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NASA NTRS2013

The Utility of the Real-Time NASA Land Information System Data for Drought Monitoring Applications

Measurements of soil moisture are a crucial component for the proper monitoring of drought conditions. The large spatial variability of soil moisture complicates the problem. Unfortunately, in situ soil moisture observing networks typically consist of sparse point observations, and conventional numerical model analyses of soil moisture used to diagnose drought are of coarse spatial resolution. Decision support systems such as the U.S. Drought Monitor contain drought impact resolution on sub-county scales, which may not be supported by the existing soil moisture networks or analyses. The NASA Land Information System, which is run with 3 km grid spacing over the eastern United States, has demonstrated utility for monitoring soil moisture. Some of the more useful output fields from the Land Information System are volumetric soil moisture in the 0-10 cm and 40-100 cm layers, column-integrated relative soil moisture, and the real-time green vegetation fraction derived from MODIS (Moderate Resolution Imaging Spectroradiometer) swath data that are run within the Land Information System in place of the monthly climatological vegetation fraction. While these and other variables have primarily been used in local weather models and other operational forecasting applications at National Weather Service offices, the use of the Land Information System for drought monitoring has demonstrated utility for feedback to the Drought Monitor. Output from the Land Information System is currently being used at NWS Huntsville to assess soil moisture, and to provide input to the Drought Monitor. Since feedback to the Drought Monitor takes place on a weekly basis, weekly difference plots of column-integrated relative soil moisture are being produced by the NASA Short-term Prediction Research and Transition Center and analyzed to facilitate the process. In addition to the Drought Monitor, these data are used to assess drought conditions for monthly feedback to the Alabama Drought Monitoring and Impact Group and the Tennessee Drought Task Force, which are comprised of federal, state, and local agencies and other water resources professionals.

White, Kristopher D.↗

NASA NTRS2017

Dynamic Routing of Aircraft in the Presence of Adverse Weather Using a POMDP Framework

Each year weather-related airline delays result in hundreds of millions of dollars in additional fuel burn, maintenance, and lost revenue, not to mention passenger inconvenience. The current approaches for aircraft route planning in the presence of adverse weather still mainly rely on deterministic methods. In contrast, this work aims to deal with the problem using a Partially Observable Markov Decision Processes (POMDPs) framework, which allows for reasoning over uncertainty (including uncertainty in weather evolution over time) and results in solutions that are more robust to disruptions. The POMDP-based decision support system is demonstrated on several scenarios involving convective weather cells and is benchmarked against a deterministic planning system with functionality similar to those currently in use or under development.

Decision making↗

NASA NTRS2017

Reusing JPSS Ground System Components to Process Aura Ozone Monitoring Instrument Science Products

New Earth observation instruments are planned to enable advancements in Earth science research over the next decade. Diversity of Earth observing instruments and their observing platforms will continue to increase as new instrument technologies emerge and are deployed as part of National programs such as Joint Polar Satellite System (JPSS), Geostationary Operational Environmental Satellite system (GOES), Landsat as well as the potential for many CubeSat and aircraft missions. The practical use and value of these observational data often extends well beyond their original purpose. The practicing community needs intuitive and standardized tools to enable quick unfettered development of tailored products for specific applications and decision support systems. However, the associated data processing system can take years to develop and requires inherent knowledge and the ability to integrate increasingly diverse data types from multiple sources. This paper describes the adaptation of a large-scale data processing system built for supporting JPSS algorithm calibration and validation (CalVal) node to a simplified science data system for rapid application. The new configurable data system reuses scalable JAVA technologies built for the JPSS Government Resource for Algorithm Verification, Independent Test, and Evaluation (GRAVITE) system to run within a laptop environment and support product generation and data processing of AURA Ozone Monitoring Instrument (OMI) science products. Of particular interest are the root requirements necessary for integrating experimental algorithms and Hierarchical Data Format (HDF) data access libraries into a science data production system. This study demonstrates the ability to reuse existing Ground System technologies to support future missions with minimal changes.

Science Data Systems↗

NASA NTRS2006

Linking Asthma Exacerbation and Air Pollution Data: A Step Toward Public Health and Environmental Data Integration

Studies have shown that reducing exposure to triggers such as air pollutants can reduce symptoms and the need for medication in asthma patients. However, systems that track asthma are generally not integrated with those that track environmental hazards related to asthma. Tlvs lack of integration hinders public health awareness and responsiveness to these environmental triggers. The current study is a collaboration between health and environmental professionals to utilize NASA-derived environmental data to develop a decision support system (DSS) for asthma prediction, surveillance, and intervention. The investigators link asthma morbidity data from the University of Mississippi Medical Center (UMMC) and Mississippi Department of Health (MDH) with air quality data from the Mississippi Department of Environmental Quality (MDEQ) and remote sensing data from NASA. Daily ambient environmental hazard data for PM2.5 and ozone are obtained from the MDEQ air quality monitoring locations and are combined with remotely sensed data from NASA to develop a state-wide spatial and time series profile of environmental air quality. These data are then used to study the correlation of these measures of air quality variation with the asthma exacerbation incidence throughout the state over time. The goal is to utilize these readily available measures to allow real-time risk assessment for asthma exacerbations. GeoMedStat, a DSS previously developed for biosurveillance, will integrate these measures to monitor, analyze and report the real-time risk assessment for asthma exacerbation throughout the state.

Faruque, Fazlay↗

NASA NTRS2012

On the Transition and Migration of Flight Functions in the Airspace System

Since ~400 BC, when man first replicated flying behavior with kites, up until the turn of the 20th century, when the Wright brothers performed the first successful powered human flight, flight functions have become available to man via significant support from man-made structures and devices. Over the past 100 years or so, technology has enabled several flight functions to migrate to automation and/or decision support systems. This migration continues with the United States NextGen and Europe s Single European Sky (a.k.a. SESAR) initiatives. These overhauls of the airspace system will be accomplished by accommodating the functional capabilities, benefits, and limitations of technology and automation together with the unique and sometimes overlapping functional capabilities, benefits, and limitations of humans. This paper will discuss how a safe and effective migration of any flight function must consider several interrelated issues, including, for example, shared situation awareness, and automation addiction, or over-reliance on automation. A long-term philosophical perspective is presented that considers all of these issues by primarily asking the following questions: How does one find an acceptable level of risk tolerance when allocating functions to automation versus humans? How does one measure or predict with confidence what the risks will be? These two questions and others will be considered from the two most-discussed paradigms involving the use of increasingly complex systems in the future: humans as operators and humans as monitors.

Morris, Allan Terry↗

NASA NTRS2004

Aura Earth Observing System

Aura is designed to answer questions about changes in our life-sustaining atmosphere. Aura's four instruments will study the atmosphere's chemistry and dynamics. Aura's measurements will enable us to investigate questions about ozone trends, air quality changes and their linkage to climate change. Aura's measurements will provide accurate data for predictive models and provide useful information for local and national agency decision support systems. Aura is the third in a series of large Earth observing platforms to be flown by the National Aeronautics and Space Administration (NASA) with international contributions. Aura along with EOS Terra (launched December, 1999) and Aqua (launched May, 2002) will provide an unprecedented view of the global Earth system.

Hilsenrath, Ernest↗

NASA NTRS1993

Software Products

MAST is a decision support system to help in the management of dairy herds. Data is collected on dairy herds around the country and processed at regional centers. One center is Cornell University, where Dr. Lawrence Jones and his team developed MAST. The system draws conclusions from the data and summarizes it graphically. CLIPS, which is embedded in MAST, gives the system the ability to make decisions without user interaction. With this technique, dairy managers can identify herd problems quickly, resulting in improved animal health and higher milk quality. CLIPS (C Language Integrated Production System) was developed by NASA's Johnson Space Center. It is a shell for developing expert systems designed to permit research, development and delivery on conventional computers.

Source record↗

NASA NTRS2007

Using NASA Techniques to Atmospherically Correct AWiFS Data for Carbon Sequestration Studies

Carbon dioxide is a greenhouse gas emitted in a number of ways, including the burning of fossil fuels and the conversion of forest to agriculture. Research has begun to quantify the ability of vegetative land cover and oceans to absorb and store carbon dioxide. The USDA (U.S. Department of Agriculture) Forest Service is currently evaluating a DSS (decision support system) developed by researchers at the NASA Ames Research Center called CASA-CQUEST (Carnegie-Ames-Stanford Approach-Carbon Query and Evaluation Support Tools). CASA-CQUEST is capable of estimating levels of carbon sequestration based on different land cover types and of predicting the effects of land use change on atmospheric carbon amounts to assist land use management decisions. The CASA-CQUEST DSS currently uses land cover data acquired from MODIS (the Moderate Resolution Imaging Spectroradiometer), and the CASA-CQUEST project team is involved in several projects that use moderate-resolution land cover data derived from Landsat surface reflectance. Landsat offers higher spatial resolution than MODIS, allowing for increased ability to detect land use changes and forest disturbance. However, because of the rate at which changes occur and the fact that disturbances can be hidden by regrowth, updated land cover classifications may be required before the launch of the Landsat Data Continuity Mission, and consistent classifications will be needed after that time. This candidate solution investigates the potential of using NASA atmospheric correction techniques to produce science-quality surface reflectance data from the Indian Remote Sensing Advanced Wide-Field Sensor on the RESOURCESAT-1 mission to produce land cover classification maps for the CASA-CQUEST DSS.

Holekamp, Kara L.↗

NASA NTRS2015

Electronic Procedures for Medical Operations

Electronic procedures are replacing text-based documents for recording the steps in performing medical operations aboard the International Space Station. S&K Aerospace, LLC, has developed a content-based electronic system-based on the Extensible Markup Language (XML) standard-that separates text from formatting standards and tags items contained in procedures so they can be recognized by other electronic systems. For example, to change a standard format, electronic procedures are changed in a single batch process, and the entire body of procedures will have the new format. Procedures can be quickly searched to determine which are affected by software and hardware changes. Similarly, procedures are easily shared with other electronic systems. The system also enables real-time data capture and automatic bookmarking of current procedure steps. In Phase II of the project, S&K Aerospace developed a Procedure Representation Language (PRL) and tools to support the creation and maintenance of electronic procedures for medical operations. The goal is to develop these tools in such a way that new advances can be inserted easily, leading to an eventual medical decision support system.

Source record↗

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.↗

NASA NTRS2023

Exploration Medical Capability Clinical Decision Support Use Cases for CDSS Test Bed

Long-duration, deep-space exploration missions present significant challenges to crew health and performance. These challenges include the individual and combined effects of microgravity, radiation exposure, isolation, limited resources (mass, volume, power, data, and crew time), limited options for evacuation, and those associated with delayed or constrained communications. Each of these challenges necessitates greater degrees of crew autonomy as our distance from Earth increases. Specifically, as communication delays intensify - and evacuation capability diminishes the further we explore space - the unqualified need for Earth-independent medical operations focused on autonomous diagnosis, treatment and prevention will become key to mission continuation and success. This need will be especially true should a crewmember become ill or injured wherein treatment and disposition “in-situ” ultimately falls to the crew itself to determine. To augment the requisite knowledge, skills, and abilities (KSAs) of a time-constrained exploration mission crew operating under stressful conditions, combatting fatigue, and facing a potential medical crisis, a robust clinical decision support system (CDSS) is a probable solution. A CDSS would facilitate, guide, and inform Earth-independent medical operations while assisting crewmembers through various clinical presentations. The CDSS would allow crewmembers to take advantage of pre-mission training tied to the in-flight/in-mission use of pre-planned protocols that offer both a range of diagnostic options and “just-in-time” (refamiliarization) training and assistance. CDSS will expand such capabilities by improving the utility and effectiveness of various available diagnostic, treatment, and health maintenance tools, techniques, and measures.

ExMC↗

NASA NTRS1990

Automating hypertext for decision support

A decision support system (DSS) shell is being constructed that can support applications in a variety of fields, e.g., engineering, manufacturing, finance. The shell provides a hypertext-style interface for 'navigating' among DSS application models, data, and reports. The traditional notion of hypertext had to be enhanced. Hypertext normally requires manually, pre-defined links. A DSS shell, however, requires that hypertext connections to be built 'on the fly'. The role of hypertext is discussed in augmenting DSS applications and the decision making process. Also discussed is how hypertext nodes, links, and link markers tailored to an arbitrary DSS application were automatically generated.

Bieber, Michael↗

NASA NTRS2014

Carbon-Temperature-Water Change Analysis for Peanut Production Under Climate Change: A Prototype for the AgMIP Coordinated Climate-Crop Modeling Project (C3MP)

Climate change is projected to push the limits of cropping systems and has the potential to disrupt the agricultural sector from local to global scales. This article introduces the Coordinated Climate-Crop Modeling Project (C3MP), an initiative of the Agricultural Model Intercomparison and Improvement Project (AgMIP) to engage a global network of crop modelers to explore the impacts of climate change via an investigation of crop responses to changes in carbon dioxide concentration ([CO2]), temperature, and water. As a demonstration of the C3MP protocols and enabled analyses, we apply the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Peanut crop model for Henry County, Alabama, to evaluate responses to the range of plausible [CO2], temperature changes, and precipitation changes projected by climate models out to the end of the 21st century. These sensitivity tests are used to derive crop model emulators that estimate changes in mean yield and the coefficient of variation for seasonal yields across a broad range of climate conditions, reproducing mean yields from sensitivity test simulations with deviations of ca. 2% for rain-fed conditions. We apply these statistical emulators to investigate how peanuts respond to projections from various global climate models, time periods, and emissions scenarios, finding a robust projection of modest (<10%) median yield losses in the middle of the 21st century accelerating to more severe (>20%) losses and larger uncertainty at the end of the century under the more severe representative concentration pathway (RCP8.5). This projection is not substantially altered by the selection of the AgMERRA global gridded climate dataset rather than the local historical observations, differences between the Third and Fifth Coupled Model Intercomparison Project (CMIP3 and CMIP5), or the use of the delta method of climate impacts analysis rather than the C3MP impacts response surface and emulator approach.

climate change↗

NASA NTRS2013

Near Real-Time Applications of Earth Remote Sensing for Response to Meteorological Disasters

Numerous on‐orbit satellites provide a wide range of spatial, spectral, and temporal resolutions supporting the use of their resulting imagery in assessments of disasters that are meteorological in nature. This presentation will provide an overview of recent use of Earth remote sensing by NASA's Short‐term Prediction Research and Transition (SPoRT) Center in response to disaster activities in 2012 and 2013, along with case studies supporting ongoing research and development. The SPoRT Center, with support from NASA's Applied Sciences Program, has explored a variety of new applications of Earth‐observing sensors to support disaster response. In May 2013, the SPoRT Center developed unique power outage composites representing 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. Subsequent ASTER, MODIS, Landsat‐7 and Landsat‐8 imagery help to identify the damaged area. Higher resolution imagery of Moore, Oklahoma were provided by commercial satellites and the recently available International Space Station (ISS) SERVIR Environmental Research and Visualization System (ISERV) instrument. New techniques are being explored by the SPoRT team in order to better identify damage visible in high resolution imagery, and to monitor ongoing recovery for Moore, Oklahoma. Other applications are being developed to refine light source detections with the VIIRS day‐night band and to map hail during the growing season through combination of available satellite and radar imagery. The aforementioned products and support are not useful unless they are distributed in a timely manner and within an appropriate decision support system. This presentation will provide an update on ongoing activities to support inclusion of these data sets within the NOAA National Weather Service Damage Assessment Toolkit, which allows meteorologists in the field to consult available satellite imagery while performing their damage assessment.

Molthan, Andrew L.↗

NASA NTRS2013

Near Real-Time Applications of Earth Remote Sensing for Response to Meteorological Disasters

Molthan, Andrew L.↗

NASA NTRS2006

Simulating Visible/Infrared Imager Radiometer Suite Normalized Difference Vegetation Index Data Using Hyperion and MODIS

The success of MODIS (the Moderate Resolution Imaging Spectrometer) in creating unprecedented, timely, high-quality data for vegetation and other studies has created great anticipation for data from VIIRS (the Visible/Infrared Imager Radiometer Suite). VIIRS will be carried onboard the joint NASA/Department of Defense/National Oceanic and Atmospheric Administration NPP (NPOESS (National Polar-orbiting Operational Environmental Satellite System) Preparatory Project). Because the VIIRS instruments will have lower spatial resolution than the current MODIS instruments 400 m versus 250 m at nadir for the channels used to generate Normalized Difference Vegetation Index data, scientists need the answer to this question: how will the change in resolution affect vegetation studies? By using simulated VIIRS measurements, this question may be answered before the VIIRS instruments are deployed in space. Using simulated VIIRS products, the U.S. Department of Agriculture and other operational agencies can then modify their decision support systems appropriately in preparation for receipt of actual VIIRS data. VIIRS simulations and validations will be based on the ART (Application Research Toolbox), an integrated set of algorithms and models developed in MATLAB(Registerd TradeMark) that enables users to perform a suite of simulations and statistical trade studies on remote sensing systems. Specifically, the ART provides the capability to generate simulated multispectral image products, at various scales, from high spatial hyperspectral and/or multispectral image products. The ART uses acquired ( real ) or synthetic datasets, along with sensor specifications, to create simulated datasets. For existing multispectral sensor systems, the simulated data products are used for comparison, verification, and validation of the simulated system s actual products. VIIRS simulations will be performed using Hyperion and MODIS datasets. The hyperspectral and hyperspatial properties of Hyperion data will be used to produce simulated MODIS and VIIRS products. Hyperion-derived MODIS data will be compared with near-coincident MODIS collects to validate both spectral and spatial synthesis, which will ascertain the accuracy of converting from MODIS to VIIRS. MODIS-derived VIIRS data is needed for global coverage and for the generation of time series for regional and global investigations. These types of simulations will have errors associated with aliasing for some scene types. This study will help quantify these errors and will identify cases where high-quality, MODIS-derived VIIRS data will be available.

Ross, Kenton W.↗

NASA NTRS1997

An Integrated Product Environment

Mechanical Advantage is a mechanical design decision support system. Unlike our CAD/CAM cousins, Mechanical Advantage addresses true engineering processes, not just the form and fit of geometry. If we look at a traditional engineering environment, we see that an engineer starts with two things - performance goals and design rules. The intent is to have a product perform specific functions and accomplish that within a designated environment. Geometry should be a simple byproduct of that engineering process - not the controller of it. Mechanical Advantage is a performance modeler allowing engineers to consider all these criteria in making their decisions by providing such capabilities as critical parameter analysis, tolerance and sensitivity analysis, math driven Geometry, and automated design optimizations. If you should desire an industry standard solid model, we would produce an ACIS-based solid model. If you should desire an ANSI/ISO standard drawing, we would produce this as well with a virtual push of the button. For more information on this and other Advantage Series products, please contact the author.

Higgins, Chuck↗

NASA NTRS2004

Data Communications Performance of AOCDL and AUTOMET Over a VDL Mode 2 Link

Airline Operational Control Data Link (AOCDL) is a service that allows for downlink of in-flight data to help an airline operate efficiently. Automated Meteorological Transmission (AUTOMET) is a weather reporting system that provides forecasts and atmospheric conditions to pilots during flight. These are two examples of new or extended services that will be enabled by implementation of the ATN and its digital air/ground communications data links. One of the possible data links identified for these services is VDL Mode 2. This research focuses on the data link performance of AOCDL and AUTOMET services in a 2015 scenario using VDL Mode 2 as the data link. In the near term, it is expected that the Controller-Pilot Data Link Communication (CPDLC) and Decision Support System Data Link (DSSDL) services will also use the VDL Mode 2 link. CPDLC and DSSDL are high-priority services that communicate aircraft control information and require low end-to-end delays for safety. VDL Mode 3, which is the preferred link for these services because it provides priority-based link access, will not be deployed in time for earlier implementations of these services to use. As such, the research also investigates the impact of CPDLC and DSSDL services on the same VDL link as AOCDL and AUTOMET. Performance of these services over the data link will be separately examined for the airport, terminal, and en route domains. OPNET simulations are performed for each domain. The number of aircraft for each domain is representative of the expected peak aircraft in 2015. Results are collected during a steady-state condition, with aircraft neither entering nor exiting the domain. The study explores the services in terms of the traffic load they present to the VDL Mode 2 radio. The amount of load each service contributes to the data link will be shown for each domain. The end-to-end delays for each service will be discussed. Data link metrics such as subnetwork and queuing delays, channel utilization, and protocol overhead will be used to show the impact of these services on VDL Mode 2. All results will be presented both with and without the inclusion of CPDLC and DSSDL services.

Bretmersky, Steven↗