Search NASA⌕ Search

SEARCH · Search NASA

Results for “secure data”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A New Remote Communications Link to Reduce Residential PV Solar Costs

Monitoring of PV/DER site production is expensive to install and unreliable. Among third party systems providers, lost communications links are a growing concern. Nearly 20% of links are failing, provisioning is complex, recovery is expensive, production data is lost, and access is fragmented. FleetLink is a new concept in DER system communications, purpose built for lowering the cost of maintaining active contact with residential end user sites and ensuring that production data is reliably available to third party systems providers. Systems providers require accurate, secure system monitoring and reporting of production data and system faults while driving down overall costs to compete effectively. This plug and play, independently operating communications solution lowers the cost of fleet contact from typically .08 dollars-$.12/W down to .02 dollars -.03/W including installation and maintenance expenses. FleetLink establishes a breakthrough in simplicity that facilitates rapid expansion of residential solar by reducing initial capital outlay and lowering installation labor time and skill levels. The solution also facilitates higher DER installation growth rates by driving down maintenance costs and eliminating communications trouble calls. This is accomplished by the FleetLink’s unique network technology that enables dynamic network configuration for fast changes, and active, self-healing DER site contact for uptime assurance. Using an open source network framework with proprietary, application specific enhancements, FleetLink independently manages connectivity, security, recovery, grid control communications, and fleet expansion while presenting a compliant SunSpec interface to the third party operations centers. The net system cost savings of at least .05 dollars/W supports the SunShot cost goals and the flexibility and scalability of the solution accelerates the velocity and ubiquitous adoption of solar.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Experiments for Securing Air Traffic Against Cyber-Physical System Attacks

This presentation describes experiments conducted with single board computers to investigate methods for creating trust for enabling the development of cyber-resilient air transportation systems. Methods included secure communication to prevent unauthorized access to data, consistency of data obtained via sensors and by processing, and built-in safeguards to prevent mission failure. The motivation for this work are the following. The future air transportation system needs to ensure availability, integrity, confidentiality and safety of operations. Safety of vehicles and operations is paramount for successful integration of Urban Air Mobility (UAM), Unmanned Aerial Systems (UAS), supersonic aircraft and launch vehicles with conventional aviation operations in the National Airspace System. Security is becoming critical because the sensors, networks and computers are far more vulnerable to bad actors than their mechanical or human predecessors. The goal therefore is to design and develop cyber-resilient systems that continue to function even in degraded states. The main findings are (1) off-the-shelf hardware can support development of cyber-resilient onboard flight computers and (2) trust in system design and implementation can be accomplished by integrating layers in depth (detail) and in breadth (scope).

cyber-resilient autonomy, trust, secure communicat↗
DOE OSTI2022

First Report of the Nuclear Data Subcommittee of the Nuclear Science Advisory Committee

Accurate, reliable nuclear data is essential for the success of Federal missions such as nonproliferation, nuclear forensics, homeland security, national defense, space exploration, clean energy generation, and scientific research. Data access is also key to innovative commercial developments such as new medicines, automated industrial controls, energy exploration, energy security, nuclear reactor design, and isotope production. The United States Nuclear Data Program (USNDP) is the domestic custodian of nuclear data. In its April 2022 meeting, the DOE/NSF Nuclear Science Advisory Committee was charged with preparing two reports on nuclear data. In this first report, we review recent accomplishments of the USNDP and discuss complementary and collaborative international efforts. Detailed descriptions of nuclear data needs for basic science, nonproliferation, national security, nuclear energy together with medical and space applications are also presented. Lastly, a set of specific cross-cutting nuclear data needs with relevance for multiple applications areas are also identified for further discussion in a follow-on report planned for release at the end of January 2023.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Nevada National Security Site 2017 Waste Management Monitoring Report Area 3 and Area 5 Radioactive Waste Management Sites

Environmental monitoring data are collected at and around the Area 3 and Area 5 Radioactive Waste Management Sites (RWMSs) within the Nevada National Security Site (NNSS). These data include direct radiation exposure, as well as radiation from the air, groundwater, meteorology, and vadose zone. This report summarizes the 2017 environmental data.

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

Frictionless knowledge injection for few-shot learning

Cutting-edge machine learning methods often require large volumes of curated training data, precluding their use in national security problems with rare events in massive datasets. We present a method for incorporating abstract knowledge into models tailored for sparse data. A subject matter expert defines salient concepts using data examples, which are encoded in the model’s embedding space. Models are then trained to respect these concepts. This method enables knowledge injection, yielding effective models with limited labeled data and the ability to assess model sensitivity for subject matter expertise across the nonproliferation mission space, as demonstrated with Raman spectra analysis.

Stomps, Jordan [ORNL] (ORCID:0000000178114479)↗
NASA NTRS2016

Developing a Crop Mask for Agricultural Assessments in Kenya

Kenya relies on agricultural production for supporting local consumption and other processing value chains. The role of agriculture in supporting Kenya's economy is critical, with its contribution to the Gross Domestic product (GDP) estimated at over 277,000 Million in 2016. With changing climate in a rain-fed dependent agricultural production system, cropping zones are shifting and proper decision making will require updated data for proper delineation of cropping areas and extent; especially in agriculture and food security assessments. Where up-to-date data is not available it is important that it is generated and passed over to relevant stakeholders to inform their decision making processes. It is important that government agencies, non-governmental agencies and other agricultural stakeholders access updated tools and information to assist in their assessments. To support agricultural decision making, SERVIR E&SA will develop an updated agricultural crop mask. Due to intercropping especially in small holder farming, the mask will cover all crops to provide an overall map of cropped areas.

environment↗
DOE OSTI2023

Second Report of the Nuclear Data Subcommittee of the Nuclear Science Advisory Committee

The central importance of the nuclear data curated by the US Nuclear Data Program (USNDP) for clean energy generation, national security, nonproliferation, medical applications, and space exploration as well as basic science was described in a prior report issued by the DOE/NSF Nuclear Science Advisory Committee subcommittee on Nuclear Data (NSAC-ND) in September 2022. In this report, we present a set of fourteen (14) recommendations that will enhance and advance DOE-NP's stewardship of nuclear data. The first three recommendations focus on the existing core USNDP capabilities, namely: 1) Support the nuclear structure evaluation workforce to improve the currency, consistency, and accessibility of the Evaluated Nuclear Structure Data File (ENSDF); 2) Enhance nuclear reaction evaluation within the USNDP in support of the Evaluated Nuclear Data File (ENDF) through expansion of the workforce and integration of high-performance computing, automation, and machine learning and; 3) Continue atomic mass evaluation in support AME and NUBASE databases. This is followed by eight (8) recommendations representing new cross-cutting initiatives involving both measurement and evaluation to address outstanding nuclear data needs. These new initiatives require a highly trained, diverse workforce that includes personnel with expertise from both inside and outside the nuclear physics community from which evaluators have traditionally been recruited. As such, many of these initiatives are accomplished via a Topical Nuclear Data Collaborations (TNDC). A TNDC is made up of domestic and international stakeholders, subject matter and nuclear data experts, and nuclear data evaluators and features a workforce development plan to ensure that nuclear data evaluators maintain currency in the relevant applications and are seen as equity partners in the endeavor. These include: 1) Establish a coordinated effort to improve evaluation and modeling in nuclear astrophysics for stellar dynamics, multi-messenger astronomy and nucleosynthesis; 2) Initiate a TNDC to develop and maintain nuclear structure evaluation beyond discrete states, including nuclear level densities, photon strength functions and photonuclear data for improved reaction modeling, and exploring nuclear structure at finite temperature; 3) Create a TNDC to perform correlated fission data evaluation, including cross sections, fragment yields, v(A), v(E n ) for nuclear energy, national security, nonproliferation and basic science; 4) From a panel of subject matter experts to establish and annually update a roster of key decay data to nurture its accelerated dissemination including both measurement and evaluation for targeted high-value nuclides for national security, nonproliferation and medical applications; 5) Comprehensive, consistent neutron-induced structure and reaction data for nuclear energy, national security, nonproliferation and planetary nuclear spectroscopy; 6) Charged-particle stopping powers for detector design, space effects and ion beam therapy; 7) High-energy reactions for space exploration and medical nuclide production, and; 8) The creation of an infrastructure for open data and data preservation for use by the entire nuclear physics community. All told, these initiatives require approximately $6.5M increase in NP support of the USNDP in fiscal year 2023 dollars and would require at least 3-5 years to carry out due to the length of time needed to recruit and train new nuclear data researchers. This relatively modest investment would help ensure that the fruits of the nuclear data research carried out by DOE-NP and its collaborators would be brought to bear to address some of the most important needs of our nation and the world. To ensure effective execution of this plan, we present an overview of recruitment, training, and retention goals for the USNDP, the centerpiece of which is a mutually agreed upon code of conduct. Finally, we identify the facility and instrumentation needed to perform the recommended experimental activities. This includes a short review of target fabrication capabilities, reactors, neutron beam, light- and heavy-stable ion, gamma-ray, high-energy and radioactive ion beam facilities. Lastly, a more complete appendix of experimental facilities previously compiled is included with new input provided for 6 facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

A holistic cyber-physical security protocol for authenticating the provenance and integrity of structural health monitoring imagery data

Modern infrastructure systems, such as bridges, dams, power generation stations, and buildings increasingly have an intrinsic cyber-physical nature to them. Infrastructure now commonly, includes actuators, network connections, sensors, control systems, and computational resources. It is of increasing concern that modern infrastructure is vulnerable to cyber-attacks that can damage both the cyber and physical nature of the infrastructure. To date, the physical and cyber health of infrastructure has been considered separately. However, the increasing concerns associated with the cyber-physical security of infrastructure coupled with the emergence of 5G networks made using components that are not universally considered trustworthy, and the emergence of techniques for creating deepfakes and adversarial examples suggests the time has come to begin considering cyber health and structural health with a more holistic approach. In this work, a protocol is developed for ensuring the imagery data captured by a structural health monitoring system can be unambiguously attributed to legitimate sensors associated with the structural health monitoring system. A computer vision approach based on the idea of mutual information is then presented to detect damage in an image. This work presents the protocol for authenticating the provenance of imager data and demonstrates that this protocol does not have overly adverse effects when used with the mutual information-based technique for detecting damage in the resulting imagery data.

Jung, HweeKwon↗
DOE OSTI2019

Nuclear Smuggling Detection and Deterrence (FY 2018 Data Analysis Annual Report)

The National Nuclear Security Administration’s Office of Nuclear Smuggling Detection and Deterrence (NSDD) has facilitated the installation of more than 3,728 radiation portal monitors (RPMs) at 660 sites in 63 countries. This collection of RPMs represents the world’s largest network of radiation detectors and provides one element of the defense-in-depth approach that supports the Global Nuclear Detection Architecture. These systems support NSDD’s mission to build partner country capability to deter, detect, and interdict the illicit transport of radiological and fissile material through strategic points of entry and exit at seaports, airports, and border crossings.NSDD works collaboratively with partner countries and international organizations to optimize the operation of these RPMs. The large amount of data provided by NSDD partner countries (summarized in the banner to the right) highlights the close cooperation and partnerships NSDD has built with 63 countries around the world. Thirty-two of these countries shared at least some RPM-related data with NSDD in fiscal year (FY) 2018. This significant level of data sharing is a key element that distinguishes the NSDD office as unique among nuclear nonproliferation programs and initiatives: NSDD can provide specific, objective, data-driven decisions and support for sustaining the radiation detection systems it helped deploy. This data analysis report summarizes and aggregates the RPM data provided to the NSDD office for analysis and review in FY 2018.The data can be used to describe RPM performance and characterize the wide diversity of NSDD deployment sites. For example, NSDD deploys detector systems across sites with natural background radiation levels that can vary by a factor of up to nine from site to site. Some RPM lanes have few occupancies, whereas others have up to approximately 8,000 occupancies per day, and the different types of cargo traveling through a site can result in site-wide alarm rates that range from near 0% at some sites to above 3% at others. Based on the data received, the global average uptime for NSDD RPMs was 97% for FY 2018. NSDD takes all these factors into account in making recommendations to partner countries on how to most effectively manage and maintain site operations. NSDD utilizes reports and other information products created by ORNL Radiation Inspection Systems Team (RIST) data analysts to efficiently allocate the resources needed to detect and ultimately interdict illicit nuclear and radiological material.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2017

Nuclear Smuggling Detection and Deterrence FY 2016 Data Analysis Annual Report

The National Nuclear Security Administration’s Office of Nuclear Smuggling Detection and Deterrence (NSDD) has facilitated the installation of more than 3,500 radiation portal monitors (RPMs) at 606 sites in 56 countries worldwide. This collection of RPMs represents the world’s largest network of radiation detectors and provides one element in the defense-in-depth approach that supports the Global Nuclear Detection Architecture. These systems support NSDD’s mission to build partner country capability to deter, detect, and interdict the illicit transport of radiological and fissile material through strategic points of entry and exit at seaports, airports, and border crossings. NSDD works collaboratively with partner countries and international organizations to optimize the operation of these RPMs. The large amount of data provided by NSDD partner countries highlights the close cooperation and partnerships NSDD has built with 56 countries around the world. Thirty-seven of these countries shared at least some RPM-related data with NSDD in fiscal year 2016. This significant level of data sharing is a key element that distinguishes the NSDD office as unique among nuclear nonproliferation programs and initiatives: NSDD can provide specific, objective, data-driven decisions and support for sustaining the radiation detection systems it helped deploy. This data analysis report summarizes and aggregates the RPM data provided to the NSDD office for analysis and review in fiscal year 2016. The data can be used to describe RPM performance and characterize the wide diversity of NSDD deployment sites. For example, NSDD deploys detector systems across sites with natural background radiation levels that can vary by a factor of approximately six from site to site. Some lanes have few occupancies, whereas others have approximately 8,000 occupancies per day and the different types of cargo that travel through a site can result in site-wide alarm rates that range from near 0% at some sites to above 3% at others. Based on the data received, the global average uptime for NSDD RPMs was above 96% for fiscal year 2016. NSDD takes all of these factors into account in making recommendations to partner countries on how to most effectively manage and maintain site operations. NSDD utilizes reports and other information products created by data analysts to efficiently allocate the resources needed to detect and ultimately interdict illicit nuclear and radiological material.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

A review of artificial intelligence applications in manufacturing operations

Abstract Artificial intelligence (AI) and machine learning (ML) can improve manufacturing efficiency, productivity, and sustainability. However, using AI in manufacturing also presents several challenges, including issues with data acquisition and management, human resources, infrastructure, as well as security risks, trust, and implementation challenges. For example, getting the data needed to train AI models can be difficult for rare events or costly for large datasets that need labeling. AI models can also pose security risks when integrated into industrial control systems. In addition, some industry players may be hesitant to use AI due to a lack of trust or understanding of how it works. Despite these challenges, AI has the potential to be extremely helpful in manufacturing, particularly in applications such as predictive maintenance, quality assurance, and process optimization. It is important to consider the specific needs and capabilities of each manufacturing scenario when deciding whether and how to use AI in manufacturing. This review identifies current developments, challenges, and future directions in AI/ML relevant to manufacturing, with the goal of improving understanding of AI/ML technologies available for solving manufacturing problems, providing decision‐support for prioritizing and selecting appropriate AI/ML technologies, and identifying areas where further research can yield transformational returns for the industry. Early experience suggests that AI/ML can have significant cost and efficiency benefits in manufacturing, especially when combined with the ability to capture enormous amounts of data from manufacturing systems.

Plathottam, Siby Jose↗
NASA NTRS2010

Tropospheric Airborne Meteorological Data Reporting (TAMDAR) Sensor Validation and Verification on National Oceanographic and Atmospheric Administration (NOAA) Lockheed WP-3D Aircraft

As part of the National Aeronautics and Space Administration's Aviation Safety and Security Program, the Tropospheric Airborne Meteorological Data Reporting project (TAMDAR) developed a low-cost sensor for aircraft flying in the lower troposphere. This activity was a joint effort with support from Federal Aviation Administration, National Oceanic and Atmospheric Administration, and industry. This paper reports the TAMDAR sensor performance validation and verification, as flown on board NOAA Lockheed WP-3D aircraft. These flight tests were conducted to assess the performance of the TAMDAR sensor for measurements of temperature, relative humidity, and wind parameters. The ultimate goal was to develop a small low-cost sensor, collect useful meteorological data, downlink the data in near real time, and use the data to improve weather forecasts. The envisioned system will initially be used on regional and package carrier aircraft. The ultimate users of the data are National Centers for Environmental Prediction forecast modelers. Other users include air traffic controllers, flight service stations, and airline weather centers. NASA worked with an industry partner to develop the sensor. Prototype sensors were subjected to numerous tests in ground and flight facilities. As a result of these earlier tests, many design improvements were made to the sensor. The results of tests on a final version of the sensor are the subject of this report. The sensor is capable of measuring temperature, relative humidity, pressure, and icing. It can compute pressure altitude, indicated air speed, true air speed, ice presence, wind speed and direction, and eddy dissipation rate. Summary results from the flight test are presented along with corroborative data from aircraft instruments.

Tsoucalas, George↗
DOE OSTI2016

The Need for Precise and Well-documented Experimental Data on Prompt Fission Neutron Spectra from Neutron-induced Fission of {sup 239}Pu

The spectrum of neutrons emitted promptly after {sup 239}Pu(n,f)—a so-called prompt fission neutron spectrum (PFNS)—is a quantity of high interest, for instance, for reactor physics and global security. However, there are only few experimental data sets available that are suitable for evaluations. In addition, some of those data sets differ by more than their 1-σ uncertainty boundaries. We present the results of MCNP studies indicating that these differences are partly caused by underestimated multiple scattering contributions, over-corrected background, and inconsistent deconvolution methods. A detailed uncertainty quantification for suitable experimental data was undertaken including these effects, and test-evaluations were performed with the improved uncertainty information. The test-evaluations illustrate that the inadequately estimated effects and detailed uncertainty quantification have an impact on the evaluated PFNS and associated uncertainties as well as the neutron multiplicity of selected critical assemblies. A summary of data and documentation needs to improve the quality of the experimental database is provided based on the results of simulations and test-evaluations. Given the possibly substantial distortion of the PFNS by multiple scattering and background effects, special care should be taken to reduce these effects in future measurements, e.g., by measuring the {sup 239}Pu PFNS as a ratio to either the {sup 235}U or {sup 252}Cf PFNS.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Application of DLT cybersecurity stack to TES applications for a scalable, cybersecure, and interoperable future

Transactive Energy Systems (TES) are expected to improve upon existing grid operations and capabilities by enabling the integration of traditional grid resources with distributed energy resources (DER). Distributed Ledger Technology or DLT (e.g., blockchain) presents itself as a viable instrument to support decentralized, autonomous, and tamper-evident applications, which can be leveraged within TES's ecosystem. DLTs can provide pertinent security controls including access controls, data immutability, and traceability in addition to other well-known advantages such as decentralization and scalability. This work demonstrates the DLT Cybersecurity stack and its applicability to TES-based use-cases/applications. The seven-layer DLT cybersecurity stack is a DLT-agnostic framework that can quickly be used to classify and group the individual needs of an application into the different processing and cybersecurity layers offered by a DLT using a common taxonomy and an architectural mapping framework. This enables application engineers to demystify and strengthen the overall security aspects of their systems while maintaining an open perspective towards features and drawbacks that may hinder their performance in real-world scenarios. The paper leverages the work performed by the IEEE P2418.5 - Blockchain for Energy Standards working group.

Blockchain, blockchain interoperability, Cybersecu↗
DOE OSTI2018

VULCON: A System for Vulnerability Prioritization, Mitigation, and Management

Vulnerability remediation is a critical task in operational software and network security management. In this paper, an effective vulnerability management strategy, called VULCON (VULnerability CONtrol), is developed and evaluated. The strategy is based on two fundamental performance metrics: i). Time-to-Vulnerability Remediation (TVR) and; ii). Total Vulnerability Exposure (TVE). VULCON takes as input real vulnerability scan reports, metadata about the discovered vulnerabilities, asset criticality, and personnel resources. VULCON uses a mixed integer multi-objective optimization algorithm to prioritize vulnerabilities for patching, such that the above performance metrics are optimized subject to the given resource constraints. VULCON has been tested on multiple months of real scan data from a Cyber-Security Operations Center (CSOC). Results indicate an overall Total Vulnerability Exposure reduction of 8.97\% when VULCON optimizes a realistic security analyst workforce's effort. Additionally, it is demonstrated that VULCON can determine monthly resources required to maintain a target TVE score. As such, VULCON provides valuable operational guidance for improving vulnerability response processes in CSOCs.

Farris, Katheryn A.↗
NASA NTRS2011

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

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 LANCE (Land, Atmosphere Near-Real-Time Capability for EOS) in 2009. LANCE consists of special processing elements, co-located with selected EOSDIS data centers and processing facilities. A primary goal of LANCE is to bring multiple near-real-time systems under one umbrella, offering commonality in data access, quality control, and latency. LANCE now processes and distributes data from the Moderate Resolution Imaging Spectroradiometer (MODIS), Atmospheric Infrared Sounder (AIRS), Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E), Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) instruments within 3 hours of satellite observation. The Rapid Response System and the Fire Information for Resource Management System (FIRMS) capabilities will be incorporated into LANCE in 2011. LANCE maintains a central website to facilitate easy access to data and user services. LANCE products are extensively tested and compared with science products before being made available to users. Each element also plans to implement redundant network, power and server infrastructure to ensure high availability of data and services. Through the user registration system, users are informed of any data outages and when new products or services will be available for access. Building on a significant investment by NASA in developing science algorithms and products, LANCE creates products that have a demonstrated utility for applications requiring near-real-time data. From lower level data products such as calibrated geolocated radiances to higher-level products such as sea ice extent, snow cover, and cloud cover, users have integrated LANCE data into forecast models and decision support systems. The table above shows the current near-real-time product categories by instrument. The ESDIS Project continues to improve the LANCE system and use the experience gained through practice to seek adjustments to improve the quality and performance of the system. For example, anGC-compliant Web Map Service (WMS) will be added shortly that will allow users to download geo-referenced MODIS images for arbitrary bounding boxes. Further, an OGC-compliant Web Coverage Service (WCS) will be added later this year that will expedite user access to arbitrary data subsets or re-formatted products. AIRS images are now served through WMS and available in multiple formats (PNG, GeoTIFF, KMZ). NASA has established a LANCE User Working Group to steer the development of the system and create a forum for sharing ideas and experiences that are expected to further improve the LANCE capabilities. The LANCE system has proved a success by satisfying the growing needs of the applications and operational communities for land and atmosphere data in near-real-time. NASA's Earth Sciences Division was able to leverage existing science research capabilities to provide the near-real-time community with products and imagery that support monitoring of disasters in a timely manner.

Murphy, Kevin J.↗