized Difference Vegetation Index (NDVI) anomalies and satellite-driven Drought Severity Index (DSI) at 0.05°. The bias-corrected high-resolution data can effectively capture observed drought conditions as shown by the satellite-based drought estimates. High resolution near real-time dataset can provide valuable information for decision-making at district and sub-basin levels.

High-Resolution Near Real-Time Drought Monitoring in South Asia

NASA Astrophysics Data System (ADS)

Aadhar, S.; Mishra, V.

2017-12-01

Drought in South Asia affect food and water security and pose challenges for millions of people. For policy-making, planning and management of water resources at the sub-basin or administrative levels, high-resolution datasets of precipitation and air temperature are required in near-real time. Here we develop a high resolution (0.05 degree) bias-corrected precipitation and temperature data that can be used to monitor near real-time drought conditions over South Asia. Moreover, the dataset can be used to monitor climatic extremes (heat waves, cold waves, dry and wet anomalies) in South Asia. A distribution mapping method was applied to correct bias in precipitation and air temperature (maximum and minimum), which performed well compared to the other bias correction method based on linear scaling. Bias-corrected precipitation and temperature data were used to estimate Standardized precipitation index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) to assess the historical and current drought conditions in South Asia. We evaluated drought severity and extent against the satellite-based Normalized Difference Vegetation Index (NDVI) anomalies and satellite-driven Drought Severity Index (DSI) at 0.05˚. We find that the bias-corrected high-resolution data can effectively capture observed drought conditions as shown by the satellite-based drought estimates. High resolution near real-time dataset can provide valuable information for decision-making at district and sub- basin levels.

Applications for Near-Real Time Satellite Cloud and Radiation Products

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Palikonda, Rabindra; Chee, Thad L.; Bedka, Kristopher M.; Smith, W.; Ayers, Jeffrey K.; Benjamin, Stanley; Chang, F.-L.; Nguyen, Louis; Norris, Peter;

The Use of NASA near Real-time and Archived Satellite Data to Support Disaster Assessment

NASA Technical Reports Server (NTRS)

McGrath, Kevin M.; Molthan, Andrew; Burks, Jason

2014-01-01

With support from a NASA's Applied Sciences Program, The Short-term Prediction Research and Transition (SPoRT) Center has explored a variety of techniques for utilizing archived and near real-time NASA satellite data to support disaster assessment activities. MODIS data from the NASA Land Atmosphere Near Real-time Capability for EOS currently provides true color and other imagery for assessment and potential applications including, but not limited to, flooding, fires, and tornadoes. In May 2013, the SPoRT Center developed unique power outage composites using the VIIRS Day/Night Band to represent the first clear sky view of damage inflicted upon Moore and Oklahoma City, Oklahoma following the devastating EF-5 tornado that occurred on May 20. Pre-event imagery provided by the NASA funded Web-Enabled Landsat Data project offer a basis of comparison for monitoring post-disaster recovery efforts. Techniques have also been developed to generate products from higher resolution imagery from the recently available International Space Station SERVIR Environmental Research and Visualization System instrument. Of paramount importance is to deliver these products to end users expeditiously and in formats compatible with Decision Support Systems (DSS). Delivery techniques include a Tile Map Service (TMS) and a Web Mapping Service (WMS). These mechanisms allow easy integration of satellite products into DSS's, including the National Weather Service's Damage Assessment Toolkit for use by personnel conducting damage surveys. This poster will present an overview of the developed techniques and products and compare the strengths and weaknesses of the TMS and WMS.

The SSABLE system - Automated archive, catalog, browse and distribution of satellite data in near-real time

NASA Technical Reports Server (NTRS)

Simpson, James J.; Harkins, Daniel N.

1993-01-01

Historically, locating and browsing satellite data has been a cumbersome and expensive process. This has impeded the efficient and effective use of satellite data in the geosciences. SSABLE is a new interactive tool for the archive, browse, order, and distribution of satellite date based upon X Window, high bandwidth networks, and digital image rendering techniques. SSABLE provides for automatically constructing relational database queries to archived image datasets based on time, data, geographical location, and other selection criteria. SSABLE also provides a visual representation of the selected archived data for viewing on the user's X terminal. SSABLE is a near real-time system; for example, data are added to SSABLE's database within 10 min after capture. SSABLE is network and machine independent; it will run identically on any machine which satisfies the following three requirements: 1) has a bitmapped display (monochrome or greater); 2) is running the X Window system; and 3) is on a network directly reachable by the SSABLE system. SSABLE has been evaluated at over 100 international sites. Network response time in the United States and Canada varies between 4 and 7 s for browse image updates; reported transmission times to Europe and Australia typically are 20-25 s.

Near real time observational data collection for SPRUCE experiment- PakBus protocol for slow satellite connections

NASA Astrophysics Data System (ADS)

Krassovski, Misha; Hanson, Paul; Riggs, Jeff

2017-04-01

Climate change studies are one of the most important aspects of modern science and related experiments are getting bigger and more complex. One such experiment is the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE, http://mnspruce.ornl.gov) conducted in in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO2 atmosphere. This manipulation experiment generates a lot of observational data and requires a reliable onsite data collection system, dependable methods to transfer data to a robust scientific facility, and real-time monitoring capabilities. This publication shares our experience of establishing near real time data collection and monitoring system via a satellite link using PakBus protocol.

Near Real-Time Automatic Marine Vessel Detection on Optical Satellite Images

NASA Astrophysics Data System (ADS)

Máttyus, G.

2013-05-01

Vessel monitoring and surveillance is important for maritime safety and security, environment protection and border control. Ship monitoring systems based on Synthetic-aperture Radar (SAR) satellite images are operational. On SAR images the ships made of metal with sharp edges appear as bright dots and edges, therefore they can be well distinguished from the water. Since the radar is independent from the sun light and can acquire images also by cloudy weather and rain, it provides a reliable service. Vessel detection from spaceborne optical images (VDSOI) can extend the SAR based systems by providing more frequent revisit times and overcoming some drawbacks of the SAR images (e.g. lower spatial resolution, difficult human interpretation). Optical satellite images (OSI) can have a higher spatial resolution thus enabling the detection of smaller vessels and enhancing the vessel type classification. The human interpretation of an optical image is also easier than as of SAR image. In this paper I present a rapid automatic vessel detection method which uses pattern recognition methods, originally developed in the computer vision field. In the first step I train a binary classifier from image samples of vessels and background. The classifier uses simple features which can be calculated very fast. For the detection the classifier is slided along the image in various directions and scales. The detector has a cascade structure which rejects most of the background in the early stages which leads to faster execution. The detections are grouped together to avoid multiple detections. Finally the position, size(i.e. length and width) and heading of the vessels is extracted from the contours of the vessel. The presented method is parallelized, thus it runs fast (in minutes for 16000 × 16000 pixels image) on a multicore computer, enabling near real-time applications, e.g. one hour from image acquisition to end user.

NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE): Changing patterns in the use of NRT satellite imagery

NASA Astrophysics Data System (ADS)

Davies, D.; Michael, K.; Schmaltz, J. E.; Harrison, S.; Ding, F.; Durbin, P. B.; Boller, R. A.; Cechini, M. F.; Rinsland, P. L.; Ye, G.; Mauoka, E.

2015-12-01

NASA's Land, Atmosphere Near real-time Capability for EOS (Earth Observing System) (LANCE) provides data and imagery approximately 3 hours from satellite observation, to monitor natural events globally and to meet the needs of the near real-time (NRT) applications community. This article describes LANCE, and how the use of NRT data and imagery has evolved. Since 2010 there has been a four-fold increase in both the volume of data and the number of files downloaded. Over the last year there has been a marked shift in the way in which users are accessing NRT imagery; users are gravitating towards Worldview and the Global Imagery Browse Services (GIBS) and away from MODIS Rapid Response, in part due to the increased exposure through social media. In turn this is leading to a broader range of users viewing NASA NRT imagery. This article also describes new, and planned, product enhancements to LANCE. Over the last year, LANCE has expanded to support NRT products from the Advanced Microwave Scanning Radiometer 2 (AMSR2), and the Multi-angle Imaging SpectroRadiometer (MISR). LANCE elements are also planning to ingest and process NRT data from the Visible Infrared Imager Radiometer Suite (VIIRS), and the advanced Ozone Mapping and Profiler Suite (OMPS) instruments onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite in the near future.

Satellite clock corrections estimation to accomplish real time ppp: experiments for brazilian real time network

NASA Astrophysics Data System (ADS)

Marques, Haroldo; Monico, João; Aquino, Marcio; Melo, Weyller

2014-05-01

The real time PPP method requires the availability of real time precise orbits and satellites clocks corrections. Currently, it is possible to apply the solutions of clocks and orbits available by BKG within the context of IGS Pilot project or by using the operational predicted IGU ephemeris. The accuracy of the satellite position available in the IGU is enough for several applications requiring good quality. However, the satellites clocks corrections do not provide enough accuracy (3 ns ~ 0.9 m) to accomplish real time PPP with the same level of accuracy. Therefore, for real time PPP application it is necessary to further research and develop appropriated methodologies for estimating the satellite clock corrections in real time with better accuracy. Currently, it is possible to apply the real time solutions of clocks and orbits available by Federal Agency for Cartography and Geodesy (BKG) within the context of IGS Pilot project. The BKG corrections are disseminated by a new proposed format of the RTCM 3.x and can be applied in the broadcasted orbits and clocks. Some investigations have been proposed for the estimation of the satellite clock corrections using GNSS code and phase observable at the double difference level between satellites and epochs (MERVAT, DOUSA, 2007). Another possibility consists of applying a Kalman Filter in the PPP network mode (HAUSCHILD, 2010) and it is also possible the integration of both methods, using network PPP and observables at double difference level in specific time intervals (ZHANG; LI; GUO, 2010). For this work the methodology adopted consists in the estimation of the satellite clock corrections based on the data adjustment in the PPP mode, but for a network of GNSS stations. The clock solution can be solved by using two types of observables: code smoothed by carrier phase or undifferenced code together with carrier phase. In the former, we estimate receiver clock error; satellite clock correction and troposphere, considering

Land and Atmosphere Near-Real-Time Capability for Earth Observing System

NASA Technical Reports Server (NTRS)

Murphy, Kevin J.

2011-01-01

The past decade has seen a rapid increase in availability and usage of near-real-time data from satellite sensors. The EOSDIS (Earth Observing System Data and Information System) was not originally designed to provide data with sufficiently low latency to satisfy the requirements for near-real-time users. The EOS (Earth Observing System) instruments aboard the Terra, Aqua and Aura satellites make global measurements daily, which are processed into higher-level 'standard' products within 8-40 hours of observation and then made available to users, primarily earth science researchers. However, applications users, operational agencies, and even researchers desire EOS products in near-real-time to support research and applications, including numerical weather and climate prediction and forecasting, monitoring of natural hazards, ecological/invasive species, agriculture, air quality, disaster relief and homeland security. These users often need data much sooner than routine science processing allows, usually within 3 hours, and are willing to trade science product quality for timely access. While Direct Broadcast provides more timely access to data, it does not provide global coverage. In 2002, a joint initiative between NASA (National Aeronautics and Space Administration), NOAA (National Oceanic and Atmospheric Administration), and the DOD (Department of Defense) was undertaken to provide data from EOS instruments in near-real-time. The NRTPE (Near Real Time Processing Effort) provided products within 3 hours of observation on a best-effort basis. As the popularity of these near-real-time products and applications grew, multiple near-real-time systems began to spring up such as the Rapid Response System. In recognizing the dependence of customers on this data and the need for highly reliable and timely data access, NASA's Earth Science Division sponsored the Earth Science Data and Information System Project (ESDIS)-led development of a new near-real-time system called

SIMSAT: An object oriented architecture for real-time satellite simulation

NASA Technical Reports Server (NTRS)

Williams, Adam P.

1993-01-01

Real-time satellite simulators are vital tools in the support of satellite missions. They are used in the testing of ground control systems, the training of operators, the validation of operational procedures, and the development of contingency plans. The simulators must provide high-fidelity modeling of the satellite, which requires detailed system information, much of which is not available until relatively near launch. The short time-scales and resulting high productivity required of such simulator developments culminates in the need for a reusable infrastructure which can be used as a basis for each simulator. This paper describes a major new simulation infrastructure package, the Software Infrastructure for Modelling Satellites (SIMSAT). It outlines the object oriented design methodology used, describes the resulting design, and discusses the advantages and disadvantages experienced in applying the methodology.

Near real-time estimation of ionosphere vertical total electron content from GNSS satellites using B-splines in a Kalman filter

NASA Astrophysics Data System (ADS)

Erdogan, Eren; Schmidt, Michael; Seitz, Florian; Durmaz, Murat

2017-02-01

Although the number of terrestrial global navigation satellite system (GNSS) receivers supported by the International GNSS Service (IGS) is rapidly growing, the worldwide rather inhomogeneously distributed observation sites do not allow the generation of high-resolution global ionosphere products. Conversely, with the regionally enormous increase in highly precise GNSS data, the demands on (near) real-time ionosphere products, necessary in many applications such as navigation, are growing very fast. Consequently, many analysis centers accepted the responsibility of generating such products. In this regard, the primary objective of our work is to develop a near real-time processing framework for the estimation of the vertical total electron content (VTEC) of the ionosphere using proper models that are capable of a global representation adapted to the real data distribution. The global VTEC representation developed in this work is based on a series expansion in terms of compactly supported B-spline functions, which allow for an appropriate handling of the heterogeneous data distribution, including data gaps. The corresponding series coefficients and additional parameters such as differential code biases of the GNSS satellites and receivers constitute the set of unknown parameters. The Kalman filter (KF), as a popular recursive estimator, allows processing of the data immediately after acquisition and paves the way of sequential (near) real-time estimation of the unknown parameters. To exploit the advantages of the chosen data representation and the estimation procedure, the B-spline model is incorporated into the KF under the consideration of necessary constraints. Based on a preprocessing strategy, the developed approach utilizes hourly batches of GPS and GLONASS observations provided by the IGS data centers with a latency of 1 h in its current realization. Two methods for validation of the results are performed, namely the self consistency analysis and a comparison

US GEOLOGICAL SURVEY'S NATIONAL SYSTEM FOR PROCESSING AND DISTRIBUTION OF NEAR REAL-TIME HYDROLOGICAL DATA.

USGS Publications Warehouse

Shope, William G.; ,

1987-01-01

The US Geological Survey is utilizing a national network of more than 1000 satellite data-collection stations, four satellite-relay direct-readout ground stations, and more than 50 computers linked together in a private telecommunications network to acquire, process, and distribute hydrological data in near real-time. The four Survey offices operating a satellite direct-readout ground station provide near real-time hydrological data to computers located in other Survey offices through the Survey's Distributed Information System. The computerized distribution system permits automated data processing and distribution to be carried out in a timely manner under the control and operation of the Survey office responsible for the data-collection stations and for the dissemination of hydrological information to the water-data users.

Global Near Real-Time Satellite-based Flood Monitoring and Product Dissemination

NASA Astrophysics Data System (ADS)

Smith, M.; Slayback, D. A.; Policelli, F.; Brakenridge, G. R.; Tokay, M.

2012-12-01

Flooding is among the most destructive, frequent, and costly natural disasters faced by modern society, with several major events occurring each year. In the past few years, major floods have devastated parts of China, Thailand, Pakistan, Australia, and the Philippines, among others. The toll of these events, in financial costs, displacement of individuals, and deaths, is substantial and continues to rise as climate change generates more extreme weather events. When these events do occur, the disaster management community requires frequently updated and easily accessible information to better understand the extent of flooding and better coordinate response efforts. With funding from NASA's Applied Sciences program, we have developed, and are now operating, a near real-time global flood mapping system to help provide critical flood extent information within 24-48 hours after flooding events. The system applies a water detection algorithm to MODIS imagery received from the LANCE (Land Atmosphere Near real-time Capability for EOS) system at NASA Goddard. The LANCE system typically processes imagery in less than 3 hours after satellite overpass, and our flood mapping system can output flood products within ½ hour of acquiring the LANCE products. Using imagery from both the Terra (10:30 AM local time overpass) and Aqua (1:30 PM) platforms allows an initial assessment of flooding extent by late afternoon, every day, and more robust assessments after accumulating imagery over a longer period; the MODIS sensors are optical, so cloud cover remains an issue, which is partly overcome by using multiple looks over one or more days. Other issues include the relatively coarse scale of the MODIS imagery (250 meters), the difficulty of detecting flood waters in areas with continuous canopy cover, confusion of shadow (cloud or terrain) with water, and accurately identifying detected water as flood as opposed to normal water extents. We have made progress on some of these issues

A daily wetness index from satellite gravity for near-real time global monitoring of hydrological extremes

NASA Astrophysics Data System (ADS)

Gouweleeuw, Ben; Kvas, Andreas; Gruber, Christian; Mayer-Gürr, Torsten; Flechtner, Frank; Hasan, Mehedi; Güntner, Andreas

2017-04-01

Since April 2002, the Gravity Recovery and Climate Experiment (GRACE) satellite mission has been churning out water storage anomaly data, which has been shown to be a unique descriptor of large-scale hydrological extreme events. Nonetheless, efforts to assess the comprehensive information from GRACE on total water storage variations for near-real time flood or drought monitoring have been limited so far, primarily due to its coarse temporal (weekly to monthly) and spatial (> 150.000 km2) resolution and the latency of standard products of about 2 months,. Pending the status of the aging GRACE satellite mission, the Horizon 2020 funded EGSIEM (European Gravity Service for Improved Emergency Management) project is scheduled to launch a 6 month duration near-real time test run of GRACE gravity field data from April 2017 onward, which will provide daily gridded data with a latency of 5 days. This fast availability allows the monitoring of total water storage variations related to hydrological extreme events, as they occur, as opposed to a 'confirmation after occurrence', which is the current situation. This contribution proposes a global GRACE-derived gridded wetness indicator, expressed as a gravity anomaly in dimensionless units of standard deviation. Results of a retrospective evaluation (April 2002-December 2015) of the proposed index against databases of hydrological extremes will be presented. It is shown that signals for large extreme floods related to heavy/monsoonal rainfall are picked up really well in the Southern Hemisphere and lower Northern Hemisphere (Africa, S-America, Australia, S-Asia), while extreme floods in the Northern Hemisphere (Russia) related to snow melt are often not. The latter is possibly related to a lack of mass movement over longer distances, e.g. when melt water is not drained due to river ice blocking.

NASA-Langley Web-Based Operational Real-time Cloud Retrieval Products from Geostationary Satellites

NASA Technical Reports Server (NTRS)

Palikonda, Rabindra; Minnis, Patrick; Spangenberg, Douglas A.; Khaiyer, Mandana M.; Nordeen, Michele L.; Ayers, Jeffrey K.; Nguyen, Louis; Yi, Yuhong; Chan, P. K.; Trepte, Qing Z.;

Near Real Time Operational Satellite Ocean Color Products From NOAA OSPO CoastWatch Okeanos System:: Status and Challenges

NASA Astrophysics Data System (ADS)

Banghua Yan, B.

2016-02-01

Near real-time (NRT) ocean color (OC) satellite operation products are generated and distributed in NOAA Okeanos Operational Product System, by using the CWAPS including the Multi-Sensor Level (MSL) 12 and the chlorophyll-a frontal algorithms. Current OC operational products include daily chlorophyll concentration (anomaly), water turbidity, remote sensing reflectance and chlorophyll frontal products from Moderate-resolution Imaging Spectroradiometer (MODIS)/Aqua. The products have been widely applied to USA local and state ecosystem research, ecosystem observations, and fisheries managements for coastal and regional forecasting of ocean water quality, phytoplankton concentrations, and primary production. Users of the products have the National Ocean Service, National Marine Fisheries Service, National Weather Service, and Oceanic and Atmospheric Research. Recently, the OC products are being extended to S-NPP VIIRS to provide global NRT ocean color products to user community suh as National Weatrher Service for application for Global Data Assimilation System and Real-Time Ocean Forecast System. However, there remain some challenges in application of the products due to certain product quality and coverage issues. Recent efforts were made to provide a comprehensive web-based Quality Assurance (QA) tool for monitoring OC products quality in near real time mode, referring to http://www.ospo.noaa.gov/Products/ocean/color_new/color.htm. The new QA monitoring tool includes but not limited to the following advanced features applicable for MODIS/Aqua and NPP/VIIRS OC products: 1) Monitoring product quality in NRT mode; 2) Monitoring the availability and quality of OC products with time; 3) Detecting anomalous OC products due to low valid pixels and other quality issues. As an example, potential application and challenges of the ocean color products to oceanic oil spill detection are investigated. It is thus expected that the Okeanos ocean color operational system in

Characterizing Global Flood Wave Travel Times to Optimize the Utility of Near Real-Time Satellite Remote Sensing Products

NASA Astrophysics Data System (ADS)

Allen, G. H.; David, C. H.; Andreadis, K. M.; Emery, C. M.; Famiglietti, J. S.

2017-12-01

Earth observing satellites provide valuable near real-time (NRT) information about flood occurrence and magnitude worldwide. This NRT information can be used in early flood warning systems and other flood management applications to save lives and mitigate flood damage. However, these NRT products are only useful to early flood warning systems if they are quickly made available, with sufficient time for flood mitigation actions to be implemented. More specifically, NRT data latency, or the time period between the satellite observation and when the user has access to the information, must be less than the time it takes a flood to travel from the flood observation location to a given downstream point of interest. Yet the paradigm that "lower latency is always better" may not necessarily hold true in river systems due to tradeoffs between data latency and data quality. Further, the existence of statistical breaks in the global distribution of flood wave travel time (i.e. a jagged statistical distribution) would represent preferable latencies for river-observation NRT remote sensing products. Here we present a global analysis of flood wave velocity (i.e. flow celerity) and travel time. We apply a simple kinematic wave model to a global hydrography dataset and calculate flow wave celerity and travel time during bankfull flow conditions. Bankfull flow corresponds to the condition of maximum celerity and thus we present the "worst-case scenario" minimum flow wave travel time. We conduct a similar analysis with respect to the time it takes flood waves to reach the next downstream city, as well as the next downstream reservoir. Finally, we conduct these same analyses, but with regards to the technical capabilities of the planned Surface Water and Ocean Topography (SWOT) satellite mission, which is anticipated to provide waterbody elevation and extent measurements at an unprecedented spatial and temporal resolution. We validate these results with discharge records from paired

Rainfall estimation for real time flood monitoring using geostationary meteorological satellite data

NASA Astrophysics Data System (ADS)

Veerakachen, Watcharee; Raksapatcharawong, Mongkol

2015-09-01

Rainfall estimation by geostationary meteorological satellite data provides good spatial and temporal resolutions. This is advantageous for real time flood monitoring and warning systems. However, a rainfall estimation algorithm developed in one region needs to be adjusted for another climatic region. This work proposes computationally-efficient rainfall estimation algorithms based on an Infrared Threshold Rainfall (ITR) method calibrated with regional ground truth. Hourly rain gauge data collected from 70 stations around the Chao-Phraya river basin were used for calibration and validation of the algorithms. The algorithm inputs were derived from FY-2E satellite observations consisting of infrared and water vapor imagery. The results were compared with the Global Satellite Mapping of Precipitation (GSMaP) near real time product (GSMaP_NRT) using the probability of detection (POD), root mean square error (RMSE) and linear correlation coefficient (CC) as performance indices. Comparison with the GSMaP_NRT product for real time monitoring purpose shows that hourly rain estimates from the proposed algorithm with the error adjustment technique (ITR_EA) offers higher POD and approximately the same RMSE and CC with less data latency.

Near-Real-Time Earth Observation Data Supporting Wildfire Management

NASA Astrophysics Data System (ADS)

Ambrosia, V. G.; Zajkowski, T.; Quayle, B.

2013-12-01

During disaster events, the most critical element needed by responding personnel and management teams is situational intelligence / awareness. During rapidly-evolving events such as wildfires, the need for timely information is critical to save lives, property and resources. The wildfire management agencies in the US rely heavily on remote sensing information both from airborne platforms as well as from orbital assets. The ability to readily have information from those systems, not just data, is critical to effective control and damage mitigation. NASA has been collaborating with the USFS to mature and operationalize various asset-information capabilities to effect improved knowledge of fire-prone areas, monitor wildfire events in real-time, assess effectiveness of fire management strategies, and provide rapid, post-fire assessment for recovery operations. Specific examples of near-real-time remote sensing asset utility include daily MODIS data employed to assess fire potential / wildfire hazard areas, and national-scale hot-spot detection, airborne thermal sensor collected during wildfire events to effect management strategies, EO-1 ALI 'pointable' satellite sensor data to assess fire-retardant application effectiveness, and Landsat 8 and other sensor data to derive burn severity indices for post-fire remediation work. These cases of where near-real-time data is used operationally during the previous few fire seasons will be presented.

Global, Daily, Near Real-Time Satellite-based Flood Monitoring and Product Dissemination

NASA Astrophysics Data System (ADS)

Slayback, D. A.; Policelli, F. S.; Brakenridge, G. R.; Tokay, M. M.; Smith, M. M.; Kettner, A. J.

2013-12-01

Flooding is the most destructive, frequent, and costly natural disaster faced by modern society, and is expected to increase in frequency and damage with climate change and population growth. Some of 2013's major floods have impacted the New York City region, the Midwest, Alberta, Australia, various parts of China, Thailand, Pakistan, and central Europe. The toll of these events, in financial costs, displacement of individuals, and deaths, is substantial and continues to rise as climate change generates more extreme weather events. When these events do occur, the disaster management community requires frequently updated and easily accessible information to better understand the extent of flooding and better coordinate response efforts. With funding from NASA's Applied Sciences program, we developed and are now operating a near real-time global flood mapping system to help provide critical flood extent information within 24-48 hours of events. The system applies a water detection algorithm to MODIS imagery received from the LANCE (Land Atmosphere Near real-time Capability for EOS) system at NASA Goddard within a few hours of satellite overpass. Using imagery from both the Terra (10:30 AM local time overpass) and Aqua (1:30 PM) platforms allows an initial daily assessment of flooding extent by late afternoon, and more robust assessments after accumulating cloud-free imagery over several days. Cloud cover is the primary limitation in detecting surface water from MODIS imagery. Other issues include the relatively coarse scale of the MODIS imagery (250 meters), the difficulty of detecting flood waters in areas with continuous canopy cover, confusion of shadow (cloud or terrain) with water, and accurately identifying detected water as flood as opposed to normal water extents. We have made progress on many of these issues, and are working to develop higher resolution flood detection using alternate sensors, including Landsat and various radar sensors. Although these

LANCE in ECHO - Merging Science and Near Real-Time Data Search and Order

NASA Astrophysics Data System (ADS)

Kreisler, S.; Murphy, K. J.; Vollmer, B.; Lighty, L.; Mitchell, A. E.; Devine, N.

2012-12-01

NASA's Earth Observing System (EOS) Data and Information System (EOSDIS) Land Atmosphere Near real-time Capability for EOS (LANCE) project provides expedited data products from the Terra, Aqua, and Aura satellites within three hours of observation. In order to satisfy latency requirements, LANCE data are produced with relaxed ancillary data resulting in a product that may have minor differences from its science quality counterpart. LANCE products are used by a number of different groups to support research and applications that require near real-time earth observations, such as disaster relief, hazard and air quality monitoring, and weather forecasting. LANCE elements process raw rate-buffered and/or session-based production datasets into higher-level products, which are freely available to registered users via LANCE FTP sites. The LANCE project also generates near real-time full resolution browse imagery from these products, which can be accessed through the Global Imagery Browse Services (GIBS). In an effort to support applications and services that require timely access to these near real-time products, the project is currently implementing the publication of LANCE product metadata to the EOS ClearingHouse (ECHO), a centralized EOSDIS registry of EOS data. Metadata within ECHO is made available through an Application Program Interface (API), and applications can utilize the API to allow users to efficiently search and order LANCE data. Publishing near real-time data to ECHO will permit applications to access near real-time product metadata prior to the release of its science quality counterpart and to associate imagery from GIBS with its underlying data product.

Implementing a combined polar-geostationary algorithm for smoke emissions estimation in near real time

NASA Astrophysics Data System (ADS)

Hyer, E. J.; Schmidt, C. C.; Hoffman, J.; Giglio, L.; Peterson, D. A.

2013-12-01

Polar and geostationary satellites are used operationally for fire detection and smoke source estimation by many near-real-time operational users, including operational forecast centers around the globe. The input satellite radiance data are processed by data providers to produce Level-2 and Level -3 fire detection products, but processing these data into spatially and temporally consistent estimates of fire activity requires a substantial amount of additional processing. The most significant processing steps are correction for variable coverage of the satellite observations, and correction for conditions that affect the detection efficiency of the satellite sensors. We describe a system developed by the Naval Research Laboratory (NRL) that uses the full raster information from the entire constellation to diagnose detection opportunities, calculate corrections for factors such as angular dependence of detection efficiency, and generate global estimates of fire activity at spatial and temporal scales suitable for atmospheric modeling. By incorporating these improved fire observations, smoke emissions products, such as NRL's FLAMBE, are able to produce improved estimates of global emissions. This talk provides an overview of the system, demonstrates the achievable improvement over older methods, and describes challenges for near-real-time implementation.

Real Time Fire Reconnaissance Satellite Monitoring System Failure Model

NASA Astrophysics Data System (ADS)

Nino Prieto, Omar Ariosto; Colmenares Guillen, Luis Enrique

2013-09-01

In this paper the Real Time Fire Reconnaissance Satellite Monitoring System is presented. This architecture is a legacy of the Detection System for Real-Time Physical Variables which is undergoing a patent process in Mexico. The methodologies for this design are the Structured Analysis for Real Time (SA- RT) [8], and the software is carried out by LACATRE (Langage d'aide à la Conception d'Application multitâche Temps Réel) [9,10] Real Time formal language. The system failures model is analyzed and the proposal is based on the formal language for the design of critical systems and Risk Assessment; AltaRica. This formal architecture uses satellites as input sensors and it was adapted from the original model which is a design pattern for physical variation detection in Real Time. The original design, whose task is to monitor events such as natural disasters and health related applications, or actual sickness monitoring and prevention, as the Real Time Diabetes Monitoring System, among others. Some related work has been presented on the Mexican Space Agency (AEM) Creation and Consultation Forums (2010-2011), and throughout the International Mexican Aerospace Science and Technology Society (SOMECYTA) international congress held in San Luis Potosí, México (2012). This Architecture will allow a Real Time Fire Satellite Monitoring, which will reduce the damage and danger caused by fires which consumes the forests and tropical forests of Mexico. This new proposal, permits having a new system that impacts on disaster prevention, by combining national and international technologies and cooperation for the benefit of humankind.

GNSS global real-time augmentation positioning: Real-time precise satellite clock estimation, prototype system construction and performance analysis

NASA Astrophysics Data System (ADS)

Chen, Liang; Zhao, Qile; Hu, Zhigang; Jiang, Xinyuan; Geng, Changjiang; Ge, Maorong; Shi, Chuang

2018-01-01

Lots of ambiguities in un-differenced (UD) model lead to lower calculation efficiency, which isn't appropriate for the high-frequency real-time GNSS clock estimation, like 1 Hz. Mixed differenced model fusing UD pseudo-range and epoch-differenced (ED) phase observations has been introduced into real-time clock estimation. In this contribution, we extend the mixed differenced model for realizing multi-GNSS real-time clock high-frequency updating and a rigorous comparison and analysis on same conditions are performed to achieve the best real-time clock estimation performance taking the efficiency, accuracy, consistency and reliability into consideration. Based on the multi-GNSS real-time data streams provided by multi-GNSS Experiment (MGEX) and Wuhan University, GPS + BeiDou + Galileo global real-time augmentation positioning prototype system is designed and constructed, including real-time precise orbit determination, real-time precise clock estimation, real-time Precise Point Positioning (RT-PPP) and real-time Standard Point Positioning (RT-SPP). The statistical analysis of the 6 h-predicted real-time orbits shows that the root mean square (RMS) in radial direction is about 1-5 cm for GPS, Beidou MEO and Galileo satellites and about 10 cm for Beidou GEO and IGSO satellites. Using the mixed differenced estimation model, the prototype system can realize high-efficient real-time satellite absolute clock estimation with no constant clock-bias and can be used for high-frequency augmentation message updating (such as 1 Hz). The real-time augmentation message signal-in-space ranging error (SISRE), a comprehensive accuracy of orbit and clock and effecting the users' actual positioning performance, is introduced to evaluate and analyze the performance of GPS + BeiDou + Galileo global real-time augmentation positioning system. The statistical analysis of real-time augmentation message SISRE is about 4-7 cm for GPS, whlile 10 cm for Beidou IGSO/MEO, Galileo and about 30 cm

Near real-time monitoring of UT1 with geodetic VLBI

NASA Astrophysics Data System (ADS)

Haas, R.; Hobiger, T.; Sekido, M.; Koyama, Y.; Kondo, T.; Takiguchi, H.; Kurihara, S.; Kokado, K.; Tanimoto, D.; Nozawa, K.; Wagner, J.; Ritakari, J.; Mujunen, A.; Uunila, M.

2011-07-01

Geodetic VLBI is unique among the geodetic space techniques since it provides a direct connection between the international terrestrial reference frame and the international celestial reference frame. The Earth rotation angle, usually expressed as UT1, can be determined directly from geodetic VLBI observations. Accurate information about the Earth rotation angle is necessary and important for navigation purposes, in particular for satellite missions and space navigation. A near real-time knowledge of UT1 with high accuracy is therefore highly desirable. During the last few years the advances in data transfer over high-speed optical fibre lines have made it possible to electronically send the observational data from a VLBI radio telescope on one side of the globe in real-time to a VLBI correlator on the other side of the globe. Thus, data of two telescopes on opposite sides of the Earth, forming a long east-west oriented baseline, can be correlated in near real-time. Furthermore, advances in automated processing of the correlation results have made it possible to derive the Earth rotation angle UT1 in near real-time. Since 2007, the VLBI research groups in Sweden, Finland and Japan collaborate to derive UT1 in near real-time. Several dedicated so-called ultra-rapid UT1-sessions with 1-2 hours duration were performed. It was shown that final UT1-results can be derived within a few minutes after the end of an observing session (Sekido et al., 2008; Matsuzaka et al., 2008). The quality of the UT1-results is on the same level as the so-called IERS rapid solutions, but with a much lower latency (Haas et al., 2010). Recently, the ultra-rapid approach has been applied to standard 24 hour long VLBI observing sessions that are organized by the International VLBI Service for Geodesy and Astrometry (IVS). The long east-west baseline between Onsala (Sweden) and Tsukuba (Japan) is used to derive UT1 with a sliding window approach already during the ongoing IVS-session. The data

MISR Level 1 Near Real Time Products

Atmospheric Science Data Center

2016-10-31

Level 1 Near Real Time The MISR Near Real Time Level 1 data products ... km MISR swath and projected onto a Space-Oblique Mercator (SOM) map grid. The Ellipsoid-projected and Terrain-projected top-of-atmosphere (TOA) radiance products provide measurements respectively resampled onto the ...

Near Real Time Detection and Tracking of the EYJAFJÖLL (iceland) Ash Cloud by the RST (robust Satellite Technique) Approach

NASA Astrophysics Data System (ADS)

Tramutoli, V.; Filizzola, C.; Marchese, F.; Paciello, R.; Pergola, N.; Sannazzaro, F.

2010-12-01

Volcanic ash clouds, besides to be an environmental issue, represent a serious problem for air traffic and an important economic threat for aviation companies. During the recent volcanic crisis due to the April-May 2010 eruption of Eyjafjöll (Iceland), ash clouds became a real problem for common citizens as well: during the first days of the eruption thousands of flights were cancelled disrupting hundred of thousands of passengers. Satellite remote sensing confirmed to be a crucial tool for monitoring this kind of events, spreading for thousands of kilometres with a very rapid space-time dynamics. Especially weather satellites, thanks to their high temporal resolution, may furnish a fundamental contribution, providing frequently updated information. However, in this particular case ash cloud was accompanied by a sudden and significant emission of water vapour, due to the ice melting of Eyjafjallajökull glacier, making satellite ash detection and discrimination very hard, especially in the first few days of the eruption, exactly when accurate information were mostly required in order to support emergency management. Among the satellite-based techniques for near real-time detection and tracking of ash clouds, the RST (Robust Satellite Technique) approach, formerly named RAT - Robust AVHRR Technique, has been long since proposed, demonstrating high performances both in terms of reliability and sensitivity. In this paper, results achieved by using RST-based detection schemes, applied during the Eyjafjöll eruption were presented. MSG-SEVIRI (Meteosat Second Generation - Spinning Enhanced and Visible Infrared Imager) records, with a temporal sampling of 15 minutes, were used applying a standard as well as an advanced RST configuration, which includes the use of SO2 absorption band together with TIR and MIR channels. Main outcomes, limits and possible future improvements were also discussed.

A Near Real-time Decision Support System Improving Forest Management in the Tropics

NASA Astrophysics Data System (ADS)

Tabor, K.; Musinsky, J.; Ledezma, J.; Rasolohery, A.; Mendoza, E.; Kistler, H.; Steininger, M.; Morton, D. C.; Melton, F. S.; Manwell, J.; Koenig, K.

2013-12-01

Conservation International (CI) has a decade of experience developing near real-time fire and deforestation monitoring and forecasting systems that channel monitoring information from satellite observations directly to national and sub-national government agencies, Non-Government Organizations (NGOs), and local communities. These systems are used to strengthen forest surveillance and monitoring, fire management and prevention, protected areas management and sustainable land use planning. With support from a NASA Wildland Fires grant, in September 2013 CI will launch a brand new near real-time alert system (FIRECAST) to better meet the outstanding needs and challenges users face in addressing ecosystem degradation from wildland fire and illegal forest activities. Outreach efforts and user feedback have indicated the need for seasonal fire forecasts for effective land use planning, faster alert delivery to enhance response to illegal forest activities, and expanded forest monitoring capabilities that enable proactive responses and that strengthen forest conservation and sustainable development actions. The new FIRECAST system addresses these challenges by integrating the current fire alert and deforestation systems and adding improved ecological forecasting of fire risk; expanding data exchange capabilities with mobile technologies; and delivering a deforestation alert product that can inform policies related to land use management and Reduced Emissions from Deforestation and forest Degradation (REDD+). In addition to demonstrating the capabilities of this new real-time alert system, we also highlight how coordination with host-country institutions enhances the system's capacity to address the implementation needs of REDD+ forest carbon projects, improve tropical forest management, strengthen environmental law enforcement, and facilitate the uptake of near real-time satellite monitoring data into business practices of these national/sub-national institutions.

Near-Real-Time Detection and Monitoring of Intense Pyroconvection from Geostationary Satellites

NASA Astrophysics Data System (ADS)

Peterson, D. A.; Fromm, M. D.; Hyer, E. J.; Surratt, M. L.; Solbrig, J. E.; Campbell, J. R.

2016-12-01

Intense fire-triggered thunderstorms, known as pyrocumulonimbus (or pyroCb), can alter fire behavior, influence smoke plume trajectories, and hinder fire suppression efforts. PyroCb are also known for injecting a significant quantity of aerosol mass into the upper-troposphere and lower-stratosphere (UTLS). Near-real-time (NRT) detection and monitoring of pyroCb is highly desirable for a variety of forecasting and research applications. The Naval Research Laboratory (NRL) recently developed the first automated NRT pyroCb detection algorithm for geostationary satellite sensors. The algorithm uses multispectral infrared observations to isolate deep convective clouds with the distinct microphysical signal of pyroCb. Application of this algorithm to 88 intense wildfires observed during the 2013 fire season in western North America resulted in detection of individual intense events, pyroCb embedded within traditional convection, and multiple, short-lived pulses of activity. Comparisons with a community inventory indicate that this algorithm captures the majority of pyroCb. The primary limitation of the current system is that pyroCb anvils can be small relative to satellite pixel size, especially in in regions with large viewing angles. The algorithm is also sensitive to some false positives from traditional convection that either ingests smoke or exhibits extreme updraft velocities. This algorithm has been automated using the GeoIPS processing system developed at NRL, which produces a variety of imagery products and statistical output for rapid analysis of potential pyroCb events. NRT application of this algorithm has been extended to the majority of regions worldwide known to have a high frequency of pyroCb occurrence. This involves a constellation comprised of GOES-East, GOES-West, and Himawari-8. Imagery is posted immediately to an NRL-maintained web page. Alerts are generated by the system and disseminated via email. This detection system also has potential to serve

Improving AirNow Air Quality Products with NASA Near-Real-Time Remote Sensing Data (Invited)

NASA Astrophysics Data System (ADS)

Dye, T.; Pasch, A. N.; DeWinter, J. L.; Haderman, M.; Szykman, J.; White, J. E.; van Donkelaar, A.; Martin, R.

2013-12-01

The U.S. Environmental Protection Agency's (EPA) AirNow program provides the public with real-time and forecasted air quality conditions. Millions of people each day use it to protect their health. The AirNow program (http://www.airnow.gov), reports ground-level ozone (O3) and fine particulate matter (PM2.5) in a standardized index called the Air Quality Index (AQI). AirNow aggregates information from over 130 state, local, and federal air quality agencies and provides tools for over 2,000 agency staff responsible for monitoring, forecasting, and communicating local air quality. Each hour, AirNow systems generate thousands of maps and products. This presentation will describe how AirNow is benefiting from NASA's remote sensing data. We will describe two applications of NASA near-real-time remote sensing data within AirNow through case studies, focusing specifically on days when large spatial gradients in AQI and wildfire smoke impacts were observed. The first case study will show how AirNow is merging satellite-estimated PM2.5 concentrations into the AQI maps via the AirNow Satellite Data Processor (ASDP). AirNow derives these satellite estimates using NASA/NOAA satellite aerosol optical depth (AOD) retrievals and GEOS-Chem modeled ratios of surface PM2.5 concentrations to AOD. The second case study will show how NASA's Global Image Browse Services (GIBS) provides a near-real-time satellite product in AirNow-Tech for agency users to quickly identify smoke plumes and access air quality conditions in data-sparse areas during wildland fires.

Near-real time orbit determination for the GPS, CHAMP, GRACE, TerraSAR-X, and TanDEM-X satellites

NASA Astrophysics Data System (ADS)

Michalak, Grzegorz; Koenig, Rolf

The GFZ German Research Centre for Geosciences developed a near-real time (NRT) orbit gen-eration system for GPS and Low Earth Orbiting (LEO) satellites to support radio occultation data processing for the CHAMP, GRACE, Terra-SAR-X and the upcoming TanDEM-X mis-sions and fast baseline determination for the TanDEM-X mission. Precise NRT orbits are being generated for the CHAMP and GRACE-A satellites since August 2006 and for TerraSAR-X since August 2007. For each LEO, the system consists of three independent chains delivering NRT orbits with different latencies and accuracies. The first chain generates in a preceding step NRT GPS orbits and clock biases and based thereon LEO orbits with delays of 30 minutes counted from the last measurement point to the time the orbit product is available. The orbit accuracies can be assessed via Satellite Laser Ranging (SLR) to 7 cm. The second chain is based on predicted GPS orbits from the International GNSS Service (IGS) but endowed with in-house estimated clock biases. This chain generates orbits with the same latency of 30 minutes but with better accuracies of 5 cm SLR RMS. The third chain, the least accurate but the fastest, is based on predicted IGS GPS orbits and clocks and delivers LEO orbits with latencies of 13 minutes and accuracies of 10 cm SLR RMS. The system design is such that it can easily be extended to cope with new satellites like TanDEM-X requiring precise and fast available orbits.

MODIS Near real-time (NRT) data for fire applications

NASA Astrophysics Data System (ADS)

Wong, M.; Davies, D.; Ilavajhala, S.; Molinario, G.; Justice, C.; Latham, J.; Martucci, A.; Murphy, K. J.

2011-12-01

This paper describes the lessons learned from the development of the Fire Information for Resource Management System (FIRMS) prototype and its transition to an operational system, the Global Fire Information Management System (GFIMS), at the United Nations Food and Agriculture Organization (FAO) in August 2010. These systems provide active fire data from the MODIS sensor, on board NASA's Terra and Aqua Earth Observing Satellites, to users at no cost, in near-real time and in easy-to-use formats. The FIRMS prototype evolved from simply providing daily active fire text files via FTP, to include services such as providing fire data in various data formats, an interactive WebGIS allowing users to view and query the data and an email alert service enabling users to receive emails of near real-time fire data of their chosen area of interest. FIRMS was designed to remove obstacles to the uptake and use of fire data by addressing issues often associated with satellite data: cost, timeliness of delivery, limited data formats and the need for technical expertise to process and analyze the data. We also illustrate how the MODIS active fire data are routinely used for firefighting and conservation monitoring. We present results from a user survey, completed by approximately 345 people from 65 countries, and provide case studies highlighting how the provision of MODIS active fire data have made an impact on conservation and firefighting, especially in remote areas where it is difficult to have on-the-ground surveillance. We highlight the gaps in current capabilities, both with users and the data. A major obstacle still for some users is having low or no internet connectivity and a possible solution is through the use of cell phone technologies such as SMS text messaging of fire locations and information. GFIMS, and its precursor, FIRMS, were developed by the University of Maryland with funding from NASA's Applied Sciences Program. With GFIMS established at FAO as an operational

Towards a Cloud Computing Environment: Near Real-time Cloud Product Processing and Distribution for Next Generation Satellites

NASA Astrophysics Data System (ADS)

Nguyen, L.; Chee, T.; Minnis, P.; Palikonda, R.; Smith, W. L., Jr.; Spangenberg, D.

2016-12-01

The NASA LaRC Satellite ClOud and Radiative Property retrieval System (SatCORPS) processes and derives near real-time (NRT) global cloud products from operational geostationary satellite imager datasets. These products are being used in NRT to improve forecast model, aircraft icing warnings, and support aircraft field campaigns. Next generation satellites, such as the Japanese Himawari-8 and the upcoming NOAA GOES-R, present challenges for NRT data processing and product dissemination due to the increase in temporal and spatial resolution. The volume of data is expected to increase to approximately 10 folds. This increase in data volume will require additional IT resources to keep up with the processing demands to satisfy NRT requirements. In addition, these resources are not readily available due to cost and other technical limitations. To anticipate and meet these computing resource requirements, we have employed a hybrid cloud computing environment to augment the generation of SatCORPS products. This paper will describe the workflow to ingest, process, and distribute SatCORPS products and the technologies used. Lessons learn from working on both AWS Clouds and GovCloud will be discussed: benefits, similarities, and differences that could impact decision to use cloud computing and storage. A detail cost analysis will be presented. In addition, future cloud utilization, parallelization, and architecture layout will be discussed for GOES-R.

POD experiments using real and simulated time-sharing observations for GEO satellites in C-band transfer ranging system

NASA Astrophysics Data System (ADS)

Fen, Cao; XuHai, Yang; ZhiGang, Li; ChuGang, Feng

2016-08-01

The normal consecutive observing model in Chinese Area Positioning System (CAPS) can only supply observations of one GEO satellite in 1 day from one station. However, this can't satisfy the project need for observing many GEO satellites in 1 day. In order to obtain observations of several GEO satellites in 1 day like GPS/GLONASS/Galileo/BeiDou, the time-sharing observing model for GEO satellites in CAPS needs research. The principle of time-sharing observing model is illuminated with subsequent Precise Orbit Determination (POD) experiments using simulated time-sharing observations in 2005 and the real time-sharing observations in 2015. From time-sharing simulation experiments before 2014, the time-sharing observing 6 GEO satellites every 2 h has nearly the same orbit precision with the consecutive observing model. From POD experiments using the real time-sharing observations, POD precision for ZX12# and Yatai7# are about 3.234 m and 2.570 m, respectively, which indicates the time-sharing observing model is appropriate for CBTR system and can realize observing many GEO satellites in 1 day.

Enhancements to NASA's Land Atmosphere Near Real-Time Capability for EOS (LANCE)

NASA Technical Reports Server (NTRS)

Davies, Diane; Michael, Karen; Schmaltz, Jeffrey; Boller, Ryan A.; Masuoka, Ed; Ye, Gang; Roman, Miguel; Vermote, Eric; Harrison, Sherry; Rinsland, Pamela;

Adapting CALIPSO Climate Measurements for Near Real Time Analyses and Forecasting

NASA Technical Reports Server (NTRS)

Vaughan, Mark A.; Trepte, Charles R.; Winker, David M.; Avery, Melody A.; Campbell, James; Hoff, Ray; Young, Stuart; Getzewich, Brian J.; Tackett, Jason L.; Kar, Jayanta

2011-01-01

The Cloud-Aerosol Lidar and Infrared Pathfinder satellite Observations (CALIPSO) mission was originally conceived and designed as a climate measurements mission, with considerable latency between data acquisition and the release of the level 1 and level 2 data products. However, the unique nature of the CALIPSO lidar backscatter profiles quickly led to the qualitative use of CALIPSO?s near real time (i.e., ? expedited?) lidar data imagery in several different forecasting applications. To enable quantitative use of their near real time analyses, the CALIPSO project recently expanded their expedited data catalog to include all of the standard level 1 and level 2 lidar data products. Also included is a new cloud cleared level 1.5 profile product developed for use by operational forecast centers for verification of aerosol predictions. This paper describes the architecture and content of the CALIPSO expedited data products. The fidelity and accuracy of the expedited products are assessed via comparisons to the standard CALIPSO data products.

U. S. GEOLOGICAL SURVEY'S NATIONAL REAL-TIME HYDROLOGIC INFORMATION SYSTEM USING GOES SATELLITE TECHNOLOGY.

USGS Publications Warehouse

Shope, William G.

1987-01-01

The U. S. Geological Survey maintains the basic hydrologic data collection system for the United States. The Survey is upgrading the collection system with electronic communications technologies that acquire, telemeter, process, and disseminate hydrologic data in near real-time. These technologies include satellite communications via the Geostationary Operational Environmental Satellite, Data Collection Platforms in operation at over 1400 Survey gaging stations, Direct-Readout Ground Stations at nine Survey District Offices and a network of powerful minicomputers that allows data to be processed and disseminate quickly.

Video Data Link Provides Television Pictures In Near Real Time Via Tactical Radio And Satellite Channels

NASA Astrophysics Data System (ADS)

Hartman, Richard V.

1987-02-01

Advances in sophisticated algorithms and parallel VLSI processing have resulted in the capability for near real-time transmission of television pictures (optical and FLIR) via existing telephone lines, tactical radios, and military satellite channels. Concepts have been field demonstrated with production ready engineering development models using transform compression techniques. Preliminary design has been completed for packaging an existing command post version into a 20 pound 1/2 ATR enclosure for use on jeeps, backpacks, RPVs, helicopters, and reconnaissance aircraft. The system will also have a built-in error correction code 2 (ECC) unit, allowing operation via communicatons media exhibiting a bit error rate of 1 X 10-or better. In the past several years, two nearly simultaneous developments show promise of allowing the breakthrough needed to give the operational commander a practical means for obtaining pictorial information from the battlefield. And, he can obtain this information in near real time using available communications channels--his long sought after pictorial force multiplier: • High speed digital integrated circuitry that is affordable, and • An understanding of the practical applications of information theory. High speed digital integrated circuits allow an analog television picture to be nearly instantaneously converted to a digital serial bit stream so that it can be transmitted as rapidly or slowly as desired, depending on the available transmission channel bandwidth. Perhaps more importantly, digitizing the picture allows it to be stored and processed in a number of ways. Most typically, processing is performed to reduce the amount of data that must be transmitted, while still maintaining maximum picture quality. Reducing the amount of data that must be transmitted is important since it allows a narrower bandwidth in the scarce frequency spectrum to be used for transmission of pictures, or if only a narrow bandwidth is available, it

Introducing Real-Time AVHRR-APT Satellite Imagery in the Classroom Environment

ERIC Educational Resources Information Center

Moxey, Lucas; Tucker, Compton; Sloan, Jim; Chadwick, John

2004-01-01

A low-cost (US$350) satellite receiving station was assembled and operated within a classroom environment in Gainesville (Florida) on October 2001 for acquiring satellite data directly from the Advanced Very High Resolution Radiometer (AVHRR) satellites. The simplicity of the satellite signal makes this source of real-time satellite data readily…

Improvements and Additions to NASA Near Real-Time Earth Imagery

NASA Technical Reports Server (NTRS)

Cechini, Matthew; Boller, Ryan; Baynes, Kathleen; Schmaltz, Jeffrey; DeLuca, Alexandar; King, Jerome; Thompson, Charles; Roberts, Joe; Rodriguez, Joshua; Gunnoe, Taylor;

Impacts of Satellite Orbit and Clock on Real-Time GPS Point and Relative Positioning.

PubMed

Shi, Junbo; Wang, Gaojing; Han, Xianquan; Guo, Jiming

2017-06-12

Satellite orbit and clock corrections are always treated as known quantities in GPS positioning models. Therefore, any error in the satellite orbit and clock products will probably cause significant consequences for GPS positioning, especially for real-time applications. Currently three types of satellite products have been made available for real-time positioning, including the broadcast ephemeris, the International GNSS Service (IGS) predicted ultra-rapid product, and the real-time product. In this study, these three predicted/real-time satellite orbit and clock products are first evaluated with respect to the post-mission IGS final product, which demonstrates cm to m level orbit accuracies and sub-ns to ns level clock accuracies. Impacts of real-time satellite orbit and clock products on GPS point and relative positioning are then investigated using the P3 and GAMIT software packages, respectively. Numerical results show that the real-time satellite clock corrections affect the point positioning more significantly than the orbit corrections. On the contrary, only the real-time orbit corrections impact the relative positioning. Compared with the positioning solution using the IGS final product with the nominal orbit accuracy of ~2.5 cm, the real-time broadcast ephemeris with ~2 m orbit accuracy provided <2 cm relative positioning error for baselines no longer than 216 km. As for the baselines ranging from 574 to 2982 km, the cm-dm level positioning error was identified for the relative positioning solution using the broadcast ephemeris. The real-time product could result in <5 mm relative positioning accuracy for baselines within 2982 km, slightly better than the predicted ultra-rapid product.

Real Time GPS- Satellite Clock Estimation Development of a RTIGS Web Service

NASA Astrophysics Data System (ADS)

Opitz, M.; Weber, R.; Caissy, M.

2006-12-01

Since 3 years the IGS (International GNSS Service) Real-Time Working Group disseminates via Internet raw observation data of a subset of stations of the IGS network. This observation data can be used to establish a real-time integrity monitoring of the IGS predicted orbits (Ultra Rapid (IGU-) Orbits) and clocks, according to the recommendations of the IGS Workshop 2004 in Bern. The Institute for "Geodesy and Geophysics" of the TU-Vienna develops in cooperation with the IGS Real-Time Working Group the software "RTR- Control", which currently provides a real-time integrity monitoring of predicted IGU Clock Corrections to GPS Time. Our poster presents the results of a prototype version which is in operation since August this year. Besides RTR-Control allows for the comparison of pseudoranges measured at any permanent station in the global network with theoretical pseudoranges calculated on basis of the IGU- orbits. Thus, the programme can diagnose incorrectly predicted satellite orbits and clocks as well as detect multi-path distorted pseudoranges in real- time. RTR- Control calculates every 15 seconds Satellite Clock Corrections with respect to the most recent IGU- clocks (updated in a 6 hours interval). The clock estimations are referenced to a stable station clock (H-maser) with a small offset to GPS- time. This real-time Satellite Clocks are corrected for individual outliers and modelling errors. The most recent GPS- Satellite Clock Corrections (updated every 60 seconds) are published in Real Time via the Internet. The user group interested in a rigorous integrity monitoring comprises on the one hand the components of IGS itself to qualify the issued orbital data and on the other hand all users of the IGS Ultra Rapid Products (e.g. for PPP in Real Time).

Real-time estimation of BDS/GPS high-rate satellite clock offsets using sequential least squares

NASA Astrophysics Data System (ADS)

Fu, Wenju; Yang, Yuanxi; Zhang, Qin; Huang, Guanwen

2018-07-01

The real-time precise satellite clock product is one of key prerequisites for real-time Precise Point Positioning (PPP). The accuracy of the 24-hour predicted satellite clock product with 15 min sampling interval and an update of 6 h provided by the International GNSS Service (IGS) is only 3 ns, which could not meet the needs of all real-time PPP applications. The real-time estimation of high-rate satellite clock offsets is an efficient method for improving the accuracy. In this paper, the sequential least squares method to estimate real-time satellite clock offsets with high sample rate is proposed to improve the computational speed by applying an optimized sparse matrix operation to compute the normal equation and using special measures to take full advantage of modern computer power. The method is first applied to BeiDou Navigation Satellite System (BDS) and provides real-time estimation with a 1 s sample rate. The results show that the amount of time taken to process a single epoch is about 0.12 s using 28 stations. The Standard Deviation (STD) and Root Mean Square (RMS) of the real-time estimated BDS satellite clock offsets are 0.17 ns and 0.44 ns respectively when compared to German Research Center for Geosciences (GFZ) final clock products. The positioning performance of the real-time estimated satellite clock offsets is evaluated. The RMSs of the real-time BDS kinematic PPP in east, north, and vertical components are 7.6 cm, 6.4 cm and 19.6 cm respectively. The method is also applied to Global Positioning System (GPS) with a 10 s sample rate and the computational time of most epochs is less than 1.5 s with 75 stations. The STD and RMS of the real-time estimated GPS satellite clocks are 0.11 ns and 0.27 ns, respectively. The accuracies of 5.6 cm, 2.6 cm and 7.9 cm in east, north, and vertical components are achieved for the real-time GPS kinematic PPP.

Using Remotely Sensed Information for Near Real-Time Landslide Hazard Assessment

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia; Adler, Robert; Peters-Lidard, Christa

2013-01-01

The increasing availability of remotely sensed precipitation and surface products provides a unique opportunity to explore how landslide susceptibility and hazard assessment may be approached at larger spatial scales with higher resolution remote sensing products. A prototype global landslide hazard assessment framework has been developed to evaluate how landslide susceptibility and satellite-derived precipitation estimates can be used to identify potential landslide conditions in near-real time. Preliminary analysis of this algorithm suggests that forecasting errors are geographically variable due to the resolution and accuracy of the current susceptibility map and the application of satellite-based rainfall estimates. This research is currently working to improve the algorithm through considering higher spatial and temporal resolution landslide susceptibility information and testing different rainfall triggering thresholds, antecedent rainfall scenarios, and various surface products at regional and global scales.

Near Real-Time Monitoring of Forest Disturbance: A Multi-Sensor Remote Sensing Approach and Assessment Framework

NASA Astrophysics Data System (ADS)

Tang, Xiaojing

Fast and accurate monitoring of tropical forest disturbance is essential for understanding current patterns of deforestation as well as helping eliminate illegal logging. This dissertation explores the use of data from different satellites for near real-time monitoring of forest disturbance in tropical forests, including: development of new monitoring methods; development of new assessment methods; and assessment of the performance and operational readiness of existing methods. Current methods for accuracy assessment of remote sensing products do not address the priority of near real-time monitoring of detecting disturbance events as early as possible. I introduce a new assessment framework for near real-time products that focuses on the timing and the minimum detectable size of disturbance events. The new framework reveals the relationship between change detection accuracy and the time needed to identify events. In regions that are frequently cloudy, near real-time monitoring using data from a single sensor is difficult. This study extends the work by Xin et al. (2013) and develops a new time series method (Fusion2) based on fusion of Landsat and MODIS (Moderate Resolution Imaging Spectroradiometer) data. Results of three test sites in the Amazon Basin show that Fusion2 can detect 44.4% of the forest disturbance within 13 clear observations (82 days) after the initial disturbance. The smallest event detected by Fusion2 is 6.5 ha. Also, Fusion2 detects disturbance faster and has less commission error than more conventional methods. In a comparison of coarse resolution sensors, MODIS Terra and Aqua combined provides faster and more accurate detection of disturbance events than VIIRS (Visible Infrared Imaging Radiometer Suite) and MODIS single sensor data. The performance of near real-time monitoring using VIIRS is slightly worse than MODIS Terra but significantly better than MODIS Aqua. New monitoring methods developed in this dissertation provide forest protection

Operational Use of Near Real Time Remote sensing Data at the U.S. National Ice Center (NIC)

NASA Astrophysics Data System (ADS)

Clemente-Colon, P.

2012-12-01

The National Ice Center (NIC) is a U.S. Government agency that brings together the Department of Defense - Navy, Department of Commerce - National Oceanic and Atmospheric Administration (NOAA), and the Department of Homeland Security - U.S. Coast Guard (USCG) to support coastal and marine sea ice operations and research in the Polar Regions. The NIC provides specialized strategic and tactical ice analyses to meet the operational needs of the U.S. government and is the only operational ice service in the world that monitors sea ice in both the Arctic, Antarctic regions as well as in other ice infested waters. NIC utilizes multiple sources of near real time satellite and in-situ observations as well as NWP and ocean-sea ice model output to produce sea ice analyses. Key users of NIC products in the Arctic include the Navy submarine force, National Weather Service, USCG and Canadian Coast Guard icebreakers, Military Sealift Command on re-supply missions to Antarctica and Greenland, and NOAA research vessels operating near sea ice cover in both hemispheres as well. Time series of NIC weekly or bi-weekly ice analysis charts, daily marginal ice zone and ice edge routine products, as well as tactical support annotated imagery are generated by expert analysts with wide access to near real time satellite imagery from VIS/IR to passive and active microwave sensors. The status of these satellite data streams and the expected availability of new capabilities in the near future will be discussed.

News at Nine: The value of near-real time data for reaching mass media

NASA Astrophysics Data System (ADS)

Allen, J.; Ward, K.; Simmon, R. B.; Carlowicz, M. J.; Scott, M.; Przyborski, P. D.; Voiland, A. P.

2012-12-01

NASA's Earth Observatory (EO) is an online publication featuring NASA Earth science news and images. Since its inception in 1999, the EO team has relied heavily on near-real time satellite data to publish imagery of breaking news events, such as volcanoes, floods, fires, and dust storms. Major news outlets (Associated Press, The Weather Channel, CNN, etc.) have regularly republished Earth Observatory imagery in their coverage of events. Because of the nature of modern 24-hour news cycle, media almost always want near-real time coverage; providing it depends heavily on rapid data turnaround, user-friendly data systems, and fast data access. We will discuss how we use near-real time data and provide examples of how data systems have been transformed in the past 13 years. We will offer some thoughts on best practices (from the view of a user) in expedited data systems and the positive effect of those practices on public awareness of our content.. Finally, we will share how we work with science teams to see the potential stories in their data and the value of providing the data in a timely fashionAcquired October 9, 2010, this natural-color image shows the toxic sludge spill from an alumina plant in southern Hungary.

Approaching near real-time biosensing: microfluidic microsphere based biosensor for real-time analyte detection.

PubMed

Cohen, Noa; Sabhachandani, Pooja; Golberg, Alexander; Konry, Tania

2015-04-15

In this study we describe a simple lab-on-a-chip (LOC) biosensor approach utilizing well mixed microfluidic device and a microsphere-based assay capable of performing near real-time diagnostics of clinically relevant analytes such cytokines and antibodies. We were able to overcome the adsorption kinetics reaction rate-limiting mechanism, which is diffusion-controlled in standard immunoassays, by introducing the microsphere-based assay into well-mixed yet simple microfluidic device with turbulent flow profiles in the reaction regions. The integrated microsphere-based LOC device performs dynamic detection of the analyte in minimal amount of biological specimen by continuously sampling micro-liter volumes of sample per minute to detect dynamic changes in target analyte concentration. Furthermore we developed a mathematical model for the well-mixed reaction to describe the near real time detection mechanism observed in the developed LOC method. To demonstrate the specificity and sensitivity of the developed real time monitoring LOC approach, we applied the device for clinically relevant analytes: Tumor Necrosis Factor (TNF)-α cytokine and its clinically used inhibitor, anti-TNF-α antibody. Based on the reported results herein, the developed LOC device provides continuous sensitive and specific near real-time monitoring method for analytes such as cytokines and antibodies, reduces reagent volumes by nearly three orders of magnitude as well as eliminates the washing steps required by standard immunoassays. Copyright © 2014 Elsevier B.V. All rights reserved.

Enhancements to NASA's Land Atmosphere Near real-time Capability for EOS (LANCE)

NASA Astrophysics Data System (ADS)

Michael, K.; Davies, D. K.; Schmaltz, J. E.; Boller, R. A.; Mauoka, E.; Ye, G.; Vermote, E.; Harrison, S.; Rinsland, P. L.; Protack, S.; Durbin, P. B.; Justice, C. O.

2016-12-01

NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) supports application users interested in monitoring a wide variety of natural and man-made phenomena. Near Real-Time (NRT) data and imagery from the AIRS, AMSR2, MISR, MLS, MODIS, OMI and VIIRS instruments are available much quicker than routine processing allows. Most data products are available within 3 hours from satellite observation. NRT imagery are generally available 3-5 hours after observation. This article describes LANCE and enhancements made to LANCE over the last year. These enhancements include: the addition of MISR L1 Georeferenced Radiance and L2 Cloud Motion Vector products, AMSR2 Unified L2B Half-Orbit 25 km EASE-Grid Surface Soil Moisture products and VIIRS VIIRS Day/Night Band, Land Surface Reflectance and Corrected Surface reflectance products. In addition, the selection of LANCE NRT imagery that can be interactively viewed through Worldview and the Global Imagery Browse Services (GIBS) has been expanded. LANCE is also working to ingest and process data from OMPS.

Real-Time Application of Multi-Satellite Precipitation Analysis for Floods and Landslides

NASA Technical Reports Server (NTRS)

Adler, Robert; Hong, Yang; Huffman, George

2007-01-01

Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets-- both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers, In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described

Assimilation of Real-Time Satellite And Human Sensor Networks for Modeling Natural Disasters

NASA Astrophysics Data System (ADS)

Aulov, O.; Halem, M.; Lary, D. J.

2011-12-01

We describe the development of underlying technologies needed to address the merging of a web of real time satellite sensor Web (SSW) and Human Sensor Web (HSW) needed to augment the US response to extreme events. As an initial prototyping step and use case scenario, we consider the development of two major system tools that can be transitioned from research to the responding operational agency for mitigating coastal oil spills. These tools consist of the capture of Situation Aware (SA) Social Media (SM) Data, and assimilation of the processed information into forecasting models to provide incident decision managers with interactive virtual spatial temporal animations superimposed with probabilistic data estimates. The system methodologies are equally applicable to the wider class of extreme events such as plume dispersions from volcanoes or massive fires, major floods, hurricane impacts, radioactive isotope dispersions from nuclear accidents, etc. A successful feasibility demonstration of this technology has been shown in the case of the Deepwater Horizon Oil Spill where Human Sensor Networks have been combined with a geophysical model to perform parameter assessments. Flickr images of beached oil were mined from the spill area, geolocated and timestamped and converted into geophysical data. This data was incorporated into General NOAA Operational Modeling Environment (GNOME), a Lagrangian forecast model that uses near real-time surface winds, ocean currents, and satellite shape profiles of oil to generate a forecast of plume movement. As a result, improved estimates of diffusive coefficients and rates of oil spill were determined. Current approaches for providing satellite derived oil distributions are collected from a satellite sensor web of operational and research sensors from many countries, and a manual analysis is performed by NESDIS. A real time SA HSW processing system based on geolocated SM data from sources such as Twitter, Flickr, YouTube etc., greatly

Land, Atmosphere Near Real-time Capability for EOS (LANCE) AMSR2 Data System

NASA Astrophysics Data System (ADS)

Smith, D. K.; Harrison, S.; Lin, H.; Flynn, S.; Nair, M.; Conover, H.; Graves, S. J.

2016-12-01

The Land, Atmosphere Near real-time Capability for EOS (LANCE) system was initiated to ensure the availability of NASA satellite data products to those partners who have grown to rely upon near real-time (NRT) data for their decision support systems. The LANCE Advanced Microwave Scanning Radiometer-EOS (AMSR-E) system was able to address the needs of the NRT community in areas such as weather prediction and forecasting, monitoring of natural hazards, disaster relief, agriculture, and homeland security for nearly one year before the instrument failed in 2011. The timely launch of Global Change Observation Mission -Water 1 (GCOM-W1) and the AMSR2 instrument by the Japanese Aerospace Exploration Agency (JAXA) in 2012 was very important to continue the time series of AMSR instruments. The LANCE element for AMSR2 was able to leverage the LANCE AMSR-E system architecture, using modified AMSR-E standard product algorithms in order to make preliminary data products available to NRT users before US AMSR2 standard product algorithms were available. This presentation will describe the five AMSR2 NRT product suites available from LANCE - Sea Ice, Snow, Rain/Ocean, and Soil Moisture. We will also discuss future plans for LANCE AMSR2.

An improved RST approach for timely alert and Near Real Time monitoring of oil spill disasters by using AVHRR data

NASA Astrophysics Data System (ADS)

Grimaldi, C. S. L.; Casciello, D.; Coviello, I.; Lacava, T.; Pergola, N.; Tramutoli, V.

2011-05-01

Information acquired and provided in Near Real Time is fundamental in contributing to reduce the impact of different sea pollution sources on the maritime environment. Optical data acquired by sensors aboard meteorological satellites, thanks to their high temporal resolution as well as to their delivery policy, can be profitably used for a Near Real Time sea monitoring, provided that accurate and reliable methodologies for analysis and investigation are designed, implemented and fully assessed. In this paper, the results achieved by the application of an improved version of RST (Robust Satellite Technique) to oil spill detection and monitoring will be shown. In particular, thermal infrared data acquired by the NOAA-AVHRR (National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer) have been analyzed and a new RST-based change detection index applied to the case of the oil spills that occurred off the Kuwait and Saudi Arabian coasts in January 1991 and during the Lebanon War in July 2006. The results obtained, even in comparison with those achieved by other AVHRR-based techniques, confirm the unique performance of the proposed approach in automatically detecting the presence of oil spill with a high level of reliability and sensitivity. Moreover, the potential of the extension of the proposed technique to sensors onboard geostationary satellites will be discussed within the context of oil spill monitoring systems, integrating products generated by high temporal (optical) and high spatial (radar) resolution satellite systems.

Near-real time Monitoring of the widespread winter Fog over the Indo-Gangetic Plains using satellite data

NASA Astrophysics Data System (ADS)

Patil, D. L.; Gautam, R.; Rizvi, S.; Singh, M. K.

2016-12-01

The persistent and widespread winter fog impacts the Indo-Gangetic Plains (IGP) on an annual basis, disrupting day-to-day lives of millions of people in parts of northern India, Pakistan, Nepal and Bangladesh. The IGP is a densely-populated region located south of the Himalaya, in the northern parts of south Asia. During the past three decades or so, associated with growing population and energy demands, the IGP has witnessed strong upward trends in air pollution, particularly leading to poor air quality in the winter months. Co-occurring with the dense haze over the IGP, severe fog episodes persist throughout the months of December and January. Building on our recent work on satellite-based detection of fog, we have further extended the detection capability towards the development of a near-real time (NRT) fog monitoring system using satellite radiances and products. Here, we use multi-spectral radiances and aerosol/cloud retrievals from Terra/Aqua MODIS data for NRT fog monitoring over the IGP for both daytime as well as nighttime. Specifically, the nighttime fog detection algorithm employs a bi-spectral brightness temperature difference technique between two spectral channels: 3.9 μm and 11 μm. Our ongoing efforts also include extending fog detection capability in NRT to geostationary satellites, for providing continuous monitoring of the onset, evolution and spatial-temporal variation of fog, as well as the geospatial integration of surface meteorological observations of visibility, relative humidity, temperature. We anticipate that the ongoing and future development of a fog monitoring system may be of particular assistance to air and rail transportation management, as well as of general interest to the public. The outputs of fog detection algorithm and related aerosol/cloud parameters are operationally disseminated via http://fogsouthasia.com/.

Engineering design knowledge recycling in near-real-time

NASA Technical Reports Server (NTRS)

Leifer, Larry; Baya, Vinod; Toye, George; Baudin, Catherine; Underwood, Jody Gevins

1994-01-01

It is hypothesized that the capture and reuse of machine readable design records is cost beneficial. This informal engineering notebook design knowledge can be used to model the artifact and the design process. Design rationale is, in part, preserved and available for examination. Redesign cycle time is significantly reduced (Baya et al, 1992). These factors contribute to making it less costly to capture and reuse knowledge than to recreate comparable knowledge (current practice). To test the hypothesis, we have focused on validation of the concept and tools in two 'real design' projects this past year: (1) a short (8 month) turnaround project for NASA life science bioreactor researchers was done by a team of three mechanical engineering graduate students at Stanford University (in a class, ME210abc 'Mechatronic Systems Design and Methodology' taught by one of the authors, Leifer); and (2) a long range (8 to 20 year) international consortium project for NASA's Space Science program (STEP: satellite test of the equivalence principle). Design knowledge capture was supported this year by assigning the use of a Team-Design PowerBook. Design records were cataloged in near-real time. These records were used to qualitatively model the artifact design as it evolved. Dedal, an 'intelligent librarian' developed at NASA-ARC, was used to navigate and retrieve captured knowledge for reuse.

One-Centimeter Orbits in Near-Real Time: The GPS Experience on OSTM/JASON-2

NASA Technical Reports Server (NTRS)

Haines, Bruce; Armatys, Michael; Bar-Sever, Yoaz; Bertiger, Willy; Desai, Shailen; Dorsey, Angela; Lane, Christopher; Weiss, Jan

2010-01-01

The advances in Precise Orbit Determination (POD) over the past three decades have been driven in large measure by the increasing demands of satellite altimetry missions. Since the launch of Seasat in 1978, both tracking-system technologies and orbit modeling capabilities have evolved considerably. The latest in a series of precise (TOPEX-class) altimeter missions is the Ocean Surface Topography Mission (OSTM, also Jason-2). GPS-based orbit solutions for this mission are accurate to 1-cm (radial RMS) within 3-5 hrs of real time. These GPS-based orbit products provide the basis for a near-real time sea-surface height product that supports increasingly diverse applications of operational oceanography and climate forecasting.

Innovative Approaches for the Dissemination of Near Real-time Geostationary Satellite Data for Terrestrial and Space Weather Applications

NASA Astrophysics Data System (ADS)

Jedlovec, G.; McGrath, K.; Meyer, P. J.; Berndt, E.

2017-12-01

A GOES-R series receiving station has been installed at the NASA Marshall Space Flight Center (MSFC) to support GOES-16 transition-to-operations projects of NASA's Earth science program and provide a community portal for GOES-16 data access. This receiving station is comprised of a 6.5-meter dish; motor-driven positioners; Quorum feed and demodulator; and three Linux workstations for ingest, processing, display, and subsequent product generation. The Community Satellite Processing Package (CSPP) is used to process GOES Rebroadcast data from the Advanced Baseline Imager (ABI), Geostationary Lightning Mapper (GLM), Solar Ultraviolet Imager (SUVI), Extreme Ultraviolet and X-ray Irradiance Sensors (EXIS), and Space Environment In-Situ Suite (SEISS) into Level 1b and Level 2 files. GeoTIFFs of the imagery from several of these instruments are ingested into an Esri Arc Enterprise Web Map Service (WMS) server with tiled imagery displayable through a web browser interface or by connecting directly to the WMS with a Geographic Information System software package. These data also drive a basic web interface where users can manually zoom to and animate regions of interest or acquire similar results using a published Application Program Interface. While not as interactive as a WMS-driven interface, this system is much more expeditious with generating and distributing requested imagery. The legacy web capability enacted for the predecessor GOES Imager currently supports approximately 500,000 unique visitors each month. Dissemination capabilities have been refined to support a significantly larger number of anticipated users. The receiving station also supports NASA's Short-term Prediction, Research, and Transition Center's (SPoRT) project activities to dissemination near real-time ABI RGB products to National Weather Service National Centers, including the Satellite Analysis Branch, National Hurricane Center, Ocean Prediction Center, and Weather Prediction Center, where they

Real-Time and Near Real-Time Data for Space Weather Applications and Services

NASA Astrophysics Data System (ADS)

Singer, H. J.; Balch, C. C.; Biesecker, D. A.; Matsuo, T.; Onsager, T. G.

2015-12-01

Space weather can be defined as conditions in the vicinity of Earth and in the interplanetary environment that are caused primarily by solar processes and influenced by conditions on Earth and its atmosphere. Examples of space weather are the conditions that result from geomagnetic storms, solar particle events, and bursts of intense solar flare radiation. These conditions can have impacts on modern-day technologies such as GPS or electric power grids and on human activities such as astronauts living on the International Space Station or explorers traveling to the moon or Mars. While the ultimate space weather goal is accurate prediction of future space weather conditions, for many applications and services, we rely on real-time and near-real time observations and model results for the specification of current conditions. In this presentation, we will describe the space weather system and the need for real-time and near-real time data that drive the system, characterize conditions in the space environment, and are used by models for assimilation and validation. Currently available data will be assessed and a vision for future needs will be given. The challenges for establishing real-time data requirements, as well as acquiring, processing, and disseminating the data will be described, including national and international collaborations. In addition to describing how the data are used for official government products, we will also give examples of how these data are used by both the public and private sector for new applications that serve the public.

Expanding NASA's Land, Atmosphere Near real-time Capability for EOS

NASA Astrophysics Data System (ADS)

Davies, D.; Michael, K.; Masuoka, E.; Ye, G.; Schmaltz, J. E.; Harrison, S.; Ziskin, D.; Durbin, P. B.; Protack, S.; Rinsland, P. L.; Slayback, D. A.; Policelli, F. S.; Olsina, O.; Fu, G.; Ederer, G. A.; Ding, F.; Braun, J.; Gumley, L.; Prins, E. M.; Davidson, C. C.; Wong, M. M.

2017-12-01

NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) is a virtual system that provides near real-time EOS data and imagery to meet the needs of scientists and application users interested in monitoring a wide variety of natural and man-made phenomena in near real-time. Over the last year: near real-time products and imagery from MOPITT, MISR, OMPS and VIIRS (Land and Atmosphere) have been added; the Fire Information for Resource Management System (FIRMS) has been updated and LANCE has begun the process of integrating the Global NRT flood product. In addition, following the AMSU-A2 instrument anomaly in September 2016, AIRS-only products have replaced the NRT level 2 AIRS+AMSU products. This presentation provides a brief overview of LANCE, describes the new products that are recently available and contains a preview of what to expect in LANCE over the coming year. For more information visit: https://earthdata.nasa.gov/lance

Near Real Time MISR Wind Observations for Numerical Weather Prediction

NASA Astrophysics Data System (ADS)

Mueller, K. J.; Protack, S.; Rheingans, B. E.; Hansen, E. G.; Jovanovic, V. M.; Baker, N.; Liu, J.; Val, S.

2014-12-01

The Multi-angle Imaging SpectroRadiometer (MISR) project, in association with the NASA Langley Atmospheric Science Data Center (ASDC), has this year adapted its original production software to generate near-real time (NRT) cloud-motion winds as well as radiance imagery from all nine MISR cameras. These products are made publicly available at the ASDC with a latency of less than 3 hours. Launched aboard the sun-synchronous Terra platform in 1999, the MISR instrument continues to acquire near-global, 275 m resolution, multi-angle imagery. During a single 7 minute overpass of any given area, MISR retrieves the stereoscopic height and horizontal motion of clouds from the multi-angle data, yielding meso-scale near-instantaneous wind vectors. The ongoing 15-year record of MISR height-resolved winds at 17.6 km resolution has been validated against independent data sources. Low-level winds dominate the sampling, and agree to within ±3 ms-1 of collocated GOES and other observations. Low-level wind observations are of particular interest to weather forecasting, where there is a dearth of observations suitable for assimilation, in part due to reliability concerns associated with winds whose heights are assigned by the infrared brightness temperature technique. MISR cloud heights, on the other hand, are generated from stereophotogrammetric pattern matching of visible radiances. MISR winds also address data gaps in the latitude bands between geostationary satellite coverage and polar orbiting instruments that obtain winds from multiple overpasses (e.g. MODIS). Observational impact studies conducted by the Naval Research Laboratory (NRL) and by the German Weather Service (Deutscher Wetterdienst) have both demonstrated forecast improvements when assimilating MISR winds. An impact assessment using the GEOS-5 system is currently in progress. To benefit air quality forecasts, the MISR project is currently investigating the feasibility of generating near-real time aerosol products.

A Deep-Ocean Observatory with Near Real-time Telemetry

NASA Astrophysics Data System (ADS)

Berger, J.; Orcutt, J. A.; Laske, G.

2014-12-01

We describe an autonomously deployable, deep-ocean observatory designed to provide long term and near-real-time observations from sites far offshore. The key feature of this new system is its ability to telemeter sensor data from the seafloor to shore without a cable or moored surface buoy. In the future the observatory will be deployable without a ship. The first application of this system is seismology. While permanent ocean seismic stations on the seafloor have long been a goal of global seismology, today there are still no ocean bottom stations in the Global Seismographic Network, mostly for reasons of life-cycle costs. Yet real-time data from stations in oceanic areas are critical for both national and international agencies in monitoring and characterizing earthquakes, tsunamis, and nuclear explosions. The system comprises an ocean bottom instrumentation package and a free-floating surface communications gateway, which uses a Liquid Robotics wave glider. The glider consists of a surfboard-sized float propelled by a tethered, submerged glider, which converts wave motion into thrust. For navigation, the wave gliders are equipped with a small computer, a GPS receiver, a rudder, solar panels and batteries, and an Iridium satellite modem. Wave gliders have demonstrated trans-oceanic range combined with long-term station holding. The 'communications gateway,' which provides the means of communicating between the ocean bottom package and land comprises a wave glider and a towed acoustic communications 'tow body'. Acoustic communications connect the subsea instruments and the surface gateway while communications between the gateway and land is provided by the Iridium satellite constellation. Tests of the surface gateway in 4350 m of water demonstrated the ability to send four channels of compressed 24-bit, 1 sample per second data from the ocean bottom to the gateway with an average power draw of approximately 0.2 W.

New Near-Real Time Monitoring of the Ionosphere over Europe Available On-line

NASA Astrophysics Data System (ADS)

Chevalier, J. M.; Bergeot, N.; Bruyninx, C.; Pottiaux, E.; Aerts, W.; Baire, Q.; Legrand, J.; Defraigne, P.

2012-04-01

With the beginning of the 24th Solar cycle, the increased Solar activity requires having a close eye on the ionosphere for better understanding Space Weather physics and its effects on radio communications. In that frame, near-real time ionospheric models over Europe are now routinely generated at the Royal Observatory of Belgium (ROB). These models are made available to the public through new interactive web pages at the web site of the GNSS team (www.gnss.be) and the Solar Influences Data Analysis Center (www.sidc.be) of ROB. The models are ionospheric Vertical Total Electron Content (VTEC) maps estimated every 15 minutes on a 0.5°x0.5° grid. They use the high-rate GPS observations of the real-time stations in the EUREF Permanent Network (EPN) provided by the ROB NTRIP broadcaster. The maps are published on the ROB web site with a latency of 7-15 minutes with respect to the last GPS measurement included in the 15-minute observation files. In a first step, this paper presents the processing strategy used to generate the VTEC maps: input data, parameter estimation, data cleaning and interpolation method. In addition, the tools developed to further exploit the product are introduced, e.g. on-demand animated VTEC maps. In a second step, the VTEC maps are compared with external ionospheric products and models such as Global Ionospheric Maps and IRI 2011. These new near-real time VTEC maps will allow any user within the geographical scope of the maps to estimate in near-real time the ionospheric delay induced along the signal of any observed satellite. In the future, the web site will continuously be updated in response to evolving user needs. This paper opens doors to discussions with the user community to target their needs.

Monitoring Natural Events Globally in Near Real-Time Using NASA's Open Web Services and Tools

NASA Technical Reports Server (NTRS)

Boller, Ryan A.; Ward, Kevin Alan; Murphy, Kevin J.

2015-01-01

Since 1960, NASA has been making global measurements of the Earth from a multitude of space-based missions, many of which can be useful for monitoring natural events. In recent years, these measurements have been made available in near real-time, making it possible to use them to also aid in managing the response to natural events. We present the challenges and ongoing solutions to using NASA satellite data for monitoring and managing these events.

A framework to monitor activities of satellite data processing in real-time

NASA Astrophysics Data System (ADS)

Nguyen, M. D.; Kryukov, A. P.

2018-01-01

Space Monitoring Data Center (SMDC) of SINP MSU is one of the several centers in the world that collects data on the radiational conditions in near-Earth orbit from various Russian (Lomonosov, Electro-L1, Electro-L2, Meteor-M1, Meteor-M2, etc.) and foreign (GOES 13, GOES 15, ACE, SDO, etc.) satellites. The primary purposes of SMDC are: aggregating heterogeneous data from different sources; providing a unified interface for data retrieval, visualization, analysis, as well as development and testing new space weather models; and controlling the correctness and completeness of data. Space weather models rely on data provided by SMDC to produce forecasts. Therefore, monitoring the whole data processing cycle is crucial for further success in the modeling of physical processes in near-Earth orbit based on the collected data. To solve the problem described above, we have developed a framework called Live Monitor at SMDC. Live Monitor allows watching all stages and program components involved in each data processing cycle. All activities of each stage are logged by Live Monitor and shown in real-time on a web interface. When an error occurs, a notification message will be sent to satellite operators via email and the Telegram messenger service so that they could take measures in time. The Live Monitor’s API can be used to create a customized monitoring service with minimum coding.

Forensic Disaster Analysis in Near-real Time

NASA Astrophysics Data System (ADS)

Kunz, Michael; Zschau, Jochen; Wenzel, Friedemann; Khazai, Bijan; Kunz-Plapp, Tina; Trieselmann, Werner

2014-05-01

The impacts of extreme hydro-meteorological and geophysical events are controlled by various factors including severity of the event (intensity, duration, spatial extent), amplification with other phenomena (multihazard or cascading effects), interdependencies of technical systems and infrastructure, preparedness and resilience of the society. The Center for Disaster Management and Risk Reduction Technology (CEDIM) has adopted the comprehensive understanding of disasters and develops methodologies of near real-time FDA as a complementing component of the FORIN program of IRDR. The new research strategy 'Near Real-Time Forensic Disaster Analysis (FDA)' aims at scrutinizing disasters closely with a multi-disciplinary approach in order to assess the various aspects of disasters and to identify mechanisms most relevant for an extreme event to become a disaster (e.g., causal loss analysis). Recent technology developments - which have opened unprecedented opportunities for real-time hazard, vulnerability and loss assessment - are used for analyzing disasters and their impacts in combination with databases of historical events. The former covers modern empirical and analytical methods available in engineering and remote sensing for rapid impact assessments, rapid information extraction from crowd sourcing as well as rapid assessments of socio-economic impacts and economic losses. The event-driven science-based assessments of CEDIM are compiled based on interdisciplinary expertise and include the critical evaluation, assessment, validation, and quantification of an event. An important component of CEDIM's FDA is the near real-time approach which is expected to significantly speed up our understanding of natural disasters and be used to provide timely, relevant and valuable information to various user groups within their respective contexts. Currently, CEDIM has developed models and methodologies to assess different types of hazard. These approaches were applied to several

Near real-time geomagnetic data for space weather applications in the European sector

NASA Astrophysics Data System (ADS)

Johnsen, M. G.; Hansen, T. L.

2012-12-01

Tromsø Geophysical Observatory (TGO) is responsible for making and maintaining long time-series of geomagnetic measurements in Norway. TGO is currently operating 3 geomagnetic observatories and 11 variometer stations from southern Norway to Svalbard . Data from these 14 locations are acquired, processed and made available for the user community in near real-time. TGO is participating in several European Union (EU) and European Space Agency (ESA) space weather related projects where both near real-time data and derived products are provided. In addition the petroleum industry is benefiting from our real-time data services for directional drilling. Near real-time data from TGO is freely available for non-commercial purposes. TGO is exchanging data in near real-time with several institutions, enabling the presentation of near real-time geomagnetic data from more than 40 different locations in Fennoscandia and Greenland. The open exchange of non real-time geomagnetic data has been successfully going on for many years through services such as the world data center in Kyoto, SuperMAG, IMAGE and SPIDR. TGO's vision is to take this one step further and make the exchange of near real-time geomagnetic data equally available for the whole community. This presentation contains an overview of TGO, our activities and future aims. We will show how our near real-time data are presented. Our contribution to the space weather forecasting and nowcasting effort in the EU and ESA will be presented with emphasis on our real-time auroral activity index and brand new auroral activity monitor and electrojet tracker.

Near Real Time website for IASI observations of atmospheric anomalies

NASA Astrophysics Data System (ADS)

Hayer, Catherine; Grainger, Don; Marsh, Kevin; Carboni, Elisa; Ventress, Lucy; Smith, Andrew

2014-05-01

Rapid analysis of satellite observations of the state of the atmosphere and the contaminant levels within it can be used for pollution monitoring, forest fire detection and volcanic activity monitoring. There are numerous operational satellite instruments for which this is possible. The IASI instruments, currently flying on board the MetOp-A and MetOp-B satellite platforms, are used to produce Near Real Time (NRT) data using analysis algorithms developed by Oxford University. The data is then displayed on a website within 3 hours of measurement. This allows for the semi-continuous monitoring of the state of the atmosphere over most of the globe, both in daylight and at night. Global coverage is achieved 4 times per day, which is a significant advantage over most of the alternatives, either geostationary, giving limited spatial coverage, or UV instruments which are only able to observe during the daylight side of the orbit. The website includes flags for atmospheric contaminants detectable by IASI, including dust, biomass burning-derived species and volcanic ash and SO2. In the near future, the website will be developed to also include a quantitative estimate of the mass loading of SO2 contained within any volcanic cloud. Emissions of volcanic products, such as ash and SO2, are useful indicators of a change in the activity level of a volcano. Since many volcanoes are only monitored by remote sensing methods, such as satellite instruments, this can be the only such indicator available. These emissions are also dangerous to passing aircraft, causing damage to external surfaces of the plane and to the engines, sometimes leading to failure. Evacuation of regions surrounding volcanoes, and cessation or diversion of air traffic around actively erupting volcanoes is costly and highly disruptive but is sometimes required. Up to date information is of critical importance as to when to make these sensitive decisions. An archive of data will be available to allow for easy

Expanding NASA's Land, Atmosphere Near Real-Time Capability for EOS (LANCE)

NASA Technical Reports Server (NTRS)

Davies, Diane; Michael, Karen; Masuoka, Ed; Ye, Gang; Schmaltz, Jeffrey; Harrison, Sherry; Ziskin, Daniel; Durbin, Phil B; Protack, Steve; Rinsland, Pamela Livingstone;

Easing the Discovery of NASA and International Near-Real-Time Data Using the Global Change Master Directory

NASA Astrophysics Data System (ADS)

Ritz, S.; Olsen, L. M.; Morahan, M.; Stevens, T.; Aleman, A.; Grebas, S. K.

2011-12-01

The Global Change Master Directory (GCMD) provides an extensive directory of descriptive and spatial information about data sets and data-related services, which are relevant to Earth science research. The directory's data discovery components include controlled keywords, free-text searches, and map/date searches. The GCMD portal for NASA's Land Atmosphere Near-real-time Capability for EOS (LANCE) data products leverages these discovery features by providing users a direct route to NASA's Near-Real-Time (NRT) collections. This portal offers direct access to collection entries by instrument name, informing users of the availability of data. After a relevant collection entry is found through the GCMD's search components, the "Get Data" URL within the entry directs the user to the desired data. Building on the importance of Near-Real-Time (NRT) data, the Committee on Earth Observation Satellites (CEOS) International Directory Network (IDN) is targeting an effort to identify NRT data set collections from the CEOS international members. The international collections will be advertised as the "CEOS IDN NRT" portal to assist users in rapidly discovering these products, which are potentially useful for their research or public response. [This portal is expected to be released in 2012.

Expanding Access and Usage of NASA Near Real-Time Imagery and Data

NASA Astrophysics Data System (ADS)

Cechini, M.; Murphy, K. J.; Boller, R. A.; Schmaltz, J. E.; Thompson, C. K.; Huang, T.; McGann, J. M.; Ilavajhala, S.; Alarcon, C.; Roberts, J. T.

2013-12-01

In late 2009, the Land Atmosphere Near-real-time Capability for EOS (LANCE) was created to greatly expand the range of near real-time data products from a variety of Earth Observing System (EOS) instruments. Since that time, NASA's Earth Observing System Data and Information System (EOSDIS) developed the Global Imagery Browse Services (GIBS) to provide highly responsive, scalable, and expandable imagery services that distribute near real-time imagery in an intuitive and geo-referenced format. The GIBS imagery services provide access through standards-based protocols such as the Open Geospatial Consortium (OGC) Web Map Tile Service (WMTS) and standard mapping file formats such as the Keyhole Markup Language (KML). Leveraging these standard mechanisms opens NASA near real-time imagery to a broad landscape of mapping libraries supporting mobile applications. By easily integrating with mobile application development libraries, GIBS makes it possible for NASA imagery to become a reliable and valuable source for end-user applications. Recently, EOSDIS has taken steps to integrate near real-time metadata products into the EOS ClearingHOuse (ECHO) metadata repository. Registration of near real-time metadata allows for near real-time data discovery through ECHO clients. In kind with the near real-time data processing requirements, the ECHO ingest model allows for low-latency metadata insertion and updates. Combining with the ECHO repository, the fast visual access of GIBS imagery can now be linked directly back to the source data file(s). Through the use of discovery standards such as OpenSearch, desktop and mobile applications can connect users to more than just an image. As data services, such as OGC Web Coverage Service, become more prevalent within the EOSDIS system, applications may even be able to connect users from imagery to data values. In addition, the full resolution GIBS imagery provides visual context to other GIS data and tools. The NASA near real-time imagery

Near-real-time data fusion, phase 2

DOT National Transportation Integrated Search

1999-10-01

Report developed under SBIR contract for topic N93-084. In Phase I of this project, we explored several different approaches to Near-Real-Time Data Fusion (NRTDF), and in Phase II we developed the most promising architecture into a prototype NRTDF sy...

Near real-time traffic routing

NASA Technical Reports Server (NTRS)

Yang, Chaowei (Inventor); Xie, Jibo (Inventor); Zhou, Bin (Inventor); Cao, Ying (Inventor)

2012-01-01

A near real-time physical transportation network routing system comprising: a traffic simulation computing grid and a dynamic traffic routing service computing grid. The traffic simulator produces traffic network travel time predictions for a physical transportation network using a traffic simulation model and common input data. The physical transportation network is divided into a multiple sections. Each section has a primary zone and a buffer zone. The traffic simulation computing grid includes multiple of traffic simulation computing nodes. The common input data includes static network characteristics, an origin-destination data table, dynamic traffic information data and historical traffic data. The dynamic traffic routing service computing grid includes multiple dynamic traffic routing computing nodes and generates traffic route(s) using the traffic network travel time predictions.

USGS Provision of Near Real Time Remotely Sensed Imagery for Emergency Response

NASA Astrophysics Data System (ADS)

Jones, B. K.

2014-12-01

The use of remotely sensed imagery in the aftermath of a disaster can have an important impact on the effectiveness of the response for many types of disasters such as floods, earthquakes, volcanic eruptions, landslides, and other natural or human-induced disasters. Ideally, responders in areas that are commonly affected by disasters would have access to archived remote sensing imagery plus the ability to easily obtain the new post event data products. The cost of obtaining and storing the data and the lack of trained professionals who can process the data into a mapping product oftentimes prevent this from happening. USGS Emergency Operations provides remote sensing and geospatial support to emergency managers by providing access to satellite images from numerous domestic and international space agencies including those affiliated with the International Charter Space and Major Disasters and their space-based assets and by hosting and distributing thousands of near real time event related images and map products through the Hazards Data Distribution System (HDDS). These data may include digital elevation models, hydrographic models, base satellite images, vector data layers such as roads, aerial photographs, and other pre and post disaster data. These layers are incorporated into a Web-based browser and data delivery service, the Hazards Data Distribution System (HDDS). The HDDS can be made accessible either to the general public or to specific response agencies. The HDDS concept anticipates customer requirements and provides rapid delivery of data and services. This presentation will provide an overview of remotely sensed imagery that is currently available to support emergency response operations and examples of products that have been created for past events that have provided near real time situational awareness for responding agencies.

Near Real Time Tools for ISS Plasma Science and Engineering Applications

NASA Technical Reports Server (NTRS)

Minow, Joseph I.; Willis, Emily M.; Parker, Linda Neergaard; Shim, Ja Soon; Kuznetsova, Maria M.; Pulkkinen, Antti, A.

2013-01-01

The International Space Station (ISS) program utilizes a plasma environment forecast for estimating electrical charging hazards for crews during extravehicular activity (EVA). The process uses ionospheric electron density (Ne) and temperature (Te) measurements from the ISS Floating Potential Measurement Unit (FPMU) instrument suite with the assumption that the plasma conditions will remain constant for one to fourteen days with a low probability for a space weather event which would significantly change the environment before an EVA. FPMU data is typically not available during EVA's, therefore, the most recent FPMU data available for characterizing the state of the ionosphere during EVA is typically a day or two before the start of an EVA or after the EVA has been completed. Three near real time space weather tools under development for ISS applications are described here including: (a) Ne from ground based ionosonde measurements of foF2 (b) Ne from near real time satellite radio occultation measurements of electron density profiles (c) Ne, Te from a physics based ionosphere model These applications are used to characterize the ISS space plasma environment during EVA periods when FPMU data is not available, monitor for large changes in ionosphere density that could render the ionosphere forecast and plasma hazard assessment invalid, and validate the "persistence of conditions" forecast assumption. In addition, the tools are useful for providing space environment input to science payloads on ISS and anomaly investigations during periods the FPMU is not operating.

Near-real-time TOMS, telecommunications and meteorological support for the 1987 Airborne Antarctic Ozone Experiment

NASA Technical Reports Server (NTRS)

Ardanuy, P.; Victorine, J.; Sechrist, F.; Feiner, A.; Penn, L.

1988-01-01

The goal of the 1987 Airborne Antarctic Ozone Experiment was to improve the understanding of the mechanisms involved in the formation of the Antarctic ozone hole. Total ozone data taken by the Nimbus-7 Total Ozone Mapping Spectrometer (TOMS) played a central role in the successful outcome of the experiment. During the experiment, the near-real-time TOMS total ozone observations were supplied within hours of real time to the operations center in Punta Arenas, Chile. The final report summarizes the role which Research and Data Systems (RDS) Corporation played in the support of the experiment. The RDS provided telecommunications to support the science and operations efforts for the Airborne Antarctic Ozone Experiment, and supplied near real-time weather information to ensure flight and crew safety; designed and installed the telecommunications network to link NASA-GSFC, the United Kingdom Meteorological Office (UKMO), Palmer Station, the European Center for Medium-Range Weather Forecasts (ECMWF) to the operation at Punta Arenas; engineered and installed stations and other stand-alone systems to collect data from designated low-orbiting polar satellites and beacons; provided analyses of Nimbus-7 TOMS data and backup data products to Punta Arenas; and provided synoptic meteorological data analysis and reduction.

Steps Towards an Operational Service Using Near Real-Time Altimeter Data

NASA Astrophysics Data System (ADS)

Ash, E. R.

2006-07-01

Thanks largely to modern computing power, numerical forecasts of w inds and waves over the oceans ar e ev er improving, offering greater accuracy and finer resolution in time and sp ace. Howev er, it is recognized that met-ocean models still have difficulty in accurately forecasting sever e w eather conditions, conditions that cause the most damag e and difficulty in mar itime operations. Ther efore a key requir emen t is to provid e improved information on sever e conditions. No individual measur emen t or prediction system is perfect. Offshore buoys provide a continuous long-ter m record of wind and wave conditions, but only at a limited numb er of sites. Satellite data offer all-weath er global cov erage, but with relatively infrequen t samp ling. Forecasts rely on imperf ect numerical schemes and the ab ility to manage a vast quantity of input data. Therefore the best system is one that integr ates information from all available sources, taking advantage of the benef its that each can offer. We report on an initiative supported by the European Space Agen cy (ESA) which investig ated how satellite data could be used to enhan ce systems to provide Near Real Time mon itor ing of met-ocean conditions.

Near Real-Time Call Detail Record ETL Flows

NASA Astrophysics Data System (ADS)

Cochinwala, Munir; Panagos, Euthimios

Telecommunication companies face significant business challenges as they strive to reduce subscriber churn and increase average revenue per user (ARPU) by offering new services and incorporating new functionality into existing services. The increased number of service offerings and available functionality result in an ever growing volume of call detail records (CDRs). For many services (e.g., pre-paid), CDRs need to be processed and analyzed in near real-time for several reasons, including charging, on-line subscriber access to their accounts, and analytics for predicting subscriber usage and preventing fraudulent activity. In this paper, we describe the challenges associated with near real-time extract, transform, and load (ETL) of CDR data warehouse flows for supporting both the operational and business intelligence needs of telecommunication services, and we present our approach to addressing these challenges.

Hurricane Wave Topography and Directional Wave Spectra in Near Real-Time

DTIC Science & Technology

2005-09-30

Develop and/or modify the real - time operating system and analysis techniques and programs of the NASA Scanning Radar Altimeter (SRA) to process the...Wayne Wright is responsible for the real - time operating system of the SRA and making whatever modifications are required to enable near real-time

Automated Historical and Real-Time Cyclone Discovery With Multimodal Remote Satellite Measurements

NASA Astrophysics Data System (ADS)

Ho, S.; Talukder, A.; Liu, T.; Tang, W.; Bingham, A.

2008-12-01

methodology can be applied to (i) historical data to support Earth scientists in climate modeling, cyclonic-climate interactions, and obtain a better understanding of the cause and effects of cyclone (e.g. cyclo-genesis), and (ii) automatic cyclone discovery in near real-time using streaming satellite to support and improve the planning of global cyclone field campaigns. Additional satellite data from GOES and other orbiting satellites can be easily assimilated and integrated into our automated cyclone detection and tracking module to improve the temporal tracking accuracy of cyclones down to ½ hr and reduce the incidence of false alarms.

Demonstration of near real-time Sentinel-2A Landsat-8 registration

NASA Astrophysics Data System (ADS)

Yan, L.; Roy, D. P.; Huang, H.; Li, Z.; Zhang, H.

2017-12-01

The potential for near daily global medium-spatial-resolution optical wavelength remote sensing has been advanced by the availability of European Space Agency (ESA) Sentinel-2 data. Sentinel-2A (S2A) and Landsat-8 (L8) are known to have systematic misregistration errors due to factors including a Landsat geolocation reference discrepancy and a S2A satellite yaw orientation knowledge error (rectified in the recent S2A processing baseline V02.04). In order to undertake low temporal latency applications, such as change detection, near real-time sensor data registration is required. This study considered 2,459 S2A L1C tile images and 355 L8 Collection-1 images defined in UTM zone 35 acquired June to November 2016 over 700 × 1,200 km of Southern Africa. Misregistration characterizations among the S2A L1C tile time series and then among the Landsat-8 Collection-1 time series are first reported. Image matching was undertaken between near-infrared S2A 10 m image pairs and L8 image pairs (resampled to 10 m) using a recently published hierarchical image pyramid approach. The S2A V02.04 products had a 0.45 pixel (10 m) mean intra-misregistration, while the L8 Collection-1 images had a 0.12 pixel (10 m) mean intra-misregistration. Given these findings, we choose to register the S2A to the L8 data. Rather than registering individual images, which is not always robust to missing data, clouds or land surface changes, whole orbits falling over the same UTM zone were registered. A least-squares adjustment was applied using match points between S2A orbit images and L8 images as observations. Each orbit of S2A images was mached to multiple spatially-overlapping and contemporaneous L8 images to generate affine transformation coefficients for its registration. This provided a registered S2A and L8 time series with 0.3 pixel (10 m) misregistration (2σ) and demonstrates a near real-time methodology that can be applied as new sensor data are collected.

Interactive Visualization of Near Real-Time and Production Global Precipitation Mission Data Online Using CesiumJS

NASA Astrophysics Data System (ADS)

Lammers, M.

2016-12-01

Advancements in the capabilities of JavaScript frameworks and web browsing technology make online visualization of large geospatial datasets viable. Commonly this is done using static image overlays, pre-rendered animations, or cumbersome geoservers. These methods can limit interactivity and/or place a large burden on server-side post-processing and storage of data. Geospatial data, and satellite data specifically, benefit from being visualized both on and above a three-dimensional surface. The open-source JavaScript framework CesiumJS, developed by Analytical Graphics, Inc., leverages the WebGL protocol to do just that. It has entered the void left by the abandonment of the Google Earth Web API, and it serves as a capable and well-maintained platform upon which data can be displayed. This paper will describe the technology behind the two primary products developed as part of the NASA Precipitation Processing System STORM website: GPM Near Real Time Viewer (GPMNRTView) and STORM Virtual Globe (STORM VG). GPMNRTView reads small post-processed CZML files derived from various Level 1 through 3 near real-time products. For swath-based products, several brightness temperature channels or precipitation-related variables are available for animating in virtual real-time as the satellite observed them on and above the Earth's surface. With grid-based products, only precipitation rates are available, but the grid points are visualized in such a way that they can be interactively examined to explore raw values. STORM VG reads values directly off the HDF5 files, converting the information into JSON on the fly. All data points both on and above the surface can be examined here as well. Both the raw values and, if relevant, elevations are displayed. Surface and above-ground precipitation rates from select Level 2 and 3 products are shown. Examples from both products will be shown, including visuals from high impact events observed by GPM constellation satellites.

Design and Implementation of an Interactive Web-Based Near Real-Time Forest Monitoring System

PubMed Central

Pratihast, Arun Kumar; DeVries, Ben; Avitabile, Valerio; de Bruin, Sytze; Herold, Martin; Bergsma, Aldo

2016-01-01

This paper describes an interactive web-based near real-time (NRT) forest monitoring system using four levels of geographic information services: 1) the acquisition of continuous data streams from satellite and community-based monitoring using mobile devices, 2) NRT forest disturbance detection based on satellite time-series, 3) presentation of forest disturbance data through a web-based application and social media and 4) interaction of the satellite based disturbance alerts with the end-user communities to enhance the collection of ground data. The system is developed using open source technologies and has been implemented together with local experts in the UNESCO Kafa Biosphere Reserve, Ethiopia. The results show that the system is able to provide easy access to information on forest change and considerably improves the collection and storage of ground observation by local experts. Social media leads to higher levels of user interaction and noticeably improves communication among stakeholders. Finally, an evaluation of the system confirms the usability of the system in Ethiopia. The implemented system can provide a foundation for an operational forest monitoring system at the national level for REDD+ MRV applications. PMID:27031694

Design and Implementation of an Interactive Web-Based Near Real-Time Forest Monitoring System.

PubMed

Pratihast, Arun Kumar; DeVries, Ben; Avitabile, Valerio; de Bruin, Sytze; Herold, Martin; Bergsma, Aldo

2016-01-01

This paper describes an interactive web-based near real-time (NRT) forest monitoring system using four levels of geographic information services: 1) the acquisition of continuous data streams from satellite and community-based monitoring using mobile devices, 2) NRT forest disturbance detection based on satellite time-series, 3) presentation of forest disturbance data through a web-based application and social media and 4) interaction of the satellite based disturbance alerts with the end-user communities to enhance the collection of ground data. The system is developed using open source technologies and has been implemented together with local experts in the UNESCO Kafa Biosphere Reserve, Ethiopia. The results show that the system is able to provide easy access to information on forest change and considerably improves the collection and storage of ground observation by local experts. Social media leads to higher levels of user interaction and noticeably improves communication among stakeholders. Finally, an evaluation of the system confirms the usability of the system in Ethiopia. The implemented system can provide a foundation for an operational forest monitoring system at the national level for REDD+ MRV applications.

Near real-time estimation of burned area using VIIRS 375 m active fire product

NASA Astrophysics Data System (ADS)

Oliva, P.; Schroeder, W.

2016-12-01

Every year, more than 300 million hectares of land burn globally, causing significant ecological and economic consequences, and associated climatological effects as a result of fire emissions. In recent decades, burned area estimates generated from satellite data have provided systematic global information for ecological analysis of fire impacts, climate and carbon cycle models, and fire regimes studies, among many others. However, there is still need of near real-time burned area estimations in order to assess the impacts of fire and estimate smoke and emissions. The enhanced characteristics of the Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m channels on board the Suomi National Polar-orbiting Partnesship (S-NPP) make possible the use of near real-time active fire detection data for burned area estimation. In this study, consecutive VIIRS 375 m active fire detections were aggregated to produce the VIIRS 375 m burned area (BA) estimation over ten ecologically diverse study areas. The accuracy of the BA estimations was assessed by comparison with Landsat-8 supervised burned area classification. The performance of the VIIRS 375 m BA estimates was dependent on the ecosystem characteristics and fire behavior. Higher accuracy was observed in forested areas characterized by large long-duration fires, while grasslands, savannas and agricultural areas showed the highest omission and commission errors. Complementing those analyses, we performed the burned area estimation of the largest fires in Oregon and Washington states during 2015 and the Fort McMurray fire in Canada 2016. The results showed good agreement with NIROPs airborne fire perimeters proving that the VIIRS 375 m BA estimations can be used for near real-time assessments of fire effects.

Near Real Time Structural Health Monitoring with Multiple Sensors in a Cloud Environment

NASA Astrophysics Data System (ADS)

Bock, Y.; Todd, M.; Kuester, F.; Goldberg, D.; Lo, E.; Maher, R.

2017-12-01

A repeated near real time 3-D digital surrogate representation of critical engineered structures can be used to provide actionable data on subtle time-varying displacements in support of disaster resiliency. We describe a damage monitoring system of optimally-integrated complementary sensors, including Global Navigation Satellite Systems (GNSS), Micro-Electro-Mechanical Systems (MEMS) accelerometers coupled with the GNSS (seismogeodesy), light multi-rotor Unmanned Aerial Vehicles (UAVs) equipped with high-resolution digital cameras and GNSS/IMU, and ground-based Light Detection and Ranging (LIDAR). The seismogeodetic system provides point measurements of static and dynamic displacements and seismic velocities of the structure. The GNSS ties the UAV and LIDAR imagery to an absolute reference frame with respect to survey stations in the vicinity of the structure to isolate the building response to ground motions. The GNSS/IMU can also estimate the trajectory of the UAV with respect to the absolute reference frame. With these constraints, multiple UAVs and LIDAR images can provide 4-D displacements of thousands of points on the structure. The UAV systematically circumnavigates the target structure, collecting high-resolution image data, while the ground LIDAR scans the structure from different perspectives to create a detailed baseline 3-D reference model. UAV- and LIDAR-based imaging can subsequently be repeated after extreme events, or after long time intervals, to assess before and after conditions. The unique challenge is that disaster environments are often highly dynamic, resulting in rapidly evolving, spatio-temporal data assets with the need for near real time access to the available data and the tools to translate these data into decisions. The seismogeodetic analysis has already been demonstrated in the NASA AIST Managed Cloud Environment (AMCE) designed to manage large NASA Earth Observation data projects on Amazon Web Services (AWS). The Cloud provides

Interactive Visualization of Near Real Time and Production Global Precipitation Measurement (GPM) Mission Data Online Using CesiumJS

NASA Technical Reports Server (NTRS)

Lammers, Matthew

2016-01-01

Advancements in the capabilities of JavaScript frameworks and web browsing technology make online visualization of large geospatial datasets viable. Commonly this is done using static image overlays, prerendered animations, or cumbersome geoservers. These methods can limit interactivity andor place a large burden on server-side post-processing and storage of data. Geospatial data, and satellite data specifically, benefit from being visualized both on and above a three-dimensional surface. The open-source JavaScript framework CesiumJS, developed by Analytical Graphics, Inc., leverages the WebGL protocol to do just that. It has entered the void left by the abandonment of the Google Earth Web API, and it serves as a capable and well-maintained platform upon which data can be displayed. This paper will describe the technology behind the two primary products developed as part of the NASA Precipitation Processing System STORM website: GPM Near Real Time Viewer (GPMNRTView) and STORM Virtual Globe (STORM VG). GPMNRTView reads small post-processed CZML files derived from various Level 1 through 3 near real-time products. For swath-based products, several brightness temperature channels or precipitation-related variables are available for animating in virtual real-time as the satellite-observed them on and above the Earths surface. With grid-based products, only precipitation rates are available, but the grid points are visualized in such a way that they can be interactively examined to explore raw values. STORM VG reads values directly off the HDF5 files, converting the information into JSON on the fly. All data points both on and above the surface can be examined here as well. Both the raw values and, if relevant, elevations are displayed. Surface and above-ground precipitation rates from select Level 2 and 3 products are shown. Examples from both products will be shown, including visuals from high impact events observed by GPM constellation satellites.

Near-Real-Time and Laboratory Data by State

EPA Pesticide Factsheets

RadNet data from individual near-real-time air monitors is available on a clickable map and is also listed by state and city. Sampling locations with drinking water, precipitation and air filter analysis results in 2016 are also listed.

ISKANDARnet IOMOS: Near real-time equatorial space weather monitoring and alert system in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Musa, Tajul Ariffin; Leong, Shien Kwun; Abdullah, Khairul Anuar; Othman, Rusli

2012-11-01

This work proposes ISKANDARnet Ionospheric Outburst MOnitoring and alert System (IOMOS), along with Ionospheric Outburst Index (IOX) to develop an operational near real-time space weather service for Malaysia. The IOMOS is based on Global Positioning System (GPS) Network-based Real-Time Kinematic (NRTK) concept which is by nature for atmospheric (ionosphere and troposphere) modeling within the network coverage. The elegance of this solution lies in the fact that IOMOS utilize differential ionospheric residual from network of GPS baselines which incur no additional cost for operation. Users will be informed about the ionospheric perturbation through Short Message Service (SMS), email or Twitter®. This approach will ultimately beneficial for the navigation and satellite positioning communities, particularly during the coming Solar Cycle 24. In addition, a combination of local and global GPS network has been employed to study the equatorial ionosphere geomorphology and climatology in the Malaysian sector. Equatorial Total Electron Content (TEC) over Malaysia shows semi-annual, annual, and seasonal variations with maximum values appearing during equinoctial months and minimum during solstices months. The TEC value during vernal equinox is about 21% higher than autumnal equinox, and December solstice exceeds that at the June solstice by around 14%. It is also found that semi-annual variation is present at all levels of solar activity, whereas June solstice predominates December solstice during high solar activity for annual and seasonal variations. In near future, a near real-time TEC derivation system will be developed to support equatorial ionosphere modeling to enhance space weather service for Malaysia.

Remotely-sensed near real-time monitoring of reservoir storage in India

NASA Astrophysics Data System (ADS)

Tiwari, A. D.; Mishra, V.

2017-12-01

Real-time reservoir storage information at a high temporal resolution is crucial to mitigate the influence of extreme events like floods and droughts. Despite large implications of near real-time reservoir monitoring in India for water resources and irrigation, remotely sensed monitoring systems have been lacking. Here we develop remotely sensed real-time monitoring systems for 91 large reservoirs in India for the period from 2000 to 2017. For the reservoir storage estimation, we combined Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day 250 m Enhanced Vegetation Index (EVI), and Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and land Elevation Satellite (ICESat) ICESat/GLAS elevation data. Vegetation data with the highest temporal resolution available from the MODIS is at 16 days. To increase the temporal resolution to 8 days, we developed the 8-day composite of near infrared, red, and blue band surface reflectance. Surface reflectance 8-Day L3 Global 250m only have NIR band and Red band, therefore, surface reflectance of 8-Day L3 Global at 500m is used for the blue band, which was regridded to 250m spatial resolution. An area-elevation relationship was derived using area from an unsupervised classification of MODIS image followed by an image enhancement and elevation data from ICESat/GLAS. A trial and error method was used to obtain the area-elevation relationship for those reservoirs for which ICESat/GLAS data is not available. The reservoir storages results were compared with the gauge storage data from 2002 to 2009 (training period), which were then evaluated for the period of 2010 to 2016. Our storage estimates were highly correlated with observations (R2 = 0.6 to 0.96), and the normalized root mean square error (NRMSE) ranged between 10% and 50%. We also developed a relationship between precipitation and reservoir storage that can be used for prediction of storage during the dry season.

Real-Time and Seamless Monitoring of Ground-Level PM2.5 Using Satellite Remote Sensing

NASA Astrophysics Data System (ADS)

Li, Tongwen; Zhang, Chengyue; Shen, Huanfeng; Yuan, Qiangqiang; Zhang, Liangpei

2018-04-01

Satellite remote sensing has been reported to be a promising approach for the monitoring of atmospheric PM2.5. However, the satellite-based monitoring of ground-level PM2.5 is still challenging. First, the previously used polar-orbiting satellite observations, which can be usually acquired only once per day, are hard to monitor PM2.5 in real time. Second, many data gaps exist in satellitederived PM2.5 due to the cloud contamination. In this paper, the hourly geostationary satellite (i.e., Harawari-8) observations were adopted for the real-time monitoring of PM2.5 in a deep learning architecture. On this basis, the satellite-derived PM2.5 in conjunction with ground PM2.5 measurements are incorporated into a spatio-temporal fusion model to fill the data gaps. Using Wuhan Urban Agglomeration as an example, we have successfully derived the real-time and seamless PM2.5 distributions. The results demonstrate that Harawari-8 satellite-based deep learning model achieves a satisfactory performance (out-of-sample cross-validation R2 = 0.80, RMSE = 17.49 μg/m3) for the estimation of PM2.5. The missing data in satellite-derive PM2.5 are accurately recovered, with R2 between recoveries and ground measurements of 0.75. Overall, this study has inherently provided an effective strategy for the realtime and seamless monitoring of ground-level PM2.5.

Single frequency GPS measurements in real-time artificial satellite orbit determination

NASA Astrophysics Data System (ADS)

Chiaradia, orbit determination A. P. M.; Kuga, H. K.; Prado, A. F. B. A.

2003-07-01

A simplified and compact algorithm with low computational cost providing an accuracy around tens of meters for artificial satellite orbit determination in real-time and on-board is developed in this work. The state estimation method is the extended Kalman filter. The Cowell's method is used to propagate the state vector, through a simple Runge-Kutta numerical integrator of fourth order with fixed step size. The modeled forces are due to the geopotential up to 50th order and degree of JGM-2 model. To time-update the state error covariance matrix, it is considered a simplified force model. In other words, in computing the state transition matrix, the effect of J 2 (Earth flattening) is analytically considered, which unloads dramatically the processing time. In the measurement model, the single frequency GPS pseudorange is used, considering the effects of the ionospheric delay, clock offsets of the GPS and user satellites, and relativistic effects. To validate this model, real live data are used from Topex/Poseidon satellite and the results are compared with the Topex/Poseidon Precision Orbit Ephemeris (POE) generated by NASA/JPL, for several test cases. It is concluded that this compact algorithm enables accuracies of tens of meters with such simplified force model, analytical approach for computing the transition matrix, and a cheap GPS receiver providing single frequency pseudorange measurements.

A Cloud-Based Infrastructure for Near-Real-Time Processing and Dissemination of NPP Data

NASA Astrophysics Data System (ADS)

Evans, J. D.; Valente, E. G.; Chettri, S. S.

2011-12-01

We are building a scalable cloud-based infrastructure for generating and disseminating near-real-time data products from a variety of geospatial and meteorological data sources, including the new National Polar-Orbiting Environmental Satellite System (NPOESS) Preparatory Project (NPP). Our approach relies on linking Direct Broadcast and other data streams to a suite of scientific algorithms coordinated by NASA's International Polar-Orbiter Processing Package (IPOPP). The resulting data products are directly accessible to a wide variety of end-user applications, via industry-standard protocols such as OGC Web Services, Unidata Local Data Manager, or OPeNDAP, using open source software components. The processing chain employs on-demand computing resources from Amazon.com's Elastic Compute Cloud and NASA's Nebula cloud services. Our current prototype targets short-term weather forecasting, in collaboration with NASA's Short-term Prediction Research and Transition (SPoRT) program and the National Weather Service. Direct Broadcast is especially crucial for NPP, whose current ground segment is unlikely to deliver data quickly enough for short-term weather forecasters and other near-real-time users. Direct Broadcast also allows full local control over data handling, from the receiving antenna to end-user applications: this provides opportunities to streamline processes for data ingest, processing, and dissemination, and thus to make interpreted data products (Environmental Data Records) available to practitioners within minutes of data capture at the sensor. Cloud computing lets us grow and shrink computing resources to meet large and rapid fluctuations in data availability (twice daily for polar orbiters) - and similarly large fluctuations in demand from our target (near-real-time) users. This offers a compelling business case for cloud computing: the processing or dissemination systems can grow arbitrarily large to sustain near-real time data access despite surges in

A Modern Operating System for Near-real-time Environmental Observatories

NASA Astrophysics Data System (ADS)

Orcutt, John; Vernon, Frank

2014-05-01

The NSF Ocean Observatory Initiative (OOI) provided an opportunity for expanding the capabilities for managing open, near-real-time (latencies of seconds) data from ocean observatories. The sensors deployed in this system largely return data from seafloor, cabled fiber optic cables as well as satellite telemetry. Bandwidth demands range from high-definition movies to the transmission of data via Iridium satellite. The extended Internet also provides an opportunity to not only return data, but to also control the sensors and platforms that comprise the observatory. The data themselves are openly available to any users. In order to provide heightened network security and overall reliability, the connections to and from the sensors/platforms are managed without Layer 3 of the Internet, but instead rely upon message passing using an open protocol termed Advanced Queuing Messaging Protocol (AMQP). The highest bandwidths in the system are in the Regional Scale Network (RSN) off Oregon and Washington and on the continent with highly reliable network connections between observatory components at 10 Gbps. The maintenance of metadata and life cycle histories of sensors and platforms is critical for providing data provenance over the years. The integrated cyberinfrastructure is best thought of as an operating system for the observatory - like the data, the software is also open and can be readily applied to new observatories, for example, in the rapidly evolving Arctic.

Global Near Real-Time MODIS and Landsat Flood Mapping and Product Delivery

NASA Astrophysics Data System (ADS)

Policelli, F. S.; Slayback, D. A.; Tokay, M. M.; Brakenridge, G. R.

2014-12-01

Flooding is the most destructive, frequent, and costly natural disaster faced by modern society, and is increasing in frequency and damage (deaths, displacements, and financial costs) as populations increase and climate change generates more extreme weather events. When major flooding events occur, the disaster management community needs frequently updated and easily accessible information to better understand the extent of flooding and coordinate response efforts. With funding from NASA's Applied Sciences program, we developed and are now operating a near real-time global flood mapping system to help provide flood extent information within 24-48 hours of events. The principal element of the system applies a water detection algorithm to MODIS imagery, which is processed by the LANCE (Land Atmosphere Near real-time Capability for EOS) system at NASA Goddard within a few hours of satellite overpass. Using imagery from both the Terra (10:30 AM local time overpass) and Aqua (1:30 PM) platforms allows the system to deliver an initial daily assessment of flood extent by late afternoon, and more robust assessments after accumulating cloud-free imagery over several days. Cloud cover is the primary limitation in detecting surface water from MODIS imagery. Other issues include the relatively coarse scale of the MODIS imagery (250 meters) for some events, the difficulty of detecting flood waters in areas with continuous canopy cover, confusion of shadow (cloud or terrain) with water, and accurately identifying detected water as flood as opposed to normal water extent. We are working on improvements to address these limitations. We have also begun delivery of near real time water maps at 30 m resolution from Landsat imagery. Although Landsat is not available daily globally, but only every 8 days if imagery from both operating platforms (Landsat 7 and 8) is accessed, it can provide useful higher resolution data on water extent when a clear acquisition coincides with an active

GPS Satellite Orbit Prediction at User End for Real-Time PPP System.

PubMed

Yang, Hongzhou; Gao, Yang

2017-08-30

This paper proposed the high-precision satellite orbit prediction process at the user end for the real-time precise point positioning (PPP) system. Firstly, the structure of a new real-time PPP system will be briefly introduced in the paper. Then, the generation of satellite initial parameters (IP) at the sever end will be discussed, which includes the satellite position, velocity, and the solar radiation pressure (SRP) parameters for each satellite. After that, the method for orbit prediction at the user end, with dynamic models including the Earth's gravitational force, lunar gravitational force, solar gravitational force, and the SRP, are presented. For numerical integration, both the single-step Runge-Kutta and multi-step Adams-Bashforth-Moulton integrator methods are implemented. Then, the comparison between the predicted orbit and the international global navigation satellite system (GNSS) service (IGS) final products are carried out. The results show that the prediction accuracy can be maintained for several hours, and the average prediction error of the 31 satellites are 0.031, 0.032, and 0.033 m for the radial, along-track and cross-track directions over 12 h, respectively. Finally, the PPP in both static and kinematic modes are carried out to verify the accuracy of the predicted satellite orbit. The average root mean square error (RMSE) for the static PPP of the 32 globally distributed IGS stations are 0.012, 0.015, and 0.021 m for the north, east, and vertical directions, respectively; while the RMSE of the kinematic PPP with the predicted orbit are 0.031, 0.069, and 0.167 m in the north, east and vertical directions, respectively.

GPS Satellite Orbit Prediction at User End for Real-Time PPP System

PubMed Central

Yang, Hongzhou; Gao, Yang

2017-01-01

This paper proposed the high-precision satellite orbit prediction process at the user end for the real-time precise point positioning (PPP) system. Firstly, the structure of a new real-time PPP system will be briefly introduced in the paper. Then, the generation of satellite initial parameters (IP) at the sever end will be discussed, which includes the satellite position, velocity, and the solar radiation pressure (SRP) parameters for each satellite. After that, the method for orbit prediction at the user end, with dynamic models including the Earth’s gravitational force, lunar gravitational force, solar gravitational force, and the SRP, are presented. For numerical integration, both the single-step Runge–Kutta and multi-step Adams–Bashforth–Moulton integrator methods are implemented. Then, the comparison between the predicted orbit and the international global navigation satellite system (GNSS) service (IGS) final products are carried out. The results show that the prediction accuracy can be maintained for several hours, and the average prediction error of the 31 satellites are 0.031, 0.032, and 0.033 m for the radial, along-track and cross-track directions over 12 h, respectively. Finally, the PPP in both static and kinematic modes are carried out to verify the accuracy of the predicted satellite orbit. The average root mean square error (RMSE) for the static PPP of the 32 globally distributed IGS stations are 0.012, 0.015, and 0.021 m for the north, east, and vertical directions, respectively; while the RMSE of the kinematic PPP with the predicted orbit are 0.031, 0.069, and 0.167 m in the north, east and vertical directions, respectively. PMID:28867771

TerraSAR-X precise orbit determination with real-time GPS ephemerides

NASA Astrophysics Data System (ADS)

Wermuth, Martin; Hauschild, Andre; Montenbruck, Oliver; Kahle, Ralph

TerraSAR-X is a German Synthetic Aperture Radar (SAR) satellite, which was launched in June 2007 from Baikonour. Its task is to acquire radar images of the Earth's surface. In order to locate the radar data takes precisely, the satellite is equipped with a high-quality dual-frequency GPS receiver -the Integrated Geodetic and Occultation Receiver (IGOR) provided by the GeoForschungsZentrum Potsdam (GFZ). Using GPS observations from the IGOR instrument in a reduced dynamic precise orbit determination (POD), the German Space Operations Center (DLR/GSOC) is computing rapid and science orbit products on a routine basis. The rapid orbit products arrive with a latency of about one hour after data reception with an accuracy of 10-20 cm. Science orbit products are computed with a latency of five days achieving an accuracy of about 5cm (3D-RMS). For active and future Earth observation missions, the availability of near real-time precise orbit information is becoming more and more important. Other applications of near real-time orbit products include the processing of GNSS radio occulation measurements for atmospheric sounding as well as altimeter measurements of ocean surface heights, which are nowadays employed in global weather and ocean circulation models with short latencies. For example after natural disasters it is necessary to evaluate the damage by satellite images as soon as possible. The latency and quality of POD results is mainly driven by the availability of precise GPS ephemerides. In order to have high-quality GPS ephemerides available at real-time, GSOC has developed the real-time clock estimation system RETICLE. The system receives NTRIP-data streams with GNSS observations from the global tracking network of IGS in real-time. Using the known station position, RETICLE estimates precise GPS satellite clock offsets and drifts based on the most recent available IGU predicted orbits. The clock offset estimates have an accuracy of better than 0.3 ns and are

System for near real-time crustal deformation monitoring

NASA Technical Reports Server (NTRS)

Macdoran, P. F. (Inventor)

1979-01-01

A system is described for use in detecting earth crustal deformation using an RF interferometer technique for such purposes as earthquake predictive research and eventual operational predictions. A lunar based RF transmission or transmissions from earth orbiting satellites are received at two locations on Earth, and a precise time dependent phase measurement is made of the RF signal as received at the two locations to determine two or three spatial parameters of the antenna relative positions. The received data are precisely time tagged and land-line routed to a central station for real-time phase comparison and analysis. By monitoring the antenna relative positions over an extended period of months or years, crustal deformation of the Earth can be detected.

Capability of a Mobile Monitoring System to Provide Real-Time Data Broadcasting and Near Real-Time Source Attribution

NASA Astrophysics Data System (ADS)

Erickson, M.; Olaguer, J.; Wijesinghe, A.; Colvin, J.; Neish, B.; Williams, J.

2014-12-01

It is becoming increasingly important to understand the emissions and health effects of industrial facilities. Many areas have no or limited sustained monitoring capabilities, making it difficult to quantify the major pollution sources affecting human health, especially in fence line communities. Developments in real-time monitoring and micro-scale modeling offer unique ways to tackle these complex issues. This presentation will demonstrate the capability of coupling real-time observations with micro-scale modeling to provide real-time information and near real-time source attribution. The Houston Advanced Research Center constructed the Mobile Acquisition of Real-time Concentrations (MARC) laboratory. MARC consists of a Ford E-350 passenger van outfitted with a Proton Transfer Reaction Mass Spectrometer (PTR-MS) and meteorological equipment. This allows for the fast measurement of various VOCs important to air quality. The data recorded from the van is uploaded to an off-site database and the information is broadcast to a website in real-time. This provides for off-site monitoring of MARC's observations, which allows off-site personnel to provide immediate input to the MARC operators on how to best achieve project objectives. The information stored in the database can also be used to provide near real-time source attribution. An inverse model has been used to ascertain the amount, location, and timing of emissions based on MARC measurements in the vicinity of industrial sites. The inverse model is based on a 3D micro-scale Eulerian forward and adjoint air quality model known as the HARC model. The HARC model uses output from the Quick Urban and Industrial Complex (QUIC) wind model and requires a 3D digital model of the monitored facility based on lidar or industrial permit data. MARC is one of the instrument platforms deployed during the 2014 Benzene and other Toxics Exposure Study (BEE-TEX) in Houston, TX. The main goal of the study is to quantify and explain the

Real-time, autonomous precise satellite orbit determination using the global positioning system

NASA Astrophysics Data System (ADS)

Goldstein, David Ben

2000-10-01

The desire for autonomously generated, rapidly available, and highly accurate satellite ephemeris is growing with the proliferation of constellations of satellites and the cost and overhead of ground tracking resources. Autonomous Orbit Determination (OD) may be done on the ground in a post-processing mode or in real-time on board a satellite and may be accomplished days, hours or immediately after observations are processed. The Global Positioning System (GPS) is now widely used as an alternative to ground tracking resources to supply observation data for satellite positioning and navigation. GPS is accurate, inexpensive, provides continuous coverage, and is an excellent choice for autonomous systems. In an effort to estimate precise satellite ephemeris in real-time on board a satellite, the Goddard Space Flight Center (GSFC) created the GPS Enhanced OD Experiment (GEODE) flight navigation software. This dissertation offers alternative methods and improvements to GEODE to increase on board autonomy and real-time total position accuracy and precision without increasing computational burden. First, GEODE is modified to include a Gravity Acceleration Approximation Function (GAAF) to replace the traditional spherical harmonic representation of the gravity field. Next, an ionospheric correction method called Differenced Range Versus Integrated Doppler (DRVID) is applied to correct for ionospheric errors in the GPS measurements used in GEODE. Then, Dynamic Model Compensation (DMC) is added to estimate unmodeled and/or mismodeled forces in the dynamic model and to provide an alternative process noise variance-covariance formulation. Finally, a Genetic Algorithm (GA) is implemented in the form of Genetic Model Compensation (GMC) to optimize DMC forcing noise parameters. Application of GAAF, DRVID and DMC improved GEODE's position estimates by 28.3% when applied to GPS/MET data collected in the presence of Selective Availability (SA), 17.5% when SA is removed from the GPS

An Optimized Method to Detect BDS Satellites' Orbit Maneuvering and Anomalies in Real-Time.

PubMed

Huang, Guanwen; Qin, Zhiwei; Zhang, Qin; Wang, Le; Yan, Xingyuan; Wang, Xiaolei

2018-02-28

The orbital maneuvers of Global Navigation Satellite System (GNSS) Constellations will decrease the performance and accuracy of positioning, navigation, and timing (PNT). Because satellites in the Chinese BeiDou Navigation Satellite System (BDS) are in Geostationary Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO), maneuvers occur more frequently. Also, the precise start moment of the BDS satellites' orbit maneuvering cannot be obtained by common users. This paper presented an improved real-time detecting method for BDS satellites' orbit maneuvering and anomalies with higher timeliness and higher accuracy. The main contributions to this improvement are as follows: (1) instead of the previous two-steps method, a new one-step method with higher accuracy is proposed to determine the start moment and the pseudo random noise code (PRN) of the satellite orbit maneuvering in that time; (2) BDS Medium Earth Orbit (MEO) orbital maneuvers are firstly detected according to the proposed selection strategy for the stations; and (3) the classified non-maneuvering anomalies are detected by a new median robust method using the weak anomaly detection factor and the strong anomaly detection factor. The data from the Multi-GNSS Experiment (MGEX) in 2017 was used for experimental analysis. The experimental results and analysis showed that the start moment of orbital maneuvers and the period of non-maneuver anomalies can be determined more accurately in real-time. When orbital maneuvers and anomalies occur, the proposed method improved the data utilization for 91 and 95 min in 2017.

A near-real-time full-parallax holographic display for remote operations

NASA Technical Reports Server (NTRS)

Iavecchia, Helene P.; Huff, Lloyd; Marzwell, Neville I.

1991-01-01

A near real-time, full parallax holographic display system was developed that has the potential to provide a 3-D display for remote handling operations in hazardous environments. The major components of the system consist of a stack of three spatial light modulators which serves as the object source of the hologram; a near real-time holographic recording material (such as thermoplastic and photopolymer); and an optical system for relaying SLM images to the holographic recording material and to the observer for viewing.

Near real-time digital holographic microscope based on GPU parallel computing

NASA Astrophysics Data System (ADS)

Zhu, Gang; Zhao, Zhixiong; Wang, Huarui; Yang, Yan

2018-01-01

A transmission near real-time digital holographic microscope with in-line and off-axis light path is presented, in which the parallel computing technology based on compute unified device architecture (CUDA) and digital holographic microscopy are combined. Compared to other holographic microscopes, which have to implement reconstruction in multiple focal planes and are time-consuming the reconstruction speed of the near real-time digital holographic microscope can be greatly improved with the parallel computing technology based on CUDA, so it is especially suitable for measurements of particle field in micrometer and nanometer scale. Simulations and experiments show that the proposed transmission digital holographic microscope can accurately measure and display the velocity of particle field in micrometer scale, and the average velocity error is lower than 10%.With the graphic processing units(GPU), the computing time of the 100 reconstruction planes(512×512 grids) is lower than 120ms, while it is 4.9s using traditional reconstruction method by CPU. The reconstruction speed has been raised by 40 times. In other words, it can handle holograms at 8.3 frames per second and the near real-time measurement and display of particle velocity field are realized. The real-time three-dimensional reconstruction of particle velocity field is expected to achieve by further optimization of software and hardware. Keywords: digital holographic microscope,

Satellite on-board real-time SAR processor prototype

NASA Astrophysics Data System (ADS)

Bergeron, Alain; Doucet, Michel; Harnisch, Bernd; Suess, Martin; Marchese, Linda; Bourqui, Pascal; Desnoyers, Nicholas; Legros, Mathieu; Guillot, Ludovic; Mercier, Luc; Châteauneuf, François

2017-11-01

A Compact Real-Time Optronic SAR Processor has been successfully developed and tested up to a Technology Readiness Level of 4 (TRL4), the breadboard validation in a laboratory environment. SAR, or Synthetic Aperture Radar, is an active system allowing day and night imaging independent of the cloud coverage of the planet. The SAR raw data is a set of complex data for range and azimuth, which cannot be compressed. Specifically, for planetary missions and unmanned aerial vehicle (UAV) systems with limited communication data rates this is a clear disadvantage. SAR images are typically processed electronically applying dedicated Fourier transformations. This, however, can also be performed optically in real-time. Originally the first SAR images were optically processed. The optical Fourier processor architecture provides inherent parallel computing capabilities allowing real-time SAR data processing and thus the ability for compression and strongly reduced communication bandwidth requirements for the satellite. SAR signal return data are in general complex data. Both amplitude and phase must be combined optically in the SAR processor for each range and azimuth pixel. Amplitude and phase are generated by dedicated spatial light modulators and superimposed by an optical relay set-up. The spatial light modulators display the full complex raw data information over a two-dimensional format, one for the azimuth and one for the range. Since the entire signal history is displayed at once, the processor operates in parallel yielding real-time performances, i.e. without resulting bottleneck. Processing of both azimuth and range information is performed in a single pass. This paper focuses on the onboard capabilities of the compact optical SAR processor prototype that allows in-orbit processing of SAR images. Examples of processed ENVISAT ASAR images are presented. Various SAR processor parameters such as processing capabilities, image quality (point target analysis), weight and

Near real-time qualitative monitoring of lake water chlorophyll globally using GoogleEarth Engine

NASA Astrophysics Data System (ADS)

Zlinszky, András; Supan, Peter; Koma, Zsófia

2017-04-01

Monitoring ocean chlorophyll and suspended sediment has been made possible using optical satellite imaging, and has contributed immensely to our understanding of the Earth and its climate. However, lake water quality monitoring has limitations due to the optical complexity of shallow, sediment- and organic matter-laden waters. Meanwhile, timely and detailed information on basic lake water quality parameters would be essential for sustainable management of inland waters. Satellite-based remote sensing can deliver area-covering, high resolution maps of basic lake water quality parameters, but scientific application of these datasets for lake monitoring has been hindered by limitations to calibration and accuracy evaluation, and therefore access to such data has been the privilege of scientific users. Nevertheless, since for many inland waters satellite imaging is the only source of monitoring data, we believe it is urgent to make map products of chlorophyll and suspended sediment concentrations available to a wide range of users. Even if absolute accuracy can not be validated, patterns, processes and qualitative information delivered by such datasets in near-real time can act as an early warning system, raise awareness to water quality processes and serve education, in addition to complementing local monitoring activities. By making these datasets openly available on the internet through an easy to use framework, dialogue between stakeholders, management and governance authorities can be facilitated. We use GoogleEarthEngine to access and process archive and current satellite data. GoogleEarth Engine is a development and visualization framework that provides access to satellite datasets and processing capacity for analysis at the Petabyte scale. Based on earlier investigations, we chose the fluorescence line height index to represent water chlorophyll concentration. This index relies on the chlorophyll fluorescence peak at 680 nm, and has been tested for open ocean

Graphic Server: A real time system for displaying and monitoring telemetry data of several satellites

NASA Technical Reports Server (NTRS)

Douard, Stephane

1994-01-01

Known as a Graphic Server, the system presented was designed for the control ground segment of the Telecom 2 satellites. It is a tool used to dynamically display telemetry data within graphic pages, also known as views. The views are created off-line through various utilities and then, on the operator's request, displayed and animated in real time as data is received. The system was designed as an independent component, and is installed in different Telecom 2 operational control centers. It enables operators to monitor changes in the platform and satellite payloads in real time. It has been in operation since December 1991.

Near-Real Time Monitoring of TEC Over Japan at NICT (RWC Tokyo OF ISES)

NASA Astrophysics Data System (ADS)

Miyake, W.; Jin, H.

2010-05-01

The world wide use of global navigation satellite systems such as GPS offers unique opportunities for a permanent monitoring of the total electron content (TEC) of the ionosphere. We have developed a system of the rapid derivation of TEC from GEONET (a dense GPS receiver network in Japan). In addition to a previous plot of TEC temporal variation over Japan, we have recently developed a near-real-time two-dimensional TEC map and have used it for the daily operation of Space Weather Forecast Center at NICT (Regional Warning Center Tokyo of International Space Environment Service). The TEC map can be used to continuously monitor the ionospheric disturbances over Japan, including spatial and temporal development of ionospheric storms, large-amplitude traveling ionospheric disturbances, and plasma bubbles intruding over Japan, with high time resolution. The development of the real-time monitoring system of TEC enables us to monitor large ionospheric disturbances, ranging from global- to small-scale disturbances, expected in the next solar maximum. The plot and maps are open to the public and are available on http://wdc.nict.go.jp/IONO/index_E.html.

Assessment of a demonstration project to supply near real-time sea ice information to end users

NASA Astrophysics Data System (ADS)

Blackford, C.; Howes, Sally; Whitelaw, Alan S.; Laxon, S.; Mantripp, D.

1994-12-01

Sea ice maps are required by a diverse range of users for scientific research and operational activities. Satellite remote sensing provides opportunities for monitoring and producing sea ice maps at a range of scales, in near real time. During March 1994 ESYS Limited and the University College London Mullard Space Science Laboratory (MSSL) operated a sea ice demonstration project to supply near real time sea ice maps in the southern ocean. The sea ice information was derived from a number of data sources: DMSP SSM/I data; ERS-1 SAR and Radar Altimeter fast delivery data; NOAA AVHRR data; and PoSAT-1 imagery. The maps were supplied to three users, two involved in yacht races in the southern ocean and a ship on an oceanographic research cruise in the waters of the Princess Elizabeth Trough region of Antarctica. The demonstration was successful, supplying the users with sea ice information which they had previously not received and combining data from various sources to produce sea ice maps. The demonstration also developed operational skills within ESYS and enabled the transfer of knowledge from MSSL to ESYS.

A near real time regional JPSS and GOES-R data assimilation system for high impact weather research and applications

NASA Astrophysics Data System (ADS)

Li, J.; Wang, P.; Han, H.; Schmit, T. J.

2014-12-01

JPSS and GOES-R observations play important role in numerical weather prediction (NWP). However, how to best represent the information from satellite observations and how to get value added information from these satellite data into regional NWP models, including both radiance and derived products, still need investigations. In order to enhance the applications of JPSS and GOES-R data in regional NWP for high impact weather forecasts, scientists from Cooperative Institute of Meteorological Satellite Studies (CIMSS) at University of Wisconsin-Madison have recently developed a near realtime regional Satellite Data Assimilation system for Tropical storm forecasts (SDAT) (http://cimss.ssec.wisc.edu/sdat). The system consists of the community Gridpoint Statistical Interpolation (GSI) assimilation system and the advanced Weather Research Forecast (WRF) model. In addition to assimilate GOES, AMSUA/AMSUB, HIRS, MHS, ATMS (Suomi-NPP), AIRS and IASI radiances, the SDAT is also able to assimilate satellite-derived products such as hyperspectral IR retrieved temperature and moisture profiles, total precipitable water (TPW), GOES Sounder (and future GOES-R) layer precipitable water (LPW) and GOES Imager atmospheric motion vector (AMV) products into the system. Real time forecasted GOES infrared (IR) images simulated from SDAT output have also been part of the SDAT system for applications and forecast evaluations. To set up the system parameters, a series of experiments have been carried out to test the impacts of different initialization schemes, including different background error matrix, different NCEP global model date sets, and different WRF model horizontal resolutions. Using SDAT as a research testbed, researches have been conducted for different satellite data impacts study, as well as different techniques for handling clouds in radiance assimilation. Since the fall of 2013, the SDAT system has been running in near real time. The results from historical cases and 2014

An improved grey model for the prediction of real-time GPS satellite clock bias

NASA Astrophysics Data System (ADS)

Zheng, Z. Y.; Chen, Y. Q.; Lu, X. S.

2008-07-01

In real-time GPS precise point positioning (PPP), real-time and reliable satellite clock bias (SCB) prediction is a key to implement real-time GPS PPP. It is difficult to hold the nuisance and inenarrable performance of space-borne GPS satellite atomic clock because of its high-frequency, sensitivity and impressionable, it accords with the property of grey model (GM) theory, i. e. we can look on the variable process of SCB as grey system. Firstly, based on limits of quadratic polynomial (QP) and traditional GM to predict SCB, a modified GM (1,1) is put forward to predict GPS SCB in this paper; and then, taking GPS SCB data for example, we analyzed clock bias prediction with different sample interval, the relationship between GM exponent and prediction accuracy, precision comparison of GM to QP, and concluded the general rule of different type SCB and GM exponent; finally, to test the reliability and validation of the modified GM what we put forward, taking IGS clock bias ephemeris product as reference, we analyzed the prediction precision with the modified GM, It is showed that the modified GM is reliable and validation to predict GPS SCB and can offer high precise SCB prediction for real-time GPS PPP.

Towards a Three-Dimensional Near-Real Time Cloud Product for Aviation Safety and Weather Diagnoses

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Nguyen, Louis; Palikonda, Rabindra; Spangeberg, Douglas; Nordeen, Michele L.; Yi, Yu-Hong; Ayers, J. Kirk

2004-01-01

Satellite data have long been used for determining the extent of cloud cover and for estimating the properties at the cloud tops. The derived properties can also be used to estimate aircraft icing potential to improve the safety of air traffic in the region. Currently, cloud properties and icing potential are derived in near-real time over the United States of America (USA) from the Geostationary Operational Environmental Satellite GOES) imagers at 75 W and 135 W. Traditionally, the results have been given in two dimensions because of the lack of knowledge about the vertical extent of clouds and the occurrence of overlapping clouds. Aircraft fly in a three-dimensional space and require vertical as well as horizontal information about clouds, their intensity, and their potential for icing. To improve the vertical component of the derived cloud and icing parameters, this paper explores various methods and datasets for filling in the three-dimensional space over the USA with cloud water.

Remote-Sensing and Automated Water Resources Tracking: Near Real-Time Decision Support for Water Managers Facing Drought and Flood

NASA Astrophysics Data System (ADS)

Reiter, M. E.; Elliott, N.; Veloz, S.; Love, F.; Moody, D.; Hickey, C.; Fitzgibbon, M.; Reynolds, M.; Esralew, R.

2016-12-01

Innovative approaches for tracking the Earth's natural resources, especially water which is essential for all living things, are essential during a time of rapid environmental change. The Central Valley is a nexus for water resources in California, draining the Sacramento and San Joaquin River watersheds. The distribution of water throughout California and the Central Valley, while dynamic, is highly managed through an extensive regional network of canals, levees, and pumps. Water allocation and delivery is determined through a complex set of rules based on water contracts, historic priority, and other California water policies. Furthermore, urban centers, agriculture, and the environment throughout the state are already competing for water, particularly during drought. Competition for water is likely to intensify as California is projected to experience continued increases in demand due to population growth and more arid growing conditions, while also having reduced or modified water supply due to climate change. As a result, it is difficult to understand or predict how water will be used to fulfill wildlife and wetland conservation needs. A better understanding of the spatial distribution of water in near real-time can facilitate adaptation of water resource management to changing conditions on the landscape, both over the near- and long-term. The Landsat satellite mission delivers imagery every 16-days from nearly every place on the earth at a high spatial resolution. We have integrated remote sensing of satellite data, classification modeling, bioinformatics, optimization, and ecological analyses to develop an automated near real-time water resources tracking and decision-support system for the Central Valley of California. Our innovative system has applications for coordinated water management in the Central Valley to support people, places, and wildlife and is being used to understand the factors that drive variation in the distribution and abundance of water

Real Time Radiation Exposure And Health Risks

NASA Technical Reports Server (NTRS)

Hu, Shaowen; Barzilla, Janet E.; Semones, Edward J.

2015-01-01

Radiation from solar particle events (SPEs) poses a serious threat to future manned missions outside of low Earth orbit (LEO). Accurate characterization of the radiation environment in the inner heliosphere and timely monitoring the health risks to crew are essential steps to ensure the safety of future Mars missions. In this project we plan to develop an approach that can use the particle data from multiple satellites and perform near real-time simulations of radiation exposure and health risks for various exposure scenarios. Time-course profiles of dose rates will be calculated with HZETRN and PDOSE from the energy spectrum and compositions of the particles archived from satellites, and will be validated from recent radiation exposure measurements in space. Real-time estimation of radiation risks will be investigated using ARRBOD. This cross discipline integrated approach can improve risk mitigation by providing critical information for risk assessment and medical guidance to crew during SPEs.

Near real-time monitoring systems for adaptive management and improved forest governance

NASA Astrophysics Data System (ADS)

Musinsky, J.; Tabor, K.; Cano, A.

2012-12-01

The destruction and degradation of the world's forests from deforestation, illegal logging and fire has wide-ranging environmental and economic impacts, including biodiversity loss, the degradation of ecosystem services and the emission of greenhouse gases. In an effort to strengthen local capacity to respond to these threats, Conservation International has developed a suite of near real-time satellite monitoring systems generating daily alerts, maps and reports of forest fire, fire risk, deforestation and degradation that are used by national and sub-national government agencies, NGO's, scientists, communities, and the media to respond to and report on threats to forest resources. Currently, the systems support more than 1000 subscribers from 45 countries, focusing on Madagascar, Indonesia, Bolivia and Peru. This presentation will explore the types of innovative applications users have found for these data, challenges they've encountered in data acquisition and accuracy, and feedback they've given on the usefulness of these systems for REDD+ implementation, protected areas management and improved forest governance.;

Development of a Near Real-Time Hail Damage Swath Identification Algorithm for Vegetation

NASA Technical Reports Server (NTRS)

Bell, Jordan R.; Molthan, Andrew L.; Schultz, Kori A.; McGrath, Kevin M.; Burks, Jason E.

2015-01-01

Every year in the Midwest and Great Plains, widespread greenness forms in conjunction with the latter part of the spring-summer growing season. This prevalent greenness forms as a result of the high concentration of agricultural areas having their crops reach their maturity before the fall harvest. This time of year also coincides with an enhanced hail frequency for the Great Plains (Cintineo et al. 2012). These severe thunderstorms can bring damaging winds and large hail that can result in damage to the surface vegetation. The spatial extent of the damage can relatively small concentrated area or be a vast swath of damage that is visible from space. These large areas of damage have been well documented over the years. In the late 1960s aerial photography was used to evaluate crop damage caused by hail. As satellite remote sensing technology has evolved, the identification of these hail damage streaks has increased. Satellites have made it possible to view these streaks in additional spectrums. Parker et al. (2005) documented two streaks using the Moderate Resolution Imaging Spectroradiometer (MODIS) that occurred in South Dakota. He noted the potential impact that these streaks had on the surface temperature and associated surface fluxes that are impacted by a change in temperature. Gallo et al. (2012) examined at the correlation between radar signatures and ground observations from storms that produced a hail damage swath in Central Iowa also using MODIS. Finally, Molthan et al. (2013) identified hail damage streaks through MODIS, Landsat-7, and SPOT observations of different resolutions for the development of a potential near-real time applications. The manual analysis of hail damage streaks in satellite imagery is both tedious and time consuming, and may be inconsistent from event to event. This study focuses on development of an objective and automatic algorithm to detect these areas of damage in a more efficient and timely manner. This study utilizes the

Can Real-Time Data Also Be Climate Quality?

NASA Astrophysics Data System (ADS)

Brewer, M.; Wentz, F. J.

2015-12-01

GMI, AMSR-2 and WindSat herald a new era of highly accurate and timely microwave data products. Traditionally, there has been a large divide between real-time and re-analysis data products. What if these completely separate processing systems could be merged? Through advanced modeling and physically based algorithms, Remote Sensing Systems (RSS) has narrowed the gap between real-time and research-quality. Satellite microwave ocean products have proven useful for a wide array of timely Earth science applications. Through cloud SST capabilities have enormously benefited tropical cyclone forecasting and day to day fisheries management, to name a few. Oceanic wind vectors enhance operational safety of shipping and recreational boating. Atmospheric rivers are of import to many human endeavors, as are cloud cover and knowledge of precipitation events. Some activities benefit from both climate and real-time operational data used in conjunction. RSS has been consistently improving microwave Earth Science Data Records (ESDRs) for several decades, while making near real-time data publicly available for semi-operational use. These data streams have often been produced in 2 stages: near real-time, followed by research quality final files. Over the years, we have seen this time delay shrink from months or weeks to mere hours. As well, we have seen the quality of near real-time data improve to the point where the distinction starts to blur. We continue to work towards better and faster RFI filtering, adaptive algorithms and improved real-time validation statistics for earlier detection of problems. Can it be possible to produce climate quality data in real-time, and what would the advantages be? We will try to answer these questions…

Small real time detection satellites for MDA using hyperspectral imaging

NASA Astrophysics Data System (ADS)

Nakaya, Daiki; Yanagida, Hiroki; Shin, Satori; Ito, Tomonori; Takeuchi, Yusuke

2017-10-01

Hyperspectral Images are now used in the field of agriculture, cosmetics, and space exploring. Behind this fact, there is a result of efforts to contrive miniaturization and decrease in costs. This paper describes low-cost and small Hyperspectral Camera (HSC) under development and a method of utilizing it. Real Time Detection System for MDA is that government agencies put those cameras in small satellites and use them for MDA (Maritime Domain Awareness). We assume early detection of unidentified floating objects to find out disguised fishing ships and submarines.

Research of real-time communication software

NASA Astrophysics Data System (ADS)

Li, Maotang; Guo, Jingbo; Liu, Yuzhong; Li, Jiahong

2003-11-01

Real-time communication has been playing an increasingly important role in our work, life and ocean monitor. With the rapid progress of computer and communication technique as well as the miniaturization of communication system, it is needed to develop the adaptable and reliable real-time communication software in the ocean monitor system. This paper involves the real-time communication software research based on the point-to-point satellite intercommunication system. The object-oriented design method is adopted, which can transmit and receive video data and audio data as well as engineering data by satellite channel. In the real-time communication software, some software modules are developed, which can realize the point-to-point satellite intercommunication in the ocean monitor system. There are three advantages for the real-time communication software. One is that the real-time communication software increases the reliability of the point-to-point satellite intercommunication system working. Second is that some optional parameters are intercalated, which greatly increases the flexibility of the system working. Third is that some hardware is substituted by the real-time communication software, which not only decrease the expense of the system and promotes the miniaturization of communication system, but also aggrandizes the agility of the system.

Strategies for Near Real Time Estimates of Precipitable Water Vapor from GPS Ground Receivers

NASA Technical Reports Server (NTRS)

Y., Bar-Sever; Runge, T.; Kroger, P.

1995-01-01

GPS-based estimates of precipitable water vapor (PWV) may be useful in numerical weather models to improve short-term weather predictions. To be effective in numerical weather prediction models, GPS PWV estimates must be produced with sufficient accuracy in near real time. Several estimation strategies for the near real time processing of GPS data are investigated.

Versatile Software Package For Near Real-Time Analysis of Experimental Data

NASA Technical Reports Server (NTRS)

Wieseman, Carol D.; Hoadley, Sherwood T.

1998-01-01

This paper provides an overview of a versatile software package developed for time- and frequency-domain analyses of experimental wind-tunnel data. This package, originally developed for analyzing data in the NASA Langley Transonic Dynamics Tunnel (TDT), is applicable for analyzing any time-domain data. A Matlab-based software package, TDT-analyzer, provides a compendium of commonly-required dynamic analysis functions in a user-friendly interactive and batch processing environment. TDT-analyzer has been used extensively to provide on-line near real-time and post-test examination and reduction of measured data acquired during wind tunnel tests of aeroelastically-scaled models of aircraft and rotorcraft as well as a flight test of the NASA High Alpha Research Vehicle (HARV) F-18. The package provides near real-time results in an informative and timely manner far exceeding prior methods of data reduction at the TDT.

A Multimodel Global Drought Information System (GDIS) for Near Real-Time Monitoring of Surface Water Conditions (Invited)

NASA Astrophysics Data System (ADS)

Nijssen, B.

2013-12-01

While the absolute magnitude of economic losses associated with weather and climate disasters such as droughts is greatest in the developed world, the relative impact is much larger in the developing world, where agriculture typically constitutes a much larger percentage of the labor force and food insecurity is a major concern. Nonetheless, our ability to monitor and predict the development and occurrence of droughts at a global scale in near real-time is limited and long-term records of soil moisture are essentially non-existent globally The problem is particularly critical given that many of the most damaging droughts occur in parts of the world that are most deficient in terms of in situ precipitation observations. In recent years, a number of near real-time drought monitoring systems have been developed with regional or global extent. While direct observations of key variables such as moisture storage are missing, the evolution of land surface models that are globally applicable provides a means of reconstructing them. The implementation of a multi-model drought monitoring system is described, which provides near real-time estimates of surface moisture storage for the global land areas between 50S and 50N with a time lag of about one day. Near real-time forcings are derived from satellite-based precipitation estimates and modeled air temperatures. The system is distinguished from other operational systems in that it uses multiple land surface models to simulate surface moisture storage, which are then combined to derive a multi-model estimate of drought. Previous work has shown that while land surface models agree in broad context, particularly in terms of soil moisture percentiles, important differences remain, which motivates a multi-model ensemble approach. The system is an extension of similar systems developed by at the University of Washington for the Pacific Northwest and for the United States, but global application of the protocols used in the U

Development of a Near-Real Time Hail Damage Swath Identification Algorithm for Vegetation

NASA Technical Reports Server (NTRS)

Bell, Jordan R.; Molthan, Andrew L.; Schultz, Lori A.; McGrath, Kevin M.; Burks, Jason E.

2015-01-01

The Midwest is home to one of the world's largest agricultural growing regions. Between the time period of late May through early September, and with irrigation and seasonal rainfall these crops are able to reach their full maturity. Using moderate to high resolution remote sensors, the monitoring of the vegetation can be achieved using the red and near-infrared wavelengths. These wavelengths allow for the calculation of vegetation indices, such as Normalized Difference Vegetation Index (NDVI). The vegetation growth and greenness, in this region, grows and evolves uniformly as the growing season progresses. However one of the biggest threats to Midwest vegetation during the time period is thunderstorms that bring large hail and damaging winds. Hail and wind damage to crops can be very expensive to crop growers and, damage can be spread over long swaths associated with the tracks of the damaging storms. Damage to the vegetation can be apparent in remotely sensed imagery and is visible from space after storms slightly damage the crops, allowing for changes to occur slowly over time as the crops wilt or more readily apparent if the storms strip material from the crops or destroy them completely. Previous work on identifying these hail damage swaths used manual interpretation by the way of moderate and higher resolution satellite imagery. With the development of an automated and near-real time hail swath damage identification algorithm, detection can be improved, and more damage indicators be created in a faster and more efficient way. The automated detection of hail damage swaths will examine short-term, large changes in the vegetation by differencing near-real time eight day NDVI composites and comparing them to post storm imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua and Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi NPP. In addition land surface temperatures from these instruments will be examined as

First results of the EGSIEM Near Real-Time Service

NASA Astrophysics Data System (ADS)

Kvas, Andreas; Gruber, Christian; Gouweleeuw, Ben; Chen, Qiang; Poropat, Lea; Flechtner, Frank; Mayer-Gürr, Torsten; Güntner, Andreas

2017-04-01

To enable the use of GRACE and GRACE-FO earth observation data for rapid monitoring applications, the Horizon2020 funded EGSIEM (European Gravity Service for Improved Emergency Management) project has established a demonstrator for a near real-time (NRT) gravity field service. The service aims to increase the temporal resolution of mass transport products from one month to one day and to reduce the latency from currently two months to five days. This allows the monitoring of hydrological extreme events as they occur, in contrast to a 'confirmation after occurrence' as is the situation today. The service will be jointly run by GFZ (German Research Centre for Geosciences) and Graz University of Technology, with each analysis center providing an independent solution. On-line validation will be performed by the University of Luxembourg using GNSS loading. A six-month long operational test run of the service starting in April 2017 is planned, in case GRACE Quick-Look data (provided by JPL) is still available. Within this time period, daily gravity field solutions serve as input to the EGSIEM Hydrological Service, which derives flood and drought indicators to be used within DLR's Center for Satellite Based Crisis Information and the Global Flood Awareness System (GloFAS). This contribution highlights the current status of the NRT service and the results of the preparation phase. The performance of the NRT mass transport products will be shown by comparison with independent GNSS loading and ocean bottom pressure data as well as as catchment aggregated values for hydrological extreme events.

Near real time/low latency data collection for climate warming manipulations and an elevated CO2 SPRUCE experiment

NASA Astrophysics Data System (ADS)

Krassovski, M.; Hanson, P. J.; Riggs, J. S.; Nettles, W. R., IV

2017-12-01

Climate change studies are one of the most important aspects of modern science and related experiments are getting bigger and more complex. One such experiment is the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE, http://mnspruce.ornl.gov) conducted in in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO2 atmosphere. This manipulation experiment generates a lot of observational data and requires a reliable onsite data collection system, dependable methods to transfer data to a robust scientific facility, and real-time monitoring capabilities. This presentation shares our experience of establishing near real time/low latency data collection and monitoring system using satellite communication.

IOOS: Aiding Aquaculture Industries and Their Harvest with Near Real-Time Data

NASA Astrophysics Data System (ADS)

Kerkering, H.; Shandy Buckley; Jan Newton; Julie Thomas

2011-12-01

networks are being designed to address scientific understanding and uncertainty as well as the management needs of various stakeholder groups. Better communication and delivery of near real time data will assist aquaculture growers to predict when larvae will recruit in the natural system, when and if to relocate crops, and when to pump water in a tanks system. Though an integrated west coast observational network satellite sea surface temperature, HAB tracking systems, ocean acidification buoys, and biological monitoring programs can be pulled together into a cohesive program. A network of scientists and industry stakeholders providing and utilizing a near real time data network saves money and increases efficiency. It is not possible to prevent variability in temperature, nutrients, pH and algal blooms, but increasing understanding will lead to more accurate predictions, and ultimately, better human adaptation to the harmful economic impacts of HABs and ocean acidification.

Applications of Near Real-Time Image and Fire Products from MODIS

NASA Astrophysics Data System (ADS)

Schmaltz, J. E.; Ilavajhala, S.; Teague, M.; Ye, G.; Masuoka, E.; Davies, D.; Murphy, K. J.; Michael, K.

2010-12-01

NASA’s MODIS Rapid Response Project (http://rapidfire.sci.gsfc.nasa.gov/) has been providing MODIS fire detections and imagery in near real-time since 2001. The Rapid Response system is part of the Land and Atmospheres Near-real time Capability for EOS (LANCE-MODIS) system. Current capabilities include providing MODIS imagery in true color and false color band combinations, a vegetation index, and temperature - in both uncorrected swath format and geographically corrected subset regions. The geographically-corrected subsets images cover the world's land areas and adjoining waters, as well as the entire Arctic and Antarctic. These data are available within a few hours of data acquisition. The images are accessed by large number of user communities to obtain a rapid, 250 meter-resolution overview of ground conditions for fire management, crop and famine monitoring and forecasting, disaster response (fires, oil spills, floods, storms), dust and aerosol monitoring, aviation (tracking volcanic ash), monitoring sea ice conditions, environmental monitoring, and more. In addition, the scientific community uses imagery to locate phenomena of interest prior to ordering and processing data and to support the day-to-day planning of field campaigns. The MODIS Rapid Response project has also been providing a near real-time data feed on fire locations and MODIS imagery subsets to the Fire Information for Resource Management System (FIRMS) project (http://maps.geog.umd.edu/firms). FIRMS provides timely availability of fire location information, which is essential in preventing and fighting large forest/wild fires. Products are available through a WebGIS for visualizing MODIS hotspots and MCD45 Burned Area images, an email alerting tool to deliver fire data on daily/weekly/near real-time basis, active data downloads in formats such as shape, KML, CSV, WMS, etc., along with MODIS imagery subsets. FIRMS’ user base covers more than 100 countries and territories. A recent user

Real-Time Estimation of Volcanic ASH/SO2 Cloud Height from Combined Uv/ir Satellite Observations and Numerical Modeling

NASA Astrophysics Data System (ADS)

Vicente, Gilberto A.

An efficient iterative method has been developed to estimate the vertical profile of SO2 and ash clouds from volcanic eruptions by comparing near real-time satellite observations with numerical modeling outputs. The approach uses UV based SO2 concentration and IR based ash cloud images, the volcanic ash transport model PUFF and wind speed, height and directional information to find the best match between the simulated and the observed displays. The method is computationally fast and is being implemented for operational use at the NOAA Volcanic Ash Advisory Centers (VAACs) in Washington, DC, USA, to support the Federal Aviation Administration (FAA) effort to detect, track and measure volcanic ash cloud heights for air traffic safety and management. The presentation will show the methodology, results, statistical analysis and SO2 and Aerosol Index input products derived from the Ozone Monitoring Instrument (OMI) onboard the NASA EOS/Aura research satellite and from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument in the MetOp-A. The volcanic ash products are derived from AVHRR instruments in the NOAA POES-16, 17, 18, 19 as well as MetOp-A. The presentation will also show how a VAAC volcanic ash analyst interacts with the system providing initial condition inputs such as location and time of the volcanic eruption, followed by the automatic real-time tracking of all the satellite data available, subsequent activation of the iterative approach and the data/product delivery process in numerical and graphical format for operational applications.

Near Real Time Tools for ISS Plasma Science and Engineering Applications

NASA Astrophysics Data System (ADS)

Minow, J. I.; Willis, E. M.; Parker, L. N.; Shim, J.; Kuznetsova, M. M.; Pulkkinen, A. A.

2013-12-01

The International Space Station (ISS) program utilizes a plasma environment forecast for estimating electrical charging hazards for crews during extravehicular activity (EVA). The process uses ionospheric electron density and temperature measurements from the ISS Floating Potential Measurement Unit (FPMU) instrument suite with the assumption that the plasma conditions will remain constant for one to fourteen days with a low probability for a space weather event which would significantly change the environment before an EVA. FPMU data is typically not available during EVA's, therefore, the most recent FPMU data available for characterizing the state of the ionosphere during EVA is typically a day or two before the start of an EVA or after the EVA has been completed. In addition to EVA support, information on ionospheric plasma densities is often needed for support of ISS science payloads and anomaly investigations during periods when the FPMU is not operating. This presentation describes the application of space weather tools developed by MSFC using data from near real time satellite radio occultation and ground based ionosonde measurements of ionospheric electron density and a first principle ionosphere model providing electron density and temperature run in a real time mode by GSFC. These applications are used to characterize the space environment during EVA periods when FPMU data is not available, monitor for large charges in ionosphere density that could render the ionosphere forecast and plasma hazard assessment invalid, and validate the assumption of 'persistence of conditions' used in deriving the hazard forecast. In addition, the tools are used to provide space environment input to science payloads on ISS and anomaly investigations during periods the FPMU is not operating.

NASA Langley Atmospheric Science Data Centers Near Real-Time Data Products

NASA Astrophysics Data System (ADS)

Davenport, T.; Parker, L.; Rinsland, P. L.

2014-12-01

Over the past decade the Atmospheric Science Data Center (ASDC) at NASA Langley Research Center has archived and distributed a variety of satellite mission data sets. NASA's goal in Earth science is to observe, understand, and model the Earth system to discover how it is changing, to better predict change, and to understand the consequences for life on Earth. The ASDC has collaborated with Science Teams to accommodate emerging science users in the climate and modeling communities. The ASDC has expanded its original role to support operational usage by related Earth Science satellites, support land and ocean assimilations, support of field campaigns, outreach programs, and application projects for agriculture and energy industries to bridge the gap between Earth science research results and the adoption of data and prediction capabilities for reliable and sustained use in Decision Support Systems (DSS). For example; these products are being used by the community performing data assimilations to regulate aerosol mass in global transport models to improve model response and forecast accuracy, to assess the performance of components of a global coupled atmospheric-ocean climate model, improve atmospheric motion vector (winds) impact on numerical weather prediction models, and to provide internet-based access to parameters specifically tailored to assist in the design of solar and wind powered renewable energy systems. These more focused applications often require Near Real-Time (NRT) products. Generating NRT products pose their own unique set challenges for the ASDC and the Science Teams. Examples of ASDC NRT products and challenges will be discussed.

Visualization and Analysis for Near-Real-Time Decision Making in Distributed Workflows

DOE PAGES

Pugmire, David; Kress, James; Choi, Jong; ...

2016-08-04

Data driven science is becoming increasingly more common, complex, and is placing tremendous stresses on visualization and analysis frameworks. Data sources producing 10GB per second (and more) are becoming increasingly commonplace in both simulation, sensor and experimental sciences. These data sources, which are often distributed around the world, must be analyzed by teams of scientists that are also distributed. Enabling scientists to view, query and interact with such large volumes of data in near-real-time requires a rich fusion of visualization and analysis techniques, middleware and workflow systems. Here, this paper discusses initial research into visualization and analysis of distributed datamore » workflows that enables scientists to make near-real-time decisions of large volumes of time varying data.« less

Real-Time Eddy-Resolving Ocean Prediction in the Caribbean

NASA Astrophysics Data System (ADS)

Hurlburt, H. E.; Smedstad, O. M.; Shriver, J. F.; Townsend, T. L.; Murphy, S. J.

2001-12-01

A {1/16}o eddy-resolving, nearly global ocean prediction system has been developed by the Naval Research Laboratory (NRL), Stennis Space Center, MS. It has been run in real-time by the Naval Oceanographic Office (NAVO), Stennis Space Center, MS since 18 Oct 2000 with daily updates for the nowcast and 30-day forecasts performed every Wednesday. The model has ~8 km resolution in the Caribbean region and assimilates real-time altimeter sea surface height (SSH) data from ERS-2, GFO and TOPEX/POSEIDON plus multi-channel sea surface temperature (MCSST) from satellite IR. Real-time and archived results from the system can be seen at web site: http://www7320.nrlssc.navy.mil/global\

Near real-time stereo vision system

NASA Technical Reports Server (NTRS)

Anderson, Charles H. (Inventor); Matthies, Larry H. (Inventor)

1993-01-01

The apparatus for a near real-time stereo vision system for use with a robotic vehicle is described. The system is comprised of two cameras mounted on three-axis rotation platforms, image-processing boards, a CPU, and specialized stereo vision algorithms. Bandpass-filtered image pyramids are computed, stereo matching is performed by least-squares correlation, and confidence ranges are estimated by means of Bayes' theorem. In particular, Laplacian image pyramids are built and disparity maps are produced from the 60 x 64 level of the pyramids at rates of up to 2 seconds per image pair. The first autonomous cross-country robotic traverses (of up to 100 meters) have been achieved using the stereo vision system of the present invention with all computing done onboard the vehicle. The overall approach disclosed herein provides a unifying paradigm for practical domain-independent stereo ranging.

Flood and Landslide Applications of High Time Resolution Satellite Rain Products

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Hong, Yang; Huffman, George J.

2006-01-01

Experimental, potentially real-time systems to detect floods and landslides related to heavy rain events are described. A key basis for these applications is high time resolution satellite rainfall analyses. Rainfall is the primary cause for devastating floods across the world. However, in many countries, satellite-based precipitation estimation may be the best source of rainfall data due to insufficient ground networks and absence of data sharing along many trans-boundary river basins. Remotely sensed precipitation from the NASA's TRMM Multi-satellite Precipitation Analysis (TMPA) operational system (near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg) is used to monitor extreme precipitation events. Then these data are ingested into a macro-scale hydrological model which is parameterized using spatially distributed elevation, soil and land cover datasets available globally from satellite remote sensing. Preliminary flood results appear reasonable in terms of location and frequency of events, with implementation on a quasi-global basis underway. With the availability of satellite rainfall analyses at fine time resolution, it has also become possible to assess landslide risk on a near-global basis. Early results show that landslide occurrence is closely associated with the spatial patterns and temporal distribution of TRMM rainfall characteristics. Particularly, the number of landslides triggered by rainfall is related to rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms. For the purpose of prediction, an empirical TMPA-based rainfall intensity-duration threshold is developed and shown to have skill in determining potential areas of landslides. These experimental findings, in combination with landslide surface susceptibility information based on satellite-based land surface information, form a starting point towards a potential operational landslide monitoring/warning system

A Methadology for Near-Real-Time Access to Environmental Data through Federation

NASA Astrophysics Data System (ADS)

Orcutt, J. A.; Rajasekar, A.; Moore, R. W.; Vernon, F.

2015-12-01

The availability of near-real-time data can be critical for response to rapid changes including violent storms, tsunamis and earthquakes. While climate changes relatively slowly, compared to a tsunami, the increasing variance in weather over time and warming must also be considered in terms of civil impacts. A simple example is the decreasing resilience of coastal communities to severe weather as sea level increases. The integration of these data for modeling and response activities in near-real-time must be pursued to make data collection practical. We present an approach to data and metadata integration that has occurred over the past 10-20 years in Earth and Ocean sciences that provide a model for the future. The NSF Data Federation Consortium (DFC) is working to integrate data and metadata from a number of fields using iRODS (Integrated Rule-Oriented Data System). iRODS is open source software for building distributed data collections. In particular, the SCION (SCIence Observatory Network) funded by the NSF provides Python-based software for data and metadata access from a variety of near-real-time data sets relevant to climate studies including weather and hazards from other observational systems. As an example, we are working on the integration of data on shore and offshore in southern California using resources from the High Performance Wireless Research and Education Network (HPWREN) and the Southern California Coastal Ocean Observing System (SCCOOS). National and International integration of near-real-time earthquake data through the Incorporated Research Institutions for Seismology (IRIS) and the International Federation of Digital Seismic Networks (FDSN) provide a well-integrated data and metadata system for both research and civil uses. ObsPy, written in Python, has proved to be a highly successful methodology for accessing global data from thousands of stations with well-developed metadata. The persistence of the data and metadata, in turn, provides

Congestion relief by travel time minimization in near real time : Detroit area I-75 corridor study.

DOT National Transportation Integrated Search

2008-12-01

"This document summarizes the activities concerning the project: Congestion Relief by : Travel Time Minimization in Near Real Time -- Detroit Area I-75 Corridor Study since : the inception of the project (Nov. 22, 2006 through September 30, 2008). : ...

Real-Time Global Flood Estimation Using Satellite-Based Precipitation and a Coupled Land Surface and Routing Model

NASA Technical Reports Server (NTRS)

Wu, Huan; Adler, Robert F.; Tian, Yudong; Huffman, George J.; Li, Hongyi; Wang, JianJian

2014-01-01

A widely used land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing-based runoff-routing model to form the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model, which serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS uses real-time satellite-based precipitation to derive flood monitoring parameters for the latitude band 50 deg. N - 50 deg. S at relatively high spatial (approximately 12 km) and temporal (3 hourly) resolution. Examples of model results for recent flood events are computed using the real-time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS, the DRIVE model is run retrospectively for 15 years using both research-quality and real-time satellite precipitation products. Evaluation results are slightly better for the research-quality input and significantly better for longer duration events (3 day events versus 1 day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is approximately 0.9 and the false alarm ratio is approximately 0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1121 river gauges across the quasi-global domain. Validation using real-time precipitation across the tropics (30 deg. S - 30 deg. N) gives positive daily Nash-Sutcliffe Coefficients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. There were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.

Real-time global flood estimation using satellite-based precipitation and a coupled land surface and routing model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Huan; Adler, Robert F.; Tian, Yudong

2014-03-01

A widely used land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing-based runoff-routing model to form the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model, which serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS uses real-time satellite-based precipitation to derive flood monitoring parameters for the latitude band 50°N–50°S at relatively high spatial (~12 km) and temporal (3 hourly) resolution. Examples of model results for recent flood events are computed using the real-time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS,more » the DRIVE model is run retrospectively for 15 years using both research-quality and real-time satellite precipitation products. Evaluation results are slightly better for the research-quality input and significantly better for longer duration events (3 day events versus 1 day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is ~0.9 and the false alarm ratio is ~0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1121 river gauges across the quasi-global domain. Validation using real-time precipitation across the tropics (30°S–30°N) gives positive daily Nash-Sutcliffe Coefficients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. Finally, there were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.« less

Real-time satellite monitoring of Nornahraun lava flow NE Iceland

NASA Astrophysics Data System (ADS)

Jónsdóttir, Ingibjörg; Þórðarson, Þorvaldur; Höskuldsson, Ármann; Davis, Ashley; Schneider, David; Wright, Robert; Kestay, Laszlo; Hamilton, Christopher; Harris, Andrew; Coppola, Diego; Tumi Guðmundsson, Magnús; Durig, Tobias; Pedersen, Gro; Drouin, Vincent; Höskuldsson, Friðrik; Símonarson, Hreggviður; Örn Arnarson, Gunnar; Örn Einarsson, Magnús; Riishuus, Morten

2015-04-01

An effusive eruption started in Holuhraun, NE Iceland, on 31 August 2014, producing the Nornahraun lava flow field which had, by the beginning of 2015, covered over 83 km2. Throughout this event, various satellite images have been analyzed to monitor the development, active areas and map the lava extent in close collaboration with the field group, which involved regular exchange of direct observations and satellite based data for ground truthing and suggesting possible sites for lava sampling. From the beginning, satellite images in low geometric but high temporal resolution (NOAA AVHRR, MODIS) were used to monitor main regions of activity and position new vents to within 1km accuracy. As they became available, multispectral images in higher resolution (LANDSAT 8, LANDSAT 7, ASTER, EO-1 ALI) were used to map the lava channels, study lava structures and classify regions of varying activity. Hyper spectral sensors (EO-1 HYPERION), though with limited area coverage, have given a good indication of vent and lava temperature and effusion rates. All available radar imagery (SENTINEL-1, RADARSAT, COSMO SKYMED, TERRASAR X) have been used for studying lava extent, landscape and roughness. The Icelandic Coast Guard has, on a number of occasions, provided high resolution radar and thermal images from reconnaissance flights. These data sources compliment each other well and have improved analysis of events. Whilst classical TIR channels were utilized to map the temperature history of the lava, SWIR and NIR channels caught regions of highest temperature, allowing an estimate of the most active lava channels and even indicating potential changes in channel structure. Combining thermal images and radar images took this prediction a step further, improving interpretation of both image types and studying the difference between open and closed lava channels. Efforts are underway of comparing different methods of estimating magma discharge and improving the process for use in real

Investigations into near-real-time surveying for geophysical data collection using an autonomous ground vehicle

USGS Publications Warehouse

Phelps, Geoffrey A.; Ippolito, C.; Lee, R.; Spritzer, R.; Yeh, Y.

2014-01-01

The U.S. Geological Survey and the National Aeronautics and Space Administration are cooperatively investigating the utility of unmanned vehicles for near-real-time autonomous surveys of geophysical data collection. Initially focused on unmanned ground vehicle collection of magnetic data, this cooperative effort has brought unmanned surveying, precision guidance, near-real-time communication, on-the-fly data processing, and near-real-time data interpretation into the realm of ground geophysical surveying, all of which offer advantages over current methods of manned collection of ground magnetic data. An unmanned ground vehicle mission has demonstrated that these vehicles can successfully complete missions to collect geophysical data, and add advantages in data collection, processing, and interpretation. We view the current experiment as an initial phase in further unmanned vehicle data-collection missions, including aerial surveying.

A Scientific Workflow System for Satellite Data Processing with Real-Time Monitoring

NASA Astrophysics Data System (ADS)

Nguyen, Minh Duc

2018-02-01

This paper provides a case study on satellite data processing, storage, and distribution in the space weather domain by introducing the Satellite Data Downloading System (SDDS). The approach proposed in this paper was evaluated through real-world scenarios and addresses the challenges related to the specific field. Although SDDS is used for satellite data processing, it can potentially be adapted to a wide range of data processing scenarios in other fields of physics.

An ocean bottom seismic observatory with near real-time telemetry

NASA Astrophysics Data System (ADS)

Berger, J.; Laske, G.; Babcock, J.; Orcutt, J.

2016-02-01

We describe a new technology that can provide near real-time telemetry of sensor data from the ocean bottom without a moored buoy or a cable to shore. The breakthrough technology that makes this system possible is an autonomous surface vehicle called a Wave Glider developed by Liquid Robotics, Inc. of Sunnyvale, CA, which harvests wave and solar energy for motive and electrical power. We present results from several deployments of a prototype system that demonstrate the feasibility of this concept. We also demonstrated that a wave glider could tow a suitably designed ocean bottom package with acceptable loss of speed. With further development such a system could be deployed autonomously and provide real-time telemetry of data from seafloor sensors.

Off-the-shelf real-time monitoring of satellite constellations in a visual 3-D environment

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.; Hervias, Felipe; Cheng, Cecilia Han; Mactutis, Anthony; Angelino, Robert

1996-01-01

The multimission spacecraft analysis system (MSAS) data monitor is a generic software product for future real-time data monitoring and analysis. The system represents the status of a satellite constellation through the shape, color, motion and position of graphical objects floating in a three dimensional virtual reality environment. It may be used for the monitoring of large volumes of data, for viewing results in configurable displays, and for providing high level and detailed views of a constellation of monitored satellites. It is considered that the data monitor is an improvement on conventional graphic and text-based displays as it increases the amount of data that the operator can absorb in a given period, and can be installed and configured without the requirement for software development by the end user. The functionality of the system is described, including: the navigation abilities; the representation of alarms in the cybergrid; limit violation; real-time trend analysis, and alarm status indication.

Near Real Time Ship Detection Experiments

NASA Astrophysics Data System (ADS)

Brusch, S.; Lehner, S.; Schwarz, E.; Fritz, T.

2010-04-01

A new Near Real Time (NRT) ship detection processor SAINT (SAR AIS Integrated Toolbox) was developed in the framework of the ESA project MARISS. Data are received at DLRs ground segment DLR-BN (Neustrelitz, Germany). Results of the ship detection are available on ftp server within 30 min after the acquisition started. The detectability of ships on Synthetic Aperture Radar (SAR) ERS-2, ENVISAT ASAR and TerraSAR-X (TS-X) images is validated by coastal (live) AIS and space AIS. The monitoring areas chosen for surveillance are the North-, Baltic Sea, and Cape Town. The detectability in respect to environmental parameters like wind field, sea state, currents and changing coastlines due to tidal effects is investigated. In the South Atlantic a tracking experiment of the German research vessel Polarstern has been performed. Issues of piracy in particular in respect to ships hijacked at the Somali coast are discussed. Some examples using high resolution images from TerraSAR-X are given.

A first near real-time seismology-based landquake monitoring system.

PubMed

Chao, Wei-An; Wu, Yih-Min; Zhao, Li; Chen, Hongey; Chen, Yue-Gau; Chang, Jui-Ming; Lin, Che-Min

2017-03-02

Hazards from gravity-driven instabilities on hillslope (termed 'landquake' in this study) are an important problem facing us today. Rapid detection of landquake events is crucial for hazard mitigation and emergency response. Based on the real-time broadband data in Taiwan, we have developed a near real-time landquake monitoring system, which is a fully automatic process based on waveform inversion that yields source information (e.g., location and mechanism) and identifies the landquake source by examining waveform fitness for different types of source mechanisms. This system has been successfully tested offline using seismic records during the passage of the 2009 Typhoon Morakot in Taiwan and has been in online operation during the typhoon season in 2015. In practice, certain levels of station coverage (station gap < 180°), signal-to-noise ratio (SNR ≥ 5.0), and a threshold of event size (volume >10 6  m 3 and area > 0.20 km 2 ) are required to ensure good performance (fitness > 0.6 for successful source identification) of the system, which can be readily implemented in other places in the world with real-time seismic networks and high landquake activities.

A first near real-time seismology-based landquake monitoring system

PubMed Central

Chao, Wei-An; Wu, Yih-Min; Zhao, Li; Chen, Hongey; Chen, Yue-Gau; Chang, Jui-Ming; Lin, Che-Min

2017-01-01

Hazards from gravity-driven instabilities on hillslope (termed ‘landquake’ in this study) are an important problem facing us today. Rapid detection of landquake events is crucial for hazard mitigation and emergency response. Based on the real-time broadband data in Taiwan, we have developed a near real-time landquake monitoring system, which is a fully automatic process based on waveform inversion that yields source information (e.g., location and mechanism) and identifies the landquake source by examining waveform fitness for different types of source mechanisms. This system has been successfully tested offline using seismic records during the passage of the 2009 Typhoon Morakot in Taiwan and has been in online operation during the typhoon season in 2015. In practice, certain levels of station coverage (station gap < 180°), signal-to-noise ratio (SNR ≥ 5.0), and a threshold of event size (volume >106 m3 and area > 0.20 km2) are required to ensure good performance (fitness > 0.6 for successful source identification) of the system, which can be readily implemented in other places in the world with real-time seismic networks and high landquake activities. PMID:28252039

The improved broadband Real-Time Seismic Network in Romania

NASA Astrophysics Data System (ADS)

Neagoe, C.; Ionescu, C.

2009-04-01

Starting with 2002 the National Institute for Earth Physics (NIEP) has developed its real-time digital seismic network. This network consists of 96 seismic stations of which 48 broad band and short period stations and two seismic arrays are transmitted in real-time. The real time seismic stations are equipped with Quanterra Q330 and K2 digitizers, broadband seismometers (STS2, CMG40T, CMG 3ESP, CMG3T) and strong motions sensors Kinemetrics episensors (+/- 2g). SeedLink and AntelopeTM (installed on MARMOT) program packages are used for real-time (RT) data acquisition and exchange. The communication from digital seismic stations to the National Data Center in Bucharest is assured by 5 providers (GPRS, VPN, satellite communication, radio lease line and internet), which will assure the back-up communications lines. The processing centre runs BRTT's AntelopeTM 4.10 data acquisition and processing software on 2 workstations for real-time processing and post processing. The Antelope Real-Time System is also providing automatic event detection, arrival picking, event location and magnitude calculation. It provides graphical display and reporting within near-real-time after a local or regional event occurred. Also at the data center was implemented a system to collect macroseismic information using the internet on which macro seismic intensity maps are generated. In the near future at the data center will be install Seiscomp 3 data acquisition processing software on a workstation. The software will run in parallel with Antelope software as a back-up. The present network will be expanded in the near future. In the first half of 2009 NIEP will install 8 additional broad band stations in Romanian territory, which also will be transmitted to the data center in real time. The Romanian Seismic Network is permanently exchanging real -time waveform data with IRIS, ORFEUS and different European countries through internet. In Romania, magnitude and location of an earthquake are now

Innovative Near Real-Time Data Dissemination Tools Developed by the Space Weather Research Center

NASA Astrophysics Data System (ADS)

Maddox, Marlo M.; Mullinix, Richard; Mays, M. Leila; Kuznetsova, Maria; Zheng, Yihua; Pulkkinen, Antti; Rastaetter, Lutz

2013-03-01

Access to near real-time and real-time space weather data is essential to accurately specifying and forecasting the space environment. The Space Weather Research Center at NASA Goddard Space Flight Center's Space Weather Laboratory provides vital space weather forecasting services primarily to NASA robotic mission operators, as well as external space weather stakeholders including the Air Force Weather Agency. A key component in this activity is the iNtegrated Space Weather Analysis System which is a joint development project at NASA GSFC between the Space Weather Laboratory, Community Coordinated Modeling Center, Applied Engineering & Technology Directorate, and NASA HQ Office Of Chief Engineer. The iSWA system was developed to address technical challenges in acquiring and disseminating space weather environment information. A key design driver for the iSWA system was to generate and present vast amounts of space weather resources in an intuitive, user-configurable, and adaptable format - thus enabling users to respond to current and future space weather impacts as well as enabling post-impact analysis. Having access to near real-time and real-time data is essential to not only ensuring that relevant observational data is available for analysis - but also in ensuring that models can be driven with the requisite input parameters at proper and efficient temporal and spacial resolutions. The iSWA system currently manages over 300 unique near-real and real-time data feeds from various sources consisting of both observational and simulation data. A comprehensive suite of actionable space weather analysis tools and products are generated and provided utilizing a mixture of the ingested data - enabling new capabilities in quickly assessing past, present, and expected space weather effects. This paper will highlight current and future iSWA system capabilities including the utilization of data from the Solar Dynamics Observatory mission. http://iswa.gsfc.nasa.gov/

Integrating SAR with Optical and Thermal Remote Sensing for Operational Near Real-Time Volcano Monitoring

NASA Astrophysics Data System (ADS)

Meyer, F. J.; Webley, P.; Dehn, J.; Arko, S. A.; McAlpin, D. B.

2013-12-01

multiple observation geometries in change detection procedures. Additionally, it will be shown how SAR-based hazard information can be integrated with data from optical satellites, thermal sensors, webcams and models to create near-real time volcano hazard information. We will introduce a prototype monitoring system that integrates SAR-based hazard information into the near real-time volcano hazard monitoring system of the Alaska Volcano Observatory. This prototype system was applied to historic eruptions of the volcanoes Okmok and Augustine, both located in the North Pacific. We will show that for these historic eruptions, the addition of SAR data lead to a significant improvement in activity detection and eruption monitoring, and improved the accuracy and timeliness of eruption alerts.

[Mobile hospital -real time mobile telehealthcare system with ultrasound and CT van using high-speed satellite communication-].

PubMed

Takizawa, Masaomi; Miyashita, Toyohisa; Murase, Sumio; Kanda, Hirohito; Karaki, Yoshiaki; Yagi, Kazuo; Ohue, Toru

2003-01-01

A real-time telescreening system is developed to detect early diseases for rural area residents using two types of mobile vans with a portable satellite station. The system consists of a satellite communication system with 1.5Mbps of the JCSAT-1B satellite, a spiral CT van, an ultrasound imaging van with two video conference system, a DICOM server and a multicast communication unit. The video image and examination image data are transmitted from the van to hospitals and the university simultaneously. Physician in the hospital observes and interprets exam images from the van and watches the video images of the position of ultrasound transducer on screenee in the van. After the observation images, physician explains a results of the examination by the video conference system. Seventy lung CT screening and 203 ultrasound screening were done from March to June 2002. The trial of this real time screening suggested that rural residents are given better healthcare without visit to the hospital. And it will open the gateway to reduce the medical cost and medical divide between city area and rural area.

Towards Near Real-time Convective Rainfall Observations over Kenya

NASA Astrophysics Data System (ADS)

Hoedjes, Joost; Said, Mohammed; Becht, Robert; Kifugo, Shem; Kooiman, André; Limo, Agnes; Maathuis, Ben; Moore, Ian; Mumo, Mark; Nduhiu Mathenge, Joseph; Su, Bob; Wright, Iain

2013-04-01

The existing meteorological infrastructure in Kenya is poorly suited for the countrywide real-time monitoring of precipitation. Rainfall radar is not available, and the existing network of rain gauges is sparse and challenging to maintain. This severely restricts Kenya's capacity to warn for, and respond to, weather related emergencies. Furthermore, the lack of accurate rainfall observations severely limits Kenya's climate change adaptation capabilities. Over the past decade, the mobile telephone network in Kenya has expanded rapidly. This network makes extensive use of terrestrial microwave (MW) links, received signal level (RSL) data from which can be used for the calculation of rainfall intensities. We present a novel method for the near-real time observation of convective rainfall over Kenya, based on the combined use of MW RSL data and Meteosat Second Generation (MSG) satellite data. In this study, the variable density rainfall information derived from several MW links is scaled up using MSG data to provide full rainfall information coverage for the region surrounding the links. Combining MSG data and MW link derived rainfall data for several adjacent MW links makes it possible to make the distinction between wet and dry pixels. This allows the disaggregation of the MW link derived rainfall intensities. With the distinction between wet and dry pixels made, and the MW derived rainfall intensities disaggregated, these data can then be used to develop instantaneous empirical relationships linking rainfall intensities to cloud physical properties. These relationships are then used to calculate rainfall intensities for the MSG scene. Since both the MSG and the MW data are available at the same temporal resolution, unique empirical coefficients can be determined for each interval. This approach ensures that changes in convective conditions from one interval to the next are taken into account. Initial results from a pilot study, which took place from November 2012

Developing a Near Real-time System for Earthquake Slip Distribution Inversion

NASA Astrophysics Data System (ADS)

Zhao, Li; Hsieh, Ming-Che; Luo, Yan; Ji, Chen

2016-04-01

Advances in observational and computational seismology in the past two decades have enabled completely automatic and real-time determinations of the focal mechanisms of earthquake point sources. However, seismic radiations from moderate and large earthquakes often exhibit strong finite-source directivity effect, which is critically important for accurate ground motion estimations and earthquake damage assessments. Therefore, an effective procedure to determine earthquake rupture processes in near real-time is in high demand for hazard mitigation and risk assessment purposes. In this study, we develop an efficient waveform inversion approach for the purpose of solving for finite-fault models in 3D structure. Full slip distribution inversions are carried out based on the identified fault planes in the point-source solutions. To ensure efficiency in calculating 3D synthetics during slip distribution inversions, a database of strain Green tensors (SGT) is established for 3D structural model with realistic surface topography. The SGT database enables rapid calculations of accurate synthetic seismograms for waveform inversion on a regular desktop or even a laptop PC. We demonstrate our source inversion approach using two moderate earthquakes (Mw~6.0) in Taiwan and in mainland China. Our results show that 3D velocity model provides better waveform fitting with more spatially concentrated slip distributions. Our source inversion technique based on the SGT database is effective for semi-automatic, near real-time determinations of finite-source solutions for seismic hazard mitigation purposes.

4D Near Real-Time Environmental Monitoring Using Highly Temporal LiDAR

NASA Astrophysics Data System (ADS)

Höfle, Bernhard; Canli, Ekrem; Schmitz, Evelyn; Crommelinck, Sophie; Hoffmeister, Dirk; Glade, Thomas

2016-04-01

The last decade has witnessed extensive applications of 3D environmental monitoring with the LiDAR technology, also referred to as laser scanning. Although several automatic methods were developed to extract environmental parameters from LiDAR point clouds, only little research has focused on highly multitemporal near real-time LiDAR (4D-LiDAR) for environmental monitoring. Large potential of applying 4D-LiDAR is given for landscape objects with high and varying rates of change (e.g. plant growth) and also for phenomena with sudden unpredictable changes (e.g. geomorphological processes). In this presentation we will report on the most recent findings of the research projects 4DEMON (http://uni-heidelberg.de/4demon) and NoeSLIDE (https://geomorph.univie.ac.at/forschung/projekte/aktuell/noeslide/). The method development in both projects is based on two real-world use cases: i) Surface parameter derivation of agricultural crops (e.g. crop height) and ii) change detection of landslides. Both projects exploit the "full history" contained in the LiDAR point cloud time series. One crucial initial step of 4D-LiDAR analysis is the co-registration over time, 3D-georeferencing and time-dependent quality assessment of the LiDAR point cloud time series. Due to the high amount of datasets (e.g. one full LiDAR scan per day), the procedure needs to be performed fully automatically. Furthermore, the online near real-time 4D monitoring system requires to set triggers that can detect removal or moving of tie reflectors (used for co-registration) or the scanner itself. This guarantees long-term data acquisition with high quality. We will present results from a georeferencing experiment for 4D-LiDAR monitoring, which performs benchmarking of co-registration, 3D-georeferencing and also fully automatic detection of events (e.g. removal/moving of reflectors or scanner). Secondly, we will show our empirical findings of an ongoing permanent LiDAR observation of a landslide (Gresten

Near real time determination of the magnetopause and bow shock shape and position

NASA Astrophysics Data System (ADS)

Kartalev, M. D.; Keremidarska, V. I.; Grigorov, K. G.; Romanov, D. K.

2002-03-01

We present a web based near real time (once in 90 minutes) automated running of our 3D magnetosheath gasdynamic numerical model. (http://geospace.nat.bg). The determination of the shape and position of the bow shock and the magnetopause is a part of the solution. This approach of the model is utilizing the realistic semi-empirical Tsyganenko magnetosphere model T96-01 for ensuring the pressure balance at the magnetopause. In this realization, we use a real time ACE data, averaged over a 6 minutes time interval.

Near-real-time acoustic monitoring of beaked whales and other cetaceans using a Seaglider™.

PubMed

Klinck, Holger; Mellinger, David K; Klinck, Karolin; Bogue, Neil M; Luby, James C; Jump, William A; Shilling, Geoffrey B; Litchendorf, Trina; Wood, Angela S; Schorr, Gregory S; Baird, Robin W

2012-01-01

In most areas, estimating the presence and distribution of cryptic marine mammal species, such as beaked whales, is extremely difficult using traditional observational techniques such as ship-based visual line transect surveys. Because acoustic methods permit detection of animals underwater, at night, and in poor weather conditions, passive acoustic observation has been used increasingly often over the last decade to study marine mammal distribution, abundance, and movements, as well as for mitigation of potentially harmful anthropogenic effects. However, there is demand for new, cost-effective tools that allow scientists to monitor areas of interest autonomously with high temporal and spatial resolution in near-real time. Here we describe an autonomous underwater vehicle--a glider--equipped with an acoustic sensor and onboard data processing capabilities to passively scan an area for marine mammals in near-real time. The glider was tested extensively off the west coast of the Island of Hawai'i, USA. The instrument covered approximately 390 km during three weeks at sea and collected a total of 194 h of acoustic data. Detections of beaked whales were successfully reported to shore in near-real time. Manual analysis of the recorded data revealed a high number of vocalizations of delphinids and sperm whales. Furthermore, the glider collected vocalizations of unknown origin very similar to those made by known species of beaked whales. The instrument developed here can be used to cost-effectively screen areas of interest for marine mammals for several months at a time. The near-real-time detection and reporting capabilities of the glider can help to protect marine mammals during potentially harmful anthropogenic activities such as seismic exploration for sub-sea fossil fuels or naval sonar exercises. Furthermore, the glider is capable of under-ice operation, allowing investigation of otherwise inaccessible polar environments that are critical habitats for many

Near-Real-Time Acoustic Monitoring of Beaked Whales and Other Cetaceans Using a Seaglider™

PubMed Central

Klinck, Holger; Mellinger, David K.; Klinck, Karolin; Bogue, Neil M.; Luby, James C.; Jump, William A.; Shilling, Geoffrey B.; Litchendorf, Trina; Wood, Angela S.; Schorr, Gregory S.; Baird, Robin W.

2012-01-01

In most areas, estimating the presence and distribution of cryptic marine mammal species, such as beaked whales, is extremely difficult using traditional observational techniques such as ship-based visual line transect surveys. Because acoustic methods permit detection of animals underwater, at night, and in poor weather conditions, passive acoustic observation has been used increasingly often over the last decade to study marine mammal distribution, abundance, and movements, as well as for mitigation of potentially harmful anthropogenic effects. However, there is demand for new, cost-effective tools that allow scientists to monitor areas of interest autonomously with high temporal and spatial resolution in near-real time. Here we describe an autonomous underwater vehicle – a glider – equipped with an acoustic sensor and onboard data processing capabilities to passively scan an area for marine mammals in near-real time. The glider was tested extensively off the west coast of the Island of Hawai'i, USA. The instrument covered approximately 390 km during three weeks at sea and collected a total of 194 h of acoustic data. Detections of beaked whales were successfully reported to shore in near-real time. Manual analysis of the recorded data revealed a high number of vocalizations of delphinids and sperm whales. Furthermore, the glider collected vocalizations of unknown origin very similar to those made by known species of beaked whales. The instrument developed here can be used to cost-effectively screen areas of interest for marine mammals for several months at a time. The near-real-time detection and reporting capabilities of the glider can help to protect marine mammals during potentially harmful anthropogenic activities such as seismic exploration for sub-sea fossil fuels or naval sonar exercises. Furthermore, the glider is capable of under-ice operation, allowing investigation of otherwise inaccessible polar environments that are critical habitats for many

Real Time Volcanic Cloud Products and Predictions for Aviation Alerts

NASA Technical Reports Server (NTRS)

Krotkov, Nickolay A.; Habib, Shahid; da Silva, Arlindo; Hughes, Eric; Yang, Kai; Brentzel, Kelvin; Seftor, Colin; Li, Jason Y.; Schneider, David; Guffanti, Marianne;

After an Earthquake: Accessing Near Real-Time Data in the Classroom

NASA Astrophysics Data System (ADS)

Bravo, T. K.; Coleman, B.; Hubenthal, M.; Owens, T. J.; Taber, J.; Welti, R.; Weertman, B. R.

2010-12-01

One of the best ways to engage students in scientific content is to give them opportunities to work with real scientific instruments and data and enable them to experience the discovery of scientific information. In addition, newsworthy earthquakes can capture the attention and imagination of students. IRIS and collaborating partners provide a range of options to leverage that attention through access to near-real-time earthquake location and waveform data stored in the IRIS Data Management System and elsewhere via a number of web-based tools and a new Java-based application. The broadest audience is reached by the Seismic Monitor, a simple Web-based tool for observing near-real-time seismicity. The IRIS Earthquake Browser (IEB) allows users to explore recent and cataloged earthquakes and aftershock patterns online with more flexibility, and K-12 classroom activities for understanding plate tectonics and estimating seismic hazards have been designed around its use. Waveforms are easily viewed and explored on the web using the Rapid Earthquake Viewer (REV), developed by the University of South Carolina in collaboration with IRIS E&O. Data from recent well-known earthquakes available via REV are used in exercises to determine Earth’s internal structure and to locate earthquakes. Three component data is presented to the students, allowing a much more realistic analysis of the data than is presented in most textbooks. The Seismographs in Schools program uses real-time data in the classroom to interest and engage students about recent earthquakes. Through the IRIS website, schools can share event data and 24-hr images. Additionally, data is available in real-time via the API. This API allows anyone to extract data, re-purpose it, and display it however they need to, as is being done by the British Geological Survey Seismographs in Schools program. Over 350 schools throughout the US and internationally are currently registered with the IRIS Seismographs in Schools

Near-real-time cheatgrass percent cover in the Northern Great Basin, USA, 2015

USGS Publications Warehouse

Boyte, Stephen; Wylie, Bruce K.

2016-01-01

Cheatgrass (Bromus tectorum L.) dramatically changes shrub steppe ecosystems in the Northern Great Basin, United States.Current-season cheatgrass location and percent cover are difficult to estimate rapidly.We explain the development of a near-real-time cheatgrass percent cover dataset and map in the Northern Great Basin for the current year (2015), display the current year’s map, provide analysis of the map, and provide a website link to download the map (as a PDF) and the associated dataset.The near-real-time cheatgrass percent cover dataset and map were consistent with non-expedited, historical cheatgrass percent cover datasets and maps.Having cheatgrass maps available mid-summer can help land managers, policy makers, and Geographic Information Systems personnel as they work to protect socially relevant areas such as critical wildlife habitats.

Real-Time seismic waveforms monitoring with BeiDou Navigation Satellite System (BDS) observations for the 2015 Mw 7.8 Nepal earthquake

NASA Astrophysics Data System (ADS)

Geng, T.

2015-12-01

Nowadays more and more high-rate Global Navigation Satellite Systems (GNSS) data become available in real time, which provide more opportunities to monitor the seismic waveforms. China's GNSS, BeiDou Navigation Satellite System (BDS), has already satisfied the requirement of stand-alone precise positioning in Asia-Pacific region with 14 in-orbit satellites, which promisingly suggests that BDS could be applied to the high-precision earthquake monitoring as GPS. In the present paper, real-time monitoring of seismic waveforms using BDS measurements is assessed. We investigate a so-called "variometric" approach to measure real-time seismic waveforms with high-rate BDS observations. This approach is based on time difference technique and standard broadcast products which are routinely available in real time. The 1HZ BDS data recorded by Beidou Experimental Tracking Stations (BETS) during the 2015 Mw 7.8 Nepal earthquake is analyzed. The results indicate that the accuracies of velocity estimation from BDS are 2-3 mm/s in horizontal components and 8-9 mm/s in vertical component, respectively, which are consistent with GPS. The seismic velocity waveforms during earthquake show good agreement between BDS and GPS. Moreover, the displacement waveforms is reconstructed by an integration of velocity time series with trend removal. The displacement waveforms with the accuracy of 1-2 cm are derived by comparing with post-processing GPS precise point positioning (PPP).

Near Real{time Data Assimilation for the HYSPLIT Aerosol Dispersion Model

NASA Astrophysics Data System (ADS)

Kalpakis, K.; Yang, S.; Yesha, Y.

2010-12-01

Konstantinos Kalpakis, Shiming Yang, and Yaacov Yesha Department of Computer Science and Electrical Engineering University of Maryland Baltimore County 1000 Hilltop Circle, Baltimore, MD, U.S.A. {kalpakis, shiming1, yayeshag}@csee.umbc.edu ABSTRACT We are working on an IBM-funded project seeking to develop a prototype system for real-time plume dispersion and fire and smoke detection and monitoring. Our prototype system utilizes HYSPLIT and observation data from various sources. HYSPLIT is a model developed by NOAA's Air Resources Laboratory for forecasting aerosol trajectories, dispersion, and concentration from emission sources. It is used extensively by NOAA to routinely provide a number of data products. We develop a data assimilation system for assimilating observational data into the forecasting model in order to improve its forecasting accuracy. Our system is based on the Local Ensemble Transform Kalman Filter (LETKF) algorithm and it is computationally efficient. We evaluate our data assimilation system with real in-situ observational data, and find that our system improves upon HYSPLIT's forecast by reducing the normalized mean squared error and the bias. We are also experimenting with assimilating MODIS data with HYSPLIT model forecasts. To this end, we extrapolate ground concentrations from MODIS Aerosol Optical Depth (AOD) data. Our extrapolation approach relies on spatially localized linear regressions of aerosol concentrations from ground stations in the Air Quality System (AQS) network and MODIS AOD data. We expect that assimilating the extrapolated concentrations leads into further improvements of HYSPLIT forecasts. Furthermore, we are investigating using additional sources of in-situ and remotely sensed observations, such as GOES AOD 30-minute data, and UAV data from the Ikhana AMS fire missions. These sources provide higher spatial resolution and more frequent temporal coverage. Moreover, GOES and UAVs provide near-real time data which should be

Real-time science and outreach from the UNOLS fleet via HiSeasNet

NASA Astrophysics Data System (ADS)

Foley, S.; Berger, J.; Orcutt, J. A.; Brice, D.; Coleman, D. F.; Grabowski, E. M.

2010-12-01

The HiSeasNet satellite communications network has ben providing cost-effective, reliable, continuous Internet connectivity to the UNOLS oceanographic research fleet for nearly nine years. During that time, HiSeasNet has supported science and outreach programs with a variety of real-time interactions back to shore including videoconferencing, webcasting, shared whiteboards, and streaming high-definition video feeds. Solutions have varied in scale, cost, and capability. As real-time science and outreach becomes more common, experience with a variety of technologies continues to build, and more opportunities yet to explore.

Near real-time shadow detection and removal in aerial motion imagery application

NASA Astrophysics Data System (ADS)

Silva, Guilherme F.; Carneiro, Grace B.; Doth, Ricardo; Amaral, Leonardo A.; Azevedo, Dario F. G. de

2018-06-01

This work presents a method to automatically detect and remove shadows in urban aerial images and its application in an aerospace remote monitoring system requiring near real-time processing. Our detection method generates shadow masks and is accelerated by GPU programming. To obtain the shadow masks, we converted images from RGB to CIELCh model, calculated a modified Specthem ratio, and applied multilevel thresholding. Morphological operations were used to reduce shadow mask noise. The shadow masks are used in the process of removing shadows from the original images using the illumination ratio of the shadow/non-shadow regions. We obtained shadow detection accuracy of around 93% and shadow removal results comparable to the state-of-the-art while maintaining execution time under real-time constraints.

Near Real Time Review of Instrument Performance using the Airborne Data Processing and Analysis Software Package

NASA Astrophysics Data System (ADS)

Delene, D. J.

2014-12-01

Research aircraft that conduct atmospheric measurements carry an increasing array of instrumentation. While on-board personnel constantly review instrument parameters and time series plots, there are an overwhelming number of items. Furthermore, directing the aircraft flight takes up much of the flight scientist time. Typically, a flight engineer is given the responsibility of reviewing the status of on-board instruments. While major issues like not receiving data are quickly identified during a flight, subtle issues like low but believable concentration measurements may go unnoticed. Therefore, it is critical to review data after a flight in near real time. The Airborne Data Processing and Analysis (ADPAA) software package used by the University of North Dakota automates the post-processing of aircraft flight data. Utilizing scripts to process the measurements recorded by data acquisition systems enables the generation of data files within an hour of flight completion. The ADPAA Cplot visualization program enables plots to be quickly generated that enable timely review of all recorded and processed parameters. Near real time review of aircraft flight data enables instrument problems to be identified, investigated and fixed before conducting another flight. On one flight, near real time data review resulted in the identification of unusually low measurements of cloud condensation nuclei, and rapid data visualization enabled the timely investigation of the cause. As a result, a leak was found and fixed before the next flight. Hence, with the high cost of aircraft flights, it is critical to find and fix instrument problems in a timely matter. The use of a automated processing scripts and quick visualization software enables scientists to review aircraft flight data in near real time to identify potential problems.

Near-real-time Estimation and Forecast of Total Precipitable Water in Europe

NASA Astrophysics Data System (ADS)

Bartholy, J.; Kern, A.; Barcza, Z.; Pongracz, R.; Ihasz, I.; Kovacs, R.; Ferencz, C.

2013-12-01

Information about the amount and spatial distribution of atmospheric water vapor (or total precipitable water) is essential for understanding weather and the environment including the greenhouse effect, the climate system with its feedbacks and the hydrological cycle. Numerical weather prediction (NWP) models need accurate estimations of water vapor content to provide realistic forecasts including representation of clouds and precipitation. In the present study we introduce our research activity for the estimation and forecast of atmospheric water vapor in Central Europe using both observations and models. The Eötvös Loránd University (Hungary) operates a polar orbiting satellite receiving station in Budapest since 2002. This station receives Earth observation data from polar orbiting satellites including MODerate resolution Imaging Spectroradiometer (MODIS) Direct Broadcast (DB) data stream from satellites Terra and Aqua. The received DB MODIS data are automatically processed using freely distributed software packages. Using the IMAPP Level2 software total precipitable water is calculated operationally using two different methods. Quality of the TPW estimations is a crucial question for further application of the results, thus validation of the remotely sensed total precipitable water fields is presented using radiosonde data. In a current research project in Hungary we aim to compare different estimations of atmospheric water vapor content. Within the frame of the project we use a NWP model (DBCRAS; Direct Broadcast CIMSS Regional Assimilation System numerical weather prediction software developed by the University of Wisconsin, Madison) to forecast TPW. DBCRAS uses near real time Level2 products from the MODIS data processing chain. From the wide range of the derived Level2 products the MODIS TPW parameter found within the so-called mod07 results (Atmospheric Profiles Product) and the cloud top pressure and cloud effective emissivity parameters from the so

Near real-time adverse drug reaction surveillance within population-based health networks: methodology considerations for data accrual.

PubMed

Avery, Taliser R; Kulldorff, Martin; Vilk, Yury; Li, Lingling; Cheetham, T Craig; Dublin, Sascha; Davis, Robert L; Liu, Liyan; Herrinton, Lisa; Brown, Jeffrey S

2013-05-01

This study describes practical considerations for implementation of near real-time medical product safety surveillance in a distributed health data network. We conducted pilot active safety surveillance comparing generic divalproex sodium to historical branded product at four health plans from April to October 2009. Outcomes reported are all-cause emergency room visits and fractures. One retrospective data extract was completed (January 2002-June 2008), followed by seven prospective monthly extracts (January 2008-November 2009). To evaluate delays in claims processing, we used three analytic approaches: near real-time sequential analysis, sequential analysis with 1.5 month delay, and nonsequential (using final retrospective data). Sequential analyses used the maximized sequential probability ratio test. Procedural and logistical barriers to active surveillance were documented. We identified 6586 new users of generic divalproex sodium and 43,960 new users of the branded product. Quality control methods identified 16 extract errors, which were corrected. Near real-time extracts captured 87.5% of emergency room visits and 50.0% of fractures, which improved to 98.3% and 68.7% respectively with 1.5 month delay. We did not identify signals for either outcome regardless of extract timeframe, and slight differences in the test statistic and relative risk estimates were found. Near real-time sequential safety surveillance is feasible, but several barriers warrant attention. Data quality review of each data extract was necessary. Although signal detection was not affected by delay in analysis, when using a historical control group differential accrual between exposure and outcomes may theoretically bias near real-time risk estimates towards the null, causing failure to detect a signal. Copyright © 2013 John Wiley & Sons, Ltd.

Near Real-Time Processing of Proteomics Data Using Hadoop.

PubMed

Hillman, Chris; Ahmad, Yasmeen; Whitehorn, Mark; Cobley, Andy

2014-03-01

This article presents a near real-time processing solution using MapReduce and Hadoop. The solution is aimed at some of the data management and processing challenges facing the life sciences community. Research into genes and their product proteins generates huge volumes of data that must be extensively preprocessed before any biological insight can be gained. In order to carry out this processing in a timely manner, we have investigated the use of techniques from the big data field. These are applied specifically to process data resulting from mass spectrometers in the course of proteomic experiments. Here we present methods of handling the raw data in Hadoop, and then we investigate a process for preprocessing the data using Java code and the MapReduce framework to identify 2D and 3D peaks.

Solar Demon: near real-time solar eruptive event detection on SDO/AIA images

NASA Astrophysics Data System (ADS)

Kraaikamp, Emil; Verbeeck, Cis

Solar flares, dimmings and EUV waves have been observed routinely in extreme ultra-violet (EUV) images of the Sun since 1996. These events are closely associated with coronal mass ejections (CMEs), and therefore provide useful information for early space weather alerts. The Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA) generates such a massive dataset that it becomes impossible to find most of these eruptive events manually. Solar Demon is a set of automatic detection algorithms that attempts to solve this problem by providing both near real-time warnings of eruptive events and a catalog of characterized events. Solar Demon has been designed to detect and characterize dimmings, EUV waves, as well as solar flares in near real-time on SDO/AIA data. The detection modules are running continuously at the Royal Observatory of Belgium on both quick-look data and synoptic science data. The output of Solar Demon can be accessed in near real-time on the Solar Demon website, and includes images, movies, light curves, and the numerical evolution of several parameters. Solar Demon is the result of collaboration between the FP7 projects AFFECTS and COMESEP. Flare detections of Solar Demon are integrated into the COMESEP alert system. Here we present the Solar Demon detection algorithms and their output. We will focus on the algorithm and its operational implementation. Examples of interesting flare, dimming and EUV wave events, and general statistics of the detections made so far during solar cycle 24 will be presented as well.

The Atmospheric Channels of GLAS: Near Real-Time Global Lidar Remote Sensing of Clouds and Aerosols from Space

NASA Technical Reports Server (NTRS)

Palm, Stephen P.; Hlavka, Dennis; Hart, Bill; Welton, E. Judd; Spinhirne, James

2000-01-01

The Geoscience Laser Altimeter System (GLAS) will be placed into orbit in 2001 aboard the Ice, Cloud and Land Elevation Satellite (ICESat). From its nearly polar orbit (94 degree inclination), GLAS will provide continuous global measurements of the vertical distribution of clouds and aerosols while simultaneously providing high accuracy topographic profiling of surface features. During the mission, which is slated to last 3 to 5 years, the data collected by GLAS will be in near-real time to produce level 1 and 2 data products at the NASA GLAS Science Computing Facility (SCF) at Goddard Space Flight Center in Greenbelt, Maryland. The atmospheric products include cloud and aerosol layer heights, planetary boundary layer depth, polar stratospheric clouds and thin cloud and aerosol optical depth. These products will be made available to the science community within days of their creation. The processing algorithms must be robust, adaptive, efficient, and clever enough to run autonomously for the widely varying atmospheric conditions that will be encountered. This paper presents an overview of the GLAS atmospheric data products and briefly discusses the design of the processing algorithms.

Near-real-time mosaics from high-resolution side-scan sonar

USGS Publications Warehouse

Danforth, William W.; O'Brien, Thomas F.; Schwab, W.C.

1991-01-01

High-resolution side-scan sonar has proven to be a very effective tool for stuyding and understanding the surficial geology of the seafloor. Since the mid-1970s, the US Geological Survey has used high-resolution side-scan sonar systems for mapping various areas of the continental shelf. However, two problems typically encountered included the short range and the high sampling rate of high-resolution side-scan sonar systems and the acquisition and real-time processing of the enormous volume of sonar data generated by high-resolution suystems. These problems were addressed and overcome in August 1989 when the USGS conducted a side-scan sonar and bottom sampling survey of a 1000-sq-km section of the continental shelf in the Gulf of Farallones located offshore of San Francisco. The primary goal of this survey was to map an area of critical interest for studying continental shelf sediment dynamics. This survey provided an opportunity to test an image processing scheme that enabled production of a side-scan sonar hard-copy mosaic during the cruise in near real-time.

VLBI real-time analysis by Kalman Filtering

NASA Astrophysics Data System (ADS)

Karbon, M.; Nilsson, T.; Soja, B.; Heinkelmann, R.; Raposo-Pulido, V.; Schuh, H.

2013-12-01

Geodetic Very Long Baseline Interferometry (VLBI) is one of the primary space geodetic techniques providing the full set of Earth Orientation Parameter (EOP) and is unique for observing long term Universal Time (UT1) and precession/nutation. Accurate and continuous EOP obtained in near real-time are essential for satellite based navigation and positioning and for enabling the precise tracking of interplanetary spacecrafts. To meet this necessity the International VLBI Service for Geodesy and Astrometry (IVS) increased its efforts to reduce the time span between the VLBI observations and the availability of the final results. Currently the timeliness is about two weeks, but the goal is to reduce it to less than one day with the future VGOS (VLBI2010 Global Observing System) network. The FWF project VLBI-ART contributes to this new generation VLBI system by considerably accelerating the VLBI analysis procedure through the implementation of an elaborate Kalman filter. This true real-time Kalman filter will be embedded in the Vienna VLBI Software (VieVS) as a completely automated tool with no need of human interaction. This filter also allows the prediction and combination of EOP from various space geodetic techniques by implementing stochastic models to statistically account for unpredictable changes in EOP. Additionally, atmospheric angular momenta calculated from numerical weather prediction models are introduced to support the short-term EOP prediction. To optimize the performance of the new software various investigations with real as well as simulated data are foreseen. The results are compared to the ones obtained by conventional VLBI parameter estimation methods (e.g. least squares method) and to corresponding parameter series from other techniques, such as from the Global Navigation Satellite Systems (GNSS).

The near real time image navigation of pictures returned by Voyager 2 at Neptune

NASA Technical Reports Server (NTRS)

Underwood, Ian M.; Bachman, Nathaniel J.; Taber, William L.; Wang, Tseng-Chan; Acton, Charles H.

1990-01-01

The development of a process for performing image navigation in near real time is described. The process was used to accurately determine the camera pointing for pictures returned by the Voyager 2 spacecraft at Neptune Encounter. Image navigation improves knowledge of the pointing of an imaging instrument at a particular epoch by correlating the spacecraft-relative locations of target bodies in inertial space with the locations of their images in a picture taken at that epoch. More than 8,500 pictures returned by Voyager 2 at Neptune were processed in near real time. The results were used in several applications, including improving pointing knowledge for nonimaging instruments ('C-smithing'), making 'Neptune, the Movie', and providing immediate access to geometrical quantities similar to those traditionally supplied in the Supplementary Experiment Data Record.

Numerical simulations of tropical cyclones with assimilation of satellite, radar and in-situ observations: lessons learned from recent field programs and real-time experimental forecasts

NASA Astrophysics Data System (ADS)

Pu, Z.; Zhang, L.

2010-12-01

The impact of data assimilation on the predictability of tropical cyclones is examined with the cases from recent field programs and real-time hurricane forecast experiments. Mesoscale numerical simulations are performed to simulate major typhoons during the T-PARC/TCS08 field campaign with the assimilation of satellite, radar and in-situ observations. Results confirmed that data assimilation has indeed resulted in improved numerical simulations of tropical cyclones. However, positive impacts from the satellite and radar data are strongly depend on the quality of these data. Specifically, it is found that the overall impacts of assimilating AIRS retrieved atmospheric temperature and moisture profiles on numerical simulations of tropical cyclones are very sensitive to the bias corrections of the data.For instance, the dry biases of moisture profiles can cause the decay of tropical cyclones in the numerical simulations.In addition, the quality of airborne Doppler radar data has strong influence on numerical simulations of tropical cyclones in terms of their track, intensity and precipitation structures. Outcomes from assimilating radar data with various quality thresholds suggest that a trade-off between the quality and area coverage of the radar data is necessary in the practice. Some of those experiences obtained from the field case studies are applied to the near-real time experimental hurricane forecasts during the 2010 hurricane season. Results and issues raised from the case studies and real-time experiments will be discussed.

Interoperable Access to Near Real Time Ocean Observations with the Observing System Monitoring Center

NASA Astrophysics Data System (ADS)

O'Brien, K.; Hankin, S.; Mendelssohn, R.; Simons, R.; Smith, B.; Kern, K. J.

2013-12-01

The Observing System Monitoring Center (OSMC), a project funded by the National Oceanic and Atmospheric Administration's Climate Observations Division (COD), exists to join the discrete 'networks' of In Situ ocean observing platforms -- ships, surface floats, profiling floats, tide gauges, etc. - into a single, integrated system. The OSMC is addressing this goal through capabilities in three areas focusing on the needs of specific user groups: 1) it provides real time monitoring of the integrated observing system assets to assist management in optimizing the cost-effectiveness of the system for the assessment of climate variables; 2) it makes the stream of real time data coming from the observing system available to scientific end users into an easy-to-use form; and 3) in the future, it will unify the delayed-mode data from platform-focused data assembly centers into a standards- based distributed system that is readily accessible to interested users from the science and education communities. In this presentation, we will be focusing on the efforts of the OSMC to provide interoperable access to the near real time data stream that is available via the Global Telecommunications System (GTS). This is a very rich data source, and includes data from nearly all of the oceanographic platforms that are actively observing. We will discuss how the data is being served out using a number of widely used 'web services' (including OPeNDAP and SOS) and downloadable file formats (KML, csv, xls, netCDF), so that it can be accessed in web browsers and popular desktop analysis tools. We will also be discussing our use of the Environmental Research Division's Data Access Program (ERDDAP), available from NOAA/NMFS, which has allowed us to achieve our goals of serving the near real time data. From an interoperability perspective, it's important to note that access to the this stream of data is not just for humans, but also for machine-to-machine requests. We'll also delve into how we

Near Real-time Operational Use of eMODIS Expedited NDVI for Monitoring Applications and Famine Early Warning

NASA Astrophysics Data System (ADS)

Rowland, J.; Budde, M. E.

2010-12-01

The Famine Early Warning Systems Network (FEWS NET) has requirements for near real-time monitoring of vegetation conditions for food security applications. Accurate and timely assessments of crop conditions are an important element of food security decision making. FEWS NET scientists at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center are utilizing a new Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) dataset for operational monitoring of crop and pasture conditions in parts of the world where food availability is highly dependent on subsistence agriculture and animal husbandry. The expedited MODIS, or eMODIS, production system processes NDVI data using MODIS surface reflectance provided by the Land Atmosphere Near-real-time Capability for EOS (LANCE). Benefits of this production system include customized compositing schedules, near real-time data availability, and minimized re-sampling. FEWS NET has implemented a 10-day compositing scheme every five days to accommodate the need for timely information on vegetation conditions. The data are currently being processed at 250-meter spatial resolution for Central America, Hispaniola, and Africa. Data are further enhanced by the application of a temporal smoothing filter which helps remove contamination due to clouds and other atmospheric effects. The results of this near real-time monitoring capability have been the timely provision of NDVI and NDVI anomaly maps for each of the FEWS NET monitoring regions and the availability of a consistently processed dataset to aid crop assessment missions and to facilitate customized analyses of crop production, drought, and agro-pastoral conditions.

High Resolution Near Real Time Image Processing and Support for MSSS Modernization

DTIC Science & Technology

2012-09-01

00-00-2012 to 00-00-2012 4 . TITLE AND SUBTITLE High Resolution Near Real Time Image Processing and Support for MSSS Modernization 5a. CONTRACT...This current CONOPS is depicted in Fig. 4 . Fig. 4 . PCID/ASPIRE High Resolution Post...experiments were performed, and subsequently addressed in papers and presentations [3, 4 ,] that demonstrated system behavior; with details of the

Solar Demon: near real-time Flare, Dimming and EUV wave monitoring

NASA Astrophysics Data System (ADS)

Kraaikamp, Emil; Verbeeck, Cis

Dimmings and EUV waves have been observed routinely in EUV images since 1996. They are closely associated with coronal mass ejections (CMEs), and therefore provide useful information for early space weather alerts. On the one hand, automatic detection and characterization of dimmings and EUV waves can be used to gain better understanding of the underlying physical mechanisms. On the other hand, every dimming and EUV wave provides extra information on the associated front side CME, and can improve estimates of the geo-effectiveness and arrival time of the CME. Solar Demon has been designed to detect and characterize dimmings, EUV waves, as well as solar flares in near real-time on Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA) data. The detection modules are running continuously at the Royal Observatory of Belgium on both quick-look data, as well as synoptic science data. The output of Solar Demon can be accessed in near real-time on the Solar Demon website, and includes images, movies, light curves, and the numerical evolution of several parameters. Solar Demon is the result of collaboration between the FP7 projects AFFECTS and COMESEP. Flare detections of Solar Demon are integrated into the COMESEP alert system. Here we present the Solar Demon detection algorithms and their output. We will show several interesting flare, dimming and EUV wave events, and present general statistics of the detections made so far during solar cycle 24.

Uniform Data Management and Access to Near Real-Time Seismic Data (Invited)

NASA Astrophysics Data System (ADS)

Casey, R.; Ahern, T. K.; Benson, R. B.; Karstens, R.; Stromme, S.; Trabant, C. M.; Weertman, B. R.

2010-12-01

The IRIS Data Management Center has its ears to the ground, receiving relayed seismic telemetry from all parts of the globe with delay times as little as a few seconds from sensor to data center. This immediacy of always-on geophysical information has spawned a demand for ready access to persistent data streams, quality assurance metrics, and automatic production of data products based on specific triggers. For the last ten years, IRIS DMC has developed an effective near real-time data pipeline that serves the needs of seismic networks needing a central data management system as well as the scientific community that need the ability to monitor and respond to events that occurred only moments before. A number of accessible applications have been developed that provide useful data both through the web and through freely available software. Metrics and products of the raw data are cataloged and managed as a chain of events that occur in near-real time. The technical challenges faced with such a system are general to the data management community. Delayed transmission of packetized data, out of order data transmissions, verification of complete data transmission, and data flow concurrency have all been areas of focus in order to provide the best possible level of service to scientists and educators.

Monitoring activities of satellite data processing services in real-time with SDDS Live Monitor

NASA Astrophysics Data System (ADS)

Duc Nguyen, Minh

2017-10-01

This work describes Live Monitor, the monitoring subsystem of SDDS - an automated system for space experiment data processing, storage, and distribution created at SINP MSU. Live Monitor allows operators and developers of satellite data centers to identify errors occurred in data processing quickly and to prevent further consequences caused by the errors. All activities of the whole data processing cycle are illustrated via a web interface in real-time. Notification messages are delivered to responsible people via emails and Telegram messenger service. The flexible monitoring mechanism implemented in Live Monitor allows us to dynamically change and control events being shown on the web interface on our demands. Physicists, whose space weather analysis models are functioning upon satellite data provided by SDDS, can use the developed RESTful API to monitor their own events and deliver customized notification messages by their needs.

Accessible high performance computing solutions for near real-time image processing for time critical applications

NASA Astrophysics Data System (ADS)

Bielski, Conrad; Lemoine, Guido; Syryczynski, Jacek

2009-09-01

High Performance Computing (HPC) hardware solutions such as grid computing and General Processing on a Graphics Processing Unit (GPGPU) are now accessible to users with general computing needs. Grid computing infrastructures in the form of computing clusters or blades are becoming common place and GPGPU solutions that leverage the processing power of the video card are quickly being integrated into personal workstations. Our interest in these HPC technologies stems from the need to produce near real-time maps from a combination of pre- and post-event satellite imagery in support of post-disaster management. Faster processing provides a twofold gain in this situation: 1. critical information can be provided faster and 2. more elaborate automated processing can be performed prior to providing the critical information. In our particular case, we test the use of the PANTEX index which is based on analysis of image textural measures extracted using anisotropic, rotation-invariant GLCM statistics. The use of this index, applied in a moving window, has been shown to successfully identify built-up areas in remotely sensed imagery. Built-up index image masks are important input to the structuring of damage assessment interpretation because they help optimise the workload. The performance of computing the PANTEX workflow is compared on two different HPC hardware architectures: (1) a blade server with 4 blades, each having dual quad-core CPUs and (2) a CUDA enabled GPU workstation. The reference platform is a dual CPU-quad core workstation and the PANTEX workflow total computing time is measured. Furthermore, as part of a qualitative evaluation, the differences in setting up and configuring various hardware solutions and the related software coding effort is presented.

Real-Time Tropospheric Product Establishment and Accuracy Assessment in China

NASA Astrophysics Data System (ADS)

Chen, M.; Guo, J.; Wu, J.; Song, W.; Zhang, D.

2018-04-01

Tropospheric delay has always been an important issue in Global Navigation Satellite System (GNSS) processing. Empirical tropospheric delay models are difficult to simulate complex and volatile atmospheric environments, resulting in poor accuracy of the empirical model and difficulty in meeting precise positioning demand. In recent years, some scholars proposed to establish real-time tropospheric product by using real-time or near-real-time GNSS observations in a small region, and achieved some good results. This paper uses real-time observing data of 210 Chinese national GNSS reference stations to estimate the tropospheric delay, and establishes ZWD grid model in the country wide. In order to analyze the influence of tropospheric grid product on wide-area real-time PPP, this paper compares the method of taking ZWD grid product as a constraint with the model correction method. The results show that the ZWD grid product estimated based on the national reference stations can improve PPP accuracy and convergence speed. The accuracy in the north (N), east (E) and up (U) direction increase by 31.8 %,15.6 % and 38.3 %, respectively. As with the convergence speed, the accuracy of U direction experiences the most improvement.

Real-time Transmission and Distribution of NOAA Tail Doppler Radar Data and Other Data Products

NASA Astrophysics Data System (ADS)

Carswell, J.; Chang, P.; Robinson, D.; Gamache, J.; Hill, J.

2011-12-01

The NOAA WP-3D and G-IV aircraft have conducted and continue to conduct numerous research and operational measurement missions. However, typically only a fraction of the data collected aboard each flight is transmitted to the ground in near real-time utilizing low bandwidth satellite data links. The advancements in aircraft satellite phones have increased available bandwidth and reliability to a point where these systems can be utilized for near real-time data flow in support of decision making. A robust and flexible data delivery system has been developed by Remote Sensing Solutions with support from NOAA's National Environmental Satellite, Data and Information Service (NESDIS), Aircraft Operations Center (AOC) and Hurricane Forecast Improvement Project (HFIP). X-band Doppler/reflectivity measurements of tropical storms and cyclones collected from the NOAA WP-3D aircraft have been the most recent focus. Doppler measurements from volume backscatter precipitation profiles can provide critical observations of the horizontal winds as the precipitation advects with these winds. The data delivery system captures these profiles and send the radial Doppler profile observations to National Weather Service in near real-time over satellite communication data link. The design of this transmission system included features to enhance the reliability and robustness of the data flow from the P-3 aircraft to the end user. Routine real-time transmission, using this system, of the full resolution Tail Doppler Radar profile data to the ground and distribution to the NOAA's Hurricane Research Division for analysis and processing in support of initializing the operational HWRF model is planned. The end objective is to provide these Doppler profiles in a routine fashion to NWS and others in the forecasting community for operational utilization in support of hurricane forecasting and warning. Other data sources that are being collected and transmitted to the ground with this system for

Using CATS Near-Real-time Lidar Observations to Monitor and Constrain Volcanic Sulfur Dioxide (SO2) Forecasts

NASA Technical Reports Server (NTRS)

Hughes, E. J.; Yorks, J.; Krotkov, N. A.; da Silva, A. M.; Mcgill, M.

2016-01-01

An eruption of Italian volcano Mount Etna on 3 December 2015 produced fast-moving sulfur dioxide (SO2) and sulfate aerosol clouds that traveled across Asia and the Pacific Ocean, reaching North America in just 5 days. The Ozone Profiler and Mapping Suite's Nadir Mapping UV spectrometer aboard the U.S. National Polar-orbiting Partnership satellite observed the horizontal transport of the SO2 cloud. Vertical profiles of the colocated volcanic sulfate aerosols were observed between 11.5 and 13.5 km by the new Cloud Aerosol Transport System (CATS) space-based lidar aboard the International Space Station. Backward trajectory analysis estimates the SO2 cloud altitude at 7-12 km. Eulerian model simulations of the SO2 cloud constrained by CATS measurements produced more accurate dispersion patterns compared to those initialized with the back trajectory height estimate. The near-real-time data processing capabilities of CATS are unique, and this work demonstrates the use of these observations to monitor and model volcanic clouds.

Using CATS Near-Real-Time Lidar Observations to Monitor and Constrain Volcanic Sulfur Dioxide (SO2) Forecasts

NASA Technical Reports Server (NTRS)

Hughes, E. J.; Yorks, J.; Krotkov, N. A.; Da Silva, A. M.; McGill, M.

2016-01-01

An eruption of Italian volcano Mount Etna on 3 December 2015 produced fast-moving sulfur dioxide (SO2) and sulfate aerosol clouds that traveled across Asia and the Pacific Ocean, reaching North America in just 5days. The Ozone Profiler and Mapping Suite's Nadir Mapping UV spectrometer aboard the U.S. National Polar-orbiting Partnership satellite observed the horizontal transport of the SO2 cloud. Vertical profiles of the colocated volcanic sulfate aerosols were observed between 11.5 and 13.5 km by the new Cloud Aerosol Transport System (CATS) space-based lidar aboard the International Space Station. Backward trajectory analysis estimates the SO2 cloud altitude at 7-12 km. Eulerian model simulations of the SO2 cloud constrained by CATS measurements produced more accurate dispersion patterns compared to those initialized with the back trajectory height estimate. The near-real-time data processing capabilities of CATS are unique, and this work demonstrates the use of these observations to monitor and model volcanic clouds.

A Real-Time Robust Method to Detect BeiDou GEO/IGSO Orbital Maneuvers

PubMed Central

Huang, Guanwen; Qin, Zhiwei; Zhang, Qin; Wang, Le; Yan, Xingyuan; Fan, Lihong; Wang, Xiaolei

2017-01-01

The frequent maneuvering of BeiDou Geostationary Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO) satellites affects the availability of real-time orbit, and decreases the accuracy and performance of positioning, navigation and time (PNT) services. BeiDou satellite maneuver information cannot be obtained by common users. BeiDou broadcast ephemeris is the only indicator of the health status of satellites, which are broadcast on an hourly basis, easily leading to ineffective observations. Sometimes, identification errors of satellite abnormity also appear in the broadcast ephemeris. This study presents a real-time robust detection method for a satellite orbital maneuver with high frequency and high reliability. By using the broadcast ephemeris and pseudo-range observations, the time discrimination factor and the satellite identification factor were defined and used for the real-time detection of start time and the pseudo-random noise code (PRN) of satellites was used for orbital maneuvers. Data from a Multi-GNSS Experiment (MGEX) was collected and analyzed. The results show that the start time and the PRN of the satellite orbital maneuver could be detected accurately in real time. In addition, abnormal start times and satellite abnormities caused by non-maneuver factors also could be detected using the proposed method. The new method not only improves the utilization of observations for users with the data effective for about 92 min, but also promotes the reliability of real-time PNT services. PMID:29186058

A Real-Time Robust Method to Detect BeiDou GEO/IGSO Orbital Maneuvers.

PubMed

Huang, Guanwen; Qin, Zhiwei; Zhang, Qin; Wang, Le; Yan, Xingyuan; Fan, Lihong; Wang, Xiaolei

2017-11-29

The frequent maneuvering of BeiDou Geostationary Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO) satellites affects the availability of real-time orbit, and decreases the accuracy and performance of positioning, navigation and time (PNT) services. BeiDou satellite maneuver information cannot be obtained by common users. BeiDou broadcast ephemeris is the only indicator of the health status of satellites, which are broadcast on an hourly basis, easily leading to ineffective observations. Sometimes, identification errors of satellite abnormity also appear in the broadcast ephemeris. This study presents a real-time robust detection method for a satellite orbital maneuver with high frequency and high reliability. By using the broadcast ephemeris and pseudo-range observations, the time discrimination factor and the satellite identification factor were defined and used for the real-time detection of start time and the pseudo-random noise code (PRN) of satellites was used for orbital maneuvers. Data from a Multi-GNSS Experiment (MGEX) was collected and analyzed. The results show that the start time and the PRN of the satellite orbital maneuver could be detected accurately in real time. In addition, abnormal start times and satellite abnormities caused by non-maneuver factors also could be detected using the proposed method. The new method not only improves the utilization of observations for users with the data effective for about 92 min, but also promotes the reliability of real-time PNT services.

eMODIS Expedited: Overview of a Near Real Time MODIS Production System for Operational Vegetation Monitoring

NASA Astrophysics Data System (ADS)

Jenkerson, C.; Meyer, D. J.; Werpy, J.; Evenson, K.; Merritt, M.

2010-12-01

The expedited MODIS, or eMODIS production system derives near-real time Normalized Difference Vegetation Index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance provided by the Land and Atmosphere Near-real time Capability for EOS (LANCE). There are currently three regions covered by this U.S. Geological Survey (USGS) capability, including the continental U.S., Africa, and the Central America/Caribbean regions. Each of the eMODIS production streams is configured to output its data in map projections, compositing intervals, spatial resolutions, and file formats specific to its region and user community. The challenges of processing 1,000-meter, 500-m, and especially 250-m products by midnight on the last day of a product interval have been met with increasingly effective software and system architecture. An anonymous file transfer protocol (FTP) distribution site (ftp://emodisftp.cr.usgs.gov/eMODIS) allows users direct access to eMODIS NDVI products for operational (near-real time) monitoring of vegetation conditions like drought, crop failure, insect infestation, and other threats, thus supporting subsequent early warning of famine and the targeting of vulnerable populations for insecure food situations.

Quantitative real-time monitoring of dryer effluent using fiber optic near-infrared spectroscopy.

PubMed

Harris, S C; Walker, D S

2000-09-01

This paper describes a method for real-time quantitation of the solvents evaporating from a dryer. The vapor stream in the vacuum line of a dryer was monitored in real time using a fiber optic-coupled acousto-optic tunable filter near-infrared (AOTF-NIR) spectrometer. A balance was placed in the dryer, and mass readings were recorded for every scan of the AOTF-NIR. A partial least-squares (PLS) calibration was subsequently built based on change in mass over change in time for solvents typically used in a chemical manufacturing plant. Controlling software for the AOTF-NIR was developed. The software collects spectra, builds the PLS calibration model, and continuously fits subsequently collected spectra to the calibration, allowing the operator to follow the mass loss of solvent from the dryer. The results indicate that solvent loss can be monitored and quantitated in real time using NIR for the optimization of drying times. These time-based mass loss values have also been used to calculate "dynamic" vapor density values for the solvents. The values calculated are in agreement with values determined from the ideal gas law and could prove valuable as tools to measure temperature or pressure indirectly.

Near-Real-Time Sismo-acoustic Submarine Station for offshore monitoring

NASA Astrophysics Data System (ADS)

D'Anna, Giuseppe; D'Alessandro, Antonino; Fertitta, Gioacchino; Fraticelli, Nicola; Calore, Daniele

2016-04-01

From the early 1980's, Italian seismicity is monitored by the National Seismic Network (NSN). The network has been considerably enhanced by INGV since 2005 by 24-bit digital stations equipped with broad-band sensors. The NSN is nowadays constituted by about 300 on-land seismic station able to detect and locate also small magnitude earthquake in the whole Italian peninsula. However, the lack of offshore seismic stations does not allow the accurate estimation of hypocentral and focal parameters of small magnitude earthquakes occurring in offshore areas. As in the Mediterranean area there is an intense offshore seismic activity, an extension of the seismic monitoring to the sea would be beneficial. There are two types of stations that could be used to extend the network towards the sea: the first type is connected to the coast though a cable, the second type is isolated (or stand alone) and works autonomously. Both solutions have serious limitations: the first one, for several technical and economic problems, linked to the indispensable transmission/alimentation cable, cannot be installed far from the coast; the second one, allows access to the recorded data, only after they are recovered from the seabed. It is clear that these technical solutions are not suitable for the real time monitoring of the offshore seismicity or for the realization of a tsunami warning system. For this reason, in early 2010, the OBSLab of Gibilmanna begins the design of a submarine station able to overcome the limitations of the two systems above. The station isbuilt under the project EMSO-MedIT. The two stations built have already been tested in dock and ready for installation. One of this station will be installed, in few time, in the southern Tyrrhenian Sea, near the epicentre of the Palermo 2002 main shock. The sea bottom station will be equipped with 2 very broadband 3C seismometers, a broad band hydrophone, a differential and an absolute pressure gauge. The station includes a submarine

Real-time on-board orbit determination with DORIS

NASA Technical Reports Server (NTRS)

Berthias, J.-P.; Jayles, C.; Pradines, D.

1993-01-01

A spaceborne orbit determination system is being developed by the French Space Agency (CNES) for the SPOT 4 satellite. It processes DORIS measurements to produce an orbit with an accuracy of about 50O meters rms. In order to evaluate the reliability of the software, it was combined with the MERCATOR man/machine interface and used to process the TOPEX/Poseidon DORIS data in near real time during the validation phase of the instrument, at JPL and at CNES. This paper gives an overview of the orbit determination system and presents the results of the TOPEX/Poseidon experiment.

High Resolution Near Real Time Image Processing and Support for MSSS Modernization

NASA Astrophysics Data System (ADS)

Duncan, R. B.; Sabol, C.; Borelli, K.; Spetka, S.; Addison, J.; Mallo, A.; Farnsworth, B.; Viloria, R.

2012-09-01

This paper describes image enhancement software applications engineering development work that has been performed in support of Maui Space Surveillance System (MSSS) Modernization. It also includes R&D and transition activity that has been performed over the past few years with the objective of providing increased space situational awareness (SSA) capabilities. This includes Air Force Research Laboratory (AFRL) use of an FY10 Dedicated High Performance Investment (DHPI) cluster award -- and our selection and planned use for an FY12 DHPI award. We provide an introduction to image processing of electro optical (EO) telescope sensors data; and a high resolution image enhancement and near real time processing and summary status overview. We then describe recent image enhancement applications development and support for MSSS Modernization, results to date, and end with a discussion of desired future development work and conclusions. Significant improvements to image processing enhancement have been realized over the past several years, including a key application that has realized more than a 10,000-times speedup compared to the original R&D code -- and a greater than 72-times speedup over the past few years. The latest version of this code maintains software efficiency for post-mission processing while providing optimization for image processing of data from a new EO sensor at MSSS. Additional work has also been performed to develop low latency, near real time processing of data that is collected by the ground-based sensor during overhead passes of space objects.

Testing the use of standardised indices and GRACE satellite data to estimate the European 2015 groundwater drought in near-real time

NASA Astrophysics Data System (ADS)

Van Loon, Anne F.; Kumar, Rohini; Mishra, Vimal

2017-04-01

In 2015, central and eastern Europe were affected by a severe drought. This event has recently been studied from meteorological and streamflow perspective, but no analysis of the groundwater situation has been performed. One of the reasons is that real-time groundwater level observations often are not available. In this study, we evaluate two alternative approaches to quantify the 2015 groundwater drought over two regions in southern Germany and eastern Netherlands. The first approach is based on spatially explicit relationships between meteorological conditions and historic groundwater level observations. The second approach uses the Gravity Recovery Climate Experiment (GRACE) terrestrial water storage (TWS) and groundwater anomalies derived from GRACE-TWS and (near-)surface storage simulations by the Global Land Data Assimilation System (GLDAS) models. We combined the monthly groundwater observations from 2040 wells to establish the spatially varying optimal accumulation period between the Standardised Groundwater Index (SGI) and the Standardized Precipitation Evapotranspiration Index (SPEI) at a 0.25° gridded scale. The resulting optimal accumulation periods range between 1 and more than 24 months, indicating strong spatial differences in groundwater response time to meteorological input over the region. Based on the estimated optimal accumulation periods and available meteorological time series, we reconstructed the groundwater anomalies up to 2015 and found that in Germany a uniform severe groundwater drought persisted for several months during this year, whereas the Netherlands appeared to have relatively high groundwater levels. The differences between this event and the 2003 European benchmark drought are striking. The 2003 groundwater drought was less uniformly pronounced, both in the Netherlands and Germany. This is because slowly responding wells (the ones with optimal accumulation periods of more than 12 months) still were above average from the wet

Near-real-time and scenario earthquake loss estimates for Mexico

NASA Astrophysics Data System (ADS)

Wyss, M.; Zuñiga, R.

2017-12-01

The large earthquakes of 8 September 2017, M8.1, and 19 September 2017, M7.1 have focused attention on the dangers of Mexican seismicity. The near-real-time alerts by QLARM estimated 10 to 300 fatalities and 0 to 200 fatalities, respectively. At the time of this submission the reported death tolls are 96 and 226, respectively. These alerts were issued within 96 and 57 minutes of the occurrence times. For the M8.1 earthquake the losses due to a line model could be calculated. The line with length L=110 km extended from the initial epicenter to the NE, where the USGS had reported aftershocks. On September 19, no aftershocks were available in near-real-time, so a point source had to be used for the quick calculation of likely casualties. In both cases, the casualties were at least an order of magnitude smaller than what they could have been because on 8 September the source was relatively far offshore and on 19 September the hypocenter was relatively deep. The largest historic earthquake in Mexico occurred on 28 March 1787 and likely had a rupture length of 450 km and M8.6. Based on this event, and after verifying our tool for Mexico, we estimated the order of magnitude of a disaster, given the current population, in a maximum credible earthquake along the Pacific coast. In the countryside along the coast we expect approximately 27,000 fatalities and 480,000 injured. In the special case of Mexico City the casualties in a worst possible earthquake along the Pacific plate boundary would likely be counted as five digit numbers. The large agglomerate of the capital with its lake bed soil attracts most attention. Nevertheless, one should pay attention to the fact that the poor, rural segment of society, living in buildings of weak resistance to shaking, are likely to sustain a mortality rate about 20% larger than the population in cities on average soil.

Resistive MHD Stability Analysis in Near Real-time

NASA Astrophysics Data System (ADS)

Glasser, Alexander; Kolemen, Egemen

2017-10-01

We discuss the feasibility of a near real-time calculation of the tokamak Δ' matrix, which summarizes MHD stability to resistive modes, such as tearing and interchange modes. As the operational phase of ITER approaches, solutions for active feedback tokamak stability control are needed. It has been previously demonstrated that an ideal MHD stability analysis is achievable on a sub- O (1 s) timescale, as is required to control phenomena comparable with the MHD-evolution timescale of ITER. In the present work, we broaden this result to incorporate the effects of resistive MHD modes. Such modes satisfy ideal MHD equations in regions outside narrow resistive layers that form at singular surfaces. We demonstrate that the use of asymptotic expansions at the singular surfaces, as well as the application of state transition matrices, enable a fast, parallelized solution to the singular outer layer boundary value problem, and thereby rapidly compute Δ'. Sponsored by US DOE under DE-SC0015878 and DE-FC02-04ER54698.

Nowcasting, forecasting and hindcasting Harvey and Irma inundation in near-real time using a continental 2D hydrodynamic model

NASA Astrophysics Data System (ADS)

Sampson, C. C.; Wing, O.; Quinn, N.; Smith, A.; Neal, J. C.; Schumann, G.; Bates, P.

2017-12-01

During an ongoing natural disaster data are required on: (1) the current situation (nowcast); (2) its likely immediate evolution (forecast); and (3) a consistent view post-event of what actually happened (hindcast or reanalysis). We describe methods used to achieve all three tasks for flood inundation during the Harvey and Irma events using a continental scale 2D hydrodynamic model (Wing et al., 2017). The model solves the local inertial form of the Shallow Water equations over a regular grid of 1 arcsecond ( 30m). Terrain data are taken from the USGS National Elevation Dataset with known flood defences represented using the U.S. Army Corps of Engineers National Levee Dataset. Channels are treated as sub-grid scale features using the HydroSHEDS global hydrography data set. The model is driven using river flows, rainfall and coastal water levels. It simulates river flooding in basins > 50 km2, and fluvial and coastal flooding everywhere. Previous wide area validation tests show this model to be capable of matching FEMA maps and USGS local models built with bespoke data with hit rates of 86% and 92% respectively (Wing et al., 2017). Boundary conditions were taken from NOAA QPS data to produce nowcast and forecast simulations in near real time, before updating with NOAA observations to produce the hindcast. During the event simulation results were supplied to major insurers and multi-nationals who used them to estimate their likely capital exposure and to mitigate flood damage to their infrastructure whilst the event was underway. Simulations were validated against modelled flood footprints computed by FEMA and USACE, and composite satellite imagery produced by the Dartmouth Flood Observatory. For the Harvey event, hit rates ranged from 60-84% against these data sources, but a lack of metadata meant it was difficult to perform like-for-like comparisons. The satellite data also appeared to miss known flooding in urban areas that was picked up in the models. Despite

Intercomparison of Near-Real-Time Biomass Burning Emissions Estimates Constrained by Satellite Fire Data

EPA Science Inventory

We compare biomass burning emissions estimates from four different techniques that use satellite based fire products to determine area burned over regional to global domains. Three of the techniques use active fire detections from polar-orbiting MODIS sensors and one uses detec...

Version 2 of the IASI NH3 neural network retrieval algorithm: near-real-time and reanalysed datasets

NASA Astrophysics Data System (ADS)

Van Damme, Martin; Whitburn, Simon; Clarisse, Lieven; Clerbaux, Cathy; Hurtmans, Daniel; Coheur, Pierre-François

2017-12-01

Recently, Whitburn et al.(2016) presented a neural-network-based algorithm for retrieving atmospheric ammonia (NH3) columns from Infrared Atmospheric Sounding Interferometer (IASI) satellite observations. In the past year, several improvements have been introduced, and the resulting new baseline version, Artificial Neural Network for IASI (ANNI)-NH3-v2.1, is documented here. One of the main changes to the algorithm is that separate neural networks were trained for land and sea observations, resulting in a better training performance for both groups. By reducing and transforming the input parameter space, performance is now also better for observations associated with favourable sounding conditions (i.e. enhanced thermal contrasts). Other changes relate to the introduction of a bias correction over land and sea and the treatment of the satellite zenith angle. In addition to these algorithmic changes, new recommendations for post-filtering the data and for averaging data in time or space are formulated. We also introduce a second dataset (ANNI-NH3-v2.1R-I) which relies on ERA-Interim ECMWF meteorological input data, along with surface temperature retrieved from a dedicated network, rather than the operationally provided Eumetsat IASI Level 2 (L2) data used for the standard near-real-time version. The need for such a dataset emerged after a series of sharp discontinuities were identified in the NH3 time series, which could be traced back to incremental changes in the IASI L2 algorithms for temperature and clouds. The reanalysed dataset is coherent in time and can therefore be used to study trends. Furthermore, both datasets agree reasonably well in the mean on recent data, after the date when the IASI meteorological L2 version 6 became operational (30 September 2014).

Archiving and Near Real Time Visualization of USGS Instantaneous Data

NASA Astrophysics Data System (ADS)

Zaslavsky, I.; Ryan, D.; Whitenack, T.; Valentine, D. W.; Rodriguez, M.

2009-12-01

The CUAHSI Hydrologic Information System project has been developing databases, services and online and desktop software applications supporting standards-based publication and access to large volumes of hydrologic data from US federal agencies and academic partners. In particular, the CUAHSI WaterML 1.x schema specification for exchanging hydrologic time series, earlier published as an OGC Discussion Paper (2007), has been adopted by the United States Geological Survey to provide web service access to USGS daily values and instantaneous data. The latter service, making available raw measurements of discharge, gage height and several other parameters for over 10,000 USGS real time measurement points, was announced by USGS, as an experimental WaterML-compliant service, at the end of July 2009. We demonstrate an online application that leverages the new service for nearly continuous harvesting of USGS real time data, and simultaneous visualization and analysis of the data streams. To make this possible, we integrate service components of the CUAHSI software stack with Open Source Data Turbine (OSDT) system, an NSF-supported software environment for robust and scalable assimilation of multimedia data streams (e.g. from sensors), and interfacing with a variety of viewers, databases, archival systems and client applications. Our application continuously queries USGS Instantaneous water data service (which provides access to 15-min measurements updated at USGS every 4 hours), and maps the results for each station-variable combination to a separate "channel", which is used by OSDT to quickly access and manipulate the time series. About 15,000 channels are used, which makes it by far the largest deployment of OSDT. Using RealTime Data Viewer, users can now select one or more stations of interest (e.g. from upstream or downstream from each other), and observe and annotate simultaneous dynamics in the respective discharge and gage height values, using fast forward or

Copernicus atmospheric service for stratospheric ozone: validation and intercomparison of four near real-time analyses, 2009-2012

NASA Astrophysics Data System (ADS)

Lefever, K.; van der A, R.; Baier, F.; Christophe, Y.; Errera, Q.; Eskes, H.; Flemming, J.; Inness, A.; Jones, L.; Lambert, J.-C.; Langerock, B.; Schultz, M. G.; Stein, O.; Wagner, A.; Chabrillat, S.

2014-05-01

This paper evaluates the performance of the stratospheric ozone analyses delivered in near real time by the MACC (Monitoring Atmospheric Composition and Climate) project during the 3 year period between September 2009 and September 2012. Ozone analyses produced by four different chemistry transport models and data assimilation techniques are examined: the ECMWF Integrated Forecast System (IFS) coupled to MOZART-3 (IFS-MOZART), the BIRA-IASB Belgian Assimilation System for Chemical ObsErvations (BASCOE), the DLR/RIU Synoptic Analysis of Chemical Constituents by Advanced Data Assimilation (SACADA), and the KNMI Data Assimilation Model based on Transport Model version 3 (TM3DAM). The assimilated satellite ozone retrievals differed for each system: SACADA and TM3DAM assimilated only total ozone observations, BASCOE assimilated profiles for ozone and some related species, while IFS-MOZART assimilated both types of ozone observations. The stratospheric ozone analyses are compared to independent ozone observations from ground-based instruments, ozone sondes and the ACE-FTS (Atmospheric Chemistry Experiment - Fourier Transform Spectrometer) satellite instrument. All analyses show total column values which are generally in good agreement with groundbased observations (biases <5%) and a realistic seasonal cycle. The only exceptions are found for BASCOE which systematically underestimates total ozone in the Tropics with about 7-10% at Chengkung (Taiwan, 23.1° N/121.365° E), resulting from the fact that BASCOE does not include any tropospheric processes, and for SACADA which overestimates total ozone in the absence of UV observations for the assimilation. Due to the large weight given to column observations in the assimilation procedure, IFS-MOZART is able to reproduce total column observations very well, but alternating positive and negative biases compared to ozonesonde and ACE-FTS satellite data are found in the vertical as well as an overestimation of 30 to 60% in the

Turbo-Satori: a neurofeedback and brain-computer interface toolbox for real-time functional near-infrared spectroscopy.

PubMed

Lührs, Michael; Goebel, Rainer

2017-10-01

Turbo-Satori is a neurofeedback and brain-computer interface (BCI) toolbox for real-time functional near-infrared spectroscopy (fNIRS). It incorporates multiple pipelines from real-time preprocessing and analysis to neurofeedback and BCI applications. The toolbox is designed with a focus in usability, enabling a fast setup and execution of real-time experiments. Turbo-Satori uses an incremental recursive least-squares procedure for real-time general linear model calculation and support vector machine classifiers for advanced BCI applications. It communicates directly with common NIRx fNIRS hardware and was tested extensively ensuring that the calculations can be performed in real time without a significant change in calculation times for all sampling intervals during ongoing experiments of up to 6 h of recording. Enabling immediate access to advanced processing features also allows the use of this toolbox for students and nonexperts in the field of fNIRS data acquisition and processing. Flexible network interfaces allow third party stimulus applications to access the processed data and calculated statistics in real time so that this information can be easily incorporated in neurofeedback or BCI presentations.

Coarse Resolution SAR Imagery to Support Flood Inundation Models in Near Real Time

NASA Astrophysics Data System (ADS)

Di Baldassarre, Giuliano; Schumann, Guy; Brandimarte, Luigia; Bates, Paul

2009-11-01

In recent years, the availability of new emerging data (e.g. remote sensing, intelligent wireless sensors, etc) has led to a sudden shift from a data-sparse to a data-rich environment for hydrological and hydraulic modelling. Furthermore, the increased socioeconomic relevance of river flood studies has motivated the development of complex methodologies for the simulation of the hydraulic behaviour of river systems. In this context, this study aims at assessing the capability of coarse resolution SAR (Synthetic Aperture Radar) imagery to support and quickly validate flood inundation models in near real time. A hydraulic model of a 98km reach of the River Po (Italy), previously calibrated on a high-magnitude flood event with extensive and high quality field data, is tested using a SAR flood image, acquired and processed in near real time, during the June 2008 low-magnitude event. Specifically, the image is an acquisition by the ENVISAT-ASAR sensor in wide swath mode and has been provided through ESA (European Space Agency) Fast Registration system at no cost 24 hours after the acquisition. The study shows that the SAR image enables validation and improvement of the model in a time shorter than the flood travel time. This increases the reliability of model predictions (e.g. water elevation and inundation width along the river reach) and, consequently, assists flood management authorities in undertaking the necessary prevention activities.

The Generation of Near-Real Time Data Products for MODIS

NASA Astrophysics Data System (ADS)

Teague, M.; Schmaltz, J. E.; Ilavajhala, S.; Ye, G.; Masuoka, E.; Murphy, K. J.; Michael, K.

2010-12-01

The GSFC Terrestrial Information Systems Branch (614.5) operate the Land and Atmospheres Near-real-time Capability for EOS (LANCE-MODIS) system. Other LANCE elements include -AIRS, -MLS, -OMI, and -AMSR-E. LANCE-MODIS incorporates the former Rapid Response system and will, in early 2011, include the Fire Information for Resource Management System (FIRMS). The purpose of LANCE is to provide applications users with a variety of products on a near-real time basis. The LANCE-MODIS data products include Level 1 (L1), L2 fire, snow, sea ice, cloud mask/profiles, aerosols, clouds, land surface reflectance, land surface temperature, and L2G and L3 gridded, daily, land surface reflectance products. Data are available either by ftp access (pull) or by subscription (push) and the L1 and L2 data products are available within an average of 2.5 hours of the observation time. The use of ancillary data products input to the standard science algorithms has been modified in order to obtain these latencies. The resulting products have been approved for applications use by the MODIS Science Team. The http://lance.nasa.gov site provides registration information and extensive information concerning the MODIS data products and imagery including a comparison between the LANCE-MODIS and the standard science-quality products generated by the MODAPS system. The LANCE-MODIS system includes a variety of tools that enable users to manipulate the data products including: parameter, band, and geographic subsetting, re-projection, mosaicing, and generation of data in the GeoTIFF format. In most instances the data resulting from use of these tools has a latency of less than 3 hours. Access to these tools is available through a Web Coverage Service. A Google Earth/Web Mapping Service is available to access image products. LANCE-MODIS supports a wide variety of applications users in civilian, military, and foreign agencies as well as universities and the private sector. Examples of applications are

A New Method for Near Real Time Precipitation Estimates Using a Derived Statistical Relationship between Precipitable Water Vapor and Precipitation

NASA Astrophysics Data System (ADS)

Roman, J.

2015-12-01

The IPCC 5th Assessment found that the predicted warming of 1oC would increase the risk of extreme events such as heat waves, droughts, and floods. Weather extremes, like floods, have shown the vulnerability and susceptibility society has to these extreme weather events, through impacts such as disruption of food production, water supply, health, and damage of infrastructure. This paper examines a new way of near-real time forecasting of precipitation. A 10-year statistical climatological relationship was derived between precipitable water vapor (PWV) and precipitation by using the NASA Atmospheric Infrared Sounder daily gridded PWV product and the NASA Tropical Rainfall Measuring Mission daily gridded precipitation total. Forecasting precipitation estimates in real time is dire for flood monitoring and disaster management. Near real time PWV observations from AIRS on Aqua are available through the Goddard Earth Sciences Data and Information Service Center. In addition, PWV observations are available through direct broadcast from the NASA Suomi-NPP ATMS/CrIS instrument, the operational follow on to AIRS. The derived climatological relationship can be applied to create precipitation estimates in near real time by utilizing the direct broadcasting capabilities currently available in the CONUS region. The application of this relationship will be characterized through case-studies by using near real-time NASA AIRS Science Team v6 PWV products and ground-based SuomiNet GPS to estimate the current precipitation potential; the max amount of precipitation that can occur based on the moisture availability. Furthermore, the potential contribution of using the direct broadcasting of the NUCAPS ATMS/CrIS PWV products will be demonstrated. The analysis will highlight the advantages of applying this relationship in near-real time for flash flood monitoring and risk management. Relevance to the NWS River Forecast Centers will be discussed.

Near real-time GRACE gravity field solutions for hydrological monitoring applications

NASA Astrophysics Data System (ADS)

Kvas, Andreas; Gouweleeuw, Ben; Mayer-Gürr, Torsten; Güntner, Andreas

2016-04-01

Within the EGSIEM (European Gravity Service for Improved Emergency Management) project, a demonstrator for a near real-time (NRT) gravity field service which provides daily GRACE gravity field solutions will be established. Compared to the official GRACE gravity products, these NRT solutions will increase the temporal resolution from one month to one day and reduce the latency from currently two months to five days. This fast availability allows the monitoring of total water storage variations and of hydrological extreme events as they occur, in contrast to a 'confirmation after occurrence' as is the situation today. The service will be jointly run by GFZ (German Research Centre for Geosciences) and Graz University of Technology, with each analysis center providing an independent solution. A Kalman filter framework, in which GRACE data is combined with prior information, serves as basis for the gravity field recovery in order to increase the redundancy of the gravity field estimates. The on-line nature of the NRT service necessitates a tailored smoothing algorithm as opposed to post-processing applications, where forward-backward smoothing can be applied. This contribution gives an overview on the near real-time processing chain and highlights differences between the computed NRT solutions and the standard GRACE products. We discuss the special characteristics of the Kalman filtered gravity field models as well as derived products and give an estimate of the expected error levels. Additionally, we show the added value of the NRT solutions through comparison of the first results of the pre-operational phase with in-situ data and monthly GRACE gravity field models.

Real time near-infrared Raman spectroscopy for the diagnosis of nasopharyngeal cancer.

PubMed

Ming, Lim Chwee; Gangodu, Nagaraja Rao; Loh, Thomas; Zheng, Wei; Wang, Jianfeng; Lin, Kan; Zhiwei, Huang

2017-07-25

Near-infrared (NIR) Raman spectroscopy has been investigated as a tool to differentiate nasopharyngeal cancer (NPC) from normal nasopharyngeal tissue in an ex-vivo setting. Recently, we have miniaturized the fiber-optic Raman probe to investigate its utility in real time in-vivo surveillance of NPC patients. A posterior probability model using partial linear square (PLS) mathematical technique was constructed to verify the sensitivity and specificity of Raman spectroscopy in diagnosing NPC from post-irradiated and normal tissue using a diagnostic algorithm from three significant latent variables. NIR-Raman signals of 135 sites were measured from 79 patients with either newly diagnosed NPC (N = 12), post irradiated nasopharynx (N = 37) and normal nasopharynx (N = 30). The mean Raman spectra peaks identified differences at several Raman peaks at 853 cm-1, 940 cm-1, 1078 cm-1, 1335 cm-1, 1554 cm-1, 2885 cm-1 and 2940 cm-1 in the three different nasopharyngeal conditions. The sensitivity and specificity of distinguishing Raman signatures among normal nasopharynx versus NPC and post-irradiated nasopharynx versus NPC were 91% and 95%; and 77% and 96% respectively. Real time near-infrared Raman spectroscopy has a high specificity in distinguishing malignant from normal nasopharyngeal tissue in vivo, and may be investigated as a novel non-invasive surveillance tool in patients with nasopharyngeal cancer.

Near real-time forecasting for cholera decision making in Haiti after Hurricane Matthew

PubMed Central

Camacho, Anton; Grandesso, Francesco; Cohuet, Sandra; Lemaitre, Joseph C.; Rinaldo, Andrea

2018-01-01

Computational models of cholera transmission can provide objective insights into the course of an ongoing epidemic and aid decision making on allocation of health care resources. However, models are typically designed, calibrated and interpreted post-hoc. Here, we report the efforts of a team from academia, field research and humanitarian organizations to model in near real-time the Haitian cholera outbreak after Hurricane Matthew in October 2016, to assess risk and to quantitatively estimate the efficacy of a then ongoing vaccination campaign. A rainfall-driven, spatially-explicit meta-community model of cholera transmission was coupled to a data assimilation scheme for computing short-term projections of the epidemic in near real-time. The model was used to forecast cholera incidence for the months after the passage of the hurricane (October-December 2016) and to predict the impact of a planned oral cholera vaccination campaign. Our first projection, from October 29 to December 31, predicted the highest incidence in the departments of Grande Anse and Sud, accounting for about 45% of the total cases in Haiti. The projection included a second peak in cholera incidence in early December largely driven by heavy rainfall forecasts, confirming the urgency for rapid intervention. A second projection (from November 12 to December 31) used updated rainfall forecasts to estimate that 835 cases would be averted by vaccinations in Grande Anse (90% Prediction Interval [PI] 476-1284) and 995 in Sud (90% PI 508-2043). The experience gained by this modeling effort shows that state-of-the-art computational modeling and data-assimilation methods can produce informative near real-time projections of cholera incidence. Collaboration among modelers and field epidemiologists is indispensable to gain fast access to field data and to translate model results into operational recommendations for emergency management during an outbreak. Future efforts should thus draw together multi

Near real-time forecasting for cholera decision making in Haiti after Hurricane Matthew.

PubMed

Pasetto, Damiano; Finger, Flavio; Camacho, Anton; Grandesso, Francesco; Cohuet, Sandra; Lemaitre, Joseph C; Azman, Andrew S; Luquero, Francisco J; Bertuzzo, Enrico; Rinaldo, Andrea

2018-05-01

Computational models of cholera transmission can provide objective insights into the course of an ongoing epidemic and aid decision making on allocation of health care resources. However, models are typically designed, calibrated and interpreted post-hoc. Here, we report the efforts of a team from academia, field research and humanitarian organizations to model in near real-time the Haitian cholera outbreak after Hurricane Matthew in October 2016, to assess risk and to quantitatively estimate the efficacy of a then ongoing vaccination campaign. A rainfall-driven, spatially-explicit meta-community model of cholera transmission was coupled to a data assimilation scheme for computing short-term projections of the epidemic in near real-time. The model was used to forecast cholera incidence for the months after the passage of the hurricane (October-December 2016) and to predict the impact of a planned oral cholera vaccination campaign. Our first projection, from October 29 to December 31, predicted the highest incidence in the departments of Grande Anse and Sud, accounting for about 45% of the total cases in Haiti. The projection included a second peak in cholera incidence in early December largely driven by heavy rainfall forecasts, confirming the urgency for rapid intervention. A second projection (from November 12 to December 31) used updated rainfall forecasts to estimate that 835 cases would be averted by vaccinations in Grande Anse (90% Prediction Interval [PI] 476-1284) and 995 in Sud (90% PI 508-2043). The experience gained by this modeling effort shows that state-of-the-art computational modeling and data-assimilation methods can produce informative near real-time projections of cholera incidence. Collaboration among modelers and field epidemiologists is indispensable to gain fast access to field data and to translate model results into operational recommendations for emergency management during an outbreak. Future efforts should thus draw together multi

A New Model for Real-Time Regional Vertical Total Electron Content and Differential Code Bias Estimation Using IGS Real-Time Service (IGS-RTS) Products

NASA Astrophysics Data System (ADS)

Abdelazeem, Mohamed; Çelik, Rahmi N.; El-Rabbany, Ahmed

2016-04-01

The international global navigation satellite system (GNSS) real-time service (IGS-RTS) products have been used extensively for real-time precise point positioning and ionosphere modeling applications. In this study, we develop a regional model for real-time vertical total electron content (RT-VTEC) and differential code bias (RT-DCB) estimation over Europe using the IGS-RTS satellite orbit and clock products. The developed model has a spatial and temporal resolution of 1°×1° and 15 minutes, respectively. GPS observations from a regional network consisting of 60 IGS and EUREF reference stations are processed in the zero-difference mode using the Bernese-5.2 software package in order to extract the geometry-free linear combination of the smoothed code observations. The spherical harmonic expansion function is used to model the VTEC, the receiver and the satellite DCBs. To validate the proposed model, the RT-VTEC values are computed and compared with the final IGS-global ionospheric map (IGS-GIM) counterparts in three successive days under high solar activity including one of an extreme geomagnetic activity. The real-time satellite DCBs are also estimated and compared with the IGS-GIM counterparts. Moreover, the real-time receiver DCB for six IGS stations are obtained and compared with the IGS-GIM counterparts. The examined stations are located in different latitudes with different receiver types. The findings reveal that the estimated RT-VTEC values show agreement with the IGS-GIM counterparts with root mean-square-errors (RMSEs) values less than 2 TEC units. In addition, RMSEs of both the satellites and receivers DCBs are less than 0.85 ns and 0.65 ns, respectively in comparison with the IGS-GIM.

Real-time near IR (1310 nm) imaging of CO2 laser ablation of enamel.

PubMed

Darling, Cynthia L; Fried, Daniel

2008-02-18

The high-transparency of dental enamel in the near-IR (NIR) can be exploited for real-time imaging of ablation crater formation during drilling with lasers. NIR images were acquired with an InGaAs focal plane array and a NIR zoom microscope during drilling incisions in human enamel samples with a lambda=9.3-microm CO(2) laser operating at repetition rates of 50-300-Hz with and without a water spray. Crack formation, dehydration and thermal changes were observed during ablation. These initial images demonstrate the potential of NIR imaging to monitor laser-ablation events in real-time to provide information about the mechanism of ablation and to evaluate the potential for peripheral thermal and mechanical damage.

Detecting spatial patterns of rivermouth processes using a geostatistical framework for near-real-time analysis

USGS Publications Warehouse

Xu, Wenzhao; Collingsworth, Paris D.; Bailey, Barbara; Carlson Mazur, Martha L.; Schaeffer, Jeff; Minsker, Barbara

2017-01-01

This paper proposes a geospatial analysis framework and software to interpret water-quality sampling data from towed undulating vehicles in near-real time. The framework includes data quality assurance and quality control processes, automated kriging interpolation along undulating paths, and local hotspot and cluster analyses. These methods are implemented in an interactive Web application developed using the Shiny package in the R programming environment to support near-real time analysis along with 2- and 3-D visualizations. The approach is demonstrated using historical sampling data from an undulating vehicle deployed at three rivermouth sites in Lake Michigan during 2011. The normalized root-mean-square error (NRMSE) of the interpolation averages approximately 10% in 3-fold cross validation. The results show that the framework can be used to track river plume dynamics and provide insights on mixing, which could be related to wind and seiche events.

Real Time Space Weather Support for Chandra X-ray Observatory Operations

NASA Technical Reports Server (NTRS)

O'Dell, Stephen L.; Miller, J. Scott; Minow, Joseph I.; Wolk, Scott J.; Aldcroft, Thomas L.; Spitzbart, Bradley D.; Swartz, Douglas A.

2012-01-01

NASA launched the Chandra X-ray Observatory in July 1999. Soon after first light in August 1999, however, degradation in the energy resolution and charge transfer efficiency of the Advanced CCD Imaging Spectrometer (ACIS) x-ray detectors was observed. The source of the degradation was quickly identified as radiation damage in the charge-transfer channel of the front-illuminated CCDs, by weakly penetrating ("soft", 100-500 keV) protons as Chandra passed through the Earth s radiation belts and ring currents. As soft protons were not considered a risk to spacecraft health before launch, the only on-board radiation monitoring system is the Electron, Proton, and Helium Instrument (EPHIN) which was included on Chandra with the primary purpose of monitoring energetic solar particle events. Further damage to the ACIS detector has been successfully mitigated through a combination of careful mission planning, autonomous on-board radiation protection, and manual intervention based upon real-time monitoring of the soft-proton environment. The AE-8 and AP-8 trapped radiation models and Chandra Radiation Models are used to schedule science operations in regions of low proton flux. EPHIN has been used as the primary autonomous in-situ radiation trigger; but, it is not sensitive to the soft protons that damage the front-illuminated CCDs. Monitoring of near-real-time space weather data sources provides critical information on the proton environment outside the Earth's magnetosphere due to solar proton events and other phenomena. The operations team uses data from the Geostationary Operational Environmental Satellites (GOES) to provide near-real-time monitoring of the proton environment; however, these data do not give a representative measure of the soft-proton (less than 1 MeV) flux in Chandra s high elliptical orbit. The only source of relevant measurements of sub-MeV protons is the Electron, Proton, and Alpha Monitor (EPAM) aboard the Advanced Composition Explorer (ACE

Real Time Space Weather Support for Chandra X-Ray Observatory Operations

NASA Technical Reports Server (NTRS)

O'Dell, Stephen L.; Minow, Joseph I.; Miller, J. Scott; Wolk, Scott J.; Aldcroft, Thomas L.; Spitzbart, Bradley D.; Swartz. Douglas A.

2012-01-01

NASA launched the Chandra X-ray Observatory in July 1999. Soon after first light in August 1999, however, degradation in the energy resolution and charge transfer efficiency of the Advanced CCD Imaging Spectrometer (ACIS) x-ray detectors was observed. The source of the degradation was quickly identified as radiation damage in the charge-transfer channel of the front-illuminated CCDs, by weakly penetrating ( soft , 100 500 keV) protons as Chandra passed through the Earth s radiation belts and ring currents. As soft protons were not considered a risk to spacecraft health before launch, the only on-board radiation monitoring system is the Electron, Proton, and Helium Instrument (EPHIN) which was included on Chandra with the primary purpose of monitoring energetic solar particle events. Further damage to the ACIS detector has been successfully mitigated through a combination of careful mission planning, autonomous on-board radiation protection, and manual intervention based upon real-time monitoring of the soft-proton environment. The AE-8 and AP-8 trapped radiation models and Chandra Radiation Models are used to schedule science operations in regions of low proton flux. EPHIN has been used as the primary autonomous in-situ radiation trigger; but, it is not sensitive to the soft protons that damage the front-illuminated CCDs. Monitoring of near-real-time space weather data sources provides critical information on the proton environment outside the Earth s magnetosphere due to solar proton events and other phenomena. The operations team uses data from the Geostationary Operational Environmental Satellites (GOES) to provide near-real-time monitoring of the proton environment; however, these data do not give a representative measure of the soft-proton (< 1 MeV) flux in Chandra s high elliptical orbit. The only source of relevant measurements of sub-MeV protons is the Electron, Proton, and Alpha Monitor (EPAM) aboard the Advanced Composition Explorer (ACE) satellite at L1

Real Time Space Weather Support for Chandra X-ray Observatory Operations

NASA Astrophysics Data System (ADS)

O'Dell, S. L.; Miller, S.; Minow, J. I.; Wolk, S.; Aldcroft, T. L.; Spitzbart, B. D.; Swartz, D. A.

2012-12-01

NASA launched the Chandra X-ray Observatory in July 1999. Soon after first light in August 1999, however, degradation in the energy resolution and charge transfer efficiency of the Advanced CCD Imaging Spectrometer (ACIS) x-ray detectors was observed. The source of the degradation was quickly identified as radiation damage in the charge-transfer channel of the front-illuminated CCDs, by weakly penetrating ("soft", 100-500 keV) protons as Chandra passed through the Earth's radiation belts and ring currents. As soft protons were not considered a risk to spacecraft health before launch, the only on-board radiation monitoring system is the Electron, Proton, and Helium Instrument (EPHIN) which was included on Chandra with the primary purpose of monitoring energetic solar particle events. Further damage to the ACIS detector has been successfully mitigated through a combination of careful mission planning, autonomous on-board radiation protection, and manual intervention based upon real-time monitoring of the soft-proton environment. The AE-8 and AP-8 trapped radiation models and Chandra Radiation Models are used to schedule science operations in regions of low proton flux. EPHIN has been used as the primary autonomous in-situ radiation trigger; but, it is not sensitive to the soft protons that damage the front-illuminated CCDs. Monitoring of near-real-time space weather data sources provides critical information on the proton environment outside the Earth's magnetosphere due to solar proton events and other phenomena. The operations team uses data from the Geostationary Operational Environmental Satellites (GOES) to provide near-real-time monitoring of the proton environment; however, these data do not give a representative measure of the soft-proton (< 1 MeV) flux in Chandra's high elliptical orbit. The only source of relevant measurements of sub-MeV protons is the Electron, Proton, and Alpha Monitor (EPAM) aboard the Advanced Composition Explorer (ACE) satellite at L1

GOES satellite time code dissemination

NASA Technical Reports Server (NTRS)

Beehler, R. E.

1983-01-01

The GOES time code system, the performance achieved to date, and some potential improvements in the future are discussed. The disseminated time code is originated from a triply redundant set of atomic standards, time code generators and related equipment maintained by NBS at NOAA's Wallops Island, VA satellite control facility. It is relayed by two GOES satellites located at 75 W and 135 W longitude on a continuous basis to users within North and South America (with overlapping coverage) and well out into the Atlantic and Pacific ocean areas. Downlink frequencies are near 468 MHz. The signals from both satellites are monitored and controlled from the NBS labs at Boulder, CO with additional monitoring input from geographically separated receivers in Washington, D.C. and Hawaii. Performance experience with the received time codes for periods ranging from several years to one day is discussed. Results are also presented for simultaneous, common-view reception by co-located receivers and by receivers separated by several thousand kilometers.

The Real-Time ObjectAgent Software Architecture for Distributed Satellite Systems

DTIC Science & Technology

2001-01-01

real - time operating system selection are also discussed. The fourth section describes a simple demonstration of real-time ObjectAgent. Finally, the...experience with C++. After selecting the programming language, it was necessary to select a target real - time operating system (RTOS) and embedded...ObjectAgent software to run on the OSE Real Time Operating System . In addition, she is responsible for the integration of ObjectAgent

Real-time near-IR imaging of laser-ablation crater evolution in dental enamel

NASA Astrophysics Data System (ADS)

Darling, Cynthia L.; Fried, Daniel

2007-02-01

We have shown that the enamel of the tooth is almost completely transparent near 1310-nm in the near-infrared and that near-IR (NIR) imaging has considerable potential for the optical discrimination of sound and demineralized tissue and for observing defects in the interior of the tooth. Lasers are now routinely used for many applications in dentistry including the ablation of dental caries. The objective of this study was to test the hypothesis that real-time NIR imaging can be used to monitor laser-ablation under varying conditions to assess peripheral thermal and transient-stress induced damage and to measure the rate and efficiency of ablation. Moreover, NIR imaging may have considerable potential for monitoring the removal of demineralized areas of the tooth during cavity preparations. Sound human tooth sections of approximately 3-mm thickness were irradiated by a CO II laser under varying conditions with and without a water spray. The incision area in the interior of each sample was imaged using a tungsten-halogen lamp with band-pass filter centered at 131--nm combined with an InGaAs focal plane array with a NIR zoom microscope in transillumination. Due to the high transparency of enamel at 1310-nm, laser-incisions were clearly visible to the dentin-enamel junction and crack formation, dehydration and irreversible thermal changes were observed during ablation. This study showed that there is great potential for near-IR imaging to monitor laser-ablation events in real-time to: assess safe laser operating parameters by imaging thermal and stress-induced damage, elaborate the mechanisms involved in ablation such as dehydration, and monitor the removal of demineralized enamel.

DORIS/Jason-2: Better than 10 cm on-board orbits available for Near-Real-Time Altimetry

NASA Astrophysics Data System (ADS)

Jayles, C.; Chauveau, J. P.; Rozo, F.

2010-12-01

DIODE (DORIS Immediate Orbit on-board Determination) is a real-time on-board orbit determination software, embedded in the DORIS receiver. The purpose of this paper is to focus on DIODE performances. After a description of the recent DORIS evolutions, we detail how compliance with specifications are verified during extensive ground tests before the launch, then during the in-flight commissioning phase just after the launch, and how well they are met in the routine phase and today. Future improvements are also discussed for Jason-2 as well as for the next missions. The complete DORIS ground validation using DORIS simulator and new DORIS test equipments has shown prior to the Jason-2 flight that every functional requirement was fulfilled, and also that better than 10 cm real-time DIODE orbits would be achieved on-board Jason-2. The first year of Jason-2 confirmed this, and after correction of a slowly evolving polar motion error at the end of the commissioning phase, the DIODE on-board orbits are indeed better than the 10 cm specification: in the beginning of the routine phase, the discrepancy was already 7.7 cm Root-Mean-Square (RMS) in the radial component as compared to the final Precise Orbit Ephemerides (POE) orbit. Since the first day of Jason-2 cycle 1, the real-time DIODE orbits have been delivered in the altimetry fast delivery products. Their accuracy and their 100% availability make them a key input to fairly precise Near-Real-Time Altimetry processing. Time-tagging is at the microsecond level. In parallel, a few corrections (quaternion problem) and improvements have been gathered in an enhanced version of DIODE, which is already implemented and validated. With this new version, a 5 cm radial accuracy is achieved during ground validation over more than Jason-2 first year (cycles 1-43, from July 12th, 2008 to September 11th, 2009). The Seattle Ocean Surface Topography Science Team Meeting (OSTST) has recommended an upload of this v4.02 version on

Evaluating the performance of real-time streamflow forecasting using multi-satellite precipitation products in the Upper Zambezi, Africa

NASA Astrophysics Data System (ADS)

Demaria, E. M.; Valdes, J. B.; Wi, S.; Serrat-Capdevila, A.; Valdés-Pineda, R.; Durcik, M.

2016-12-01

In under-instrumented basins around the world, accurate and timely forecasts of river streamflows have the potential of assisting water and natural resource managers in their management decisions. The Upper Zambezi river basin is the largest basin in southern Africa and its water resources are critical to sustainable economic growth and poverty reduction in eight riparian countries. We present a real-time streamflow forecast for the basin using a multi-model-multi-satellite approach that allows accounting for model and input uncertainties. Three distributed hydrologic models with different levels of complexity: VIC, HYMOD_DS, and HBV_DS are setup at a daily time step and a 0.25 degree spatial resolution for the basin. The hydrologic models are calibrated against daily observed streamflows at the Katima-Mulilo station using a Genetic Algorithm. Three real-time satellite products: Climate Prediction Center's morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Tropical Rainfall Measuring Mission (TRMM-3B42RT) are bias-corrected with daily CHIRPS estimates. Uncertainty bounds for predicted flows are estimated with the Inverse Variance Weighting method. Because concentration times in the basin range from a few days to more than a week, we include the use of precipitation forecasts from the Global Forecasting System (GFS) to predict daily streamflows in the basin with a 10-days lead time. The skill of GFS-predicted streamflows is evaluated and the usefulness of the forecasts for short term water allocations is presented.

Real-time precise orbit determination of LEO satellites using a single-frequency GPS receiver: Preliminary results of Chinese SJ-9A satellite

NASA Astrophysics Data System (ADS)

Sun, Xiucong; Han, Chao; Chen, Pei

2017-10-01

Spaceborne Global Positioning System (GPS) receivers are widely used for orbit determination of low-Earth-orbiting (LEO) satellites. With the improvement of measurement accuracy, single-frequency receivers are recently considered for low-cost small satellite missions. In this paper, a Schmidt-Kalman filter which processes single-frequency GPS measurements and broadcast ephemerides is proposed for real-time precise orbit determination of LEO satellites. The C/A code and L1 phase are linearly combined to eliminate the first-order ionospheric effects. Systematic errors due to ionospheric delay residual, group delay variation, phase center variation, and broadcast ephemeris errors, are lumped together into a noise term, which is modeled as a first-order Gauss-Markov process. In order to reduce computational complexity, the colored noise is considered rather than estimated in the orbit determination process. This ensures that the covariance matrix accurately represents the distribution of estimation errors without increasing the dimension of the state vector. The orbit determination algorithm is tested with actual flight data from the single-frequency GPS receiver onboard China's small satellite Shi Jian-9A (SJ-9A). Preliminary results using a 7-h data arc on October 25, 2012 show that the Schmidt-Kalman filter performs better than the standard Kalman filter in terms of accuracy.

Real-Time and Post-Processed Orbit Determination and Positioning

NASA Technical Reports Server (NTRS)

Harvey, Nathaniel E. (Inventor); Lu, Wenwen (Inventor); Miller, Mark A. (Inventor); Bar-Sever, Yoaz E. (Inventor); Miller, Kevin J. (Inventor); Romans, Larry J. (Inventor); Dorsey, Angela R. (Inventor); Sibthorpe, Anthony J. (Inventor); Weiss, Jan P. (Inventor); Bertiger, William I. (Inventor);

Real-Time and Post-Processed Orbit Determination and Positioning

NASA Technical Reports Server (NTRS)

Bar-Sever, Yoaz E. (Inventor); Romans, Larry J. (Inventor); Weiss, Jan P. (Inventor); Gross, Jason (Inventor); Harvey, Nathaniel E. (Inventor); Lu, Wenwen (Inventor); Dorsey, Angela R. (Inventor); Miller, Mark A. (Inventor); Sibthorpe, Anthony J. (Inventor); Bertiger, William I. (Inventor);

Using Open and Interoperable Ways to Publish and Access LANCE AIRS Near-Real Time Data

NASA Technical Reports Server (NTRS)

Zhao, Peisheng; Lynnes, Christopher; Vollmer, Bruce; Savtchenko, Andrey; Theobald, Michael; Yang, Wenli

2011-01-01

The Atmospheric Infrared Sounder (AIRS) Near-Real Time (NRT) data from the Land Atmosphere Near real-time Capability for EOS (LANCE) element at the Goddard Earth Sciences Data and Information Services Center (GES DISC) provides information on the global and regional atmospheric state, with very low temporal latency, to support climate research and improve weather forecasting. An open and interoperable platform is useful to facilitate access to, and integration of, LANCE AIRS NRT data. As Web services technology has matured in recent years, a new scalable Service-Oriented Architecture (SOA) is emerging as the basic platform for distributed computing and large networks of interoperable applications. Following the provide-register-discover-consume SOA paradigm, this presentation discusses how to use open-source geospatial software components to build Web services for publishing and accessing AIRS NRT data, explore the metadata relevant to registering and discovering data and services in the catalogue systems, and implement a Web portal to facilitate users' consumption of the data and services.

Fit to predict? Eco-informatics for predicting the catchability of a pelagic fish in near real time.

PubMed

Scales, Kylie L; Hazen, Elliott L; Maxwell, Sara M; Dewar, Heidi; Kohin, Suzanne; Jacox, Michael G; Edwards, Christopher A; Briscoe, Dana K; Crowder, Larry B; Lewison, Rebecca L; Bograd, Steven J

2017-12-01

The ocean is a dynamic environment inhabited by a diverse array of highly migratory species, many of which are under direct exploitation in targeted fisheries. The timescales of variability in the marine realm coupled with the extreme mobility of ocean-wandering species such as tuna and billfish complicates fisheries management. Developing eco-informatics solutions that allow for near real-time prediction of the distributions of highly mobile marine species is an important step towards the maturation of dynamic ocean management and ecological forecasting. Using 25 yr (1990-2014) of NOAA fisheries' observer data from the California drift gillnet fishery, we model relative probability of occurrence (presence-absence) and catchability (total catch per gillnet set) of broadbill swordfish Xiphias gladius in the California Current System. Using freely available environmental data sets and open source software, we explore the physical drivers of regional swordfish distribution. Comparing models built upon remotely sensed data sets with those built upon a data-assimilative configuration of the Regional Ocean Modelling System (ROMS), we explore trade-offs in model construction, and address how physical data can affect predictive performance and operational capacity. Swordfish catchability was found to be highest in deeper waters (>1,500 m) with surface temperatures in the 14-20°C range, isothermal layer depth (ILD) of 20-40 m, positive sea surface height (SSH) anomalies, and during the new moon (<20% lunar illumination). We observed a greater influence of mesoscale variability (SSH, wind speed, isothermal layer depth, eddy kinetic energy) in driving swordfish catchability (total catch) than was evident in predicting the relative probability of presence (presence-absence), confirming the utility of generating spatiotemporally dynamic predictions. Data-assimilative ROMS circumvent the limitations of satellite remote sensing in providing physical data fields for species

Derivation of a New Smoke Emissions Inventory using Remote Sensing, and Its Implications for Near Real-Time Air Quality Applications

NASA Technical Reports Server (NTRS)

Ellison, Luke; Ichoku, Charles

2012-01-01

A new emissions inventory of particulate matter (PM) is being derived mainly from remote sensing data using fire radiative power (FRP) and aerosol optical depth (AOD) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, as well as wind data from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis dataset, which spans the satellite era. This product is generated using a coefficient of emission, C(sub e), that has been produced on a 1x1 degree global grid such that, when it is multiplied with satellite measurements of FRP or its time-integrated equivalent fire radiative energy (FRE) retrieved over a given area and time period, the corresponding PM emissions are estimated. This methodology of using C(sub e) to derive PM emissions is relatively new and advantageous for near real-time air quality applications compared to current methods based on post-fire burned area that may not provide emissions in a timely manner. Furthermore, by using FRP to characterize a fire s output, it will represent better accuracy than the use of raw fire pixel counts, since fires in individual pixels can differ in size and strength by orders of magnitude, resulting in similar differences in emission rates. Here we will show examples of this effect and how this new emission inventory can properly account for the differing emission rates from fires of varying strengths. We also describe the characteristics of the new emissions inventory, and propose the process chain of incorporating it into models for air quality applications.

Real-time Kp predictions from ACE real time solar wind

NASA Astrophysics Data System (ADS)

Detman, Thomas; Joselyn, Joann

1999-06-01

The Advanced Composition Explorer (ACE) spacecraft provides nearly continuous monitoring of solar wind plasma, magnetic fields, and energetic particles from the Sun-Earth L1 Lagrange point upstream of Earth in the solar wind. The Space Environment Center (SEC) in Boulder receives ACE telemetry from a group of international network of tracking stations. One-minute, and 1-hour averages of solar wind speed, density, temperature, and magnetic field components are posted on SEC's World Wide Web page within 3 to 5 minutes after they are measured. The ACE Real Time Solar Wind (RTSW) can be used to provide real-time warnings and short term forecasts of geomagnetic storms based on the (traditional) Kp index. Here, we use historical data to evaluate the performance of the first real-time Kp prediction algorithm to become operational.

Near real-time estimation of the seismic source parameters in a compressed domain

NASA Astrophysics Data System (ADS)

Rodriguez, Ismael A. Vera

Seismic events can be characterized by its origin time, location and moment tensor. Fast estimations of these source parameters are important in areas of geophysics like earthquake seismology, and the monitoring of seismic activity produced by volcanoes, mining operations and hydraulic injections in geothermal and oil and gas reservoirs. Most available monitoring systems estimate the source parameters in a sequential procedure: first determining origin time and location (e.g., epicentre, hypocentre or centroid of the stress glut density), and then using this information to initialize the evaluation of the moment tensor. A more efficient estimation of the source parameters requires a concurrent evaluation of the three variables. The main objective of the present thesis is to address the simultaneous estimation of origin time, location and moment tensor of seismic events. The proposed method displays the benefits of being: 1) automatic, 2) continuous and, depending on the scale of application, 3) of providing results in real-time or near real-time. The inversion algorithm is based on theoretical results from sparse representation theory and compressive sensing. The feasibility of implementation is determined through the analysis of synthetic and real data examples. The numerical experiments focus on the microseismic monitoring of hydraulic fractures in oil and gas wells, however, an example using real earthquake data is also presented for validation. The thesis is complemented with a resolvability analysis of the moment tensor. The analysis targets common monitoring geometries employed in hydraulic fracturing in oil wells. Additionally, it is presented an application of sparse representation theory for the denoising of one-component and three-component microseismicity records, and an algorithm for improved automatic time-picking using non-linear inversion constraints.

Automating Flood Hazard Mapping Methods for Near Real-time Storm Surge Inundation and Vulnerability Assessment

NASA Astrophysics Data System (ADS)

Weigel, A. M.; Griffin, R.; Gallagher, D.

2015-12-01

Storm surge has enough destructive power to damage buildings and infrastructure, erode beaches, and threaten human life across large geographic areas, hence posing the greatest threat of all the hurricane hazards. The United States Gulf of Mexico has proven vulnerable to hurricanes as it has been hit by some of the most destructive hurricanes on record. With projected rises in sea level and increases in hurricane activity, there is a need to better understand the associated risks for disaster mitigation, preparedness, and response. GIS has become a critical tool in enhancing disaster planning, risk assessment, and emergency response by communicating spatial information through a multi-layer approach. However, there is a need for a near real-time method of identifying areas with a high risk of being impacted by storm surge. Research was conducted alongside Baron, a private industry weather enterprise, to facilitate automated modeling and visualization of storm surge inundation and vulnerability on a near real-time basis. This research successfully automated current flood hazard mapping techniques using a GIS framework written in a Python programming environment, and displayed resulting data through an Application Program Interface (API). Data used for this methodology included high resolution topography, NOAA Probabilistic Surge model outputs parsed from Rich Site Summary (RSS) feeds, and the NOAA Census tract level Social Vulnerability Index (SoVI). The development process required extensive data processing and management to provide high resolution visualizations of potential flooding and population vulnerability in a timely manner. The accuracy of the developed methodology was assessed using Hurricane Isaac as a case study, which through a USGS and NOAA partnership, contained ample data for statistical analysis. This research successfully created a fully automated, near real-time method for mapping high resolution storm surge inundation and vulnerability for the

State of the Oceans: A Satellite Data Processing System for Visualizing Near Real-Time Imagery on Google Earth

NASA Astrophysics Data System (ADS)

Thompson, C. K.; Bingham, A. W.; Hall, J. R.; Alarcon, C.; Plesea, L.; Henderson, M. L.; Levoe, S.

2011-12-01

The State of the Oceans (SOTO) web tool was developed at NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC) at the Jet Propulsion Laboratory (JPL) as an interactive means for users to visually explore and assess ocean-based geophysical parameters extracted from the latest archived data products. The SOTO system consists of four extensible modules, a data polling tool, a preparation and imaging package, image server software, and the graphical user interface. Together, these components support multi-resolution visualization of swath (Level 2) and gridded Level 3/4) data products as either raster- or vector- based KML layers on Google Earth. These layers are automatically updated periodically throughout the day. Current parameters available include sea surface temperature, chlorophyll concentration, ocean winds, sea surface height anomaly, and sea surface temperature anomaly. SOTO also supports mash-ups, allowing KML feeds from other sources to be overlaid directly onto Google Earth such as hurricane tracks and buoy data. A version of the SOTO software has also been installed at Goddard Space Flight Center (GSFC) to support the Land Atmosphere Near real-time Capability for EOS (LANCE). The State of the Earth (SOTE) has similar functionality to SOTO but supports different data sets, among them the MODIS 250m data product.

Generation of real-time global ionospheric map based on the global GNSS stations with only a sparse distribution

NASA Astrophysics Data System (ADS)

Li, Zishen; Wang, Ningbo; Li, Min; Zhou, Kai; Yuan, Yunbin; Yuan, Hong

2017-04-01

The Earth's ionosphere is part of the atmosphere stretching from an altitude of about 50 km to more than 1000 km. When the Global Navigation Satellite System (GNSS) signal emitted from a satellite travels through the ionosphere before reaches a receiver on or near the Earth surface, the GNSS signal is significantly delayed by the ionosphere and this delay bas been considered as one of the major errors in the GNSS measurement. The real-time global ionospheric map calculated from the real-time data obtained by global stations is an essential method for mitigating the ionospheric delay for real-time positioning. The generation of an accurate global ionospheric map generally depends on the global stations with dense distribution; however, the number of global stations that can produce the real-time data is very limited at present, which results that the generation of global ionospheric map with a high accuracy is very different when only using the current stations with real-time data. In view of this, a new approach is proposed for calculating the real-time global ionospheric map only based on the current stations with real-time data. This new approach is developed on the basis of the post-processing and the one-day predicted global ionospheric map from our research group. The performance of the proposed approach is tested by the current global stations with the real-time data and the test results are also compared with the IGS-released final global ionospheric map products.

Near-Real-Time Analysis of Publicly Communicated Disaster Response Information

NASA Astrophysics Data System (ADS)

Girard, Trevor

2015-04-01

During a disaster situation the public will need to make critical actions regarding what to do, where to go, how to get there, and so on. The more informed the public is, the better actions they are able to make, resulting in reduced disaster impacts. The criteria for what information to provide the public needs to change depending on the specific needs of the disaster affected population. The method of dissemination also needs to match the communication channels that the public typically uses in disaster situations. This research project investigates the dynamic information needs of disaster affected populations and how information leads to actions. The purpose of the research project is to identify key indicators for measuring how well informed the public is during disasters. The indicators are limited to those which can be observed as communication is happening (i.e., in near-real-time). By doing so, the indicators can be analyzed as disaster situations unfold, deficiencies can be identified, and recommendations can be made to potentially improve communication while the response is still underway. The end goal of the research is to improve the ability of communicators to inform disaster affected communities. A classification scheme has been developed to categorize the information provided to the public during disasters. Under each category is a set of typical questions that the information should answer. These questions are the result of a best observed practice review of the information available during 11 disasters. For example, under the category 'Life Saving Response', the questions which should be answered are who is doing what (Evacuation, SAR), where and when, and the amount of the affected communities' needs being covered by these actions. Review of what questions remain unanswered acts as the first indicator, referred to as an 'Information Gap Analysis'. Comparative analysis of the information within categories, between categories, and between similar

(abstract) Using GPS Measurements to Identify Global Ionospheric Storms in Near Real-Time

NASA Technical Reports Server (NTRS)

Ho, C. M.; Mannucci, A. J.; Lindqwister, U. J.; Rao, A. M.; Pi, X.; Wilson, B. D.; Yuan, D. N.; Reyes, M.

1996-01-01

The solar wind interacts with the Earth's magnetosphere, eventually dissipating energy into the ionosphere and atmosphere. As a terminator, the ionosphere responds to magnetic storms, which is very important in understanding the energy coupling process between the Sun and the Earth and in forecasting space weather changes.The worldwide GPS network, for the first time, makes near real-time global ionospheric TEC measurements a possibility. Based on these measurements, global ionospheric TEC maps are generated with time resolution of from 5 minutes to hours. Using these maps, we can analyze the global evolution of ionospheric storms on temporal and spatial scales, which have been dificult to study before. We find that for certain types of storms (such as TID-driven), it is possible to identify them near onset and issue warning signals during the early stages. Main attention has been paid on northern hemispheric winter storms. Their common features and physical mechanisms are being investigated.

Real Time Precise Point Positioning: Preliminary Results for the Brazilian Region

NASA Astrophysics Data System (ADS)

Marques, Haroldo; Monico, João.; Hirokazu Shimabukuro, Milton; Aquino, Marcio

2010-05-01

GNSS positioning can be carried out in relative or absolute approach. In the last years, more attention has been driven to the real time precise point positioning (PPP). To achieve centimeter accuracy with this method in real time it is necessary to have available the satellites precise coordinates as well as satellites clocks corrections. The coordinates can be used from the predicted IGU ephemeris, but the satellites clocks must be estimated in a real time. It can be made from a GNSS network as can be seen from EUREF Permanent Network. The infra-structure to realize the PPP in real time is being available in Brazil through the Brazilian Continuous Monitoring Network (RBMC) together with the Sao Paulo State GNSS network which are transmitting GNSS data using NTRIP (Networked Transport of RTCM via Internet Protocol) caster. Based on this information it was proposed a PhD thesis in the Univ. Estadual Paulista (UNESP) aiming to investigate and develop the methodology to estimate the satellites clocks and realize PPP in real time. Then, software is being developed to process GNSS data in the real time PPP mode. A preliminary version of the software was called PPP_RT and is able to process GNSS code and phase data using precise ephemeris and satellites clocks. The PPP processing can be accomplished considering the absolute satellite antenna Phase Center Variation (PCV), Ocean Tide Loading (OTL), Earth Body Tide, among others. The first order ionospheric effects can be eliminated or minimized by ion-free combination or parameterized in the receiver-satellite direction using a stochastic process, e.g. random walk or white noise. In the case of ionosphere estimation, a pseudo-observable is introduced in the mathematical model for each satellite and the initial value can be computed from Klobuchar model or from Global Ionospheric Map (GIM). The adjustment is realized in the recursive mode and the DIA (Detection Identification and Adaptation) is used for quality control. In

A Human Sensor Network Framework in Support of Near Real Time Situational Geophysical Modeling

NASA Astrophysics Data System (ADS)

Aulov, O.; Price, A.; Smith, J. A.; Halem, M.

2013-12-01

The area of Disaster Management is well established among Federal Agencies such as FEMA, EPA, NOAA and NASA. These agencies have well formulated frameworks for response and mitigation based on near real time satellite and conventional observing networks for assimilation into geophysical models. Forecasts from these models are used to communicate with emergency responders and the general public. More recently, agencies have started using social media to broadcast warnings and alerts to potentially affected communities. In this presentation, we demonstrate the added benefits of mining and assimilating the vast amounts of social media data available from heterogeneous hand held devices and social networks into established operational geophysical modeling frameworks as they apply to the five cornerstones of disaster management - Prevention, Mitigation, Preparedness, Response and Recovery. Often, in situations of extreme events, social media provide the earliest notification of adverse extreme events. However, various forms of social media data also can provide useful geolocated and time stamped in situ observations, complementary to directly sensed conventional observations. We use the concept of a Human Sensor Network where one views social media users as carrying field deployed "sensors" whose posts are the remotely "sensed instrument measurements.' These measurements can act as 'station data' providing the resolution and coverage needed for extreme event specific modeling and validation. Here, we explore the use of social media through the use of a Human Sensor Network (HSN) approach as another data input source for assimilation into geophysical models. Employing the HSN paradigm can provide useful feedback in near real-time, but presents software challenges for rapid access, quality filtering and transforming massive social media data into formats consistent with the operational models. As a use case scenario, we demonstrate the value of HSN for disaster management

Interagency Collaborators Develop and Implement ForWarn, a National, Near Real Time Forest Monitoring Tool

NASA Technical Reports Server (NTRS)

Underwood, Lauren

2013-01-01

ForWarn is a satellite-based forest monitoring tool that is being used to detect and monitor disturbances to forest conditions and forest health. It has been developed through the synergistic efforts, capabilities and contributions of four federal agencies, including the US Forest Service Eastern Forest and Western Wildland Environmental Threat Assessment Centers, NASA Stennis Space Center (SSC), Department of Energy's (DOE) Oak Ridge National Laboratory (ORNL) and US Geological Survey Earth (USGS) Earth Research Observation System (EROS), as well as university partners, including the University of North Carolina Asheville's National Environmental Modeling and Analysis Center (NEMAC). This multi-organizational partnership is key in producing a unique, path finding near real-time forest monitoring system that is now used by many federal, state and local government end-users. Such a system could not have been produced so effectively by any of these groups on their own. The forests of the United States provide many societal values and benefits, ranging from ecological, economic, cultural, to recreational. Therefore, providing a reliable and dependable forest and other wildland monitoring system is important to ensure the continued health, productivity, sustainability and prudent use of our Nation's forests and forest resources. ForWarn does this by producing current health indicator maps of our nation's forests based on satellite data from NASA's MODIS (Moderate Resolution Imaging Spectroradiometer) sensors. Such a capability can provide noteworthy value, cost savings and significant impact at state and local government levels because at those levels of government, once disturbances are evident and cause negative impacts, a response must be carried out. The observations that a monitoring system like ForWarn provide, can also contribute to a much broader-scale understanding of vegetation disturbances.

Robust Real-Time Wide-Area Differential GPS Navigation

NASA Technical Reports Server (NTRS)

Yunck, Thomas P. (Inventor); Bertiger, William I. (Inventor); Lichten, Stephen M. (Inventor); Mannucci, Anthony J. (Inventor); Muellerschoen, Ronald J. (Inventor); Wu, Sien-Chong (Inventor)

1998-01-01

The present invention provides a method and a device for providing superior differential GPS positioning data. The system includes a group of GPS receiving ground stations covering a wide area of the Earth's surface. Unlike other differential GPS systems wherein the known position of each ground station is used to geometrically compute an ephemeris for each GPS satellite. the present system utilizes real-time computation of satellite orbits based on GPS data received from fixed ground stations through a Kalman-type filter/smoother whose output adjusts a real-time orbital model. ne orbital model produces and outputs orbital corrections allowing satellite ephemerides to be known with considerable greater accuracy than from die GPS system broadcasts. The modeled orbits are propagated ahead in time and differenced with actual pseudorange data to compute clock offsets at rapid intervals to compensate for SA clock dither. The orbital and dock calculations are based on dual frequency GPS data which allow computation of estimated signal delay at each ionospheric point. These delay data are used in real-time to construct and update an ionospheric shell map of total electron content which is output as part of the orbital correction data. thereby allowing single frequency users to estimate ionospheric delay with an accuracy approaching that of dual frequency users.

Near Real-time Scientific Data Analysis and Visualization with the ArcGIS Platform

NASA Astrophysics Data System (ADS)

Shrestha, S. R.; Viswambharan, V.; Doshi, A.

2017-12-01

Scientific multidimensional data are generated from a variety of sources and platforms. These datasets are mostly produced by earth observation and/or modeling systems. Agencies like NASA, NOAA, USGS, and ESA produce large volumes of near real-time observation, forecast, and historical data that drives fundamental research and its applications in larger aspects of humanity from basic decision making to disaster response. A common big data challenge for organizations working with multidimensional scientific data and imagery collections is the time and resources required to manage and process such large volumes and varieties of data. The challenge of adopting data driven real-time visualization and analysis, as well as the need to share these large datasets, workflows, and information products to wider and more diverse communities, brings an opportunity to use the ArcGIS platform to handle such demand. In recent years, a significant effort has put in expanding the capabilities of ArcGIS to support multidimensional scientific data across the platform. New capabilities in ArcGIS to support scientific data management, processing, and analysis as well as creating information products from large volumes of data using the image server technology are becoming widely used in earth science and across other domains. We will discuss and share the challenges associated with big data by the geospatial science community and how we have addressed these challenges in the ArcGIS platform. We will share few use cases, such as NOAA High Resolution Refresh Radar (HRRR) data, that demonstrate how we access large collections of near real-time data (that are stored on-premise or on the cloud), disseminate them dynamically, process and analyze them on-the-fly, and serve them to a variety of geospatial applications. We will also share how on-the-fly processing using raster functions capabilities, can be extended to create persisted data and information products using raster analytics

Controlled Substance Reconciliation Accuracy Improvement Using Near Real-Time Drug Transaction Capture from Automated Dispensing Cabinets.

PubMed

Epstein, Richard H; Dexter, Franklin; Gratch, David M; Perino, Michael; Magrann, Jerry

2016-06-01

Accurate accounting of controlled drug transactions by inpatient hospital pharmacies is a requirement in the United States under the Controlled Substances Act. At many hospitals, manual distribution of controlled substances from pharmacies is being replaced by automated dispensing cabinets (ADCs) at the point of care. Despite the promise of improved accountability, a high prevalence (15%) of controlled substance discrepancies between ADC records and anesthesia information management systems (AIMS) has been published, with a similar incidence (15.8%; 95% confidence interval [CI], 15.3% to 16.2%) noted at our institution. Most reconciliation errors are clerical. In this study, we describe a method to capture drug transactions in near real-time from our ADCs, compare them with documentation in our AIMS, and evaluate subsequent improvement in reconciliation accuracy. ADC-controlled substance transactions are transmitted to a hospital interface server, parsed, reformatted, and sent to a software script written in Perl. The script extracts the data and writes them to a SQL Server database. Concurrently, controlled drug totals for each patient having care are documented in the AIMS and compared with the balance of the ADC transactions (i.e., vending, transferring, wasting, and returning drug). Every minute, a reconciliation report is available to anesthesia providers over the hospital Intranet from AIMS workstations. The report lists all patients, the current provider, the balance of ADC transactions, the totals from the AIMS, the difference, and whether the case is still ongoing or had concluded. Accuracy and latency of the ADC transaction capture process were assessed via simulation and by comparison with pharmacy database records, maintained by the vendor on a central server located remotely from the hospital network. For assessment of reconciliation accuracy over time, data were collected from our AIMS from January 2012 to June 2013 (Baseline), July 2013 to April 2014

SMOS near-real-time soil moisture product: processor overview and first validation results

NASA Astrophysics Data System (ADS)

Rodríguez-Fernández, Nemesio J.; Muñoz Sabater, Joaquin; Richaume, Philippe; de Rosnay, Patricia; Kerr, Yann H.; Albergel, Clement; Drusch, Matthias; Mecklenburg, Susanne

2017-10-01

Measurements of the surface soil moisture (SM) content are important for a wide range of applications. Among them, operational hydrology and numerical weather prediction, for instance, need SM information in near-real-time (NRT), typically not later than 3 h after sensing. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite is the first mission specifically designed to measure SM from space. The ESA Level 2 SM retrieval algorithm is based on a detailed geophysical modelling and cannot provide SM in NRT. This paper presents the new ESA SMOS NRT SM product. It uses a neural network (NN) to provide SM in NRT. The NN inputs are SMOS brightness temperatures for horizontal and vertical polarizations and incidence angles from 30 to 45°. In addition, the NN uses surface soil temperature from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS). The NN was trained on SMOS Level 2 (L2) SM. The swath of the NRT SM retrieval is somewhat narrower (˜ 915 km) than that of the L2 SM dataset (˜ 1150 km), which implies a slightly lower revisit time. The new SMOS NRT SM product was compared to the SMOS Level 2 SM product. The NRT SM data show a standard deviation of the difference with respect to the L2 data of < 0.05 m3 m-3 in most of the Earth and a Pearson correlation coefficient higher than 0.7 in large regions of the globe. The NRT SM dataset does not show a global bias with respect to the L2 dataset but can show local biases of up to 0.05 m3 m-3 in absolute value. The two SMOS SM products were evaluated against in situ measurements of SM from more than 120 sites of the SCAN (Soil Climate Analysis Network) and the USCRN (US Climate Reference Network) networks in North America. The NRT dataset obtains similar but slightly better results than the L2 data. In summary, the NN SMOS NRT SM product exhibits performances similar to those of the Level 2 SM product but it has the advantage of

Real-time data and communications services of NCAR's Earth Observing Laboratory

NASA Astrophysics Data System (ADS)

Webster, C. J.; Daniels, M.; Stossmeister, G.

2011-12-01

Near real-time information is critical for mission management of atmospheric observing systems. Advances in satellite communications and Internet distribution have allowed the Earth Observing Laboratory (EOL) of NCAR to provide data, information and imagery to the scientists during evolving weather situations. Real-time data are necessary for updating interactive displays that show products from forecast models and many disparate observation systems (e.g. satellite, soundings, surface radars and aircraft in-situ observations). At the same time, network-based collaborative tools such as chat and web conferencing facilitate interactive participation between remote groups of scientists, engineers, operations centers and the observing platforms. In the recent PREDICT deployment of the NSF/NCAR GV research aircraft, dropsondes were released from the aircraft at 45,000 ft over a 1000 km x 1000 km area to give profiles of pressure, temperature, humidity and wind below the aircraft. Real-time data from the sondes was collected by the aircraft and relayed by satcom into the Global Telecommunications System (GTS) and assimilated into forecast models. The model forecast results were then fed back into ground-based and airborne displays (along with a multitude of observations) for enhanced decision-making and mission guidance. This environment of streaming data in real-time also allows more experts to look at data and compare it with other measurements. One particular benefit is that it alerts instrument operators on the ground and in the air to instrument problems, which can then be addressed very rapidly. The resulting communications and collaborations infrastructure results in unprecedented improvements to our data quality and rapid targeting of mission resources to important weather events. Using several examples, this presentation will provide an overview of current tools and processes in use at EOL, and future needs will be discussed.

Easing the Discovery of NASA and International Near-Real-Time Data Using the Global Change Master Directory

NASA Technical Reports Server (NTRS)

Olsen, Lola; Morahan, Michael; Aleman, Alicia; Cepero, Laurel; Stevens, Tyler; Ritz, Scott; Holland, Monica

2011-01-01

The Global Change Master Directory (GCMD) provides an extensive directory of descriptive and spatial information about data sets and data-related services, which are relevant to Earth science research. The directory's data discovery components include controlled keywords, free-text searches, and map/date searches. The GCMD portal for NASA's Land Atmosphere Near-real-time Capability for EOS (LANCE) data products leverages these discovery features by providing users a direct route to NASA's Near-Real-Time (NRT) collections. This portal offers direct access to collection entries by instrument name, informing users of the availability of data. After a relevant collection entry is found through the GCMD's search components, the "Get Data" URL within the entry directs the user to the desired data. http://gcmd.nasa.gov/r/p/gcmd_lance_nrt.

Using Citizen Science and Crowdsourcing via Aurorasaurus as a Near Real Time Data Source for Space Weather Applications

NASA Astrophysics Data System (ADS)

MacDonald, E.; Heavner, M.; Hall, M.; Tapia, A.; Lalone, N.; Clayon, J.; Case, N.

2014-12-01

Aurorasaurus is on the cutting edge of space science, citizen science, and computer science simultaneously with the broad goals to develop a real-time citizen science network, educate the general public about the northern lights, and revolutionize real-time space weather nowcasting of the aurora for the public. We are currently in the first solar maximum with social media, which enables the technological roots to connect users, citizen scientists, and professionals around a shared global, rare interest. We will introduce the project which has been in a prototype mode since 2012 and recently relaunched with a new mobile and web presence and active campaigns. We will showcase the interdisciplinary advancements which include a more educated public, disaster warning system applications, and improved real-time ground truth data including photographs and observations of the Northern Lights. We will preview new data which validates the proof of concept for significant improvements in real-time space weather nowcasting. Our aim is to provide better real-time notifications of the visibility of the Northern Lights to the interested public via the combination of noisy crowd-sourced ground truth with noisy satellite-based predictions. The latter data are available now but are often delivered with significant jargon and uncertainty, thus reliable, timely interpretation of such forecasts by the public are problematic. The former data show real-time characteristic significant rises (in tweets for instance) that correlate with other non-real-time indices of auroral activity (like the Kp index). We will discuss the source of 'noise' in each data source. Using citizen science as a platform to provide a basis for deeper understanding is one goal; secondly we want to improve understanding of and appreciation for the dynamics and beauty of the Northern Lights by the public and scientists alike.

A Test Run of the EGSIEM Near Real-Time Service Based on GRACE Mission Data

NASA Astrophysics Data System (ADS)

Kvas, A.; Gruber, C.; Gouweleeuw, B.; Guntner, A.; Mayer-Gürr, T.; Flechtner, F. M.

2017-12-01

To enable the use of GRACE and GRACE-FO data for rapid monitoring applications, the EGSIEM (European Gravity Service for Improved Emergency Management) project, funded by the Horizon 2020 Framework Program for Research and Innovation of the European Union, has implemented a demonstrator for a near real-time (NRT) gravity field service. The goal of this service is to provide daily gravity field solutions with a maximum latency of five days. For this purpose, two independent approaches were developed at the German Research Centre for Geosciences (GFZ) and Graz University of Technology (TUG). Based on these daily gravity field solutions, statistical flood and drought indicators are derived by the EGSIEM Hydrological Service, developed at GFZ. The NRT products are subsequently provided to the Center for Satellite based Crisis Information (ZKI) at the German Aerospace Center as well as the Global Flood Awareness System (GloFAS) at the Joint Research Center of the European Commission. In the first part of this contribution, the performance of the service based on a statistical analysis of historical flood events during the GRACE period is evaluated. Then, results from the six month long operational test run of the service which started on April 1st 2017 are presented and a comparison between historical and operational gravity products and flood indicators is made.

Real-time Visualization and Quantification of Retrograde Cardioplegia Delivery using Near Infrared Fluorescent Imaging

PubMed Central

Rangaraj, Aravind T.; Ghanta, Ravi K.; Umakanthan, Ramanan; Soltesz, Edward G.; Laurence, Rita G.; Fox, John; Cohn, Lawrence H.; Bolman, R. M.; Frangioni, John V.; Chen, Frederick Y.

2009-01-01

Background and Aim of the Study Homogeneous delivery of cardioplegia is essential for myocardial protection during cardiac surgery. Presently, there exist no established methods to quantitatively assess cardioplegia distribution intraoperatively and determine when retrograde cardioplegia is required. In this study, we evaluate the feasibility of near infrared (NIR) imaging for real-time visualization of cardioplegia distribution in a porcine model. Methods A portable, intraoperative, real-time NIR imaging system was utilized. NIR fluorescent cardioplegia solution was developed by incorporating indocyanine green (ICG) into crystalloid cardioplegia solution. Real-time NIR imaging was performed while the fluorescent cardioplegia solution was infused via the retrograde route in 5 ex-vivo normal porcine hearts and in 5 ex-vivo porcine hearts status post left anterior descending (LAD) coronary artery ligation. Horizontal cross-sections of the hearts were obtained at proximal, middle, and distal LAD levels. Videodensitometry was performed to quantify distribution of fluorophore content. Results The progressive distribution of cardioplegia was clearly visualized with NIR imaging. Complete visualization of retrograde distribution occurred within 4 minutes of infusion. Videodensitometry revealed that retrograde cardioplegia primarily distributed to the left ventricle and anterior septum. In hearts with LAD ligation, antegrade cardioplegia did not distribute to the anterior left ventricle. This deficiency was compensated for with retrograde cardioplegia supplementation. Conclusions Incorporation of ICG into cardioplegia allows real-time visualization of cardioplegia delivery via NIR imaging. This technology may prove useful in guiding intraoperative decisions pertaining to when retrograde cardioplegia is mandated. PMID:19016995

Real-time visualization and quantification of retrograde cardioplegia delivery using near infrared fluorescent imaging.

PubMed

Rangaraj, Aravind T; Ghanta, Ravi K; Umakanthan, Ramanan; Soltesz, Edward G; Laurence, Rita G; Fox, John; Cohn, Lawrence H; Bolman, R M; Frangioni, John V; Chen, Frederick Y

2008-01-01

Homogeneous delivery of cardioplegia is essential for myocardial protection during cardiac surgery. Presently, there exist no established methods to quantitatively assess cardioplegia distribution intraoperatively and determine when retrograde cardioplegia is required. In this study, we evaluate the feasibility of near infrared (NIR) imaging for real-time visualization of cardioplegia distribution in a porcine model. A portable, intraoperative, real-time NIR imaging system was utilized. NIR fluorescent cardioplegia solution was developed by incorporating indocyanine green (ICG) into crystalloid cardioplegia solution. Real-time NIR imaging was performed while the fluorescent cardioplegia solution was infused via the retrograde route in five ex vivo normal porcine hearts and in five ex vivo porcine hearts status post left anterior descending (LAD) coronary artery ligation. Horizontal cross-sections of the hearts were obtained at proximal, middle, and distal LAD levels. Videodensitometry was performed to quantify distribution of fluorophore content. The progressive distribution of cardioplegia was clearly visualized with NIR imaging. Complete visualization of retrograde distribution occurred within 4 minutes of infusion. Videodensitometry revealed retrograde cardioplegia, primarily distributed to the left ventricle (LV) and anterior septum. In hearts with LAD ligation, antegrade cardioplegia did not distribute to the anterior LV. This deficiency was compensated for with retrograde cardioplegia supplementation. Incorporation of ICG into cardioplegia allows real-time visualization of cardioplegia delivery via NIR imaging. This technology may prove useful in guiding intraoperative decisions pertaining to when retrograde cardioplegia is mandated.

A virtual remote sensing observation network for continuous, near-real-time monitoring of atmospheric instability

NASA Astrophysics Data System (ADS)

Toporov, Maria; Löhnert, Ulrich; Potthast, Roland; Cimini, Domenico; De Angelis, Francesco

2017-04-01

Short-term forecasts of current high-resolution numerical weather prediction models still have large deficits in forecasting the exact temporal and spatial location of severe, locally influenced weather such as summer-time convective storms or cool season lifted stratus or ground fog. Often, the thermodynamic instability - especially in the boundary layer - plays an essential role in the evolution of weather events. While the thermodynamic state of the atmosphere is well measured close to the surface (i.e. 2 m) by in-situ sensors and in the upper troposphere by satellite sounders, the planetary boundary layer remains a largely under-sampled region of the atmosphere where only sporadic information from radiosondes or aircraft observations is available. The major objective of the presented DWD-funded project ARON (Extramural Research Programme) is to overcome this observational gap and to design an optimized network of ground based microwave radiometers (MWR) and compact Differential Absorption Lidars (DIAL) for a continuous, near-real-time monitoring of temperature and humidity in the atmospheric boundary layer in order to monitor thermodynamic (in)stability. Previous studies showed, that microwave profilers are well suited for continuously monitoring the temporal development of atmospheric stability (i.e. Cimini et al., 2015) before the initiation of deep convection, especially in the atmospheric boundary layer. However, the vertical resolution of microwave temperature profiles is best in the lowest kilometer above the surface, decreasing rapidly with increasing height. In addition, humidity profile retrievals typically cannot be resolved with more than two degrees of freedom for signal, resulting in a rather poor vertical resolution throughout the troposphere. Typical stability indices used to assess the potential of convection rely on temperature and humidity values not only in the region of the boundary layer but also in the layers above. Therefore, satellite

Real-time Monitoring of 2017 Hurricanes and Typhoons with Lightning

NASA Astrophysics Data System (ADS)

Solorzano, N. N.; Thomas, J. N.; Bracy, C.; Holzworth, R. H., II

2017-12-01

The 2017 Atlantic season had the highest number of major hurricanes since 2005. To tackle the demand of real-time tropical cyclone (TC) monitoring, our group has developed a unique "storm-following" satellite and ground-based lightning product known as WWLLN-TC (World Wide Lightning Location Network - Tropical Cyclones; http://wwlln.net/storms/). In the present study, we explore this tool and other datasets, combining lightning and microwave data to quantify areas of intense convection in 2017 TCs Harvey, Hato, Irma, Maria, Nate, Ophelia and others. For each storm, the temporal distribution of discharges outside and within the inner core is compared to the changes in TC intensity. The intensification processes, monitored in near real-time by WWLLN-TC, are quantified in terms of pressure and/or wind speed changes. A peak in lightning activity is often observed in the inner core of TCs before and during rapid weakening, such as in Hurricanes Irma and Maria and Typhoon Hato. The microwave frequencies investigated include the 37 to 183 GHz channels of the satellite sensors DMSP/SSMIS and GPM/GMI. We reconstruct brightness temperatures from lightning data, providing more detailed pictures of the evolution of TCs at moments when satellite passes are missing or incomplete. This study also compares lightning activity in the inner core with convective and environmental parameters. Examples of environmental parameters discussed are sea surface temperature, wind shear, and sea surface height anomalies. We conclude by considering possible implications of WWLLN-TC on forecasts of rapid intensity change and rainfall.

Mapping the Recent US Hurricanes Triggered Flood Events in Near Real Time

NASA Astrophysics Data System (ADS)

Shen, X.; Lazin, R.; Anagnostou, E. N.; Wanik, D. W.; Brakenridge, G. R.

2017-12-01

Synthetic Aperture Radar (SAR) observations is the only reliable remote sensing data source to map flood inundation during severe weather events. Unfortunately, since state-of-art data processing algorithms cannot meet the automation and quality standard of a near-real-time (NRT) system, quality controlled inundation mapping by SAR currently depends heavily on manual processing, which limits our capability to quickly issue flood inundation maps at global scale. Specifically, most SAR-based inundation mapping algorithms are not fully automated, while those that are automated exhibit severe over- and/or under-detection errors that limit their potential. These detection errors are primarily caused by the strong overlap among the SAR backscattering probability density functions (PDF) of different land cover types. In this study, we tested a newly developed NRT SAR-based inundation mapping system, named Radar Produced Inundation Diary (RAPID), using Sentinel-1 dual polarized SAR data over recent flood events caused by Hurricanes Harvey, Irma, and Maria (2017). The system consists of 1) self-optimized multi-threshold classification, 2) over-detection removal using land-cover information and change detection, 3) under-detection compensation, and 4) machine-learning based correction. Algorithm details are introduced in another poster, H53J-1603. Good agreements were obtained by comparing the result from RAPID with visual interpretation of SAR images and manual processing from Dartmouth Flood Observatory (DFO) (See Figure 1). Specifically, the over- and under-detections that is typically noted in automated methods is significantly reduced to negligible levels. This performance indicates that RAPID can address the automation and accuracy issues of current state-of-art algorithms and has the potential to apply operationally on a number of satellite SAR missions, such as SWOT, ALOS, Sentinel etc. RAPID data can support many applications such as rapid assessment of damage

Real-time Identification and Control of Satellite Signal Impairments Solution and Application of the Stratonovich Equation Part 1. Theoretical Development

NASA Technical Reports Server (NTRS)

Manning, Robert M.

2016-01-01

As satellite communications systems become both more complex and reliant with respect to their operating environment, it has become imperative to be able to identify, during real-time operation, the onset of one or more impairments to the quality of overall communications system integrity. One of the most important aspects to monitor of a satellite link operating within the Earth's atmosphere is the signal fading due to the occurrence of rain and/or phase scintillations. This, of course, must be done in the presence of the associated measurement uncertainty or potentially faulty measurement equipment such as in the Advanced Communication Technology Satellite (ACTS) experiment. In the present work, an approach originally suggested in 1991, and apparently still considered iconoclastic, will be significantly developed and applied to the satellite communications link on which the deleterious composite signal fade is the result of one or many component fade mechanisms. Through the measurement (with the attendant uncertainty or 'error' in the measurement) of such a composite fading satellite signal, it is desired to extract the level of each of the individual fading mechanisms so they can be appropriately mitigated before they impact the overall performance of the communications network. Rather than employing simple-minded deterministic filtering to the real-time fading, the present approach is built around all the models and/or descriptions used to describe the individual fade components, including their dynamic evolution. The latter is usually given by a first-order Langevin equation. This circumstance allows the description of the associated temporal transition probability densities of each of the component processes. By using this description, along with the real-time measurements of the composite fade (along with the measurement errors), one can obtain statistical estimates of the levels of each of the component fading mechanisms as well as their predicted values

Algorithm for removing scalp signals from functional near-infrared spectroscopy signals in real time using multidistance optodes.

PubMed

Kiguchi, Masashi; Funane, Tsukasa

2014-11-01

A real-time algorithm for removing scalp-blood signals from functional near-infrared spectroscopy signals is proposed. Scalp and deep signals have different dependencies on the source-detector distance. These signals were separated using this characteristic. The algorithm was validated through an experiment using a dynamic phantom in which shallow and deep absorptions were independently changed. The algorithm for measurement of oxygenated and deoxygenated hemoglobins using two wavelengths was explicitly obtained. This algorithm is potentially useful for real-time systems, e.g., brain-computer interfaces and neuro-feedback systems.

An investigation into the performance of real-time GPS+GLONASS Precise Point Positioning (PPP) in New Zealand

NASA Astrophysics Data System (ADS)

Harima, Ken; Choy, Suelynn; Rizos, Chris; Kogure, Satoshi

2017-09-01

This paper presents an investigation into the performance of real-time Global Navigation Satellite Systems (GNSS) Precise Point Positioning (PPP) in New Zealand. The motivation of the research is to evaluate the feasibility of using PPP technique and a satellite based augmentation system such as the Japanese Quasi-Zenith Satellite System (QZSS) to deliver a real-time precise positioning solution in support of a nation-wide high accuracy GNSS positioning coverage in New Zealand. Two IGS real-time correction streams are evaluated alongside with the PPP correction messages transmitted by the QZSS satellite known as MDC1. MDC1 corrections stream is generated by Japan Aerospace Exploration Agency (JAXA) using the Multi-GNSS Advanced Demonstration tool for Orbit and Clock Analysis (MADOCA) software and are currently transmitted in test mode by the QZSS satellite. The IGS real-time streams are the CLK9B real-time corrections stream generated by the French Centre National D'études Spatiales (CNES) using the PPP-Wizard software, and the CLK81 real-time corrections stream produced by GMV using their MagicGNSS software. GNSS data is collected from six New Zealand CORS stations operated by Land Information New Zealand (LINZ) over a one-week period in 2015. GPS and GLONASS measurements are processed in a real-time PPP mode using the satellite orbit and clock corrections from the real-time streams. The results show that positioning accuracies of 6 cm in horizontal component and 15 cm in vertical component can be achieved in real-time PPP. The real-time GPS+GLONASS PPP solution required 30 minutes to converge to within 10 cm horizontal positioning accuracy.

genRE: A Method to Extend Gridded Precipitation Climatology Data Sets in Near Real-Time for Hydrological Forecasting Purposes

NASA Astrophysics Data System (ADS)

van Osnabrugge, B.; Weerts, A. H.; Uijlenhoet, R.

2017-11-01

To enable operational flood forecasting and drought monitoring, reliable and consistent methods for precipitation interpolation are needed. Such methods need to deal with the deficiencies of sparse operational real-time data compared to quality-controlled offline data sources used in historical analyses. In particular, often only a fraction of the measurement network reports in near real-time. For this purpose, we present an interpolation method, generalized REGNIE (genRE), which makes use of climatological monthly background grids derived from existing gridded precipitation climatology data sets. We show how genRE can be used to mimic and extend climatological precipitation data sets in near real-time using (sparse) real-time measurement networks in the Rhine basin upstream of the Netherlands (approximately 160,000 km2). In the process, we create a 1.2 × 1.2 km transnational gridded hourly precipitation data set for the Rhine basin. Precipitation gauge data are collected, spatially interpolated for the period 1996-2015 with genRE and inverse-distance squared weighting (IDW), and then evaluated on the yearly and daily time scale against the HYRAS and EOBS climatological data sets. Hourly fields are compared qualitatively with RADOLAN radar-based precipitation estimates. Two sources of uncertainty are evaluated: station density and the impact of different background grids (HYRAS versus EOBS). The results show that the genRE method successfully mimics climatological precipitation data sets (HYRAS/EOBS) over daily, monthly, and yearly time frames. We conclude that genRE is a good interpolation method of choice for real-time operational use. genRE has the largest added value over IDW for cases with a low real-time station density and a high-resolution background grid.

The surface drifter program for real time and off-line validation of ocean forecasts and reanalyses

NASA Astrophysics Data System (ADS)

Hernandez, Fabrice; Regnier, Charly; Drévillon, Marie

2017-04-01

As part of the Global Ocean Observing System, the Global Drifter Program (GDP) is comprised of an array of about 1250 drifting buoys spread over the global ocean, that provide operational, near-real time surface velocity, sea surface temperature (SST) and sea level pressure observations. This information is used mainly used for numerical weather forecasting, research, and in-situ calibration/verification of satellite observations. Since 2013 the drifting buoy SST measurements are used for near real time assessment of global forecasting systems from Canada, France, UK, USA, Australia in the frame of the GODAE OceanView Intercomparison and Validation Task. For most of these operational systems, these data are not used for assimilation, and offer an independent observation assessment. This approach mimics the validation performed for SST satellite products. More recently, validation procedures have been proposed in order to assess the surface dynamics of Mercator Océan global and regional forecast and reanalyses. Velocities deduced from drifter trajectories are used in two ways. First, the Eulerian approach where buoy and ocean model velocity values are compared at the position of drifters. Then, from discrepancies, statistics are computed and provide an evaluation of the ocean model's surface dynamics reliability. Second, the Lagrangian approach, where drifting trajectories are simulated at each location of the real drifter trajectory using the ocean model velocity fields. Then, on daily basis, real and simulated drifter trajectories are compared by analyzing the spread after one day, two days etc…. The cumulated statistics on specific geographical boxes are evaluated in term of dispersion properties of the "real ocean" as captured by drifters, and those properties in the ocean model. This approach allows to better evaluate forecasting score for surface dispersion applications, like Search and Rescue, oil spill forecast, drift of other objects or contaminant

Comparison of tropospheric NO2 from in situ aircraft measurements with near-real-time and standard product data from OMI

NASA Astrophysics Data System (ADS)

Bucsela, E. J.; Perring, A. E.; Cohen, R. C.; Boersma, K. F.; Celarier, E. A.; Gleason, J. F.; Wenig, M. O.; Bertram, T. H.; Wooldridge, P. J.; Dirksen, R.; Veefkind, J. P.

2008-08-01

We present an analysis of in situ NO2 measurements from aircraft experiments between summer 2004 and spring 2006. The data are from the INTEX-A, PAVE, and INTEX-B campaigns and constitute the most comprehensive set of tropospheric NO2 profiles to date. Profile shapes from INTEX-A and PAVE are found to be qualitatively similar to annual mean profiles from the GEOS-Chem model. Using profiles from the INTEX-B campaign, we perform error-weighted linear regressions to compare the Ozone Monitoring Instrument (OMI) tropospheric NO2 columns from the near-real-time product (NRT) and standard product (SP) with the integrated in situ columns. Results indicate that the OMI SP algorithm yields NO2 amounts lower than the in situ columns by a factor of 0.86 (±0.2) and that NO2 amounts from the NRT algorithm are higher than the in situ data by a factor of 1.68 (±0.6). The correlation between the satellite and in situ data is good (r = 0.83) for both algorithms. Using averaging kernels, the influence of the algorithm's a priori profiles on the satellite retrieval is explored. Results imply that air mass factors from the a priori profiles are on average slightly larger (˜10%) than those from the measured profiles, but the differences are not significant.

Efficient near-real-time monitoring of 3D surface displacements in complex landslide scenarios

NASA Astrophysics Data System (ADS)

Allasia, Paolo; Manconi, Andrea; Giordan, Daniele; Baldo, Marco; Lollino, Giorgio

2013-04-01

Ground deformation measurements play a key role in monitoring activities of landslides. A wide spectrum of instruments and methods is nowadays available, going from in-situ to remote sensing approaches. In emergency scenarios, monitoring is often based on automated instruments capable to achieve accurate measurements, possibly with a very high temporal resolution, in order to achieve the best information about the evolution of the landslide in near-real-time, aiming at early warning purposes. However, the available tools for a rapid and efficient exploitation, understanding and interpretation of the retrieved measurements is still a challenge. This issue is particularly relevant in contexts where monitoring is fundamental to support early warning systems aimed at ensuring safety to people and/or infrastructures. Furthermore, in many cases the results obtained might be of difficult reading and divulgation, especially when people of different backgrounds are involved (e.g. scientists, authorities, civil protection operators, decision makers, etc.). In this work, we extend the concept of automatic and near real time from the acquisition of measurements to the data processing and divulgation, in order to achieve an efficient monitoring of surface displacements in landslide scenarios. We developed an algorithm that allows to go automatically and in near-real-time from the acquisition of 3D displacements on a landslide area to the efficient divulgation of the monitoring results via WEB. This set of straightforward procedures is called ADVICE (ADVanced dIsplaCement monitoring system for Early warning), and has been already successfully applied in several emergency scenarios. The algorithm includes: (i) data acquisition and transfer protocols; (ii) data collection, filtering, and validation; (iii) data analysis and restitution through a set of dedicated software, such as ©3DA [1]; (iv) recognition of displacement/velocity threshold and early warning (v) short term

Real-time new satellite product demonstration from microwave sensors and GOES-16 at NRL TC web

NASA Astrophysics Data System (ADS)

Cossuth, J.; Richardson, K.; Surratt, M. L.; Bankert, R.

2017-12-01

The Naval Research Laboratory (NRL) Tropical Cyclone (TC) satellite webpage (https://www.nrlmry.navy.mil/TC.html) provides demonstration analyses of storm imagery to benefit operational TC forecast centers around the world. With the availability of new spectral information provided by GOES-16 satellite data and recent research into improved visualization methods of microwave data, experimental imagery was operationally tested to visualize the structural changes of TCs during the 2017 hurricane season. This presentation provides an introduction into these innovative satellite analysis methods, NRL's next generation satellite analysis system (the Geolocated Information Processing System, GeoIPSTM), and demonstration the added value of additional spectral frequencies when monitoring storms in near-realtime.

SHARPs - A Near-Real-Time Space Weather Data Product from HMI

NASA Astrophysics Data System (ADS)

Bobra, M.; Turmon, M.; Baldner, C.; Sun, X.; Hoeksema, J. T.

2012-12-01

A data product from the Helioseismic and Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO), called Space-weather HMI Active Region Patches (SHARPs), is now available through the SDO Joint Science Operations Center (JSOC) and the Virtual Solar Observatory. SHARPs are magnetically active regions identified on the solar disk and tracked automatically in time. SHARP data are processed within a few hours of the observation time. The SHARP data series contains active region-sized disambiguated vector magnetic field data in both Lambert Cylindrical Equal-Area and CCD coordinates on a 12 minute cadence. The series also provides simultaneous HMI maps of the line-of-sight magnetic field, continuum intensity, and velocity on the same ~0.5 arc-second pixel grid. In addition, the SHARP data series provides space weather quantities computed on the inverted, disambiguated, and remapped data. The values for each tracked region are computed and updated in near real time. We present space weather results for several X-class flares; furthermore, we compare said space weather quantities with helioseismic quantities calculated using ring-diagram analysis.

PAU/GNSS-R: Implementation, Performance and First Results of a Real-Time Delay-Doppler Map Reflectometer Using Global Navigation Satellite System Signals

PubMed Central

Marchan-Hernandez, Juan Fernando; Camps, Adriano; Rodriguez-Alvarez, Nereida; Bosch-Lluis, Xavier; Ramos-Perez, Isaac; Valencia, Enric

2008-01-01

Signals from Global Navigation Satellite Systems (GNSS) were originally conceived for position and speed determination, but they can be used as signals of opportunity as well. The reflection process over a given surface modifies the properties of the scattered signal, and therefore, by processing the reflected signal, relevant geophysical data regarding the surface under study (land, sea, ice…) can be retrieved. In essence, a GNSS-R receiver is a multi-channel GNSS receiver that computes the received power from a given satellite at a number of different delay and Doppler bins of the incoming signal. The first approaches to build such a receiver consisted of sampling and storing the scattered signal for later post-processing. However, a real-time approach to the problem is desirable to obtain immediately useful geophysical variables and reduce the amount of data. The use of FPGA technology makes this possible, while at the same time the system can be easily reconfigured. The signal tracking and processing constraints made necessary to fully design several new blocks. The uniqueness of the implemented system described in this work is the capability to compute in real-time Delay-Doppler maps (DDMs) either for four simultaneous satellites or just one, but with a larger number of bins. The first tests have been conducted from a cliff over the sea and demonstrate the successful performance of the instrument to compute DDMs in real-time from the measured reflected GNSS/R signals. The processing of these measurements shall yield quantitative relationships between the sea state (mainly driven by the surface wind and the swell) and the overall DDM shape. The ultimate goal is to use the DDM shape to correct the sea state influence on the L-band brightness temperature to improve the retrieval of the sea surface salinity (SSS). PMID:27879862

Automatic Near-Real-Time Image Processing Chain for Very High Resolution Optical Satellite Data

NASA Astrophysics Data System (ADS)

Ostir, K.; Cotar, K.; Marsetic, A.; Pehani, P.; Perse, M.; Zaksek, K.; Zaletelj, J.; Rodic, T.

2015-04-01

In response to the increasing need for automatic and fast satellite image processing SPACE-SI has developed and implemented a fully automatic image processing chain STORM that performs all processing steps from sensor-corrected optical images (level 1) to web-delivered map-ready images and products without operator's intervention. Initial development was tailored to high resolution RapidEye images, and all crucial and most challenging parts of the planned full processing chain were developed: module for automatic image orthorectification based on a physical sensor model and supported by the algorithm for automatic detection of ground control points (GCPs); atmospheric correction module, topographic corrections module that combines physical approach with Minnaert method and utilizing anisotropic illumination model; and modules for high level products generation. Various parts of the chain were implemented also for WorldView-2, THEOS, Pleiades, SPOT 6, Landsat 5-8, and PROBA-V. Support of full-frame sensor currently in development by SPACE-SI is in plan. The proposed paper focuses on the adaptation of the STORM processing chain to very high resolution multispectral images. The development concentrated on the sub-module for automatic detection of GCPs. The initially implemented two-step algorithm that worked only with rasterized vector roads and delivered GCPs with sub-pixel accuracy for the RapidEye images, was improved with the introduction of a third step: super-fine positioning of each GCP based on a reference raster chip. The added step exploits the high spatial resolution of the reference raster to improve the final matching results and to achieve pixel accuracy also on very high resolution optical satellite data.

Application of satellite-based rainfall and medium range meteorological forecast in real-time flood forecasting in the Mahanadi River basin

NASA Astrophysics Data System (ADS)

Nanda, Trushnamayee; Beria, Harsh; Sahoo, Bhabagrahi; Chatterjee, Chandranath

2016-04-01

Increasing frequency of hydrologic extremes in a warming climate call for the development of reliable flood forecasting systems. The unavailability of meteorological parameters in real-time, especially in the developing parts of the world, makes it a challenging task to accurately predict flood, even at short lead times. The satellite-based Tropical Rainfall Measuring Mission (TRMM) provides an alternative to the real-time precipitation data scarcity. Moreover, rainfall forecasts by the numerical weather prediction models such as the medium term forecasts issued by the European Center for Medium range Weather Forecasts (ECMWF) are promising for multistep-ahead flow forecasts. We systematically evaluate these rainfall products over a large catchment in Eastern India (Mahanadi River basin). We found spatially coherent trends, with both the real-time TRMM rainfall and ECMWF rainfall forecast products overestimating low rainfall events and underestimating high rainfall events. However, no significant bias was found for the medium rainfall events. Another key finding was that these rainfall products captured the phase of the storms pretty well, but suffered from consistent under-prediction. The utility of the real-time TRMM and ECMWF forecast products are evaluated by rainfall-runoff modeling using different artificial neural network (ANN)-based models up to 3-days ahead. Keywords: TRMM; ECMWF; forecast; ANN; rainfall-runoff modeling

Quality assessment of multi-GNSS real-time orbits and clocks

NASA Astrophysics Data System (ADS)

Kaźmierski, Kamil; Sośnica, Krzysztof; Hadaś, Tomasz

2017-04-01

A continuously increasing number of satellites of Global Navigation Satellites Systems (GNSS) and their constant modernization allow improving the positioning accuracy and enables performing the GNSS measurements in challenging environments. The constant development of GNSS, among which GPS, GLONASS, Galileo and BeiDou can be distinguished, contributes to improvements in GNSS usage in areas desired by common users or GNSS community. The Multi-GNSS experiment (MGEX) of the International GNSS Service (IGS) has been established for tracking, collating and analyzing all available GNSS signals. Provided precise orbits and clocks do not allow users to process data in real-time due to the significant latency of provided products which may reach up to even 18 days. In order to satisfy needs of real-time users IGS Real-Time Service (RTS) was launched in 2013. The service is currently insufficient for Multi-GNSS applications as it provides products for GPS and GLONASS only. One of the publicly available real-time corrections for the all GNSS, including the new systems, are those provided by the Centre National d'etudes Spatiales (CNES). Presented works evaluate clocks and orbit corrections, i.e., the availability and quality of real-time products provided by CNES (mountpoint CLK93). As a decoder of the RTCM streams the BNC software v2.12 is used. All computations are performed using the GNSS-WARP software which is developed by Institute of Geodesy and Geoinformatics (IGG) at Wroclaw University of Environmental and Life Sciences (WUELS). The final products provided by the Center of Orbit Determination in Europe (CODE) are used for the evaluation of the real-time CNES orbits and clocks. Moreover, the Satellite Laser Ranging (SLR) data are employed as an independent way of the orbit quality assessment. The availability of the real-time corrections is at the level of about 90%, when excluding BeiDou, for which the availability is at the level of about 80%. The obtained results

Real-time endoscopic guidance using near-infrared fluorescent light for thoracic surgery

NASA Astrophysics Data System (ADS)

Venugopal, Vivek; Stockdale, Alan; Neacsu, Florin; Kettenring, Frank; Frangioni, John V.; Gangadharan, Sidharta P.; Gioux, Sylvain

2013-03-01

Lung cancer is the leading cause of cancer death in the United States, accounting for 28% of all cancer deaths. Standard of care for potentially curable lung cancer involves preoperative radiographic or invasive staging, followed by surgical resection. With recent adjuvant chemotherapy and radiation studies showing a survival advantage in nodepositive patients, it is crucial to accurately stage these patients surgically in order to identify those who may benefit. However, lymphadenectomy in lung cancer is currently performed without guidance, mainly due to the lack of tools permitting real-time, intraoperative identification of lymph nodes. In this study we report the design and validation of a novel, clinically compatible near-infrared (NIR) fluorescence thoracoscope for real-time intraoperative guidance during lymphadenectomy. A novel, NIR-compatible, clinical rigid endoscope has been designed and fabricated, and coupled to a custom source and a dual channel camera to provide simultaneous color and NIR fluorescence information to the surgeon. The device has been successfully used in conjunction with a safe, FDA-approved fluorescent tracer to detect and resect mediastinal lymph nodes during thoracic surgery on Yorkshire pigs. Taken together, this study lays the foundation for the clinical translation of endoscopic NIR fluorescence intraoperative guidance and has the potential to profoundly impact the management of lung cancer patients.

Towards the Future "Earthquake" School in the Cloud: Near-real Time Earthquake Games Competition in Taiwan

NASA Astrophysics Data System (ADS)

Chen, K. H.; Liang, W. T.; Wu, Y. F.; Yen, E.

2014-12-01

To prevent the future threats of natural disaster, it is important to understand how the disaster happened, why lives were lost, and what lessons have been learned. By that, the attitude of society toward natural disaster can be transformed from training to learning. The citizen-seismologists-in-Taiwan project is designed to elevate the quality of earthquake science education by means of incorporating earthquake/tsunami stories and near-real time earthquake games competition into the traditional curricula in schools. Through pilot of courses and professional development workshops, we have worked closely with teachers from elementary, junior high, and senior high schools, to design workable teaching plans through a practical operation of seismic monitoring at home or school. We will introduce how the 9-years-old do P- and S-wave picking and measure seismic intensity through interactive learning platform, how do scientists and school teachers work together, and how do we create an environment to facilitate continuous learning (i.e., near-real time earthquake games competition), to make earthquake science fun.

NASA World Wind Near Real Time Data for Earth

NASA Astrophysics Data System (ADS)

Hogan, P.

2013-12-01

Innovation requires open standards for data exchange, not to mention ^access to data^ so that value-added, the information intelligence, can be continually created and advanced by the larger community. Likewise, innovation by academia and entrepreneurial enterprise alike, are greatly benefited by an open platform that provides the basic technology for access and visualization of that data. NASA World Wind Java, and now NASA World Wind iOS for the iPhone and iPad, provides that technology. Whether the interest is weather science or climate science, emergency response or supply chain, seeing spatial data in its native context of Earth accelerates understanding and improves decision-making. NASA World Wind open source technology provides the basic elements for 4D visualization, using Open Geospatial Consortium (OGC) protocols, while allowing for customized access to any data, big or small, including support for NetCDF. NASA World Wind includes access to a suite of US Government WMS servers with near real time data. The larger community can readily capitalize on this technology, building their own value-added applications, either open or proprietary. Night lights heat map Glacier National Park

Real-Time Single Frequency Precise Point Positioning Using SBAS Corrections

PubMed Central

Li, Liang; Jia, Chun; Zhao, Lin; Cheng, Jianhua; Liu, Jianxu; Ding, Jicheng

2016-01-01

Real-time single frequency precise point positioning (PPP) is a promising technique for high-precision navigation with sub-meter or even centimeter-level accuracy because of its convenience and low cost. The navigation performance of single frequency PPP heavily depends on the real-time availability and quality of correction products for satellite orbits and satellite clocks. Satellite-based augmentation system (SBAS) provides the correction products in real-time, but they are intended to be used for wide area differential positioning at 1 meter level precision. By imposing the constraints for ionosphere error, we have developed a real-time single frequency PPP method by sufficiently utilizing SBAS correction products. The proposed PPP method are tested with static and kinematic data, respectively. The static experimental results show that the position accuracy of the proposed PPP method can reach decimeter level, and achieve an improvement of at least 30% when compared with the traditional SBAS method. The positioning convergence of the proposed PPP method can be achieved in 636 epochs at most in static mode. In the kinematic experiment, the position accuracy of the proposed PPP method can be improved by at least 20 cm relative to the SBAS method. Furthermore, it has revealed that the proposed PPP method can achieve decimeter level convergence within 500 s in the kinematic mode. PMID:27517930

Influencing Anesthesia Provider Behavior Using Anesthesia Information Management System Data for Near Real-Time Alerts and Post Hoc Reports.

PubMed

Epstein, Richard H; Dexter, Franklin; Patel, Neil

2015-09-01

In this review article, we address issues related to using data from anesthesia information management systems (AIMS) to deliver near real-time alerts via AIMS workstation popups and/or alphanumeric pagers and post hoc reports via e-mail. We focus on reports and alerts for influencing the behavior of anesthesia providers (i.e., anesthesiologists, anesthesia residents, and nurse anesthetists). Multiple studies have shown that anesthesia clinical decision support (CDS) improves adherence to protocols and increases financial performance through facilitation of billing, regulatory, and compliance documentation; however, improved clinical outcomes have not been demonstrated. We inform developers and users of feedback systems about the multitude of concerns to consider during development and implementation of CDS to increase its effectiveness and to mitigate its potentially disruptive aspects. We discuss the timing and modalities used to deliver messages, implications of outlier-only versus individualized feedback, the need to consider possible unintended consequences of such feedback, regulations, sustainability, and portability among systems. We discuss statistical issues related to the appropriate evaluation of CDS efficacy. We provide a systematic review of the published literature (indexed in PubMed) of anesthesia CDS and offer 2 case studies of CDS interventions using AIMS data from our own institution illustrating the salient points. Because of the considerable expense and complexity of maintaining near real-time CDS systems, as compared with providing individual reports via e-mail after the fact, we suggest that if the same goal can be accomplished via delayed reporting versus immediate feedback, the former approach is preferable. Nevertheless, some processes require near real-time alerts to produce the desired improvement. Post hoc e-mail reporting from enterprise-wide electronic health record systems is straightforward and can be accomplished using system

Real-Time Precise Point Positioning (RTPPP) with raw observations and its application in real-time regional ionospheric VTEC modeling

NASA Astrophysics Data System (ADS)

Liu, Teng; Zhang, Baocheng; Yuan, Yunbin; Li, Min

2018-01-01

Precise Point Positioning (PPP) is an absolute positioning technology mainly used in post data processing. With the continuously increasing demand for real-time high-precision applications in positioning, timing, retrieval of atmospheric parameters, etc., Real-Time PPP (RTPPP) and its applications have drawn more and more research attention in recent years. This study focuses on the models, algorithms and ionospheric applications of RTPPP on the basis of raw observations, in which high-precision slant ionospheric delays are estimated among others in real time. For this purpose, a robust processing strategy for multi-station RTPPP with raw observations has been proposed and realized, in which real-time data streams and State-Space-Representative (SSR) satellite orbit and clock corrections are used. With the RTPPP-derived slant ionospheric delays from a regional network, a real-time regional ionospheric Vertical Total Electron Content (VTEC) modeling method is proposed based on Adjusted Spherical Harmonic Functions and a Moving-Window Filter. SSR satellite orbit and clock corrections from different IGS analysis centers are evaluated. Ten globally distributed real-time stations are used to evaluate the positioning performances of the proposed RTPPP algorithms in both static and kinematic modes. RMS values of positioning errors in static/kinematic mode are 5.2/15.5, 4.7/17.4 and 12.8/46.6 mm, for north, east and up components, respectively. Real-time slant ionospheric delays from RTPPP are compared with those from the traditional Carrier-to-Code Leveling (CCL) method, in terms of function model, formal precision and between-receiver differences of short baseline. Results show that slant ionospheric delays from RTPPP are more precise and have a much better convergence performance than those from the CCL method in real-time processing. 30 real-time stations from the Asia-Pacific Reference Frame network are used to model the ionospheric VTECs over Australia in real time

Real-time simulations for automated rendezvous and capture

NASA Technical Reports Server (NTRS)

Cuseo, John A.

1991-01-01

Although the individual technologies for automated rendezvous and capture (AR&C) exist, they have not yet been integrated to produce a working system in the United States. Thus, real-time integrated systems simulations are critical to the development and pre-flight demonstration of an AR&C capability. Real-time simulations require a level of development more typical of a flight system compared to purely analytical methods, thus providing confidence in derived design concepts. This presentation will describe Martin Marietta's Space Operations Simulation (SOS) Laboratory, a state-of-the-art real-time simulation facility for AR&C, along with an implementation for the Satellite Servicer System (SSS) Program.

Evaluation and analysis of real-time precise orbits and clocks products from different IGS analysis centers

NASA Astrophysics Data System (ADS)

Zhang, Liang; Yang, Hongzhou; Gao, Yang; Yao, Yibin; Xu, Chaoqian

2018-06-01

To meet the increasing demands from the real-time Precise Point Positioning (PPP) users, the real-time satellite orbit and clock products are generated by different International GNSS Service (IGS) real-time analysis centers and can be publicly received through the Internet. Based on different data sources and processing strategies, the real-time products from different analysis centers therefore differ in availability and accuracy. The main objective of this paper is to evaluate availability and accuracy of different real-time products and their effects on real-time PPP. A total of nine commonly used Real-Time Service (RTS) products, namely IGS01, IGS03, CLK01, CLK15, CLK22, CLK52, CLK70, CLK81 and CLK90, will be evaluated in this paper. Because not all RTS products support multi-GNSS, only GPS products are analyzed in this paper. Firstly, the availability of all RTS products is analyzed in two levels. The first level is the epoch availability, indicating whether there is outage for that epoch. The second level is the satellite availability, which defines the available satellite number for each epoch. Then the accuracy of different RTS products is investigated on nominal accuracy and the accuracy degradation over time. Results show that Root-Mean-Square Error (RMSE) of satellite orbit ranges from 3.8 cm to 7.5 cm for different RTS products. While the mean Standard Deviations of Errors (STDE) of satellite clocks range from 1.9 cm to 5.6 cm. The modified Signal In Space Range Error (SISRE) for all products are from 1.3 cm to 5.5 cm for different RTS products. The accuracy degradation of the orbit has the linear trend for all RTS products and the satellite clock degradation depends on the satellite clock types. The Rb clocks on board of GPS IIF satellites have the smallest degradation rate of less than 3 cm over 10 min while the Cs clocks on board of GPS IIF have the largest degradation rate of more than 10 cm over 10 min. Finally, the real-time kinematic PPP is

Real-time photo-magnetic imaging.

PubMed

Nouizi, Farouk; Erkol, Hakan; Luk, Alex; Unlu, Mehmet B; Gulsen, Gultekin

2016-10-01

We previously introduced a new high resolution diffuse optical imaging modality termed, photo-magnetic imaging (PMI). PMI irradiates the object under investigation with near-infrared light and monitors the variations of temperature using magnetic resonance thermometry (MRT). In this paper, we present a real-time PMI image reconstruction algorithm that uses analytic methods to solve the forward problem and assemble the Jacobian matrix much faster. The new algorithm is validated using real MRT measured temperature maps. In fact, it accelerates the reconstruction process by more than 250 times compared to a single iteration of the FEM-based algorithm, which opens the possibility for the real-time PMI.

Prospective validation of a near real-time EHR-integrated automated SOFA score calculator.

PubMed

Aakre, Christopher; Franco, Pablo Moreno; Ferreyra, Micaela; Kitson, Jaben; Li, Man; Herasevich, Vitaly

2017-07-01

We created an algorithm for automated Sequential Organ Failure Assessment (SOFA) score calculation within the Electronic Health Record (EHR) to facilitate detection of sepsis based on the Third International Consensus Definitions for Sepsis and Septic Shock (SEPSIS-3) clinical definition. We evaluated the accuracy of near real-time and daily automated SOFA score calculation compared with manual score calculation. Automated SOFA scoring computer programs were developed using available EHR data sources and integrated into a critical care focused patient care dashboard at Mayo Clinic in Rochester, Minnesota. We prospectively compared the accuracy of automated versus manual calculation for a sample of patients admitted to the medical intensive care unit at Mayo Clinic Hospitals in Rochester, Minnesota and Jacksonville, Florida. Agreement was calculated with Cohen's kappa statistic. Reason for discrepancy was tabulated during manual review. Random spot check comparisons were performed 134 times on 27 unique patients, and daily SOFA score comparisons were performed for 215 patients over a total of 1206 patient days. Agreement between automatically scored and manually scored SOFA components for both random spot checks (696 pairs, κ=0.89) and daily calculation (5972 pairs, κ=0.89) was high. The most common discrepancies were in the respiratory component (inaccurate fraction of inspired oxygen retrieval; 200/1206) and creatinine (normal creatinine in patients with no urine output on dialysis; 128/1094). 147 patients were at risk of developing sepsis after intensive care unit admission, 10 later developed sepsis confirmed by chart review. All were identified before onset of sepsis with the ΔSOFA≥2 point criterion and 46 patients were false-positives. Near real-time automated SOFA scoring was found to have strong agreement with manual score calculation and may be useful for the detection of sepsis utilizing the new SEPSIS-3 definition. Copyright © 2017 Elsevier B.V. All

Near Real Time Data for Operational Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Berger, T. E.

2014-12-01

Space weather operations presents unique challenges for data systems and providers. Space weather events evolve more quickly than terrestrial weather events. While terrestrial weather occurs on timescales of minutes to hours, space weather storms evolve on timescales of seconds to minutes. For example, the degradation of the High Frequency Radio communications between the ground and commercial airlines is nearly instantaneous when a solar flare occurs. Thus the customer is observing impacts at the same time that the operational forecast center is seeing the event unfold. The diversity and spatial scale of the space weather system is such that no single observation can capture the salient features. The vast space that encompasses space weather and the scarcity of observations further exacerbates the situation and make each observation even more valuable. The physics of interplanetary space, through which many major storms propagate, is very different from the physics of the ionosphere where most of the impacts are felt. And while some observations can be made from ground-based observatories, many of the most critical data comes from satellites, often in unique orbits far from Earth. In this presentation, I will describe some of the more important sources and types of data that feed into the operational alerts, watches, and warnings of space weather storms. Included will be a discussion of some of the new space weather forecast models and the data challenges that they bring forward.

Development and Test of an Infrastructure Free Real-Time Water Level Measurement System

NASA Astrophysics Data System (ADS)

Breuer, E. R.; Heitsenrether, R.; Hensley, W., III; Krug, W.; Wolcott, D.

2016-02-01

NOAA's Center for Operational Oceanographic Products and Services (CO-OPS) is responsible for developing and maintaining the National Water Level Observation Network (NWLON). NWLON consists of over 200 long term observatories that provide near real-time, 6 minute average, water level observations from locations throughout all U.S. coasts. CO-OPS continually analyzes state-of-the-art and emerging technologies to identify potential improvements in data quality and operating efficiency. NOAA, recognizing the changing conditions, anticipates a critical need for real time oceanographic and meteorological observations where traditional approaches are less feasible. CO-OPS is working on the design, development and testing of a real-time tidal measurement system, "The Hermit," for use in coastal regions. The latest prototype has recently completed a successful 3 month field test deployment in the St Andrews Sound region of Georgia, a location where relatively few long term water level records have been collected to date. The test location provided unique challenges such as having a very limited coastal infrastructure and experiencing a 7-8 foot tidal range. The Hermit consists of a bottom mounted pressure/conductivity/temperature sensor (Seabird SBE 26+) and a surface communications buoy which are linked via acoustic modems (Link Quest). The surface buoy relays data back to the CO-OPS database in near-real time using an Iridium satellite based communication system. Additionally, the buoy includes an AirMar all-in-one meteorological sensor. In addition to The Hermit deployment, three test GPS bench marks and a tide staff were installed on a nearby coastline to vertically reference water level measurements. During this deployment, The Hermit successfully provided near real-time measurements of bottom pressure, water conductivity and temperature, wind speed and direction, air temperature, and barometric pressure over the 3 month deployment. During the test period, several

Near real-time imaging of molasses injections using time-lapse electrical geophysics at the Brandywine DRMO, Brandywine, Maryland

NASA Astrophysics Data System (ADS)

Versteeg, R. J.; Johnson, T.; Major, B.; Day-Lewis, F. D.; Lane, J. W.

2010-12-01

Enhanced bioremediation, which involves introduction of amendments to promote biodegradation, increasingly is used to accelerate cleanup of recalcitrant compounds and has been identified as the preferred remedial treatment at many contaminated sites. Although blind introduction of amendments can lead to sub-optimal or ineffective remediation, the distribution of amendment throughout the treatment zone is difficult to measure using conventional sampling. Because amendments and their degradation products commonly have electrical properties that differ from those of ambient soil, time-lapse electrical geophysical monitoring has the potential to verify amendment emplacement and distribution. In order for geophysical monitoring to be useful, however, results of the injection ideally should be accessible in near real time. In August 2010, we demonstrated the feasibility of near real-time, autonomous electrical geophysical monitoring of amendment injections at the former Defense Reutilization and Marketing Office (DRMO) in Brandywine, Maryland. Two injections of about 1000 gallons each of molasses, a widely used amendment for enhanced bioremediation, were monitored using measurements taken with borehole and surface electrodes. During the injections, multi-channel resistance data were recorded; data were transmitted to a server and processed using a parallel resistivity inversion code; and results in the form of time-lapse imagery subsequently were posted to a website. This process occurred automatically without human intervention. The resulting time-lapse imagery clearly showed the evolution of the molasses plume. The delay between measurements and online delivery of images was between 45 and 60 minutes, thus providing actionable information that could support decisions about field procedures and a check on whether amendment reached target zones. This experiment demonstrates the feasibility of using electrical imaging as a monitoring tool both during amendment emplacement

Satellite time-transfer: recent developments and projects

NASA Astrophysics Data System (ADS)

Lewandowski, W.; Nawrocki, J.

2006-10-01

Global Navigation Satellite Systems (GNSS) keep a central role in the international timekeeping. American Global Positioning System (GPS) is a navigation system that has proven itself to be a reliable source of positioning for both the military community and the civilian community. But, little known by many, is the fact that GPS has proven itself to be an important and valuable utility to the timekeeping community (Lewandowski et al. 1999). GPS is a versatile and global tool which can be used to both distribute time to an arbitrary number of users and synchronise clocks over large distances with a high degree of precision and accuracy. Similar performance can be obtained with Russian Global Navigation Satellite System (GLONASS). It is expected in the near future satellites of a new European navigation system GALILEO might bring some important opportunities for international timekeeping. This paper after a brief introduction to international timekeeping focuses on the description of recent progress in time transfer techniques using GNSS satellites.

A Near-real-time Data Transport System for Selected Stations in the Magnetometer Array for Cusp and Cleft Studies (MACCS)

NASA Astrophysics Data System (ADS)

Engebretson, M. J.; Valentic, T. A.; Stehle, R. H.; Hughes, W. J.

2004-05-01

The Magnetometer Array for Cusp and Cleft Studies (MACCS) is a two-dimensional array of eight fluxgate magnetometers that was established in 1992-1993 in the Eastern Canadian Arctic from 75° to over 80° MLAT to study electrodynamic interactions between the solar wind and Earth's magnetosphere and high-latitude ionosphere. A ninth site in Nain, Labrador, extends coverage down to 66° between existing Canadian and Greenland stations. Originally designed as part of NSF's GEM (Geospace Environment Modeling) Program, MACCS has contributed to the study of transients and waves at the magnetospheric boundary and in the near-cusp region as well as to large, cooperative, studies of ionospheric convection and substorm processes. Because of the limitations of existing telephone lines to each site, it has not been possible to economically access MACCS data promptly; instead, each month's collected data is recorded and mailed to the U.S. for processing and eventual posting on a publicly-accessible web site, http://space.augsburg.edu/space. As part of its recently renewed funding, NSF has supported the development of a near-real-time data transport system using the Iridium satellite network, which will be implemented at two MACCS sites in summer 2004. At the core of the new MACCS communications system is the Data Transport Network, software developed with NSF-ITR funding to automate the transfer of scientific data from remote field stations over unreliable, bandwidth-constrained network connections. The system utilizes a store-and-forward architecture based on sending data files as attachments to Usenet messages. This scheme not only isolates the instruments from network outages, but also provides a consistent framework for organizing and accessing multiple data feeds. Client programs are able to subscribe to data feeds to perform tasks such as system health monitoring, data processing, web page updates and e-mail alerts. The MACCS sites will employ the Data Transport Network

Information Gap Analysis: near real-time evaluation of disaster response

NASA Astrophysics Data System (ADS)

Girard, Trevor

2014-05-01

Disasters, such as major storm events or earthquakes, trigger an immediate response by the disaster management system of the nation in question. The quality of this response is a large factor in its ability to limit the impacts on the local population. Improving the quality of disaster response therefore reduces disaster impacts. Studying past disasters is a valuable exercise to understand what went wrong, identify measures which could have mitigated these issues, and make recommendations to improve future disaster planning and response. While such ex post evaluations can lead to improvements in the disaster management system, there are limitations. The main limitation that has influenced this research is that ex post evaluations do not have the ability to inform the disaster response being assessed for the obvious reason that they are carried out long after the response phase is over. The result is that lessons learned can only be applied to future disasters. In the field of humanitarian relief, this limitation has led to the development of real time evaluations. The key aspect of real time humanitarian evaluations is that they are completed while the operation is still underway. This results in findings being delivered at a time when they can still make a difference to the humanitarian response. Applying such an approach to the immediate disaster response phase requires an even shorter time-frame, as well as a shift in focus from international actors to the nation in question's government. As such, a pilot study was started and methodology developed, to analyze disaster response in near real-time. The analysis uses the information provided by the disaster management system within the first 0 - 5 days of the response. The data is collected from publicly available sources such as ReliefWeb and sorted under various categories which represent each aspect of disaster response. This process was carried out for 12 disasters. The quantity and timeliness of information

New Approaches To Off-Shore Wind Energy Management Exploiting Satellite EO Data

NASA Astrophysics Data System (ADS)

Morelli, Marco; Masini, Andrea; Venafra, Sara; Potenza, Marco Alberto Carlo

2013-12-01

Wind as an energy resource has been increasingly in focus over the past decades, starting with the global oil crisis in the 1970s. The possibility of expanding wind power production to off-shore locations is attractive, especially in sites where wind levels tend to be higher and more constant. Off-shore high-potential sites for wind energy plants are currently being looked up by means of wind atlases, which are essentially based on NWP (Numerical Weather Prediction) archive data and that supply information with low spatial resolution and very low accuracy. Moreover, real-time monitoring of active off- shore wind plants is being carried out using in-situ installed anemometers, that are not very reliable (especially on long time periods) and that should be periodically substituted when malfunctions or damages occur. These activities could be greatly supported exploiting archived and near real-time satellite imagery, that could provide accurate, global coverage and high spatial resolution information about both averaged and near real-time off-shore windiness. In this work we present new methodologies aimed to support both planning and near-real-time monitoring of off-shore wind energy plants using satellite SAR(Synthetic Aperture Radar) imagery. Such methodologies are currently being developed in the scope of SATENERG, a research project funded by ASI (Italian Space Agency). SAR wind data are derived from radar backscattering using empirical geophysical model functions, thus achieving greater accuracy and greater resolution with respect to other wind measurement methods. In detail, we calculate wind speed from X-band and C- band satellite SAR data, such as Cosmo-SkyMed (XMOD2) and ERS and ENVISAT (CMOD4) respectively. Then, using also detailed models of each part of the wind plant, we are able to calculate the AC power yield expected behavior, which can be used to support either the design of potential plants (using historical series of satellite images) or the

Characteristics of recent dust storms over the Indian region using real time multi-satellite observations from the direct broadcast receiving system at IMD

NASA Astrophysics Data System (ADS)

Mitra, A. K.; Sharma, A. K.; Soni, V. K.; Kundu, P. K.

2013-04-01

In this study, observations from microwave satellites, visible and infrared instruments have been analyzed to detect dust storm over north and north-west part of India during 18-23 March 2012. This study investigated the approach to utilize the multi satellite data of Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the Terra and Aqua satellite and the Advanced Microwave Sounding Unit (AMSU) on-board NOAA satellite to study the characteristics of dust storms from real time direct broadcast (DB) receiving system installed at three places of India Meteorological Department (IMD). The dust storm detection is based on the infrared brightness temperature (BT) difference between channels at 11 and 12 μm and polarized BT difference between two channels of 89 and 23.8 GHz. It is found that the significant differences between the BT of channel 89 and 23.8 can be used as a discriminator of identifying dust storm. The Total Ozone Mapping Spectroradiometer (TOMS) Aerosol Index (AI) and AMSU-A 23 GHz channel BT from NOAA satellite over the north and north-west part of India have also been analyzed. The result indicated the characteristic behavior between BT and AI during the different phases of the dust storm. Finally, the occurrence of dust outbreaks has also been validated with sky radiometer of IMD, which confirms the presence of a dust storm over the Indian region. Further, the findings of the study and its approaches apply to the other dust storm cases which occurred during the months of April and June 2012. The integrated approach suggested the potential to use high resolution data of microwave as well as thermal-infrared using multi-satellite observations from real time direct broadcast system for the detection of severe, moderate or weak dust storms very well. The approach is found to be promising for operational application.

Real-time attitude determination and gyro calibration

NASA Technical Reports Server (NTRS)

Challa, M.; Filla, O.; Sedlak, J.; Chu, D.

1993-01-01

We present results for two real-time filters prototyped for the Compton Gamma Ray Observatory (GRO), the Extreme Ultraviolet Explorer (EUVE), the Cosmic Background Explorer (COBE), and the next generation of Geostationary Operational Environmental Satellites (GOES). Both real and simulated data were used to solve for attitude and gyro biases. These filters promise advantages over single-frame and batch methods for missions like GOES, where startup and transfer-orbit operations require quick knowledge of attitude and gyro biases.

JPSS application in a near real time regional numerical forecast system at CIMSS

NASA Astrophysics Data System (ADS)

Li, J.; Wang, P.; Han, H.; Zhu, F.; Schmit, T. J.; Goldberg, M.

2015-12-01

Observations from next generation of environmental sensors onboard the Suomi National Polar-Orbiting Parnership (S-NPP) and its successor, the Joint Polar Satellite System (JPSS), provide us the critical information for numerical weather forecast (NWP). How to better represent these satellite observations and how to get value added information into NWP system still need more studies. Recently scientists from Cooperative Institute of Meteorological Satellite Studies (CIMSS) at University of Wisconsin-Madison have developed a near realtime regional Satellite Data Assimilation system for Tropical storm forecasts (SDAT) (http://cimss.ssec.wisc.edu/sdat). The system is built with the community Gridpoint Statistical Interpolation (GSI) assimilation and advanced Weather Research Forecast (WRF) model. With GSI, SDAT can assimilate all operational available satellite data including GOES, AMSUA/AMSUB, HIRS, MHS, ATMS, AIRS and IASI radiances and some satellite derived products. In addition, some research products, such as hyperspectral IR retrieved temperature and moisture profiles, GOES imager atmospheric motion vector (AMV) and GOES sounder layer precipitable water (LPW), are also added into the system. Using SDAT as a research testbed, studies have been conducted to show how to improve high impact weather forecast by better handling cloud information in satellite data. Previously by collocating high spatial resolution MODIS data with hyperspectral resolution AIRS data, precise clear pixels of AIRS can be identified and some partially or thin cloud contamination from pixels can be removed by taking advantage of high spatial resolution and high accurate MODIS cloud information. The results have demonstrated that both of these strategies have greatly improved the hurricane track and intensity forecast. We recently have extended these methodologies into processing CrIS/VIIRS data. We also tested similar ideas in microwave sounders by the collocation of AMSU/MODIS and ATMS

Near Real-time Ecological Forecasting of Peatland Responses to Warming and CO2 Treatment through EcoPAD-SPRUCE

NASA Astrophysics Data System (ADS)

Huang, Y.; Jiang, J.; Stacy, M.; Ricciuto, D. M.; Hanson, P. J.; Sundi, N.; Luo, Y.

2016-12-01

Ecological forecasting is critical in various aspects of our coupled human-nature systems, such as disaster risk reduction, natural resource management and climate change mitigation. Novel advancements are in urgent need to deepen our understandings of ecosystem dynamics, boost the predictive capacity of ecology, and provide timely and effective information for decision-makers in a rapidly changing world. Our Ecological Platform for Assimilation of Data (EcoPAD) facilitates the integration of current best knowledge from models, manipulative experimentations, observations and other modern techniques and provides both near real-time and long-term forecasting of ecosystem dynamics. As a case study, the web-based EcoPAD platform synchronizes real- or near real-time field measurements from the Spruce and Peatland Responses Under Climatic and Environmental Change Experiment (SPRUCE), a whole ecosystem warming and CO2 enrichment treatment experiment, assimilates multiple data streams into process based models, enhances timely feedback between modelers and experimenters, and ultimately improves ecosystem forecasting and makes best utilization of current knowledge. In addition to enable users to (i) estimate model parameters or state variables, (ii) quantify uncertainty of estimated parameters and projected states of ecosystems, (iii) evaluate model structures, (iv) assess sampling strategies, and (v) conduct ecological forecasting, EcoPAD-SPRUCE automated the workflow from real-time data acquisition, model simulation to result visualization. EcoPAD-SPRUCE promotes seamless feedback between modelers and experimenters, hand in hand to make better forecasting of future changes. The framework of EcoPAD-SPRUCE (with flexible API, Application Programming Interface) is easily portable and will benefit scientific communities, policy makers as well as the general public.

The Waypoint Planning Tool: Real Time Flight Planning for Airborne Science

NASA Technical Reports Server (NTRS)

He, Yubin; Blakeslee, Richard; Goodman, Michael; Hall, John

2010-01-01

NASA Earth science research utilizes both spaceborne and airborne real time observations in the planning and operations of its field campaigns. The coordination of air and space components is critical to achieve the goals and objectives and ensure the success of an experiment. Spaceborne imagery provides regular and continual coverage of the Earth and it is a significant component in all NASA field experiments. Real time visible and infrared geostationary images from GOES satellites and multi-spectral data from the many elements of the NASA suite of instruments aboard the TRMM, Terra, Aqua, Aura, and other NASA satellites have become norm. Similarly, the NASA Airborne Science Program draws upon a rich pool of instrumented aircraft. The NASA McDonnell Douglas DC-8, Lockheed P3 Orion, DeHavilland Twin Otter, King Air B200, Gulfstream-III are all staples of a NASA's well-stocked, versatile hangar. A key component in many field campaigns is coordinating the aircraft with satellite overpasses, other airplanes and the constantly evolving, dynamic weather conditions. Given the variables involved, developing a good flight plan that meets the objectives of the field experiment can be a challenging and time consuming task. Planning a research aircraft mission within the context of meeting the science objectives is complex task because it is much more than flying from point A to B. Flight plans typically consist of flying a series of transects or involve dynamic path changes when "chasing" a hurricane or forest fire. These aircraft flight plans are typically designed by the mission scientists then verified and implemented by the navigator or pilot. Flight planning can be an arduous task requiring frequent sanity checks by the flight crew. This requires real time situational awareness of the weather conditions that affect the aircraft track. Scientists at the University of Alabama-Huntsville and the NASA Marshall Space Flight Center developed the Waypoint Planning Tool, an

Near real time water resources data for river basin management

NASA Technical Reports Server (NTRS)

Paulson, R. W. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Twenty Data Collection Platforms (DCP) are being field installed on USGS water resources stations in the Delaware River Basin. DCP's have been successfully installed and are operating well on five stream gaging stations, three observation wells, and one water quality monitor in the basin. DCP's have been installed at nine additional water quality monitors, and work is progressing on interfacing the platforms to the monitors. ERTS-related water resources data from the platforms are being provided in near real time, by the Goddard Space Flight Center to the Pennsylvania district, Water Resources Division, U.S. Geological Survey. On a daily basis, the data are computer processed by the Survey and provided to the Delaware River Basin Commission. Each daily summary contains data that were relayed during 4 or 5 of the 15 orbits made by ERTS-1 during the previous day. Water resources parameters relays by the platforms include dissolved oxygen concentrations, temperature, pH, specific conductance, well level, and stream gage height, which is used to compute stream flow for the daily summary.

The near real time Forensic Disaster Analysis of the central European flood in June 2013 - A graphical representation of the main results

NASA Astrophysics Data System (ADS)

Schröter, Kai; Elmer, Florian; Trieselmann, Werner; Kreibich, Heidi; Kunz, Michael; Khazai, Bijan; Dransch, Doris; Wenzel, Friedemann; Zschau, Jochen; Merz, Bruno; Mühr, Bernhard; Kunz-Plapp, Tina; Möhrle, Stella; Bessel, Tina; Fohringer, Joachim

2014-05-01

The Central European flood of June 2013 is one of the most severe flood events that have occurred in Central Europe in the past decades. All major German river basins were affected (Rhine, Danube, and Elbe as well as the smaller Weser catchment).In terms of spatial extent and event magnitude, it was the most severe event at least since 1950. Within the current research focus on near real time forensic disaster analysis, the Center for Disaster Management and Risk Reduction Technology (CEDIM) assessed and analysed the multiple facets of the flood event from the beginning. The aim is to describe the on-going event, analyse the event sources, link the physical characteristics to the impact and consequences of the event and to understand the root causes that turn the physical event into a disaster (or prevent it from becoming disastrous). For the near real time component of this research, tools for rapid assessment and concise presentation of analysis results are essential. This contribution provides a graphical summary of the results of the CEDIM-FDA analyses on the June 2013 flood. It demonstrates the potential of visual representations for improving the communication and hence usability of findings in a rapid, intelligible and expressive way as a valuable supplement to usual event reporting. It is based on analyses of the hydrometeorological sources, the flood pathways (from satellite imagery, data extraction from social media), the resilience of the affected regions, and causal loss analysis. The prototypical representation of the FDA-results for the June 2013 flood provides an important step in the development of graphical event templates for the visualisation of forensic disaster analyses. These are intended to become a standard component of future CEDIM-FDA event activities.

Near Real-Time Image Reconstruction

NASA Astrophysics Data System (ADS)

Denker, C.; Yang, G.; Wang, H.

2001-08-01

In recent years, post-facto image-processing algorithms have been developed to achieve diffraction-limited observations of the solar surface. We present a combination of frame selection, speckle-masking imaging, and parallel computing which provides real-time, diffraction-limited, 256×256 pixel images at a 1-minute cadence. Our approach to achieve diffraction limited observations is complementary to adaptive optics (AO). At the moment, AO is limited by the fact that it corrects wavefront abberations only for a field of view comparable to the isoplanatic patch. This limitation does not apply to speckle-masking imaging. However, speckle-masking imaging relies on short-exposure images which limits its spectroscopic applications. The parallel processing of the data is performed on a Beowulf-class computer which utilizes off-the-shelf, mass-market technologies to provide high computational performance for scientific calculations and applications at low cost. Beowulf computers have a great potential, not only for image reconstruction, but for any kind of complex data reduction. Immediate access to high-level data products and direct visualization of dynamic processes on the Sun are two of the advantages to be gained.

Real-time imaging of human brain function by near-infrared spectroscopy using an adaptive general linear model

PubMed Central

Abdelnour, A. Farras; Huppert, Theodore

2009-01-01

Near-infrared spectroscopy is a non-invasive neuroimaging method which uses light to measure changes in cerebral blood oxygenation associated with brain activity. In this work, we demonstrate the ability to record and analyze images of brain activity in real-time using a 16-channel continuous wave optical NIRS system. We propose a novel real-time analysis framework using an adaptive Kalman filter and a state–space model based on a canonical general linear model of brain activity. We show that our adaptive model has the ability to estimate single-trial brain activity events as we apply this method to track and classify experimental data acquired during an alternating bilateral self-paced finger tapping task. PMID:19457389

Real-time logic modelling on SpaceWire

NASA Astrophysics Data System (ADS)

Zhou, Qiang; Ma, Yunpeng; Fei, Haidong; Wang, Xingyou

2017-04-01

A SpaceWire is a standard for on-board satellite networks as the basis for future data-handling architectures. However, it cannot meet the deterministic requirement for safety/time critical application in spacecraft, where the delay of real-time (RT) message streams must be guaranteed. Therefore, SpaceWire-D is developed that provides deterministic delivery over a SpaceWire network. Formal analysis and verification of real-time systems is critical to their development and safe implementation, and is a prerequisite for obtaining their safety certification. Failure to meet specified timing constraints such as deadlines in hard real-time systems may lead to catastrophic results. In this paper, a formal verification method, Real-Time Logic (RTL), has been proposed to specify and verify timing properties of SpaceWire-D network. Based on the principal of SpaceWire-D protocol, we firstly analyze the timing properties of fundamental transactions, such as RMAP WRITE, and RMAP READ. After that, the RMAP WRITE transaction structure is modeled in Real-Time Logic (RTL) and Presburger Arithmetic representations. And then, the associated constraint graph and safety analysis is provided. Finally, it is suggested that RTL method can be useful for the protocol evaluation and provision of recommendation for further protocol evolutions.

Accuracy of Single Frequency GPS Observations Processing In Near Real-time With Use of Code Predicted Products

NASA Astrophysics Data System (ADS)

Wielgosz, P. A.

In this year, the system of active geodetic GPS permanent stations is going to be estab- lished in Poland. This system should provide GPS observations for a wide spectrum of users, especially it will be a great opportunity for surveyors. Many of surveyors still use cheaper, single frequency receivers. This paper focuses on processing of single frequency GPS observations only. During processing of such observations the iono- sphere plays an important role, so we concentrated on the influence of the ionosphere on the positional coordinates. Twenty consecutive days of GPS data from 2001 year were processed to analyze the accuracy of a derived three-dimensional relative vec- tor position between GPS stations. Observations from two Polish EPN/IGS stations: BOGO and JOZE were used. In addition to, a new test station - IGIK was created. In this paper, the results of single frequency GPS observations processing in near real- time are presented. Baselines of 15, 27 and 42 kilometers and sessions of 1, 2, 3, 4, and 6 hours long were processed. While processing we used CODE (Centre for Orbit De- termination in Europe, Bern, Switzerland) predicted products: orbits and ionosphere info. These products are available in real-time and enable near real-time processing. Software Bernese v. 4.2 for Linux and BPE (Bernese Processing Engine) mode were used. These results are shown with a reference to dual frequency weekly solution (the best solution). Obtained GPS positional time and GPS baseline length dependency accuracy is presented for single frequency GPS observations.

An approach for real-time fast point positioning of the BeiDou Navigation Satellite System using augmentation information

NASA Astrophysics Data System (ADS)

Tu, Rui; Zhang, Rui; Zhang, Pengfei; Liu, Jinhai; Lu, Xiaochun

2018-07-01

This study proposes an approach to facilitate real-time fast point positioning of the BeiDou Navigation Satellite System (BDS) based on regional augmentation information. We term this as the precise positioning based on augmentation information (BPP) approach. The coordinates of the reference stations were highly constrained to extract the augmentation information, which contained not only the satellite orbit clock error correlated with the satellite running state, but also included the atmosphere error and unmodeled error, which are correlated with the spatial and temporal states. Based on these mixed augmentation corrections, a precise point positioning (PPP) model could be used for the coordinates estimation of the user stations, and the float ambiguity could be easily fixed for the single-difference between satellites. Thus, this technique provided a quick and high-precision positioning service. Three different datasets with small, medium, and large baselines (0.6 km, 30 km and 136 km) were used to validate the feasibility and effectiveness of the proposed BPP method. The validations showed that using the BPP model, 1–2 cm positioning service can be provided in a 100 km wide area after just 2 s of initialization. Thus, as the proposed approach not only capitalized on both PPP and RTK but also provided consistent application, it can be used for area augmentation positioning.

Use of Real Time Satellite Infrared and Ocean Color to Produce Ocean Products

NASA Astrophysics Data System (ADS)

Roffer, M. A.; Muller-Karger, F. E.; Westhaver, D.; Gawlikowski, G.; Upton, M.; Hall, C.

2014-12-01

Real-time data products derived from infrared and ocean color satellites are useful for several types of users around the world. Highly relevant applications include recreational and commercial fisheries, commercial towing vessel and other maritime and navigation operations, and other scientific and applied marine research. Uses of the data include developing sampling strategies for research programs, tracking of water masses and ocean fronts, optimizing ship routes, evaluating water quality conditions (coastal, estuarine, oceanic), and developing fisheries and essential fish habitat indices. Important considerations for users are data access and delivery mechanisms, and data formats. At this time, the data are being generated in formats increasingly available on mobile computing platforms, and are delivered through popular interfaces including social media (Facebook, Linkedin, Twitter and others), Google Earth and other online Geographical Information Systems, or are simply distributed via subscription by email. We review 30 years of applications and describe how we develop customized products and delivery mechanisms working directly with users. We review benefits and issues of access to government databases (NOAA, NASA, ESA), standard data products, and the conversion to tailored products for our users. We discuss advantages of different product formats and of the platforms used to display and to manipulate the data.

Estimating forest structural characteristics using the airborne LiDAR scanning system and a near-real time profiling laser system

NASA Astrophysics Data System (ADS)

Zhao, Kaiguang

LiDAR (Light Detection and Ranging) directly measures canopy vertical structures, and provides an effective remote sensing solution to accurate and spatially-explicit mapping of forest characteristics, such as canopy height and Leaf Area Index. However, many factors, such as large data volume and high costs for data acquisition, precludes the operational and practical use of most currently available LiDARs for frequent and large-scale mapping. At the same time, a growing need is arising for real-time remote sensing platforms, e.g., to provide timely information for urgent applications. This study aims to develop an airborne profiling LiDAR system, featured with on-the-fly data processing, for near real- or real-time forest inventory. The development of such a system involves implementing the on-board data processing and analysis as well as building useful regression-based models to relate LiDAR measurements with forest biophysical parameters. This work established a paradigm for an on-the-fly airborne profiling LiDAR system to inventory regional forest resources in real- or near real-time. The system was developed based on an existing portable airborne laser system (PALS) that has been previously assembled at NASA by Dr. Ross Nelson. Key issues in automating PALS as an on-the-fly system were addressed, including the design of an archetype for the system workflow, the development of efficient and robust algorithms for automatic data processing and analysis, the development of effective regression models to predict forest biophysical parameters from LiDAR measurements, and the implementation of an integrated software package to incorporate all the above development. This work exploited the untouched potential of airborne laser profilers for real-time forest inventory, and therefore, documented an initial step toward developing airborne-laser-based, on-the-fly, real-time, forest inventory systems. Results from this work demonstrated the utility and effectiveness of

Real-time prediction of the occurrence of GLE events

NASA Astrophysics Data System (ADS)

Núñez, Marlon; Reyes-Santiago, Pedro J.; Malandraki, Olga E.

2017-07-01

A tool for predicting the occurrence of Ground Level Enhancement (GLE) events using the UMASEP scheme is presented. This real-time tool, called HESPERIA UMASEP-500, is based on the detection of the magnetic connection, along which protons arrive in the near-Earth environment, by estimating the lag correlation between the time derivatives of 1 min soft X-ray flux (SXR) and 1 min near-Earth proton fluxes observed by the GOES satellites. Unlike current GLE warning systems, this tool can predict GLE events before the detection by any neutron monitor (NM) station. The prediction performance measured for the period from 1986 to 2016 is presented for two consecutive periods, because of their notable difference in performance. For the 2000-2016 period, this prediction tool obtained a probability of detection (POD) of 53.8% (7 of 13 GLE events), a false alarm ratio (FAR) of 30.0%, and average warning times (AWT) of 8 min with respect to the first NM station's alert and 15 min to the GLE Alert Plus's warning. We have tested the model by replacing the GOES proton data with SOHO/EPHIN proton data, and the results are similar in terms of POD, FAR, and AWT for the same period. The paper also presents a comparison with a GLE warning system.

Source modeling and inversion with near real-time GPS: a GITEWS perspective for Indonesia

NASA Astrophysics Data System (ADS)

Babeyko, A. Y.; Hoechner, A.; Sobolev, S. V.

2010-07-01

We present the GITEWS approach to source modeling for the tsunami early warning in Indonesia. Near-field tsunami implies special requirements to both warning time and details of source characterization. To meet these requirements, we employ geophysical and geological information to predefine a maximum number of rupture parameters. We discretize the tsunamigenic Sunda plate interface into an ordered grid of patches (150×25) and employ the concept of Green's functions for forward and inverse rupture modeling. Rupture Generator, a forward modeling tool, additionally employs different scaling laws and slip shape functions to construct physically reasonable source models using basic seismic information only (magnitude and epicenter location). GITEWS runs a library of semi- and fully-synthetic scenarios to be extensively employed by system testing as well as by warning center personnel teaching and training. Near real-time GPS observations are a very valuable complement to the local tsunami warning system. Their inversion provides quick (within a few minutes on an event) estimation of the earthquake magnitude, rupture position and, in case of sufficient station coverage, details of slip distribution.

The effects of general relativity on near-earth satellites

NASA Technical Reports Server (NTRS)

Ries, J. C.; Watkins, M. M.; Tapley, B. D.; Huang, C.

1990-01-01

Whether one uses a solar system barycentric frame or a geocentric frame when including the general theory of relativity in orbit determination for near-earth satellites, the results should be equivalent to some limiting accuracy. The purpose of this paper is to clarify the effects of relativity in each frame and to demonstrate their equivalence through the analysis of three years of laser tracking data taken on the Lageos satellite. It is demonstrated that the simpler formulation in the geocentric frame is adequate for the purpose of near-earth satellite orbit determination. A correction to the conventional barycentric equations of motion is shown to be required.

The SPURS Data Management System: Real-time Situational Awareness at Sea

NASA Astrophysics Data System (ADS)

Bingham, F.; Chao, Y.; Li, P.; Vu, Q. A.

2012-12-01

SPURS (Salinity Processes in the Upper ocean Regional Study) is a field program in the North Atlantic to study the subtropical surface salinity maximum. It is a heterogeneous array consisting of research ships, profiling floats, surface drifters, gliders, microstructure profilers and moorings, as well as satellite observations and models. The SPURS Data Management System aims to capture the status of the observing system in near-real time and allow SPURS science team members to deploy observational assets "on the fly". At the heart of this is a visualization system that tracks the positions of the various assets and displays them in a an interface using Google Earth. The interface was used by program participants on land and at sea to coordinate the deployment of instrumentation. Before the Fall AGU, SPURS will have completed the first part of its mission with a 6-week cruise to the study area. This poster presents some of the highlights of the field campaign, and details the lessons learned in doing real-time oceanography on the high seas.

NOAA/APT Satellite Data for Online and Real Time Monitoring of Tungurahua Volcanic Eruption and Temperature Profile in Ecuador

NASA Astrophysics Data System (ADS)

Jaffer, G.; Nader, R.; Koudelka, O.

2010-12-01

The Ecuadorian Space Agency (EXA) has built HERMES, an online and real time ground station (GS) available to participating schools/universities for free access to NOAA and other remote sensing satellites. The GS is being used by students and scientists in Austria, USA, Japan and Ecuador to access NOAA satellites and spacecrafts online using only a computer and an internet connection with immediate access to satellite imaging and science data for their educational and research projects. The accuracy of analysed data can be used in research areas like forecasting, monitoring and damage assessment caused by eruptions. The HERMES internet-to-orbit gateway transforms a laptop into a full space-qualified GS on-the-move. The purpose of this paper is to present results of Andean mountain area in Ecuador being affected by high temperatures over 30 degree Celsius located over 3000 m high. From May 15 - 20, 2010, we received images from NOAA-18 and NOAA-19 using HERMS GS and applied Surface Temperature (ST), a remote sensing tool to process these images in real-time. Moreover, measured results have been validated by the records from the local meteorological stations network. Additionally, the visual observations revealed that due to high temperature, those glaciers were in fact receding and exposing terrain, never seen before. This paper also highlights the possible causes of this rapid thermal change. The second event dealt by this paper happened on May 28th; we captured a large ash cloud emanating from Tungurahua volcano eruption in the Andean region along with a large ash cloud from the Pacaya volcano in Guatemala using far infrared images from NOAA-18 satellite with overlaid geo-reference coordinates. Both events were analysed with remote sensing tools and image enhancement schemes like 'thermal', 'hvct' and 'fire', available in weather decoding software using free APT data. The aftermath correlation results of volcanic eruption with high temperature profile in the same

Near Real-Time Earthquake Exposure and Damage Assessment: An Example from Turkey

NASA Astrophysics Data System (ADS)

Kamer, Yavor; Çomoǧlu, Mustafa; Erdik, Mustafa

2014-05-01

Confined by infamous strike-slip North Anatolian Fault from the north and by the Hellenic subduction trench from the south Turkey is one of the most seismically active countries in Europe. Due this increased exposure and the fragility of the building stock Turkey is among the top countries exposed to earthquake hazard in terms of mortality and economic losses. In this study we focus recent and ongoing efforts to mitigate the earthquake risk in near real-time. We present actual results of recent earthquakes, such as the M6 event off-shore Antalya which occurred on 28 December 2013. Starting at the moment of detection, we obtain a preliminary ground motion intensity distribution based on epicenter and magnitude. Our real-time application is further enhanced by the integration of the SeisComp3 ground motion parameter estimation tool with the Earthquake Loss Estimation Routine (ELER). SeisComp3 provides the online station parameters which are then automatically incorporated into the ShakeMaps produced by ELER. The resulting ground motion distributions are used together with the building inventory to calculate expected number of buildings in various damage states. All these analysis are conducted in an automated fashion and are communicated within a few minutes of a triggering event. In our efforts to disseminate earthquake information to the general public we make extensive use of social networks such as Tweeter and collaborate with mobile phone operators.

Near Real Time Change-Point detection in Optical and Thermal Infrared Time Series Using Bayesian Inference over the Dry Chaco Forest

NASA Astrophysics Data System (ADS)

Barraza Bernadas, V.; Grings, F.; Roitberg, E.; Perna, P.; Karszenbaum, H.

2017-12-01

The Dry Chaco region (DCF) has the highest absolute deforestation rates of all Argentinian forests. The most recent report indicates a current deforestation rate of 200,000 Ha year-1. In order to better monitor this process, DCF was chosen to implement an early warning program for illegal deforestation. Although the area is intensively studied using medium resolution imagery (Landsat), the products obtained have a yearly pace and therefore unsuited for an early warning program. In this paper, we evaluated the performance of an online Bayesian change-point detection algorithm for MODIS Enhanced Vegetation Index (EVI) and Land Surface Temperature (LST) datasets. The goal was to to monitor the abrupt changes in vegetation dynamics associated with deforestation events. We tested this model by simulating 16-day EVI and 8-day LST time series with varying amounts of seasonality, noise, length of the time series and by adding abrupt changes with different magnitudes. This model was then tested on real satellite time series available through the Google Earth Engine, over a pilot area in DCF, where deforestation was common in the 2004-2016 period. A comparison with yearly benchmark products based on Landsat images is also presented (REDAF dataset). The results shows the advantages of using an automatic model to detect a changepoint in the time series than using only visual inspection techniques. Simulating time series with varying amounts of seasonality and noise, and by adding abrupt changes at different times and magnitudes, revealed that this model is robust against noise, and is not influenced by changes in amplitude of the seasonal component. Furthermore, the results compared favorably with REDAF dataset (near 65% of agreement). These results show the potential to combine LST and EVI to identify deforestation events. This work is being developed within the frame of the national Forest Law for the protection and sustainable development of Native Forest in Argentina in

Processing, Cataloguing and Distribution of Uas Images in Near Real Time

NASA Astrophysics Data System (ADS)

Runkel, I.

2013-08-01

can be checked and interpreted in near real-time. For sensible areas it gives you the possibility to inform remote decision makers or interpretation experts in order to provide them situations awareness, wherever they are. For monitoring and inspection tasks it speeds up the process of data capture and data interpretation. The fully automated workflow of data pre-processing, data georeferencing, data cataloguing and data dissemination in near real time was developed based on the Intergraph products ERDAS IMAGINE, ERDAS APOLLO and GEOSYSTEMS METAmorph!IT. It is offered as adaptable solution by GEOSYSTEMS GmbH.

The Waypoint Planning Tool: Real Time Flight Planning for Airborne Science

NASA Astrophysics Data System (ADS)

He, M.; Goodman, H. M.; Blakeslee, R.; Hall, J. M.

2010-12-01

NASA Earth science research utilizes both spaceborne and airborne real time observations in the planning and operations of its field campaigns. The coordination of air and space components is critical to achieve the goals and objectives and ensure the success of an experiment. Spaceborne imagery provides regular and continual coverage of the Earth and it is a significant component in all NASA field experiments. Real time visible and infrared geostationary images from GOES satellites and multi-spectral data from the many elements of the NASA suite of instruments aboard the TRMM, Terra, Aqua, Aura, and other NASA satellites have become norm. Similarly, the NASA Airborne Science Program draws upon a rich pool of instrumented aircraft. The NASA McDonnell Douglas DC-8, Lockheed P3 Orion, DeHavilland Twin Otter, King Air B200, Gulfstream-III are all staples of a NASA’s well-stocked, versatile hangar. A key component in many field campaigns is coordinating the aircraft with satellite overpasses, other airplanes and the constantly evolving, dynamic weather conditions. Given the variables involved, developing a good flight plan that meets the objectives of the field experiment can be a challenging and time consuming task. Planning a research aircraft mission within the context of meeting the science objectives is complex task because it is much more than flying from point A to B. Flight plans typically consist of flying a series of transects or involve dynamic path changes when “chasing” a hurricane or forest fire. These aircraft flight plans are typically designed by the mission scientists then verified and implemented by the navigator or pilot. Flight planning can be an arduous task requiring frequent sanity checks by the flight crew. This requires real time situational awareness of the weather conditions that affect the aircraft track. Scientists at the University of Alabama-Huntsville and the NASA Marshall Space Flight Center developed the Waypoint Planning Tool

Toward all weather, long record, and real-time land surface temperature retrievals from microwave satellite observations

NASA Astrophysics Data System (ADS)

Jimenez, Carlos; Prigent, Catherine; Aires, Filipe; Ermida, Sofia

2017-04-01

The land surface temperature can be estimated from satellite passive microwave observations, with limited contamination from the clouds as compared to the infrared satellite retrievals. With ˜60% cloud cover in average over the globe, there is a need for "all weather," long record, and real-time estimates of land surface temperature (Ts) from microwaves. A simple yet accurate methodology is developed to derive the land surface temperature from microwave conical scanner observations, with the help of pre-calculated land surface microwave emissivities. The method is applied to the Special Sensor Microwave/Imagers (SSM/I) and the Earth observation satellite (EOS) Advanced Microwave Scanning Radiometer (AMSR-E) observations?, regardless of the cloud cover. The SSM/I results are compared to infrared estimates from International Satellite Cloud Climatology Project (ISCCP) and from Advanced Along Track Scanning Radiometer (AATSR), under clear-sky conditions. Limited biases are observed (˜0.5 K for both comparisons) with a root-mean-square difference (RMSD) of ˜5 K, to be compared to the RMSE of ˜3.5 K between ISCCP et AATSR. AMSR-E results are compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) clear-sky estimates. As both instruments are on board the same satellite, this reduces the uncertainty associated to the observations match-up, resulting in a lower RMSD of ˜ 4K. The microwave Ts is compared to in situ Ts time series from a collection of ground stations over a large range of environments. For 22 stations available in the 2003-2004 period, SSM/I Ts agrees very well for stations in vegetated environments (down to RMSD of ˜2.5 K for several stations), but the retrieval methodology encounters difficulties under cold conditions due to the large variability of snow and ice surface emissivities. For 10 stations in the year 2010, AMSR-E presents an all-station mean RMSD of ˜4.0 K with respect tom the ground Ts. Over the same stations, MODIS

Near-infrared high-resolution real-time omnidirectional imaging platform for drone detection

NASA Astrophysics Data System (ADS)

Popovic, Vladan; Ott, Beat; Wellig, Peter; Leblebici, Yusuf

2016-10-01

Recent technological advancements in hardware systems have made higher quality cameras. State of the art panoramic systems use them to produce videos with a resolution of 9000 x 2400 pixels at a rate of 30 frames per second (fps).1 Many modern applications use object tracking to determine the speed and the path taken by each object moving through a scene. The detection requires detailed pixel analysis between two frames. In fields like surveillance systems or crowd analysis, this must be achieved in real time.2 In this paper, we focus on the system-level design of multi-camera sensor acquiring near-infrared (NIR) spectrum and its ability to detect mini-UAVs in a representative rural Swiss environment. The presented results show the UAV detection from the trial that we conducted during a field trial in August 2015.

A case of timely satellite image acquisitions in support of coastal emergency environmental response management

USGS Publications Warehouse

Ramsey, Elijah W.; Werle, Dirk; Lu, Zhong; Rangoonwala, Amina; Suzuoki, Yukihiro

2009-01-01

The synergistic application of optical and radar satellite imagery improves emergency response and advance coastal monitoring from the realm of “opportunistic” to that of “strategic.” As illustrated by the Hurricane Ike example, synthetic aperture radar imaging capabilities are clearly applicable for emergency response operations, but they are also relevant to emergency environmental management. Integrated with optical monitoring, the nearly real-time availability of synthetic aperture radar provides superior consistency in status and trends monitoring and enhanced information concerning causal forces of change that are critical to coastal resource sustainability, including flooding extent, depth, and frequency.

Real Time Data Management for Estimating Probabilities of Incidents and Near Misses

NASA Astrophysics Data System (ADS)

Stanitsas, P. D.; Stephanedes, Y. J.

2011-08-01

Advances in real-time data collection, data storage and computational systems have led to development of algorithms for transport administrators and engineers that improve traffic safety and reduce cost of road operations. Despite these advances, problems in effectively integrating real-time data acquisition, processing, modelling and road-use strategies at complex intersections and motorways remain. These are related to increasing system performance in identification, analysis, detection and prediction of traffic state in real time. This research develops dynamic models to estimate the probability of road incidents, such as crashes and conflicts, and incident-prone conditions based on real-time data. The models support integration of anticipatory information and fee-based road use strategies in traveller information and management. Development includes macroscopic/microscopic probabilistic models, neural networks, and vector autoregressions tested via machine vision at EU and US sites.

Satellite transitions acquired in real time by magic angle spinning (STARTMAS): ``Ultrafast'' high-resolution MAS NMR spectroscopy of spin I =3/2 nuclei

NASA Astrophysics Data System (ADS)

Thrippleton, Michael J.; Ball, Thomas J.; Wimperis, Stephen

2008-01-01

The satellite transitions acquired in real time by magic angle spinning (STARTMAS) NMR experiment combines a train of pulses with sample rotation at the magic angle to refocus the first- and second-order quadrupolar broadening of spin I =3/2 nuclei in a series of echoes, while allowing the isotropic chemical and quadrupolar shifts to evolve. The result is real-time isotropic NMR spectra at high spinning rates using conventional MAS equipment. In this paper we describe in detail how STARTMAS data can be acquired and processed with ease on commercial equipment. We also discuss the advantages and limitations of the approach and illustrate the discussion with numerical simulations and experimental data from four different powdered solids.

Using Open and Interoperable Ways to Publish and Access LANCE AIRS Near-Real Time Data

NASA Astrophysics Data System (ADS)

Zhao, P.; Lynnes, C.; Vollmer, B.; Savtchenko, A. K.; Yang, W.

2011-12-01

Atmospheric Infrared Sounder (AIRS) Near-Real Time (NRT) data from the Land Atmosphere Near real time Capability for EOS (LANCE) provide the information on the global and regional atmospheric state with very low latency. An open and interoperable platform is useful to facilitate access to and integration of LANCE AIRS NRT data. This paper discusses the use of open-source software components to build Web services for publishing and accessing AIRS NRT data in the context of Service Oriented Architecture (SOA). The AIRS NRT data have also been made available through an OPeNDAP server. OPeNDAP allows several open-source netCDF-based tools such as Integrated Data Viewer, Ferret and Panoply to directly display the Level 2 data over the network. To enable users to locate swath data files in the OPeNDAP server that lie within a certain geographical area, graphical "granule maps" are being added to show the outline of each file on a map of the Earth. The metadata of AIRS NRT data and services is then explored to implement information advertisement and discovery in catalogue systems. Datacasting, an RSS-based technology for accessing Earth Science data and information to facilitate the subscriptions to AIRS NRT data availability, filtering, downloading and viewing data, is also discussed. To provide an easy entry point to AIRS NRT data and services, a Web portal designed for customized data downloading and visualization is introduced.

Rainfall-induced slope failures near Los Angeles detected by time series of high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

McKinney, E.; Moon, S.

2017-12-01

Tectonically active, soil mantled, and often fire-scorched landscapes of the Los Angeles region are susceptible to slope failures, such as mudflow and landslides, during high-intensity precipitation events. During 2016-2017, this area received a precipitation rate that was 90 mm higher than the long-term precipitation rates averaged over 30 years. These precipitation rates were 24 % higher than the long-term averages and 245 % higher than those over the 2011-2016 period of drought. In this study, we examined the occurrences of slopes failures near Los Angeles in response to high rainfall rates over 2016-2017. We composited time series of high-resolution Planetscope satellite images with resolutions of 3 - 4 m/pixel for 4 selected locations after reviewing 190,000 km2 area in total. We mapped the surface changes by comparing satellite images before and after the winter 2016-2017. Preliminary analysis using spectral bands highlighted the surface changes made by mudflows, landslides, lake levels and land developments. We compared these changes across 2016-2017 with those over a period of recent drought (2011-2016) to assess the influence of high rainfall rates on slope failures.

Near Real-Time Prospecting for Lunar Volatiles: Demonstrating RESOLVE Science in the Field

NASA Astrophysics Data System (ADS)

Elphic, R. C.; Colaprete, A.; Heldmann, J. L.; Mattes, G.; Ennico, K.; Sanders, G. B.; Quinn, J.; Fritzler, E.; Marinova, M.; Roush, T. L.; Stoker, C.; Larson, W.; Picard, M.; McMurray, R.; Morse, S.

2012-12-01

The Regolith and Environment Science and Oxygen & Lunar Volatile Extraction (RESOLVE) project aims to demonstrate the utility of "in situ resource utilization". In situ resource utilization (ISRU) is a way to rebalance the economics of spaceflight by reducing or eliminating materials that must be brought up from Earth and placed on the surface of the Moon for human use. RESOLVE is developing a rover-borne payload that (1) can locate near subsurface volatiles, (2) excavate and analyze samples of the volatile-bearing regolith, and (3) demonstrate the form, extractability and usefulness of the materials. Such investigations are important not only for ISRU but are also critically important for understanding the scientific nature of these intriguing lunar polar volatile deposits. Temperature models and orbital data suggest near surface volatile concentrations may exist at briefly lit lunar polar locations outside persistently shadowed regions. A lunar rover could be remotely operated at some of these locations for the 4-7 days of expected sunlight at relatively low cost. In July 2012 the RESOLVE project conducted a full-scale field demonstration. In particular, the ability to perform the real-time measurement analysis necessary to search for volatiles and the ability to combine the various measurement techniques to meet the mission measurement and science goals. With help from the Pacific International Space Center for Exploration Systems (PISCES), a lunar rover prototype (provided by the Canadian Space Agency) was equipped with prospecting instruments (neutron spectrometer and near-infrared spectrometer), subsurface access and sampling tools, including both an auger and coring drill (provided by CSA) and subsurface sample analysis instrumentation, including a sample oven system, the Oxygen and Volatile Extraction Node (OVEN), and Gas Chromatograph / Mass Spectrometer system, the Lunar Advanced Volatile Analysis (LAVA) system. Given the relatively short time period this

Near Real Time Prospecting for Lunar Volatiles: Demonstrating RESOLVE Science in the Field

NASA Technical Reports Server (NTRS)

Elphic, Richard; Colaprete, Anthony; Heldmann, Jennifer; Mattes, Gregory W.; Ennico, Kimberly; Sanders, Gerald; Quinn, Jacqueline; Tegnerud, Erin Leigh; Marinova, Margarita; Larson, William E.;

Real-time seismic monitoring and functionality assessment of a building

USGS Publications Warehouse

Celebi, M.; ,

2005-01-01

This paper presents recent developments and approaches (using GPS technology and real-time double-integration) to obtain displacements and, in turn, drift ratios, in real-time or near real-time to meet the needs of the engineering and user community in seismic monitoring and assessing the functionality and damage condition of structures. Drift ratios computed in near real-time allow technical assessment of the damage condition of a building. Relevant parameters, such as the type of connections and story structural characteristics (including geometry) are used in computing drifts corresponding to several pre-selected threshold stages of damage. Thus, drift ratios determined from real-time monitoring can be compared to pre-computed threshold drift ratios. The approaches described herein can be used for performance evaluation of structures and can be considered as building health-monitoring applications.

Recent advances to obtain real - Time displacements for engineering applications

USGS Publications Warehouse

Celebi, M.

2005-01-01

This paper presents recent developments and approaches (using GPS technology and real-time double-integration) to obtain displacements and, in turn, drift ratios, in real-time or near real-time to meet the needs of the engineering and user community in seismic monitoring and assessing the functionality and damage condition of structures. Drift ratios computed in near real-time allow technical assessment of the damage condition of a building. Relevant parameters, such as the type of connections and story structural characteristics (including geometry) are used in computing drifts corresponding to several pre-selected threshold stages of damage. Thus, drift ratios determined from real-time monitoring can be compared to pre-computed threshold drift ratios. The approaches described herein can be used for performance evaluation of structures and can be considered as building health-monitoring applications.

Estimating Real-Time Zenith Tropospheric Delay over Africa Using IGS-RTS Products

NASA Astrophysics Data System (ADS)

Abdelazeem, M.

2017-12-01

Zenith Tropospheric Delay (ZTD) is a crucial parameter for atmospheric modeling, severe weather monitoring and forecasting applications. Currently, the international global navigation satellite system (GNSS) real-time service (IGS-RTS) products are used extensively in real-time atmospheric modeling applications. The objective of this study is to develop a real time zenith tropospheric delay estimation model over Africa using the IGS-RTS products. The real-time ZTDs are estimated based on the real-time precise point positioning (PPP) solution. GNSS observations from a number of reference stations are processed over a period of 7 days. Then, the estimated real-time ZTDs are compared with the IGS tropospheric products counterparts. The findings indicate that the estimated real-time ZTDs have millimeter level accuracy in comparison with the IGS counterparts.

Automated near-real-time clinical performance feedback for anesthesiology residents: one piece of the milestones puzzle.

PubMed

Ehrenfeld, Jesse M; McEvoy, Matthew D; Furman, William R; Snyder, Dylan; Sandberg, Warren S

2014-01-01

Anesthesiology residencies are developing trainee assessment tools to evaluate 25 milestones that map to the six core competencies. The effort will be facilitated by development of automated methods to capture, assess, and report trainee performance to program directors, the Accreditation Council for Graduate Medical Education and the trainees themselves. The authors leveraged a perioperative information management system to develop an automated, near-real-time performance capture and feedback tool that provides objective data on clinical performance and requires minimal administrative effort. Before development, the authors surveyed trainees about satisfaction with clinical performance feedback and about preferences for future feedback. Resident performance on 24,154 completed cases has been incorporated into the authors' automated dashboard, and trainees now have access to their own performance data. Eighty percent (48 of 60) of the residents responded to the feedback survey. Overall, residents "agreed/strongly agreed" that they desire frequent updates on their clinical performance on defined quality metrics and that they desired to see how they compared with the residency as a whole. Before deployment of the new tool, they "disagreed" that they were receiving feedback in a timely manner. Survey results were used to guide the format of the feedback tool that has been implemented. The authors demonstrate the implementation of a system that provides near-real-time feedback concerning resident performance on an extensible series of quality metrics, and which is responsive to requests arising from resident feedback about desired reporting mechanisms.

Automated Near Real-Time Clinical Performance Feedback for Anesthesiology Residents: One Piece of the Milestones Puzzle

PubMed Central

Ehrenfeld, Jesse M.; McEvoy, Matthew D.; Furman, William R.; Snyder, Dylan; Sandberg, Warren S.

2014-01-01

Background Anesthesiology residencies are developing trainee assessment tools to evaluate 25 milestones that map to the 6 core competencies. The effort will be facilitated by development of automated methods to capture, assess, and report trainee performance to program directors, the Accreditation Council for Graduate Medical Education and the trainees themselves. Methods We leveraged a perioperative information management system to develop an automated, near-real-time performance capture and feedback tool that provides objective data on clinical performance and requires minimal administrative effort. Prior to development, we surveyed trainees about satisfaction with clinical performance feedback and about preferences for future feedback. Results Resident performance on 24,154 completed cases has been incorporated into our automated dashboard, and trainees now have access to their own performance data. Eighty percent (48 of 60) of our residents responded to the feedback survey. Overall, residents ‘agreed/strongly agreed’ that they desire frequent updates on their clinical performance on defined quality metrics and that they desired to see how they compared to the residency as a whole. Prior to deployment of the new tool, they ‘disagreed’ that they were receiving feedback in a timely manner. Survey results were used to guide the format of the feedback tool that has been implemented. Conclusions We demonstrate the implementation of a system that provides near real-time feedback concerning resident performance on an extensible series of quality metrics, and which is responsive to requests arising from resident feedback about desired reporting mechanisms. PMID:24398735

Real-Time Tracking of the Extreme Rainfall of Hurricanes Harvey, Irma, and Maria using UCI CHRS's iRain System

NASA Astrophysics Data System (ADS)

Shearer, E. J.; Nguyen, P.; Ombadi, M.; Palacios, T.; Huynh, P.; Furman, D.; Tran, H.; Braithwaite, D.; Hsu, K. L.; Sorooshian, S.; Logan, W. S.

2017-12-01

During the 2017 hurricane season, three major hurricanes-Harvey, Irma, and Maria-devastated the Atlantic coast of the US and the Caribbean Islands. Harvey set the record for the rainiest storm in continental US history, Irma was the longest-lived powerful hurricane ever observed, and Maria was the costliest storm in Puerto Rican history. The recorded maximum precipitation totals for these storms were 65, 16, and 20 inches respectively. These events provided the Center for Hydrometeorology and Remote Sensing (CHRS) an opportunity to test its global real-time satellite precipitation observation system, iRain, for extreme storm events. The iRain system has been under development through a collaboration between CHRS at the University of California, Irvine (UCI) and UNESCO's International Hydrological Program (IHP). iRain provides near real-time high resolution (0.04°, approx. 4km) global (60°N - 60°S) satellite precipitation data estimated by the PERSIANN-Cloud Classification System (PERSIANN-CCS) algorithm developed by the scientists at CHRS. The user-interactive and web-accessible iRain system allows users to visualize and download real-time global satellite precipitation estimates and track the development and path of the current 50 largest storms globally from data generated by the PERSIANN-CCS algorithm. iRain continuously proves to be an effective tool for measuring real-time precipitation amounts of extreme storms-especially in locations that do not have extensive rain gauge or radar coverage. Such areas include large portions of the world's oceans and over continents such as Africa and Asia. CHRS also created a mobile app version of the system named "iRain UCI", available for iOS and Android devices. During these storms, real-time rainfall data generated by PERSIANN-CCS was consistently comparable to radar and rain gauge data. This presentation evaluates iRain's efficiency as a tool for extreme precipitation monitoring and provides an evaluation of the

The Real Time Mission Monitor: A Platform for Real Time Environmental Data Integration and Display during NASA Field Campaigns

NASA Astrophysics Data System (ADS)

He, M.; Hardin, D. M.; Goodman, M.; Blakeslee, R.

2008-05-01

The Real Time Mission Monitor (RTMM) is an interactive visualization application based on Google Earth, that provides situational awareness and field asset management during NASA field campaigns. The RTMM can integrate data and imagery from numerous sources including GOES-12, GOES-10, and TRMM satellites. Simultaneously, it can display data and imagery from surface observations including Nexrad, NPOL and SMART- R radars. In addition to all these it can display output from models and real-time flight tracks of all aircraft involved in the experiment. In some instances the RTMM can also display measurements from scientific instruments as they are being flown. All data are recorded and archived in an on-line system enabling playback and review of all sorties. This is invaluable in preparing for future deployments and in exercising case studies. The RTMM facilitates pre-flight planning, in-flight monitoring, development of adaptive flight strategies and post- flight data analyses and assessments. Since the RTMM is available via the internet - during the actual experiment - project managers, scientists and mission planners can collaborate no matter where they are located as long as they have a viable internet connection. In addition, the system is open so that the general public can also view the experiment, in-progress, with Google Earth. Predecessors of RTMM were originally deployed in 2002 as part of the Altus Cumulus Electrification Study (ACES) to monitor uninhabited aerial vehicles near thunderstorms. In 2005 an interactive Java-based web prototype supported the airborne Lightning Instrument Package (LIP) during the Tropical Cloud Systems and Processes (TCSP) experiment. In 2006 the technology was adapted to the 3D Google Earth virtual globe and in 2007 its capabilities were extended to support multiple NASA aircraft (ER-2, WB-57, DC-8) during Tropical Composition, Clouds and Climate Coupling (TC4) experiment and 2007 Summer Aerosonde field study. In April 2008

Real-Time Tropospheric Delay Estimation using IGS Products

NASA Astrophysics Data System (ADS)

Stürze, Andrea; Liu, Sha; Söhne, Wolfgang

2014-05-01

The Federal Agency for Cartography and Geodesy (BKG) routinely provides zenith tropospheric delay (ZTD) parameter for the assimilation in numerical weather models since more than 10 years. Up to now the results flowing into the EUREF Permanent Network (EPN) or E-GVAP (EUMETNET EIG GNSS water vapour programme) analysis are based on batch processing of GPS+GLONASS observations in differential network mode. For the recently started COST Action ES1206 about "Advanced Global Navigation Satellite Systems tropospheric products for monitoring severe weather events and climate" (GNSS4SWEC), however, rapid updates in the analysis of the atmospheric state for nowcasting applications require changing the processing strategy towards real-time. In the RTCM SC104 (Radio Technical Commission for Maritime Services, Special Committee 104) a format combining the advantages of Precise Point Positioning (PPP) and Real-Time Kinematic (RTK) is under development. The so-called State Space Representation approach is defining corrections, which will be transferred in real-time to the user e.g. via NTRIP (Network Transport of RTCM via Internet Protocol). Meanwhile messages for precise orbits, satellite clocks and code biases compatible to the basic PPP mode using IGS products are defined. Consequently, the IGS Real-Time Service (RTS) was launched in 2013 in order to extend the well-known precise orbit and clock products by a real-time component. Further messages e.g. with respect to ionosphere or phase biases are foreseen. Depending on the level of refinement, so different accuracies up to the RTK level shall be reachable. In co-operation of BKG and the Technical University of Darmstadt the real-time software GEMon (GREF EUREF Monitoring) is under development. GEMon is able to process GPS and GLONASS observation and RTS product data streams in PPP mode. Furthermore, several state-of-the-art troposphere models, for example based on numerical weather prediction data, are implemented. Hence, it

Analysis of GPS Data Using Near Real-Time Data from the Volcano Exploration Project in the Community College Classroom (Invited)

NASA Astrophysics Data System (ADS)

House, M.; Nagy-Shadman, E.; Wilbur, B.

2010-12-01

Using real-time data or near-real-time data in the classroom is an exciting prospect in Introductory Physical Geology courses, especially since it promises to offer students a chance to experience the excitement and uncertainty associated with the study of the natural world that appeals to so many of their instructors. However, there are several obstacles to this approach in the community college. Namely, many introductory level community college earth science courses have no mathematics prerequisites; as such, a typical classroom may include a wide range of mathematical skills and many students may be unable to participate in the analysis of “real” data. Further, reliable computer access to websites offering real-time data can be spotty at some institutions and for some students on home computers. In response to this problem we have created a multipart volcano monitoring activity based on the USGS Volcano Exploration Project: Pu`u `O`o (VEPP) website. This activity is designed for freshman or sophomore level courses in Introductory Geology or Geological Hazards for non-majors. No prior math skills are assumed; the activity can be completed without prior knowledge of GPS data, volcano monitoring or Hawaiian geology. The activity consists of three parts: (1) a background lecture on basic geology of volcanoes like Kilauea and use of GPS in volcano monitoring; (2) a lab activity or a homework assignment based on near real-time data downloaded from the VEPP website; and (3) a group wrap-up that focuses on real-time data by exploring other aspects of the VEPP website. The lab activity requires examination of downloaded GPS time series data for a specified time period (this can be modified as desired by the instructor), computation of displacements, graphing of displacement vectors for identified time intervals and determination of actual motion vectors, followed by a discussion of the displacements observed. These activities are interspersed by guided questions

Real-Time PPP Based on the Coupling Estimation of Clock Bias and Orbit Error with Broadcast Ephemeris.

PubMed

Pan, Shuguo; Chen, Weirong; Jin, Xiaodong; Shi, Xiaofei; He, Fan

2015-07-22

Satellite orbit error and clock bias are the keys to precise point positioning (PPP). The traditional PPP algorithm requires precise satellite products based on worldwide permanent reference stations. Such an algorithm requires considerable work and hardly achieves real-time performance. However, real-time positioning service will be the dominant mode in the future. IGS is providing such an operational service (RTS) and there are also commercial systems like Trimble RTX in operation. On the basis of the regional Continuous Operational Reference System (CORS), a real-time PPP algorithm is proposed to apply the coupling estimation of clock bias and orbit error. The projection of orbit error onto the satellite-receiver range has the same effects on positioning accuracy with clock bias. Therefore, in satellite clock estimation, part of the orbit error can be absorbed by the clock bias and the effects of residual orbit error on positioning accuracy can be weakened by the evenly distributed satellite geometry. In consideration of the simple structure of pseudorange equations and the high precision of carrier-phase equations, the clock bias estimation method coupled with orbit error is also improved. Rovers obtain PPP results by receiving broadcast ephemeris and real-time satellite clock bias coupled with orbit error. By applying the proposed algorithm, the precise orbit products provided by GNSS analysis centers are rendered no longer necessary. On the basis of previous theoretical analysis, a real-time PPP system was developed. Some experiments were then designed to verify this algorithm. Experimental results show that the newly proposed approach performs better than the traditional PPP based on International GNSS Service (IGS) real-time products. The positioning accuracies of the rovers inside and outside the network are improved by 38.8% and 36.1%, respectively. The PPP convergence speeds are improved by up to 61.4% and 65.9%. The new approach can change the

Central Satellite Data Repository Supporting Research and Development

NASA Astrophysics Data System (ADS)

Han, W.; Brust, J.

2015-12-01

Near real-time satellite data is critical to many research and development activities of atmosphere, land, and ocean processes. Acquiring and managing huge volumes of satellite data without (or with less) latency in an organization is always a challenge in the big data age. An organization level data repository is a practical solution to meeting this challenge. The STAR (Center for Satellite Applications and Research of NOAA) Central Data Repository (SCDR) is a scalable, stable, and reliable repository to acquire, manipulate, and disseminate various types of satellite data in an effective and efficient manner. SCDR collects more than 200 data products, which are commonly used by multiple groups in STAR, from NOAA, GOES, Metop, Suomi NPP, Sentinel, Himawari, and other satellites. The processes of acquisition, recording, retrieval, organization, and dissemination are performed in parallel. Multiple data access interfaces, like FTP, FTPS, HTTP, HTTPS, and RESTful, are supported in the SCDR to obtain satellite data from their providers through high speed internet. The original satellite data in various raster formats can be parsed in the respective adapter to retrieve data information. The data information is ingested to the corresponding partitioned tables in the central database. All files are distributed equally on the Network File System (NFS) disks to balance the disk load. SCDR provides consistent interfaces (including Perl utility, portal, and RESTful Web service) to locate files of interest easily and quickly and access them directly by over 200 compute servers via NFS. SCDR greatly improves collection and integration of near real-time satellite data, addresses satellite data requirements of scientists and researchers, and facilitates their primary research and development activities.

Status of IGS Ultra-Rapid Products for Real-Time Applications

NASA Astrophysics Data System (ADS)

Ray, J.; Griffiths, J.

2008-12-01

Since November 2000 the International GNSS Service (IGS) has produced Ultra-rapid (IGU) products for near real-time and real-time applications. They include GPS orbits, satellite clocks, and Earth rotation parameters for a sliding 48-hr period. The first day of each update is based on the most recent GPS observational data from the IGS hourly tracking network. At the time of release, these observed products have an initial latency of 3 hr. The second day of each update consists of predictions. So the predictions between about 3 and 9 hr into the second half are relevant for true real-time uses. Originally updated twice daily, the IGU products since April 2004 have been issued four times per day, at 3, 9, 15, and 21 UTC. Up to seven Analysis Centers (ACs) contribute to the IGU combinations: Astronomical Institute of the University of Berne (AIUB), European Space Operations Center (ESOC), Geodetic Observatory Pecny (GOP), GeoForschungsZentrum (GFZ) Potsdam, Natural Resources Canada (NRC), Scripps Insitution of Oceanography (SIO), U.S. Naval Observatory (USNO). This redundancy affords a high measure of reliability and enhanced orbit accuracy. IGU orbit precision has improved markedly since late 2007. This is due to a combination of factors: decommissioning of the old, poorly behaved PRN29 in October 2007; upgraded procedures implemented by GOP around the same time, by SIO in spring 2008, and by USNO in June 2008; better handling of maneuvered satellites at the combination level starting June 2008; and stricter AC rejection criteria since July 2008. As a consequence, the weighted 1D RMS residual of the IGU orbit predictions over their first 6 hr is currently about 20 to 30 mm (after a Helmert transformation) compared to the IGS Rapid orbits, averaged over the constellation. The median residual is about 15 to 20 mm. When extended to the full 24 hr prediction period, the IGU orbit errors approximately double. Systematic rotational offsets are probably more important than

Real Time, On Line Crop Monitoring and Analysis with Near Global Landsat-class Mosaics

NASA Astrophysics Data System (ADS)

Varlyguin, D.; Hulina, S.; Crutchfield, J.; Reynolds, C. A.; Frantz, R.

2015-12-01

The presentation will discuss the current status of GDA technology for operational, automated generation of 10-30 meter near global mosaics of Landsat-class data for visualization, monitoring, and analysis. Current version of the mosaic combines Landsat 8 and Landsat 7. Sentinel-2A imagery will be added once it is operationally available. The mosaics are surface reflectance calibrated and are analysis ready. They offer full spatial resolution and all multi-spectral bands of the source imagery. Each mosaic covers all major agricultural regions of the world and 16 day time window. 2014-most current dates are supported. The mosaics are updated in real-time, as soon as GDA downloads Landsat imagery, calibrates it to the surface reflectances, and generates data gap masks (all typically under 10 minutes for a Landsat scene). The technology eliminates the complex, multi-step, hands-on process of data preparation and provides imagery ready for repetitive, field-to-country analysis of crop conditions, progress, acreages, yield, and production. The mosaics can be used for real-time, on-line interactive mapping and time series drilling via GeoSynergy webGIS platform. The imagery is of great value for improved, persistent monitoring of global croplands and for the operational in-season analysis and mapping of crops across the globe in USDA FAS purview as mandated by the US government. The presentation will overview operational processing of Landsat-class mosaics in support of USDA FAS efforts and will look into 2015 and beyond.

The Use of OMPS Near Real Time Products in Volcanic Cloud Risk Mitigation and Smoke/Dust Air Quality Assessments

NASA Astrophysics Data System (ADS)

Seftor, C. J.; Krotkov, N. A.; McPeters, R. D.; Li, J. Y.; Durbin, P. B.

2015-12-01

Near real time (NRT) SO2 and aerosol index (AI) imagery from Aura's Ozone Monitoring Instrument (OMI) has proven invaluable in mitigating the risk posed to air traffic by SO2 and ash clouds from volcanic eruptions. The OMI products, generated as part of NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) NRT system and available through LANCE and both NOAA's NESDIS and ESA's Support to Aviation Control Service (SACS) portals, are used to monitor the current location of volcanic clouds and to provide input into Volcanic Ash (VA) advisory forecasts. NRT products have recently been developed using data from the Ozone Mapping and Profiler Suite onboard the Suomi NPP platform; they are currently being made available through the SACS portal and will shortly be incorporated into the LANCE NRT system. We will show examples of the use of OMPS NRT SO2 and AI imagery to monitor recent volcanic eruption events. We will also demonstrate the usefulness of OMPS AI imagery to detect and track dust storms and smoke from fires, and how this information can be used to forecast their impact on air quality in areas far removed from their source. Finally, we will show SO2 and AI imagery generated from our OMPS Direct Broadcast data to highlight the capability of our real time system.

Real time sensor for therapeutic radiation delivery

DOEpatents

Bliss, Mary; Craig, Richard A.; Reeder, Paul L.

1998-01-01

The invention is a real time sensor for therapeutic radiation. A probe is placed in or near the patient that senses in real time the dose at the location of the probe. The strength of the dose is determined by either an insertion or an exit probe. The location is determined by a series of vertical and horizontal sensing elements that gives the operator a real time read out dose location relative to placement of the patient. The increased accuracy prevents serious tissue damage to the patient by preventing overdose or delivery of a dose to a wrong location within the body.

The ASTER emergency scheduling system: A new project linking near-real-time satellite monitoring of disasters to the acquisition of high-resolution remote sensing data

NASA Astrophysics Data System (ADS)

Ramsey, M.; Dehn, J.; Wessels, R.; Byrnes, J.; Duda, K.; Maldonado, L.; Dwyer, J.

2004-12-01

organizations and the ASTER project, we expect to minimize lag time and use existing monitoring tools as triggers for the emergency response of ASTER. The first phase of this project will be integrated into the Alaska Volcano Observatory's current near-real-time volcanic monitoring system, which relies on high temporal/low spatial resolution orbital data. This synergy will allow small-scale activity to be targeted for science and response, and a calibration baseline between each sensor to be established. If successful, this will be the first time that high spatial resolution, multispectral satellite data will be routinely scheduled, acquired, and analyzed in a "rapid response" mode within an existing hazard monitoring framework. Initial testing of this system is now underway using data from previous eruptions in the north Pacific region, and modifications to the rapid data flow procedure within the ASTER science and support structure has begun.

Progress in using real-time GPS for seismic monitoring of the Cascadia megathrust

NASA Astrophysics Data System (ADS)

Szeliga, W. M.; Melbourne, T. I.; Santillan, V. M.; Scrivner, C.; Webb, F.

2014-12-01

We report on progress in our development of a comprehensive real-time GPS-based seismic monitoring system for the Cascadia subduction zone. This system is based on 1 Hz point position estimates computed in the ITRF08 reference frame. Convergence from phase and range observables to point position estimates is accelerated using a Kalman filter based, on-line stream editor. Positions are estimated using a short-arc approach and algorithms from JPL's GIPSY-OASIS software with satellite clock and orbit products from the International GNSS Service (IGS). The resulting positions show typical RMS scatter of 2.5 cm in the horizontal and 5 cm in the vertical with latencies below 2 seconds. To facilitate the use of these point position streams for applications such as seismic monitoring, we broadcast real-time positions and covariances using custom-built streaming software. This software is capable of buffering 24-hour streams for hundreds of stations and providing them through a REST-ful web interface. To demonstrate the power of this approach, we have developed a Java-based front-end that provides a real-time visual display of time-series, vector displacement, and contoured peak ground displacement. We have also implemented continuous estimation of finite fault slip along the Cascadia megathrust using an NIF approach. The resulting continuous slip distributions are combined with pre-computed tsunami Green's functions to generate real-time tsunami run-up estimates for the entire Cascadia coastal margin. This Java-based front-end is available for download through the PANGA website. We currently analyze 80 PBO and PANGA stations along the Cascadia margin and are gearing up to process all 400+ real-time stations operating in the Pacific Northwest, many of which are currently telemetered in real-time to CWU. These will serve as milestones towards our over-arching goal of extending our processing to include all of the available real-time streams from the Pacific rim. In addition

Near real-time, on-the-move software PED using VPEF

NASA Astrophysics Data System (ADS)

Green, Kevin; Geyer, Chris; Burnette, Chris; Agarwal, Sanjeev; Swett, Bruce; Phan, Chung; Deterline, Diane

2015-05-01

The scope of the Micro-Cloud for Operational, Vehicle-Based EO-IR Reconnaissance System (MOVERS) development effort, managed by the Night Vision and Electronic Sensors Directorate (NVESD), is to develop, integrate, and demonstrate new sensor technologies and algorithms that improve improvised device/mine detection using efficient and effective exploitation and fusion of sensor data and target cues from existing and future Route Clearance Package (RCP) sensor systems. Unfortunately, the majority of forward looking Full Motion Video (FMV) and computer vision processing, exploitation, and dissemination (PED) algorithms are often developed using proprietary, incompatible software. This makes the insertion of new algorithms difficult due to the lack of standardized processing chains. In order to overcome these limitations, EOIR developed the Government off-the-shelf (GOTS) Video Processing and Exploitation Framework (VPEF) to be able to provide standardized interfaces (e.g., input/output video formats, sensor metadata, and detected objects) for exploitation software and to rapidly integrate and test computer vision algorithms. EOIR developed a vehicle-based computing framework within the MOVERS and integrated it with VPEF. VPEF was further enhanced for automated processing, detection, and publishing of detections in near real-time, thus improving the efficiency and effectiveness of RCP sensor systems.

Near-infrared indocyanine dye permits real-time characterization of both venous and lymphatic circulation

NASA Astrophysics Data System (ADS)

Kurahashi, Toshikazu; Iwatsuki, Katsuyuki; Onishi, Tetsuro; Arai, Tetsuya; Teranishi, Katsunori; Hirata, Hitoshi

2016-08-01

We investigated the optical properties of a near-infrared (NIR) fluorochrome, di-β-cyclodextrin-binding indocyanine derivative (TK-1), and its pharmacokinetic differences with indocyanine green (ICG). TK-1 was designed to have hydrophilic cyclodextrin molecules and, thus, for higher water solubility and smaller particle sizes than the plasma protein-bound ICG. We compared optical properties such as the absorption and fluorescence spectra, quantum yield, and photostability between both dyes in vitro. In addition, we subcutaneously injected a 1 mM solution of TK-1 or ICG into the hind footpad of rats and observed real-time NIR fluorescence intensities in their femoral veins and accompanying lymphatics at the exposed groin site to analyze the dye pharmacokinetics. These optical experiments demonstrated that TK-1 has high water solubility, a low self-aggregation tendency, and high optical and chemical stabilities. Our in vivo imaging showed that TK-1 was transported via peripheral venous flow and lymphatic flow, whereas ICG was drained only through lymphatics. The results of this study showed that lymphatic and venous transport can be differentially regulated and is most likely influenced primarily by particle size, and that TK-1 can enable real-time NIR fluorescence imaging of whole fluids and solute movement via both microvessels and lymphatics, which conventional ICG cannot achieve.

Near Real-Time Monitoring of Global Evapotranspiration and its Application to Water Resource Management

NASA Astrophysics Data System (ADS)

Halverson, G. H.; Fisher, J.; Jewell, L. A.; Moore, G.; Verma, M.; McDonald, T.; Kim, S.; Muniz, A.

2016-12-01

Water scarcity and its impact on agriculture is a pressing world concern. At the heart of this crisis is the balance of water exchange between the land and the atmosphere. The ability to monitor evapotranspiration provides a solution by enabling sustainable irrigation practices. The Priestley-Taylor Jet Propulsion Laboratory model of evapotranspiration has been implemented to meet this need as a daily MODIS product with 1 to 5 km resolution. An automated data pipeline for this model implementation provides daily data with global coverage and near real-time latency using the Geospatial Data Abstraction Library. An interactive map providing on-demand statistical analysis enables water resource managers to monitor rates of water loss. To demonstrate the application of remotely-sensed evapotranspiration to water resource management, a partnership has been arranged with the New Mexico Office of the State Engineer (NMOSE). The online water research management tool was developed to meet the specifications of NMOSE using the Leaflet, GeoServer, and Django frameworks. NMOSE will utilize this tool to monitor drought and fire risk and manage irrigation. Through this test-case, it is hoped that real-time, user-friendly remote sensing tools will be adopted globally to make resource management decisions informed by the NASA Earth Observation System.

Development of a globally applicable model for near real-time prediction of seismically induced landslides

USGS Publications Warehouse

Nowicki, M. Anna; Wald, David J.; Hamburger, Michael W.; Hearne, Mike; Thompson, Eric M.

2014-01-01

Substantial effort has been invested to understand where seismically induced landslides may occur in the future, as they are a costly and frequently fatal threat in mountainous regions. The goal of this work is to develop a statistical model for estimating the spatial distribution of landslides in near real-time around the globe for use in conjunction with the U.S. Geological Survey (USGS) Prompt Assessment of Global Earthquakes for Response (PAGER) system. This model uses standardized outputs of ground shaking from the USGS ShakeMap Atlas 2.0 to develop an empirical landslide probability model, combining shaking estimates with broadly available landslide susceptibility proxies, i.e., topographic slope, surface geology, and climate parameters. We focus on four earthquakes for which digitally mapped landslide inventories and well-constrainedShakeMaps are available. The resulting database is used to build a predictive model of the probability of landslide occurrence. The landslide database includes the Guatemala (1976), Northridge (1994), Chi-Chi (1999), and Wenchuan (2008) earthquakes. Performance of the regression model is assessed using statistical goodness-of-fit metrics and a qualitative review to determine which combination of the proxies provides both the optimum prediction of landslide-affected areas and minimizes the false alarms in non-landslide zones. Combined with near real-time ShakeMaps, these models can be used to make generalized predictions of whether or not landslides are likely to occur (and if so, where) for earthquakes around the globe, and eventually to inform loss estimates within the framework of the PAGER system.

Near real time, accurate, and sensitive microbiological safety monitoring using an all-fibre spectroscopic fluorescence system

NASA Astrophysics Data System (ADS)

Vanholsbeeck, F.; Swift, S.; Cheng, M.; Bogomolny, E.

2013-11-01

Enumeration of microorganisms is an essential microbiological task for many industrial sectors and research fields. Various tests for detection and counting of microorganisms are used today. However most of the current methods to enumerate bacteria require either long incubation time for limited accuracy, or use complicated protocols along with bulky equipment. We have developed an accurate, all-fibre spectroscopic system to measure fluorescence signal in-situ. In this paper, we examine the potential of this setup for near real time bacteria enumeration in aquatic environment. The concept is based on a well-known phenomenon that the fluorescence quantum yields of some nucleic acid stains significantly increase upon binding with nucleic acids of microorganisms. In addition we have used GFP labeled organisms. The fluorescence signal increase can be correlated to the amount of nucleic acid present in the sample. In addition we have used GFP labeled organisms. Our results show that we are able to detect a wide range of bacteria concentrations without dilution or filtration (1-108 CFU/ml) using different optical probes we designed. This high sensitivity is due to efficient light delivery with an appropriate collection volume and in situ fluorescence detection as well as the use of a sensitive CCD spectrometer. By monitoring the laser power, we can account for laser fluctuations while measuring the fluorescence signal which improves as well the system accuracy. A synchronized laser shutter allows us to achieve a high SNR with minimal integration time, thereby reducing the photobleaching effect. In summary, we conclude that our optical setup may offer a robust method for near real time bacterial detection in aquatic environment.

Real-time monitoring of a coffee roasting process with near infrared spectroscopy using multivariate statistical analysis: A feasibility study.

PubMed

Catelani, Tiago A; Santos, João Rodrigo; Páscoa, Ricardo N M J; Pezza, Leonardo; Pezza, Helena R; Lopes, João A

2018-03-01

This work proposes the use of near infrared (NIR) spectroscopy in diffuse reflectance mode and multivariate statistical process control (MSPC) based on principal component analysis (PCA) for real-time monitoring of the coffee roasting process. The main objective was the development of a MSPC methodology able to early detect disturbances to the roasting process resourcing to real-time acquisition of NIR spectra. A total of fifteen roasting batches were defined according to an experimental design to develop the MSPC models. This methodology was tested on a set of five batches where disturbances of different nature were imposed to simulate real faulty situations. Some of these batches were used to optimize the model while the remaining was used to test the methodology. A modelling strategy based on a time sliding window provided the best results in terms of distinguishing batches with and without disturbances, resourcing to typical MSPC charts: Hotelling's T 2 and squared predicted error statistics. A PCA model encompassing a time window of four minutes with three principal components was able to efficiently detect all disturbances assayed. NIR spectroscopy combined with the MSPC approach proved to be an adequate auxiliary tool for coffee roasters to detect faults in a conventional roasting process in real-time. Copyright © 2017 Elsevier B.V. All rights reserved.

A Review on Real-Time 3D Ultrasound Imaging Technology

PubMed Central

Zeng, Zhaozheng

2017-01-01

Real-time three-dimensional (3D) ultrasound (US) has attracted much more attention in medical researches because it provides interactive feedback to help clinicians acquire high-quality images as well as timely spatial information of the scanned area and hence is necessary in intraoperative ultrasound examinations. Plenty of publications have been declared to complete the real-time or near real-time visualization of 3D ultrasound using volumetric probes or the routinely used two-dimensional (2D) probes. So far, a review on how to design an interactive system with appropriate processing algorithms remains missing, resulting in the lack of systematic understanding of the relevant technology. In this article, previous and the latest work on designing a real-time or near real-time 3D ultrasound imaging system are reviewed. Specifically, the data acquisition techniques, reconstruction algorithms, volume rendering methods, and clinical applications are presented. Moreover, the advantages and disadvantages of state-of-the-art approaches are discussed in detail. PMID:28459067

A Review on Real-Time 3D Ultrasound Imaging Technology.

PubMed

Huang, Qinghua; Zeng, Zhaozheng

2017-01-01

Real-time three-dimensional (3D) ultrasound (US) has attracted much more attention in medical researches because it provides interactive feedback to help clinicians acquire high-quality images as well as timely spatial information of the scanned area and hence is necessary in intraoperative ultrasound examinations. Plenty of publications have been declared to complete the real-time or near real-time visualization of 3D ultrasound using volumetric probes or the routinely used two-dimensional (2D) probes. So far, a review on how to design an interactive system with appropriate processing algorithms remains missing, resulting in the lack of systematic understanding of the relevant technology. In this article, previous and the latest work on designing a real-time or near real-time 3D ultrasound imaging system are reviewed. Specifically, the data acquisition techniques, reconstruction algorithms, volume rendering methods, and clinical applications are presented. Moreover, the advantages and disadvantages of state-of-the-art approaches are discussed in detail.

Near real-time vaccine safety surveillance with partially accrued data.

PubMed

Greene, Sharon K; Kulldorff, Martin; Yin, Ruihua; Yih, W Katherine; Lieu, Tracy A; Weintraub, Eric S; Lee, Grace M

2011-06-01

The Vaccine Safety Datalink (VSD) Project conducts near real-time vaccine safety surveillance using sequential analytic methods. Timely surveillance is critical in identifying potential safety problems and preventing additional exposure before most vaccines are administered. For vaccines that are administered during a short period, such as influenza vaccines, timeliness can be improved by undertaking analyses while risk windows following vaccination are ongoing and by accommodating predictable and unpredictable data accrual delays. We describe practical solutions to these challenges, which were adopted by the VSD Project during pandemic and seasonal influenza vaccine safety surveillance in 2009/2010. Adjustments were made to two sequential analytic approaches. The Poisson-based approach compared the number of pre-defined adverse events observed following vaccination with the number expected using historical data. The expected number was adjusted for the proportion of the risk window elapsed and the proportion of inpatient data estimated to have accrued. The binomial-based approach used a self-controlled design, comparing the observed numbers of events in risk versus comparison windows. Events were included in analysis only if they occurred during a week that had already passed for both windows. Analyzing data before risk windows fully elapsed improved the timeliness of safety surveillance. Adjustments for data accrual lags were tailored to each data source and avoided biasing analyses away from detecting a potential safety problem, particularly early during surveillance. The timeliness of vaccine and drug safety surveillance can be improved by properly accounting for partially elapsed windows and data accrual delays. Copyright © 2011 John Wiley & Sons, Ltd.

Application of troposphere model from NWP and GNSS data into real-time precise positioning

NASA Astrophysics Data System (ADS)

Wilgan, Karina; Hadas, Tomasz; Kazmierski, Kamil; Rohm, Witold; Bosy, Jaroslaw

2016-04-01

The tropospheric delay empirical models are usually functions of meteorological parameters (temperature, pressure and humidity). The application of standard atmosphere parameters or global models, such as GPT (global pressure/temperature) model or UNB3 (University of New Brunswick, version 3) model, may not be sufficient, especially for positioning in non-standard weather conditions. The possible solution is to use regional troposphere models based on real-time or near-real time measurements. We implement a regional troposphere model into the PPP (Precise Point Positioning) software GNSS-WARP (Wroclaw Algorithms for Real-time Positioning) developed at Wroclaw University of Environmental and Life Sciences. The software is capable of processing static and kinematic multi-GNSS data in real-time and post-processing mode and takes advantage of final IGS (International GNSS Service) products as well as IGS RTS (Real-Time Service) products. A shortcoming of PPP technique is the time required for the solution to converge. One of the reasons is the high correlation among the estimated parameters: troposphere delay, receiver clock offset and receiver height. To efficiently decorrelate these parameters, a significant change in satellite geometry is required. Alternative solution is to introduce the external high-quality regional troposphere delay model to constrain troposphere estimates. The proposed model consists of zenith total delays (ZTD) and mapping functions calculated from meteorological parameters from Numerical Weather Prediction model WRF (Weather Research and Forecasting) and ZTDs from ground-based GNSS stations using the least-squares collocation software COMEDIE (Collocation of Meteorological Data for Interpretation and Estimation of Tropospheric Pathdelays) developed at ETH Zurich.

Real-time Enhanced Vision System

NASA Technical Reports Server (NTRS)

Hines, Glenn D.; Rahman, Zia-Ur; Jobson, Daniel J.; Woodell, Glenn A.; Harrah, Steven D.

2005-01-01

Flying in poor visibility conditions, such as rain, snow, fog or haze, is inherently dangerous. However these conditions can occur at nearly any location, so inevitably pilots must successfully navigate through them. At NASA Langley Research Center (LaRC), under support of the Aviation Safety and Security Program Office and the Systems Engineering Directorate, we are developing an Enhanced Vision System (EVS) that combines image enhancement and synthetic vision elements to assist pilots flying through adverse weather conditions. This system uses a combination of forward-looking infrared and visible sensors for data acquisition. A core function of the system is to enhance and fuse the sensor data in order to increase the information content and quality of the captured imagery. These operations must be performed in real-time for the pilot to use while flying. For image enhancement, we are using the LaRC patented Retinex algorithm since it performs exceptionally well for improving low-contrast range imagery typically seen during poor visibility conditions. In general, real-time operation of the Retinex requires specialized hardware. To date, we have successfully implemented a single-sensor real-time version of the Retinex on several different Digital Signal Processor (DSP) platforms. In this paper we give an overview of the EVS and its performance requirements for real-time enhancement and fusion and we discuss our current real-time Retinex implementations on DSPs.

Real-time enhanced vision system

NASA Astrophysics Data System (ADS)

Hines, Glenn D.; Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.; Harrah, Steven D.

2005-05-01

Flying in poor visibility conditions, such as rain, snow, fog or haze, is inherently dangerous. However these conditions can occur at nearly any location, so inevitably pilots must successfully navigate through them. At NASA Langley Research Center (LaRC), under support of the Aviation Safety and Security Program Office and the Systems Engineering Directorate, we are developing an Enhanced Vision System (EVS) that combines image enhancement and synthetic vision elements to assist pilots flying through adverse weather conditions. This system uses a combination of forward-looking infrared and visible sensors for data acquisition. A core function of the system is to enhance and fuse the sensor data in order to increase the information content and quality of the captured imagery. These operations must be performed in real-time for the pilot to use while flying. For image enhancement, we are using the LaRC patented Retinex algorithm since it performs exceptionally well for improving low-contrast range imagery typically seen during poor visibility poor visibility conditions. In general, real-time operation of the Retinex requires specialized hardware. To date, we have successfully implemented a single-sensor real-time version of the Retinex on several different Digital Signal Processor (DSP) platforms. In this paper we give an overview of the EVS and its performance requirements for real-time enhancement and fusion and we discuss our current real-time Retinex implementations on DSPs.

On the analytic lunar and solar perturbations of a near earth satellite

NASA Technical Reports Server (NTRS)

Estes, R. H.

1972-01-01

The disturbing function of the moon (sun) is expanded as a sum of products of two harmonic functions, one depending on the position of the satellite and the other on the position of the moon (sun). The harmonic functions depending on the position of the perturbing body are developed into trigonometric series with the ecliptic elements l, l', F, D, and Gamma of the lunar theory which are nearly linear with respect to time. Perturbation of elements are in the form of trigonometric series with the ecliptic lunar elements and the equatorial elements omega and Omega of the satellite so that analytic integration is simple and the results accurate over a long period of time.

Real-Time Continuous Response Spectra Exceedance Calculation

NASA Astrophysics Data System (ADS)

Vernon, Frank; Harvey, Danny; Lindquist, Kent; Franke, Mathias

2017-04-01

A novel approach is presented for near real-time earthquake alarms for critical structures at distributed locations using real-time estimation of response spectra obtained from near free-field motions. Influential studies dating back to the 1980s identified spectral response acceleration as a key ground motion characteristic that correlates well with observed damage in structures. Thus, monitoring and reporting on exceedance of spectra-based thresholds are useful tools for assessing the potential for damage to facilities or multi-structure campuses based on input ground motions only. With as little as one strong-motion station per site, this scalable approach can provide rapid alarms on the damage status of remote towns, critical infrastructure (e.g., hospitals, schools) and points of interests (e.g., bridges) for a very large number of locations enabling better rapid decision making during critical and difficult immediate post-earthquake response actions. Real-time calculation of PSA exceedance and alarm dissemination are enabled with Bighorn, a module included in the Antelope software package that combines real-time spectral monitoring and alarm capabilities with a robust built-in web display server. Examples of response spectra from several M 5 events recorded by the ANZA seismic network in southern California will be presented.

Effect of general relativity on a near-Earth satellite in the geocentric and barycentric reference frames

NASA Technical Reports Server (NTRS)

Ries, J. C.; Huang, C.; Watkins, M. M.

1988-01-01

Whether one uses a solar-system barycentric frame or a geocentric frame when including the general theory of relativity in orbit determinations for near-Earth satellites, the results should be equivalent to some limiting accuracy. The purpose of this paper is to clarify the effects of relativity in each frame and to demonstrate their equivalence through the analysis of real laser-tracking data. A correction to the conventional barycentric equations of motion is shown to be required.

Satellite-Based Precipitation Datasets

NASA Astrophysics Data System (ADS)

Munchak, S. J.; Huffman, G. J.

2017-12-01

Of the possible sources of precipitation data, those based on satellites provide the greatest spatial coverage. There is a wide selection of datasets, algorithms, and versions from which to choose, which can be confusing to non-specialists wishing to use the data. The International Precipitation Working Group (IPWG) maintains tables of the major publicly available, long-term, quasi-global precipitation data sets (http://www.isac.cnr.it/ ipwg/data/datasets.html), and this talk briefly reviews the various categories. As examples, NASA provides two sets of quasi-global precipitation data sets: the older Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and current Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG). Both provide near-real-time and post-real-time products that are uniformly gridded in space and time. The TMPA products are 3-hourly 0.25°x0.25° on the latitude band 50°N-S for about 16 years, while the IMERG products are half-hourly 0.1°x0.1° on 60°N-S for over 3 years (with plans to go to 16+ years in Spring 2018). In addition to the precipitation estimates, each data set provides fields of other variables, such as the satellite sensor providing estimates and estimated random error. The discussion concludes with advice about determining suitability for use, the necessity of being clear about product names and versions, and the need for continued support for satellite- and surface-based observation.

Quality of Service for Real-Time Applications Over Next Generation Data Networks

NASA Technical Reports Server (NTRS)

Ivancic, William; Atiquzzaman, Mohammed; Bai, Haowei; Su, Hongjun; Jain, Raj; Duresi, Arjan; Goyal, Mukyl; Bharani, Venkata; Liu, Chunlei; Kota, Sastri

2001-01-01

This project, which started on January 1, 2000, was funded by NASA Glenn Research Center for duration of one year. The deliverables of the project included the following tasks: Study of QoS mapping between the edge and core networks envisioned in the Next Generation networks will provide us with the QoS guarantees that can be obtained from next generation networks. Buffer management techniques to provide strict guarantees to real-time end-to-end applications through preferential treatment to packets belonging to real-time applications. In particular, use of ECN to help reduce the loss on high bandwidth-delay product satellite networks needs to be studied. Effect of Prioritized Packet Discard to increase goodput of the network and reduce the buffering requirements in the ATM switches. Provision of new IP circuit emulation services over Satellite IP backbones using MPLS will be studied. Determine the architecture and requirements for internetworking ATN and the Next Generation Internet for real-time applications.

Real time sensor for therapeutic radiation delivery

DOEpatents

Bliss, M.; Craig, R.A.; Reeder, P.L.

1998-01-06

The invention is a real time sensor for therapeutic radiation. A probe is placed in or near the patient that senses in real time the dose at the location of the probe. The strength of the dose is determined by either an insertion or an exit probe. The location is determined by a series of vertical and horizontal sensing elements that gives the operator a real time read out dose location relative to placement of the patient. The increased accuracy prevents serious tissue damage to the patient by preventing overdose or delivery of a dose to a wrong location within the body. 14 figs.

Towards marine seismological Network: real time small aperture seismic array

NASA Astrophysics Data System (ADS)

Ilinskiy, Dmitry

2017-04-01

Most powerful and dangerous seismic events are generated in underwater subduction zones. Existing seismological networks are based on land seismological stations. Increased demands for accuracy of location, magnitude, rupture process of coming earthquakes and at the same time reduction of data processing time require information from seabed seismic stations located near the earthquake generation area. Marine stations provide important contribution for clarification of the tectonic settings in most active subduction zones of the world. Early warning system for subduction zone area is based on marine seabed array which located near the area of most hazardous seismic zone in the region. Fast track processing for location of the earthquake hypocenter and energy takes place in buoy surface unit. Information about detected and located earthquake reaches the onshore seismological center earlier than the first break waves from the same earthquake will reach the nearest onshore seismological station. Implementation of small aperture array is based on existed and shown a good proven performance and costs effective solutions such as weather moored buoy and self-pop up autonomous seabed seismic nodes. Permanent seabed system for real-time operation has to be installed in deep sea waters far from the coast. Seabed array consists of several self-popup seismological stations which continuously acquire the data, detect the events of certain energy class and send detected event parameters to the surface buoy via acoustic link. Surface buoy unit determine the earthquake location by receiving the event parameters from seabed units and send such information in semi-real time to the onshore seismological center via narrow band satellite link. Upon the request from the cost the system could send wave form of events of certain energy class, bottom seismic station battery status and other environmental parameters. When the battery life of particular seabed unit is close to became empty

Real-Time PPP Based on the Coupling Estimation of Clock Bias and Orbit Error with Broadcast Ephemeris

PubMed Central

Pan, Shuguo; Chen, Weirong; Jin, Xiaodong; Shi, Xiaofei; He, Fan

2015-01-01

Satellite orbit error and clock bias are the keys to precise point positioning (PPP). The traditional PPP algorithm requires precise satellite products based on worldwide permanent reference stations. Such an algorithm requires considerable work and hardly achieves real-time performance. However, real-time positioning service will be the dominant mode in the future. IGS is providing such an operational service (RTS) and there are also commercial systems like Trimble RTX in operation. On the basis of the regional Continuous Operational Reference System (CORS), a real-time PPP algorithm is proposed to apply the coupling estimation of clock bias and orbit error. The projection of orbit error onto the satellite-receiver range has the same effects on positioning accuracy with clock bias. Therefore, in satellite clock estimation, part of the orbit error can be absorbed by the clock bias and the effects of residual orbit error on positioning accuracy can be weakened by the evenly distributed satellite geometry. In consideration of the simple structure of pseudorange equations and the high precision of carrier-phase equations, the clock bias estimation method coupled with orbit error is also improved. Rovers obtain PPP results by receiving broadcast ephemeris and real-time satellite clock bias coupled with orbit error. By applying the proposed algorithm, the precise orbit products provided by GNSS analysis centers are rendered no longer necessary. On the basis of previous theoretical analysis, a real-time PPP system was developed. Some experiments were then designed to verify this algorithm. Experimental results show that the newly proposed approach performs better than the traditional PPP based on International GNSS Service (IGS) real-time products. The positioning accuracies of the rovers inside and outside the network are improved by 38.8% and 36.1%, respectively. The PPP convergence speeds are improved by up to 61.4% and 65.9%. The new approach can change the

Volcview: A Web-Based Platform for Satellite Monitoring of Volcanic Activity and Eruption Response

NASA Astrophysics Data System (ADS)

Schneider, D. J.; Randall, M.; Parker, T.

2014-12-01

The U.S. Geological Survey (USGS), in cooperation with University and State partners, operates five volcano observatories that employ specialized software packages and computer systems to process and display real-time data coming from in-situ geophysical sensors and from near-real-time satellite sources. However, access to these systems both inside and from outside the observatory offices are limited in some cases by factors such as software cost, network security, and bandwidth. Thus, a variety of Internet-based tools have been developed by the USGS Volcano Science Center to: 1) Improve accessibility to data sources for staff scientists across volcano monitoring disciplines; 2) Allow access for observatory partners and for after-hours, on-call duty scientists; 3) Provide situational awareness for emergency managers and the general public. Herein we describe VolcView (volcview.wr.usgs.gov), a freely available, web-based platform for display and analysis of near-real-time satellite data. Initial geographic coverage is of the volcanoes in Alaska, the Russian Far East, and the Commonwealth of the Northern Mariana Islands. Coverage of other volcanoes in the United States will be added in the future. Near-real-time satellite data from NOAA, NASA and JMA satellite systems are processed to create image products for detection of elevated surface temperatures and volcanic ash and SO2 clouds. VolcView uses HTML5 and the canvas element to provide image overlays (volcano location and alert status, annotation, and location information) and image products that can be queried to provide data values, location and measurement capabilities. Use over the past year during the eruptions of Pavlof, Veniaminof, and Cleveland volcanoes in Alaska by the Alaska Volcano Observatory, the National Weather Service, and the U.S. Air Force has reinforced the utility of shared situational awareness and has guided further development. These include overlay of volcanic cloud trajectory and

A sensor architecture for real-time, in situ measurement of overlake evaporation on the Laurentian Great Lakes

NASA Astrophysics Data System (ADS)

Kerkez, B.; Fries, K. J.; Gronewold, A.; Lenters, J. D.

2014-12-01

While overlake evaporation is a major component of the Great Lakes' water balance, our scientific understanding of the climatic drivers of evaporation and its effects on water levels is significantly impeded by limited data. Existing measurement methods, such as eddy covariance, are not easily implemented in offshore applications. As such, there are only a handful of sites making direct, overlake measurements of evaporation on the entire Great Lakes, where the lake surface area comprises nearly one third of the entire basin. Long-term forecasts of water levels are thus very uncertain, particularly relating to climatic forcing, which is known to be a major driver of evaporation. We present a novel sensor architecture which is deployed on buoys, both tethered and drifting, to provide real-time measurements of overlake evaporation across the Great Lakes. Our system is comprised of a hierarchy of low-power, cost-effective sensor nodes, which carry out on-board computations to estimate evaporation in real-time. An ultra-low power microcontroller samples a suite of sensors to compute evaporation based on the Bowen ratio energy budget approach. The readings are then transmitted via satellite modules to a cloud-based server infrastructure for real-time updated scientific analysis and forecasting. Initial assessment of our new satellite drifter platform indicates robust field performance, validating its use in ongoing efforts to deploy a large-scale evaporation observation network across the Great Lakes basin.

Use of satellite data in volcano monitoring

NASA Technical Reports Server (NTRS)

Mcclelland, Lindsay

1987-01-01

It is argued that Total Ozone Mapping Spectrometer (TOMS) data, especially data on sulfur dioxide detection in volcanic clouds, and weather satellite data complement each other. TOMS data is most useful for discovering previously unknown eruptions and indicating a minimum volume of SO sub 2 produced by a given eruption. Once an eruption has been reported, weather satellite data can be used to accurately monitor its progress. To be used effectively, these data need to be analyzed jointly and in real time. Toward this end, it is hoped that full and timely utilization can be made of existing TOMS data, a polar orbiting TOMS can be launched in the near future, and that TOMS type instruments can be included on future geostationary satellites.

Improved near real-time data management procedures for the Mediterranean ocean Forecasting System-Voluntary Observing Ship program

NASA Astrophysics Data System (ADS)

Manzella, G. M. R.; Scoccimarro, E.; Pinardi, N.; Tonani, M.

2003-01-01

A "ship of opportunity" program was launched as part of the Mediterranean Forecasting System Pilot Project. During the operational period (September 1999 to May 2000), six tracks covered the Mediterranean from the northern to southern boundaries approximately every 15 days, while a long eastwest track from Haifa to Gibraltar was covered approximately every month. XBT data were collected, sub-sampled at 15 inflection points and transmitted through a satellite communication system to a regional data centre. It was found that this data transmission system has limitations in terms of quality of the temperature profiles and quantity of data successfully transmitted. At the end of the MFSPP operational period, a new strategy for data transmission and management was developed. First of all, VOS-XBT data are transmitted with full resolution. Secondly, a new data management system, called Near Real Time Quality Control for XBT (NRT.QC.XBT), was defined to produce a parallel stream of high quality XBT data for further scientific analysis. The procedure includes: (1) Position control; (2) Elimination of spikes; (3) Re-sampling at a 1 metre vertical interval; (4) Filtering; (5) General malfunctioning check; (6) Comparison with climatology (and distance from this in terms of standard deviations); (7) Visual check; and (8) Data consistency check. The first six steps of the new procedure are completely automated; they are also performed using a new climatology developed as part of the project. The visual checks are finally done with a free-market software that allows NRT final data assessment.

Miniaturized video-microscopy system for near real-time water quality biomonitoring using microfluidic chip-based devices

NASA Astrophysics Data System (ADS)

Huang, Yushi; Nigam, Abhimanyu; Campana, Olivia; Nugegoda, Dayanthi; Wlodkowic, Donald

2016-12-01

Biomonitoring studies apply biological responses of sensitive biomonitor organisms to rapidly detect adverse environmental changes such as presence of physic-chemical stressors and toxins. Behavioral responses such as changes in swimming patterns of small aquatic invertebrates are emerging as sensitive endpoints to monitor aquatic pollution. Although behavioral responses do not deliver information on an exact type or the intensity of toxicants present in water samples, they could provide orders of magnitude higher sensitivity than lethal endpoints such as mortality. Despite the advantages of behavioral biotests performed on sentinel organisms, their wider application in real-time and near realtime biomonitoring of water quality is limited by the lack of dedicated and automated video-microscopy systems. Current behavioral analysis systems rely mostly on static test conditions and manual procedures that are time-consuming and labor intensive. Tracking and precise quantification of locomotory activities of multiple small aquatic organisms requires high-resolution optical data recording. This is often problematic due to small size of fast moving animals and limitations of culture vessels that are not specially designed for video data recording. In this work, we capitalized on recent advances in miniaturized CMOS cameras, high resolution optics and biomicrofluidic technologies to develop near real-time water quality sensing using locomotory activities of small marine invertebrates. We present proof-of-concept integration of high-resolution time-resolved video recording system and high-throughput miniaturized perfusion biomicrofluidic platform for optical tracking of nauplii of marine crustacean Artemia franciscana. Preliminary data demonstrate that Artemia sp. exhibits rapid alterations of swimming patterns in response to toxicant exposure. The combination of video-microscopy and biomicrofluidic platform facilitated straightforward recording of fast moving objects. We

Web-Based Satellite Products Database for Meteorological and Climate Applications

NASA Technical Reports Server (NTRS)

Phan, Dung; Spangenberg, Douglas A.; Palikonda, Rabindra; Khaiyer, Mandana M.; Nordeen, Michele L.; Nguyen, Louis; Minnis, Patrick

2004-01-01

The need for ready access to satellite data and associated physical parameters such as cloud properties has been steadily growing. Air traffic management, weather forecasters, energy producers, and weather and climate researchers among others can utilize more satellite information than in the past. Thus, it is essential that such data are made available in near real-time and as archival products in an easy-access and user friendly environment. A host of Internet web sites currently provide a variety of satellite products for various applications. Each site has a unique contribution with appeal to a particular segment of the public and scientific community. This is no less true for the NASA Langley's Clouds and Radiation (NLCR) website (http://www-pm.larc.nasa.gov) that has been evolving over the past 10 years to support a variety of research projects This website was originally developed to display cloud products derived from the Geostationary Operational Environmental Satellite (GOES) over the Southern Great Plains for the Atmospheric Radiation Measurement (ARM) Program. It has evolved into a site providing a comprehensive database of near real-time and historical satellite products used for meteorological, aviation, and climate studies. To encourage the user community to take advantage of the site, this paper summarizes the various products and projects supported by the website and discusses future options for new datasets.

3D Visualization of near real-time remote-sensing observation for hurricanes field campaign using Google Earth API

NASA Astrophysics Data System (ADS)

Li, P.; Turk, J.; Vu, Q.; Knosp, B.; Hristova-Veleva, S. M.; Lambrigtsen, B.; Poulsen, W. L.; Licata, S.

2009-12-01

NASA is planning a new field experiment, the Genesis and Rapid Intensification Processes (GRIP), in the summer of 2010 to better understand how tropical storms form and develop into major hurricanes. The DC-8 aircraft and the Global Hawk Unmanned Airborne System (UAS) will be deployed loaded with instruments for measurements including lightning, temperature, 3D wind, precipitation, liquid and ice water contents, aerosol and cloud profiles. During the field campaign, both the spaceborne and the airborne observations will be collected in real-time and integrated with the hurricane forecast models. This observation-model integration will help the campaign achieve its science goals by allowing team members to effectively plan the mission with current forecasts. To support the GRIP experiment, JPL developed a website for interactive visualization of all related remote-sensing observations in the GRIP’s geographical domain using the new Google Earth API. All the observations are collected in near real-time (NRT) with 2 to 5 hour latency. The observations include a 1KM blended Sea Surface Temperature (SST) map from GHRSST L2P products; 6-hour composite images of GOES IR; stability indices, temperature and vapor profiles from AIRS and AMSU-B; microwave brightness temperature and rain index maps from AMSR-E, SSMI and TRMM-TMI; ocean surface wind vectors, vorticity and divergence of the wind from QuikSCAT; the 3D precipitation structure from TRMM-PR and vertical profiles of cloud and precipitation from CloudSAT. All the NRT observations are collected from the data centers and science facilities at NASA and NOAA, subsetted, re-projected, and composited into hourly or daily data products depending on the frequency of the observation. The data products are then displayed on the 3D Google Earth plug-in at the JPL Tropical Cyclone Information System (TCIS) website. The data products offered by the TCIS in the Google Earth display include image overlays, wind vectors, clickable

On Using the Weimer Statistical Model for Real-Time Ionospheric Specifications and Forecasts

NASA Astrophysics Data System (ADS)

Bekerat, H. A.; Schunk, R. W.; Scherliess, L.

2002-12-01

The Weimer statistical model (Weimer, 2001) for the high-latitude convection pattern was tested with regard to its ability to produce real-time convection patterns. This work is being conducted under the polar section of GAIM (Global Assimilation of Ionospheric Measurements). The method adopted involves the comparison of the cross-track ion drift velocities measured by DMSP satellites with those calculated from the Weimer model. Starting with a Weimer pattern obtained using real-time IMF and solar wind data at the time of a DMSP satellite pass in the high-latitude ionosphere, the cross-track ion drift velocities along the DMSP track were calculated from the Weimer convection model and compared to those measured by the DMSP satellite. Then, in order to improve the agreement between the measurement and the model, two of the input parameters to the model, the IMF clock-angle and the solar wind speed, were varied to get the pattern that gives the best agreement with the DMSP satellite measurements. Four months of data (March, July, September, and December 1998) were used to test the Weimer model. The result shows that the agreement between the measurement and the Weimer model is improved by using this procedure. The Weimer model is good in a statistical sense, it was able to produce the large-scale structure in most cases. However, it is not good enough to be used for real-time ionospheric specifications and forecasts because it failed to produce a lot of the mesoscale structure measured along most DMSP satellite passes. Reference Weimer, D. R., J. Geophys. Res., 106, 407,2001

Real-Time Mapping alert system; characteristics and capabilities

USGS Publications Warehouse

Torres, L.A.; Lambert, S.C.; Liebermann, T.D.

1995-01-01

The U.S. Geological Survey has an extensive hydrologic network that records and transmits precipitation, stage, discharge, and other water-related data on a real-time basis to an automated data processing system. Data values are recorded on electronic data collection platforms at field sampling sites. These values are transmitted by means of orbiting satellites to receiving ground stations, and by way of telecommunication lines to a U.S. Geological Survey office where they are processed on a computer system. Data that exceed predefined thresholds are identified as alert values. The current alert status at monitoring sites within a state or region is of critical importance during floods, hurricanes, and other extreme hydrologic events. This report describes the characteristics and capabilities of a series of computer programs for real-time mapping of hydrologic data. The software provides interactive graphics display and query of hydrologic information from the network in a real-time, map-based, menu-driven environment.

An automated mapping satellite system ( Mapsat).

USGS Publications Warehouse

Colvocoresses, A.P.

1982-01-01

The favorable environment of space permits a satellite to orbit the Earth with very high stability as long as no local perturbing forces are involved. Solid-state linear-array sensors have no moving parts and create no perturbing force on the satellite. Digital data from highly stabilized stereo linear arrays are amenable to simplified processing to produce both planimetric imagery and elevation data. A satellite imaging system, called Mapsat, including this concept has been proposed to produce data from which automated mapping in near real time can be accomplished. Image maps as large as 1:50 000 scale with contours as close as a 20-m interval may be produced from Mapsat data. -from Author

First Results of the Near Real-Time Imaging Reconstruction System at Big Bear Solar Observatory

NASA Astrophysics Data System (ADS)

Yang, G.; Denker, C.; Wang, H.

2003-05-01

The Near Real-Time Imaging Reconstruction system (RTIR) at Big Bear Solar Observatory (BBSO) is designed to obtain high spatial resolution solar images at a cadence of 1 minute utilizing the power of parallel processing. With this system, we can compute near diffraction-limited images without saving huge amounts of data that are involved in the speckle masking reconstruction algorithm. It enables us to monitor active regions and give fast response to the solar activity. In this poster we present the first results of our new 32-CPU Beowulf cluster system. The images are 1024 x 1024 and the field of view (FOV) is 80'' x 80''. Our target is an active region with complex magnetic configuration. We focus on pores and small spots in the active region with the goal of better understanding the formation of penumbra structure. In addition we expect to study evolution of active regions during solar flares.

Near Real Time Flood Warning System for National Capital Territory of Delhi

NASA Astrophysics Data System (ADS)

Goyal, A.; Yadav, H.; Tyagi, H.; Gosain, A. K.

2017-12-01

Extreme floods are common phenomena during Indian Monsoons. The National Capital Territory area of India, Delhi, frequently experiences fluvial as well as pluvial inundation due to its proximity to river Yamuna and poor functioning of its stormwater drainage system. The urban floods result in severe waterlogging and heavy traffic snarls, bringing life in this megapolis to a halt. The city has witnessed six major floods since 1900 and thus its residents are well conscious of potential flood risks but the city still lacks a flood warning system. The flood related risks can be considerably reduced, if not eliminated, by issuing timely warnings and implementing adaptive measures. Therefore, the present study attempts to develop a web based platform that integrates Web-GIS technology and mathematical simulation modelling to provide an effective and reliable early flood warning service for Delhi. The study makes use of India Metorological Department's Doppler radar-derived near real time rainfall estimates of 15 minutes time step. The developed SWMM model has been validated using information from gauges, monitoring sensors and crowd sourcing techniques and utilises capabilities of cloud computing on server side for fast processing. This study also recommends safe evacuation policy and remedial measures for flooding hotspots as part of flood risk management plan. With heightened risk of floods in fast urbanizing areas, this work becomes highly pertinent as flood warning system with adequate lead time can not only save precious lives but can also substantially reduce flood damages.

Verification and Validation of NASA-Supported Enhancements to the Near Real Time Harmful Algal Blooms Observing System (HABSOS)

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hall, Calllie; McPherson, Terry; Spiering, Bruce; Brown, Richard; Estep, Lee; Lunde, Bruce; Guest, DeNeice; Navard, Andy; Pagnutti, Mary;

Estimating Advective Near-surface Currents from Ocean Color Satellite Images

DTIC Science & Technology

2015-01-01

of surface current information. The present study uses the sequential ocean color products provided by the Geostationary Ocean Color Imager (GOCI) and...on the SuomiNational Polar-Orbiting Partner- ship (S-NPP) satellite. The GOCI is the world’s first geostationary orbit satellite sensor over the...used to extract the near-surface currents by the MCC algorithm. We not only demonstrate the retrieval of currents from the geostationary satellite ocean

A near real time scenario at regional scale for the hydrogeological risk

NASA Astrophysics Data System (ADS)

Ponziani, F.; Stelluti, M.; Zauri, R.; Berni, N.; Brocca, L.; Moramarco, T.; Salciarini, D.; Tamagnini, C.

2012-04-01

satellite data daily download, used for the derivation of a soil water content index (SWI): these data are compared with instrumental ones from the TDR stations and the results of the water balance model that evaluates the contributions of water infiltration, percolation, evapotranspiration, etc. using physically based parameters obtained through a long process of characterization of soil and rock types, for each grid point; b) The assessment of the contribution due to the melting of the snow; c) the physically based - coupling model slope stability analysis, GIS-based, developed by the Department of Civil and Environmental Engineering, University of Perugia, with the aim to introduce also the actual mechanical and physical characteristics of slopes in the analysis. As result of the system, is the daily creation of near real-time and 24, 48, 72h forecast risk scenarios, that, under the intention of the Department of Civil Protection Service, will be used by the Functional Centre for the institutional tasks of hydrogeological risk evaluation and management, but also by local Administrations involved in the monitoring and assessment of landslide risk, in order to receive feedback on the effectiveness of the scenarios produced.

Real-Time Visualization Tool Integrating STEREO, ACE, SOHO and the SDO

NASA Astrophysics Data System (ADS)

Schroeder, P. C.; Luhmann, J. G.; Marchant, W.

2011-12-01

The STEREO/IMPACT team has developed a new web-based visualization tool for near real-time data from the STEREO instruments, ACE and SOHO as well as relevant models of solar activity. This site integrates images, solar energetic particle, solar wind plasma and magnetic field measurements in an intuitive way using near real-time products from NOAA and other sources to give an overview of recent space weather events. This site enhances the browse tools already available at UC Berkeley, UCLA and Caltech which allow users to visualize similar data from the start of the STEREO mission. Our new near real-time tool utilizes publicly available real-time data products from a number of missions and instruments, including SOHO LASCO C2 images from the SOHO team's NASA site, SDO AIA images from the SDO team's NASA site, STEREO IMPACT SEP data plots and ACE EPAM data plots from the NOAA Space Weather Prediction Center and STEREO spacecraft positions from the STEREO Science Center.

Real-Time Systems

DTIC Science & Technology

1992-02-01

Postgraduate School Autonomous Under Vehicle (AUV) are then examined. Autonomous underwater vehicle (AUV), hard real-time system, real - time operating system , real-time programming language, real-time system, soft real-time system.

Near-ultraviolet imaging of Jupiter's satellite Io with the Hubble Space Telescope

NASA Technical Reports Server (NTRS)

Paresce, F.; Sartoretti, P.; Albrecht, R.; Barbieri, C.; Blades, J. C.; Boksenberg, A.; Crane, P.; Deharveng, J. M.; Disney, M. J.; Jakobsen, P.

1992-01-01

The surface of Jupiter's Galilean satellite Io has been resolved for the first time in the near ultraviolet at 2850 A by the Faint Object Camera (FOC) on the Hubble Space Telescope (HST). The restored images reveal significant surface structure down to the resolution limit of the optical system corresponding to approximately 250 km at the sub-earth point.

UC Irvine CHRS Real-time Global Satellite Precipitation Monitoring System (G-WADI PERSIANN-CCS GeoServer) for Hydrometeorological Applications

NASA Astrophysics Data System (ADS)

Sorooshian, S.; Hsu, K. L.; Gao, X.; Imam, B.; Nguyen, P.; Braithwaite, D.; Logan, W. S.; Mishra, A.

2015-12-01

The G-WADI Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) GeoServer has been successfully developed by the Center for Hydrometeorology and Remote Sensing (CHRS) at the University of California Irvine in collaboration with the UNESCO's International Hydrological Programme (IHP) and a number of its international centers. The system employs state-of-the-art technologies in remote sensing and artificial intelligence to estimate precipitation globally from satellite imagery in real-time and high spatiotemporal resolution (4km, hourly). It offers graphical tools and data service to help the user in emergency planning and management for natural disasters related to hydrological processes. The G-WADI PERSIANN-CCS GeoServer has been upgraded with new user-friendly functionalities. The precipitation data generated by the GeoServer is disseminated to the user community through support provided by ICIWaRM (The International Center for Integrated Water Resources Management), UNESCO and UC Irvine. Recently a number of new applications for mobile devices have been developed by our students. The RainMapper has been available on App Store and Google Play for the real-time PERSIANN-CCS observations. A global crowd sourced rainfall reporting system named iRain has also been developed to engage the public globally to provide qualitative information about real-time precipitation in their location which will be useful in improving the quality of the PERSIANN-CCS data. A number of recent examples of the application and use of the G-WADI PERSIANN-CCS GeoServer information will also be presented.

Soil Moisture Drought Monitoring and Forecasting Using Satellite and Climate Model Data over Southwestern China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Xuejun; Tang, Qiuhong; Liu, Xingcai

Real-time monitoring and predicting drought development with several months in advance is of critical importance for drought risk adaptation and mitigation. In this paper, we present a drought monitoring and seasonal forecasting framework based on the Variable Infiltration Capacity (VIC) hydrologic model over Southwest China (SW). The satellite precipitation data are used to force VIC model for near real-time estimate of land surface hydrologic conditions. As initialized with satellite-aided monitoring, the climate model-based forecast (CFSv2_VIC) and ensemble streamflow prediction (ESP)-based forecast (ESP_VIC) are both performed and evaluated through their ability in reproducing the evolution of the 2009/2010 severe drought overmore » SW. The results show that the satellite-aided monitoring is able to provide reasonable estimate of forecast initial conditions (ICs) in a real-time manner. Both of CFSv2_VIC and ESP_VIC exhibit comparable performance against the observation-based estimates for the first month, whereas the predictive skill largely drops beyond 1-month. Compared to ESP_VIC, CFSv2_VIC shows better performance as indicated by the smaller ensemble range. This study highlights the value of this operational framework in generating near real-time ICs and giving a reliable prediction with 1-month ahead, which has great implications for drought risk assessment, preparation and relief.« less

Stationary orbits of satellites of disk galaxies

NASA Technical Reports Server (NTRS)

Polyachenko, Valerij L.

1990-01-01

The satellite of an S-galaxy will experience opposing dynamical-friction forces from the stars of the disk and the halo. If these forces are in balance, the satellite may travel in a stable, near-circular orbit whose radius, for a wide range of physical parameters, should be limited to a zone 1.2 to 1.4 times the disk radius, much as is observed. The idea is very simple. The dynamical friction acting on a small satellite, moving through a stellar galactic halo, makes this satellite slow down. On the other hand, a stellar disk, rotating faster than a satellite, makes it speed up. But the density distributions in radius for disk's and halo's stars in real flat galaxies are quite different (respectively, exponential and power-law). Moreover, the observational data show that the exponential profile for disk's surface density drops abruptly at some radius (r sub d). So it is natural to expect that a stationary orbit could be near the edge of a disk (where two effects are mutually compensated).

Real-time Shakemap implementation in Austria

NASA Astrophysics Data System (ADS)

Weginger, Stefan; Jia, Yan; Papi Isaba, Maria; Horn, Nikolaus

2017-04-01

ShakeMaps provide near-real-time maps of ground motion and shaking intensity following significant earthquakes. They are automatically generated within a few minutes after occurrence of an earthquake. We tested and included the USGS ShakeMap 4.0 (experimental code) based on python in the Antelope real-time system with local modified GMPE and Site Effects based on the conditions in Austria. The ShakeMaps are provided in terms of Intensity, PGA, PGV and PSA. Future presentation of ShakeMap contour lines and Ground Motion Parameter with interactive maps and data exchange over Web-Services are shown.

Cloud-Based Numerical Weather Prediction for Near Real-Time Forecasting and Disaster Response

NASA Technical Reports Server (NTRS)

Molthan, Andrew; Case, Jonathan; Venners, Jason; Schroeder, Richard; Checchi, Milton; Zavodsky, Bradley; Limaye, Ashutosh; O'Brien, Raymond

2015-01-01

The use of cloud computing resources continues to grow within the public and private sector components of the weather enterprise as users become more familiar with cloud-computing concepts, and competition among service providers continues to reduce costs and other barriers to entry. Cloud resources can also provide capabilities similar to high-performance computing environments, supporting multi-node systems required for near real-time, regional weather predictions. Referred to as "Infrastructure as a Service", or IaaS, the use of cloud-based computing hardware in an on-demand payment system allows for rapid deployment of a modeling system in environments lacking access to a large, supercomputing infrastructure. Use of IaaS capabilities to support regional weather prediction may be of particular interest to developing countries that have not yet established large supercomputing resources, but would otherwise benefit from a regional weather forecasting capability. Recently, collaborators from NASA Marshall Space Flight Center and Ames Research Center have developed a scripted, on-demand capability for launching the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS), which includes pre-compiled binaries of the latest version of the Weather Research and Forecasting (WRF) model. The WRF-EMS provides scripting for downloading appropriate initial and boundary conditions from global models, along with higher-resolution vegetation, land surface, and sea surface temperature data sets provided by the NASA Short-term Prediction Research and Transition (SPoRT) Center. This presentation will provide an overview of the modeling system capabilities and benchmarks performed on the Amazon Elastic Compute Cloud (EC2) environment. In addition, the presentation will discuss future opportunities to deploy the system in support of weather prediction in developing countries supported by NASA's SERVIR Project, which provides capacity building

Near Real Time Integration of Satellite and Radar Data for Probabilistic Nearcasting of Severe Weather

NASA Astrophysics Data System (ADS)

Pilone, D.; Quinn, P.; Mitchell, A. E.; Baynes, K.; Shum, D.

2014-12-01

This talk introduces the audience to some of the very real challenges associated with visualizing data from disparate data sources as encountered during the development of real world applications. In addition to the fundamental challenges of dealing with the data and imagery, this talk discusses usability problems encountered while trying to provide interactive and user-friendly visualization tools. At the end of this talk the audience will be aware of some of the pitfalls of data visualization along with tools and techniques to help mitigate them. There are many sources of variable resolution visualizations of science data available to application developers including NASA's Global Imagery Browse Services (GIBS), however integrating and leveraging visualizations in modern applications faces a number of challenges, including: - Varying visualized Earth "tile sizes" resulting in challenges merging disparate sources - Multiple visualization frameworks and toolkits with varying strengths and weaknesses - Global composite imagery vs. imagery matching EOSDIS granule distribution - Challenges visualizing geographically overlapping data with different temporal bounds - User interaction with overlapping or collocated data - Complex data boundaries and shapes combined with multi-orbit data and polar projections - Discovering the availability of visualizations and the specific parameters, color palettes, and configurations used to produce them In addition to discussing the challenges and approaches involved in visualizing disparate data, we will discuss solutions and components we'll be making available as open source to encourage reuse and accelerate application development.

New Trends in Two-Way Time and Frequency Transfer via Satellite

DTIC Science & Technology

1999-12-01

Recent developments performed with SATRE two-way time transfer ( TWSTFT ) modems resulted in significant performance upgrades and operational...improvements of the TWSTFT method These are aimed to reduce : manpower effort and to provide reliable, real-time data via a centralized monitoring and...collection have been used throughout the experiment INTRODUCTION Two-Way Time and Frequency Transfer via Satellite ( TWSTFT ) is a well established method to

Use of NTRIP for optimizing the decoding algorithm for real-time data streams.

PubMed

He, Zhanke; Tang, Wenda; Yang, Xuhai; Wang, Liming; Liu, Jihua

2014-10-10

As a network transmission protocol, Networked Transport of RTCM via Internet Protocol (NTRIP) is widely used in GPS and Global Orbiting Navigational Satellite System (GLONASS) Augmentation systems, such as Continuous Operational Reference System (CORS), Wide Area Augmentation System (WAAS) and Satellite Based Augmentation Systems (SBAS). With the deployment of BeiDou Navigation Satellite system(BDS) to serve the Asia-Pacific region, there are increasing needs for ground monitoring of the BeiDou Navigation Satellite system and the development of the high-precision real-time BeiDou products. This paper aims to optimize the decoding algorithm of NTRIP Client data streams and the user authentication strategies of the NTRIP Caster based on NTRIP. The proposed method greatly enhances the handling efficiency and significantly reduces the data transmission delay compared with the Federal Agency for Cartography and Geodesy (BKG) NTRIP. Meanwhile, a transcoding method is proposed to facilitate the data transformation from the BINary EXchange (BINEX) format to the RTCM format. The transformation scheme thus solves the problem of handing real-time data streams from Trimble receivers in the BeiDou Navigation Satellite System indigenously developed by China.

Near real-time finite fault source inversion for moderate-large earthquakes in Taiwan using teleseismic P waveform

NASA Astrophysics Data System (ADS)

Wong, T. P.; Lee, S. J.; Gung, Y.

2017-12-01

Taiwan is located at one of the most active tectonic regions in the world. Rapid estimation of the spatial slip distribution of moderate-large earthquake (Mw6.0) is important for emergency response. It is necessary to have a real-time system to provide the report immediately after earthquake happen. The earthquake activities in the vicinity of Taiwan can be monitored by Real-Time Moment Tensor Monitoring System (RMT) which provides the rapid focal mechanism and source parameters. In this study, we follow up the RMT system to develop a near real-time finite fault source inversion system for the moderate-large earthquakes occurred in Taiwan. The system will be triggered by the RMT System when an Mw6.0 is detected. According to RMT report, our system automatically determines the fault dimension, record length, and rise time. We adopted one segment fault plane with variable rake angle. The generalized ray theory was applied to calculate the Green's function for each subfault. The primary objective of the system is to provide the first order image of coseismic slip pattern and identify the centroid location on the fault plane. The performance of this system had been demonstrated by 23 big earthquakes occurred in Taiwan successfully. The results show excellent data fits and consistent with the solutions from other studies. The preliminary spatial slip distribution will be provided within 25 minutes after an earthquake occurred.

Enhancements and Evolution of the Real Time Mission Monitor

NASA Technical Reports Server (NTRS)

Goodman, Michael; Blakeslee, Richard; Hardin, Danny; Hall, John; He, Yubin; Regner, Kathryn

2008-01-01

The Real Time Mission Monitor (RTMM) is a visualization and information system that fuses multiple Earth science data sources, to enable real time decision-making for airborne and ground validation experiments. Developed at the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center, RTMM is a situational awareness, decision-support system that integrates satellite imagery, radar, surface and airborne instrument data sets, model output parameters, lightning location observations, aircraft navigation data, soundings, and other applicable Earth science data sets. The integration and delivery of this information is made possible using data acquisition systems, network communication links, network server resources, and visualizations through the Google Earth virtual globe application. RTMM has proven extremely valuable for optimizing individual Earth science airborne field experiments. Flight planners, mission scientists, instrument scientists and program managers alike appreciate the contributions that RTMM makes to their flight projects. We have received numerous plaudits from a wide variety of scientists who used RTMM during recent field campaigns including the 2006 NASA African Monsoon Multidisciplinary Analyses (NAMMA), 2007 Tropical Composition, Cloud, and Climate Coupling (TC4), 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) missions, the 2007-2008 NOAA-NASA Aerosonde Hurricane flights and the 2008 Soil Moisture Active-Passive Validation Experiment (SMAP-VEX). Improving and evolving RTMM is a continuous process. RTMM recently integrated the Waypoint Planning Tool, a Java-based application that enables aircraft mission scientists to easily develop a pre-mission flight plan through an interactive point-and-click interface. Individual flight legs are automatically calculated for altitude, latitude, longitude, flight leg distance, cumulative distance, flight leg time, cumulative time, and

Enhancements and Evolution of the Real Time Mission Monitor

NASA Astrophysics Data System (ADS)

Goodman, M.; Blakeslee, R.; Hardin, D.; Hall, J.; He, Y.; Regner, K.

2008-12-01

The Real Time Mission Monitor (RTMM) is a visualization and information system that fuses multiple Earth science data sources, to enable real time decision-making for airborne and ground validation experiments. Developed at the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center, RTMM is a situational awareness, decision-support system that integrates satellite imagery, radar, surface and airborne instrument data sets, model output parameters, lightning location observations, aircraft navigation data, soundings, and other applicable Earth science data sets. The integration and delivery of this information is made possible using data acquisition systems, network communication links, network server resources, and visualizations through the Google Earth virtual earth application. RTMM has proven extremely valuable for optimizing individual Earth science airborne field experiments. Flight planners, mission scientists, instrument scientists and program managers alike appreciate the contributions that RTMM makes to their flight projects. RTMM has received numerous plaudits from a wide variety of scientists who used RTMM during recent field campaigns including the 2006 NASA African Monsoon Multidisciplinary Analyses (NAMMA), 2007 Tropical Composition, Cloud, and Climate Coupling (TC4), 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) missions, the 2007-2008 NOAA-NASA Aerosonde Hurricane flights and the 2008 Soil Moisture Active-Passive Validation Experiment (SMAP-VEX). Improving and evolving RTMM is a continuous process. RTMM recently integrated the Waypoint Planning Tool, a Java-based application that enables aircraft mission scientists to easily develop a pre-mission flight plan through an interactive point-and-click interface. Individual flight legs are automatically calculated for altitude, latitude, longitude, flight leg distance, cumulative distance, flight leg time, cumulative time, and

The JPL near-real-time VLBI system and its application to clock synchronization and earth orientation measurements

NASA Technical Reports Server (NTRS)

Callahan, P. S.; Eubanks, T. M.; Roth, M. G.; Steppe, J. A.; Esposito, P. B.

1983-01-01

The JPL near-real-time VLBI system called Block I is discussed. The hardware and software of the system are described, and the Time and Earth Motion Precision Observations (TEMPO) which utilize Block I are discussed. These observations are designed to provide interstation clock synchronization to 10 nsec and to determine earth orientation (UT1 and polar motion - UTPM) to 30 cm or better in each component. TEMPO results for clock synchronization and UTPM are presented with data from the July 1980-August 1981 analyzed using the most recent JPL solution software and source catalog. Future plans for TEMPO and Block I are discussed.

Real Time Agricultural Monitoring with the Planet SmallSat Constellation

NASA Astrophysics Data System (ADS)

Mascaro, J.

2017-12-01

Planet—an aerospace and data analytics company (www.planet.com)—now operates 190 earth observation satellites, collecting approximately 85% of the land-surface of the Earth every day in multispectral, 3.7m-resolution imagery. This frequency and spatial resolution provides for unique monitoring of global agriculture, especially billions of smallholder farms that feed much of the world. Through our Education and Research Program, anyone at a university is eligible to access a portion of Planet data to power their research at no cost. Here, we present innovative results from our research partners. Most critically, several users have undertaken the development of models for regularizing spectrally disparate data feeds from Planet, Sentinel and Landsat; these approaches have generated standardized, 3.7m-resolution, daily data feeds for NDVI, LAI and (in combination with eddy covariance data) crop water use. The key breakthrough is interoperability: ingesting multiple, disparate satellite information fields for the generation of actionable agricultural indicators. This foundational methodology, aided by computer vision, can provide near real-time updates on the yield, health and welfare of smallholder farms. Storms, drought and disease can be detected faster than ever before, enabling smart intervention and enhancing the effectiveness of insurance and disaster relief mechanisms.

Accessing near real-time Antarctic meteorological data through an OGC Sensor Observation Service (SOS)

NASA Astrophysics Data System (ADS)

Kirsch, Peter; Breen, Paul

2013-04-01

We wish to highlight outputs of a project conceived from a science requirement to improve discovery and access to Antarctic meteorological data in near real-time. Given that the data was distributed in both spatial and temporal domains and is to be accessed across several science disciplines, the creation of an interoperable, OGC compliant web service was deemed the most appropriate approach. We will demonstrate an implementation of the OGC SOS Interface Standard to discover, browse, and access Antarctic meteorological data-sets. A selection of programmatic (R, Perl) and web client interfaces utilizing open technologies ( e.g. jQuery, Flot, openLayers ) will be demonstrated. In addition we will show how high level abstractions can be constructed to allow the users flexible and straightforward access to SOS retrieved data.

Real time forecasting of near-future evolution.

PubMed

Gerrish, Philip J; Sniegowski, Paul D

2012-09-07

A metaphor for adaptation that informs much evolutionary thinking today is that of mountain climbing, where horizontal displacement represents change in genotype, and vertical displacement represents change in fitness. If it were known a priori what the 'fitness landscape' looked like, that is, how the myriad possible genotypes mapped onto fitness, then the possible paths up the fitness mountain could each be assigned a probability, thus providing a dynamical theory with long-term predictive power. Such detailed genotype-fitness data, however, are rarely available and are subject to change with each change in the organism or in the environment. Here, we take a very different approach that depends only on fitness or phenotype-fitness data obtained in real time and requires no a priori information about the fitness landscape. Our general statistical model of adaptive evolution builds on classical theory and gives reasonable predictions of fitness and phenotype evolution many generations into the future.