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At least 415 records · Page 23

Measurement and Modelling of Multicopter UAS Rotor Blades in Hover

Multicopters are becoming one of the more common and popular type of unmanned aircraft systems (UAS) which have both civilian and military applications. One example being the concept of drone deliveries proposed by the distribution company Amazon [1]. The electrical propulsion is considered to have both faster and easier deliveries and also environmental benefits compared to other vehicles that still use fossil fuel. Other examples include surveillance and just simple entertainment. The reason behind their success is often said to be due to their small size, relatively low cost, simple structure and finally simple usage. With an increase in the UAS market comes challenges in terms of security, as both people and other aircrafts could be harmed if not used correctly. Therefore further studies and regulations are needed to ensure that future use of drones, especially in the civilian and public sectors, are safe and efficient. Thorough research has been done on full scale, man or cargo transporting, helicopters so that most parts of flight and performance are fairly well understood. Yet not much of it have been verified for small multicopters. Until today many studies and research projects have been done on the control systems, navigation and aerodynamics of multicopters. Many of the methods used today for building multicopters involve a process of trial an error of what will work well together, and once that is accomplished some structural analysis of the multicopter bodies might be done to verify that the product will be strong enough and have a decent aerodynamic performance. However, not much has been done on the research of the rotor blades, especially in terms of structural stress analyses and ways to ensure that the commonly used parts are indeed safe and follow safety measures. Some producers claim that their propellers indeed have been tested, but again that usually tends towards simple fluid dynamic analyses and even simpler stress analyses. There is no real deflection measurement of said blades and all theory is today based on the theory developed for full scale helicopters. This report thus intends to highlight the problems that come with blade deflection theory and measurements for multicopters. This thesis starts with the introduction and problem formulation where the grounds for what the report contains are laid out. Then a literature review of the research within the area follows where previous and current research and methods are presented. In the background information and theory relevant to the area are presented. After that the methods and set up of the different experimental and computer simulation approaches are depicted. In the results section the obtained results are presented and compared. Lastly there is a discussion where the results and methods are evaluated and analyzed, followed by the most important conclusions.

Multicopter UAS Rotor Blades↗

Decision Engines for Software Analysis Using Satisfiability Modulo Theories Solvers

The area of software analysis, testing and verification is now undergoing a revolution thanks to the use of automated and scalable support for logical methods. A well-recognized premise is that at the core of software analysis engines is invariably a component using logical formulas for describing states and transformations between system states. The process of using this information for discovering and checking program properties (including such important properties as safety and security) amounts to automatic theorem proving. In particular, theorem provers that directly support common software constructs offer a compelling basis. Such provers are commonly called satisfiability modulo theories (SMT) solvers. Z3 is a state-of-the-art SMT solver. It is developed at Microsoft Research. It can be used to check the satisfiability of logical formulas over one or more theories such as arithmetic, bit-vectors, lists, records and arrays. The talk describes some of the technology behind modern SMT solvers, including the solver Z3. Z3 is currently mainly targeted at solving problems that arise in software analysis and verification. It has been applied to various contexts, such as systems for dynamic symbolic simulation (Pex, SAGE, Vigilante), for program verification and extended static checking (Spec#/Boggie, VCC, HAVOC), for software model checking (Yogi, SLAM), model-based design (FORMULA), security protocol code (F7), program run-time analysis and invariant generation (VS3). We will describe how it integrates support for a variety of theories that arise naturally in the context of the applications. There are several new promising avenues and the talk will touch on some of these and the challenges related to SMT solvers. Proceedings

Bjorner, Nikolaj↗

Modeling, simulation, and analysis of optical remote sensing systems

Remote Sensing of the Earth's resources from space-based sensors has evolved in the past 20 years from a scientific experiment to a commonly used technological tool. The scientific applications and engineering aspects of remote sensing systems have been studied extensively. However, most of these studies have been aimed at understanding individual aspects of the remote sensing process while relatively few have studied their interrelations. A motivation for studying these interrelationships has arisen with the advent of highly sophisticated configurable sensors as part of the Earth Observing System (EOS) proposed by NASA for the 1990's. Two approaches to investigating remote sensing systems are developed. In one approach, detailed models of the scene, the sensor, and the processing aspects of the system are implemented in a discrete simulation. This approach is useful in creating simulated images with desired characteristics for use in sensor or processing algorithm development. A less complete, but computationally simpler method based on a parametric model of the system is also developed. In this analytical model the various informational classes are parameterized by their spectral mean vector and covariance matrix. These class statistics are modified by models for the atmosphere, the sensor, and processing algorithms and an estimate made of the resulting classification accuracy among the informational classes. Application of these models is made to the study of the proposed High Resolution Imaging Spectrometer (HRIS). The interrelationships among observational conditions, sensor effects, and processing choices are investigated with several interesting results.

Kerekes, John Paul↗

SeaTrack: Ground station orbit prediction and planning software for sea-viewing satellites

An orbit prediction software package (Sea Track) was designed to assist High Resolution Picture Transmission (HRPT) stations in the acquisition of direct broadcast data from sea-viewing spacecraft. Such spacecraft will be common in the near future, with the launch of the Sea viewing Wide Field-of-view Sensor (SeaWiFS) in 1994, along with the continued Advanced Very High Resolution Radiometer (AVHRR) series on NOAA platforms. The Brouwer-Lyddane model was chosen for orbit prediction because it meets the needs of HRPT tracking accuracies, provided orbital elements can be obtained frequently (up to within 1 week). Sea Track requires elements from the U.S. Space Command (NORAD Two-Line Elements) for the satellite's initial position. Updated Two-Line Elements are routinely available from many electronic sources (some are listed in the Appendix). Sea Track is a menu-driven program that allows users to alter input and output formats. The propagation period is entered by a start date and end date with times in either Greenwich Mean Time (GMT) or local time. Antenna pointing information is provided in tabular form and includes azimuth/elevation pointing angles, sub-satellite longitude/latitude, acquisition of signal (AOS), loss of signal (LOS), pass orbit number, and other pertinent pointing information. One version of Sea Track (non-graphical) allows operation under DOS (for IBM-compatible personal computers) and UNIX (for Sun and Silicon Graphics workstations). A second, graphical, version displays orbit tracks, and azimuth-elevation for IBM-compatible PC's, but requires a VGA card and Microsoft FORTRAN.

Lambert, Kenneth S.↗

SAVS: A Space and Atmospheric Visualization Science system

The research environment faced by space and atmospheric scientists in the 1990s is characterized by unprecedented volumes of new data, by ever-increasing repositories of unexploited mission files, and by the widespread use of empirical and large-scale computational models needed for the synthesis of understanding across data sets and discipline boundaries. The effective analysis and interpretation of such massive amounts of information have become the subjects of legitimate concern. With SAVS (a Space and Atmospheric Visualization Science System), we address these issues by creating a 'push-button' software environment that mimics the logical scientific processes in data acquisition, reduction, and analysis without requiring a detailed understanding of the methods, networks, and modules that link the tools and effectively execute the functions. SAVS provides (1) a customizable framework for accessing a powerful set of visualization tools based on the popular AVS visualization software with hooks to PV-Wave and access to Khoros modules, (2) a set of mathematical and statistical tools, (3) an extensible library of discipline-specific functions and models (e.g., MSIS, IRI, Feldstein Oval, IGRF, satellite tracking with CADRE-3, etc.), and (4) capabilities for local and remote data base access. The system treats scalar, vector, and image data, and runs on most common Unix workstations. We present a description of SAVS and its components, followed by several applications based on generic research interests in interplanetary and magnetospheric physics (IMP/ISTP), active experiments in space (CRRES), and mission planning focused on the Earth's thermospheric, ionospheric, and mesospheric domains (TIMED).

Szuszczewicz, E. P.↗

Application of ML/AI for Identifying Earth Science Datasets in Research Publications

NASA Data Active Archive Centers, or DAACs, ingest, store and distribute data acquired from satellites, ground systems as well as modelling data. These data are organized by the datasets, each presenting collection of files usually associated with the certain mission, instrument, processing level, parameter(s), algorithm and/or model. The number of datasets offered by a single DAAC to the public varies. GES DISC, for example, currently offers for public use approximately ~1,300 datasets. While each publicly offered dataset comes with supporting documentation, it is challenging for novice and even experienced scientists to navigate among the datasets that offer similar parameters to find the datasets for their particular research application. Supplying dataset documentation with the scientific paper citations that refer to that dataset provides means for the dataset users to educate themselves with the application research that dataset is being used in. Collecting citations of the papers that use the datasets for their research yield valuable insights into application areas of those datasets, information about usage of the dataset groups for specific applications and those application topics. It also gives insights into the “deep metrics” of the dataset usage, as opposed to the common metrics of the dataset usage such as number of users who downloaded the dataset files and volumes of downloaded data. Association of a certain scientific paper with the dataset(s) presents a challenge because most of the paper authors do not properly cite the datasets, datasets usually have cryptic names and Digital Object Identifiers (DOIs) that are used for dataset identification were assigned to the datasets only few years ago. Simple Google or online library search do not provide even meaningful fraction of the results when performed by the dataset name or DOI, however they provide too many results when the search is done by more broader terms such as mission and instrument names. Attempts to create an AI system capable to identify dataset in the scientific papers have already been made using neural networks classifiers on the basis of the dataset mission, instrument and variable name. This method was applied to NASA SEDAC, which has 41 datasets in total. In GES DISC there can be as many as ~100 datasets per mission/instrument with some of the datasets consisting of multiple variables so there is a need for more differentiating parameters for dataset identification in the paper. The approach we are currently investigating is creating AI classifiers that are based on multiple dataset features, or keywords, extracted from the NASA Earthdata Common Dataset Repository (CMR). The features are weighted based on how precisely they can identify a dataset. The classifier uses preprocessed paper text as input and searches for the CMR datasets whose feature sets are the closest to the feature sets contained in the paper. The challenges of dataset identification include variety of ways the paper authors describe the datasets in their papers and incomplete tagging of the CMR dataset description (DIFs).

Irina Gerasimov↗

Earth's Earliest Ecosystems in the C: The Use of Microbial Mats to Demonstrate General Principles of Scientific Inquiry and Microbial Ecology

Microbial mats are living examples of the most ancient biological communities on Earth. As Earth's earliest ecosystems, they are centrally important to understanding the history of life on our planet and are useful models for the search for life elsewhere. As relatively compact (but complete) ecosystems, microbial mats are also extremely useful for educational activities. Mats may be used to demonstrate a wide variety of concepts in general and microbial ecology, including the biogeochemical cycling of elements, photosynthesis and respiration, and the origin of the Earth's present oxygen containing atmosphere. Microbial mats can be found in a number of common environments accessible to teachers, and laboratory microbial mats can be constructed using materials purchased from biological supply houses. With funding from NASA's Exobiology program, we have developed curriculum and web-based activities centered on the use of microbial mats as tools for demonstrating general principles in ecology, and the scientific process. Our web site (http://microbes.arc.nasa.gov) includes reference materials, lesson plans, and a "Web Lab", featuring living mats maintained in a mini-aquarium. The site also provides information as to how research on microbial mats supports NASA's goals, and various NASA missions. A photo gallery contains images of mats, microscopic views of the organisms that form them, and our own research activities. An animated educational video on the web site uses computer graphic and video microscopy to take students on a journey into a microbial mat. These activities are targeted to a middle school audience and are aligned with the National Science Standards.

Bebout, Brad M.↗

Harvesting NASA's Common Metadata Repository (CMR)

As part of NASA's Earth Observing System Data and Information System (EOSDIS), the Common Metadata Repository (CMR) stores metadata for over 30,000 datasets from both NASA and international providers along with over 300M granules. This metadata enables sub-second discovery and facilitates data access. While the CMR offers a robust temporal, spatial and keyword search functionality to the general public and international community, it is sometimes more desirable for international partners to harvest the CMR metadata and merge the CMR metadata into a partner's existing metadata repository. This poster will focus on best practices to follow when harvesting CMR metadata to ensure that any changes made to the CMR can also be updated in a partner's own repository. Additionally, since each partner has distinct metadata formats they are able to consume, the best practices will also include guidance on retrieving the metadata in the desired metadata format using CMR's Unified Metadata Model translation software.

Earth Resources↗

Analysis of the Global Microwave Polarization Data of Clouds

Information about the characteristics of ice particles in clouds is necessary for improving our understanding of the states, processes, and subsequent modeling of clouds and precipitation for numerical weather prediction and climate analysis. Two NASA passive microwave radiometers, the satellite-borne Global Precipitation Measurement (GPM) Microwave Imager (GMI) and the aircraft-borne Conical Scanning Millimeter-Wave Imaging Radiometer (CoSMIR), measure vertically and horizontally polarized microwaves emitted by clouds (including precipitating particles) and Earth’s surface below. In this paper, GMI (or CoSMIR) data are analyzed with CloudSat (or aircraft-borne radar) data to find polarized difference (PD) signals not affected by the surface, thereby obtaining the information on ice particles. Statistical analysis of 4 years of GMI and CloudSat data, for the first time, reveals that optically thick clouds contribute positively to GMI PD at 166GHz over all the latitudes and their positive magnitude of 166-GHz GMI PD varies little with latitude. This result suggests that horizontally oriented ice crystals in thick clouds are common from the tropics to high latitudes, which contrasts the result of Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) that horizontally oriented ice crystals are rare in optically thin ice clouds.

Xiping Zeng↗

ELISA, a demonstrator environment for information systems architecture design

This paper describes an approach of reusability of software engineering technology in the area of ground space system design. System engineers have lots of needs similar to software developers: sharing of a common data base, capitalization of knowledge, definition of a common design process, communication between different technical domains. Moreover system designers need to simulate dynamically their system as early as possible. Software development environments, methods and tools now become operational and widely used. Their architecture is based on a unique object base, a set of common management services and they host a family of tools for each life cycle activity. In late '92, CNES decided to develop a demonstrative software environment supporting some system activities. The design of ground space data processing systems was chosen as the application domain. ELISA (Integrated Software Environment for Architectures Specification) was specified as a 'demonstrator', i.e. a sufficient basis for demonstrations, evaluation and future operational enhancements. A process with three phases was implemented: system requirements definition, design of system architectures models, and selection of physical architectures. Each phase is composed of several activities that can be performed in parallel, with the provision of Commercial Off the Shelves Tools. ELISA has been delivered to CNES in January 94, currently used for demonstrations and evaluations on real projects (e.g. SPOT4 Satellite Control Center). It is on the way of new evolutions.

Panem, Chantal↗

A diagnosis system using object-oriented fault tree models

Spaceborne computing systems must provide reliable, continuous operation for extended periods. Due to weight, power, and volume constraints, these systems must manage resources very effectively. A fault diagnosis algorithm is described which enables fast and flexible diagnoses in the dynamic distributed computing environments planned for future space missions. The algorithm uses a knowledge base that is easily changed and updated to reflect current system status. Augmented fault trees represented in an object-oriented form provide deep system knowledge that is easy to access and revise as a system changes. Given such a fault tree, a set of failure events that have occurred, and a set of failure events that have not occurred, this diagnosis system uses forward and backward chaining to propagate causal and temporal information about other failure events in the system being diagnosed. Once the system has established temporal and causal constraints, it reasons backward from heuristically selected failure events to find a set of basic failure events which are a likely cause of the occurrence of the top failure event in the fault tree. The diagnosis system has been implemented in common LISP using Flavors.

Iverson, David L.↗

Electronic photography at NASA Langley Research Center

The field of photography began a metamorphosis several years ago which promises to fundamentally change how images are captured, transmitted, and output. At this time the metamorphosis is still in the early stages, but already new processes, hardware, and software are allowing many individuals and organizations to explore the entry of imaging into the information revolution. Exploration at this time is prerequisite to leading expertise in the future, and a number of branches at LaRC have ventured into electronic and digital imaging. Their progress until recently has been limited by two factors: the lack of an integrated approach and the lack of an electronic photographic capability. The purpose of the research conducted was to address these two items. In some respects, the lack of electronic photographs has prevented application of an integrated imaging approach. Since everything could not be electronic, the tendency was to work with hard copy. Over the summer, the Photographics Section has set up an Electronic Photography Laboratory. This laboratory now has the capability to scan film images, process the images, and output the images in a variety of forms. Future plans also include electronic capture capability. The current forms of image processing available include sharpening, noise reduction, dust removal, tone correction, color balancing, image editing, cropping, electronic separations, and halftoning. Output choices include customer specified electronic file formats which can be output on magnetic or optical disks or over the network, 4400 line photographic quality prints and transparencies to 8.5 by 11 inches, and 8000 line film negatives and transparencies to 4 by 5 inches. The problem of integrated imaging involves a number of branches at LaRC including Visual Imaging, Research Printing and Publishing, Data Visualization and Animation, Advanced Computing, and various research groups. These units must work together to develop common approaches to image processing and archiving. The ultimate goal is to be able to search for images using an on-line database and image catalog. These images could then be retrieved over the network as needed, along with information on the acquisition and processing prior to storage. For this goal to be realized, a number of standard processing protocols must be developed to allow the classification of images into categories. Standard series of processing algorithms can then be applied to each category (although many of these may be adaptive between images). Since the archived image files would be standardized, it should also be possible to develop standard output processing protocols for a number of output devices. If LaRC continues the research effort begun this summer, it may be one of the first organizations to develop an integrated approach to imaging. As such, it could serve as a model for other organizations in government and the private sector.

Holm, Jack M.↗

Vertical Cloud Climatology During TC4 Derived from High-Altitude Aircraft Merged Lidar and Radar Profiles

Aircraft lidar works by shooting laser pulses toward the earth and recording the return time and intensity of any of the light returning to the aircraft after scattering off atmospheric particles and/or the Earth s surface. The scattered light signatures can be analyzed to tell the exact location of cloud and aerosol layers and, with the aid of a few optical assumptions, can be analyzed to retrieve estimates of optical properties such as atmospheric transparency. Radar works in a similar fashion except it sends pulses toward earth at a much larger wavelength than lidar. Radar records the return time and intensity of cloud or rain reflection returning to the aircraft. Lidar can measure scatter from optically thin cirrus and aerosol layers whose particles are too small for the radar to detect. Radar can provide reflection profiles through thick cloud layers of larger particles that lidar cannot penetrate. Only after merging the two instrument products can accurate measurements of the locations of all layers in the full atmospheric column be achieved. Accurate knowledge of the vertical distribution of clouds is important information for understanding the Earth/atmosphere radiative balance and for improving weather/climate forecast models. This paper describes one such merged data set developed from the Tropical Composition, Cloud and Climate Coupling (TC4) experiment based in Costa Rica in July-August 2007 using the nadir viewing Cloud Physics Lidar (CPL) and the Cloud Radar System (CRS) on board the NASA ER-2 aircraft. Statistics were developed concerning cloud probability through the atmospheric column and frequency of the number of cloud layers. These statistics were calculated for the full study area, four sub-regions, and over land compared to over ocean across all available flights. The results are valid for the TC4 experiment only, as preferred cloud patterns took priority during mission planning. The TC4 Study Area was a very cloudy region, with cloudy profiles occurring 94 percent of the time during the ER-2 flights. One to three cloud layers were common, with the average calculated at 2.03 layers per profile. The upper troposphere had a cloud frequency generally over 30%, reaching 42 percent near 13 km during the study. There were regional differences. The Caribbean was much clearer than the Pacific regions. Land had a much higher frequency of high clouds than ocean areas. One region just south and west of Panama had a high probability of clouds below 15 km altitude with the frequency never dropping below 25% and reaching a maximum of 60% at 11-13 km altitude. These cloud statistics will help characterize the cloud volume for TC4 scientists as they try to understand the complexities of the tropical atmosphere.

Hlavka, Dennis↗

Development of Super Ensemble-Based Aviation Turbulence Guidance (SEATG) for Air Traffic Management

A new method for forecasting turbulence is developed and evaluated using the high resolution weather model and in situ turbulence observations from commercial aircraft. The new method is an ensemble of various turbulence metrics from multiple time-lagged ensemble forecasts created using a sequence of four procedures. These include weather modeling, calculation of turbulence metrics, mapping the metrics into a common turbulence-scale, and production of final forecast. The new method uses similar methodology as current operational turbulence forecast with three improvements. First, it uses a higher resolution ((delta)x = 3 km) weather model to capture cloud resolving scale phenomena. Second, it computes the metrics for multiple forecasts that are combined at the same valid time resulting in a time-lagged ensemble of multiple turbulence metrics. Finally, it provides both deterministic and probabilistic turbulence forecasts. Results show the new forecasts match well with observed radar reflectivity along a surface front as well as convectively induced turbulence outside the clouds on research period. Overall performance skill of the new turbulence forecast compared with the observed EDR data during the research period is superior to any single turbulence metric. The probabilistic turbulence forecast is used in an example air traffic management application for creating a wind-optimal route considering turbulence information. The wind-optimal route passing through areas of 50% potential for moderate-or-greater turbulence and the lateral turbulence avoidance routes starting from three different waypoints along the wind-optimal route from Los Angeles international airport to John F. Kennedy international airport are calculated using different turbulence forecasts. This example shows additional flight time is required to avoid potential turbulence encounters.

modeling↗

Bayesian Rules of Thumb: Robust Uncertainty Quantification in Early Project Cost Estimation

Systems engineers often make use of cost Rules ofThumb in order to estimate cost during early phases of projectformulation. These Rules of Thumb typically take the form ofa sequence of percentages over which a total cost is allocatedacross NASA WBS elements. Rules of Thumb can then be usedto extrapolate cost from one or more known WBS elements tothe remaining unknown WBS elements, assisting early projectformulation architecture studies (such as those in JPL’s Team Xand A Team).A number of issues can arise when generating and using costRules of Thumb. For example, many records of project costsconsist of incomplete data. Typical methods of dealing withincomplete cost allocation data include (a) ignoring missionswith incomplete data, or (b) taking averages of the non-zero percentagesacross missions, but both of these methods can result inbiased estimates if the existence of incomplete data correlateswith total mission cost or any particular WBS element. Anothercommon example is cost reported in one or more incorrect WBSelements. This is especially prevalent in smaller missions whereit is more common for engineers to perform tasks that fall underthe purview of multiple WBS elements.Furthermore, a Rule of Thumb estimate is typically reported asa point estimate; there is no reported uncertainty around thepercentages used to generate an allocation. Even in the rarecase in which confidence intervals around mean percentages areprovided, there may be positive or negative correlations betweenWBS elements which can skew estimates.Here we attempt to address these problems by formulatingprobabilistic Rules of Thumb in which a distribution of allocationschemes, rather than a single allocation scheme, is generated.We use a bootstrap imputation method to simultaneouslyaccount for uncertainty in the missing data while using allavailable information contained in the dataset. The imputeddatasets are then input into a multivariate Bayesian modelwhich accounts for correlations between WBS elements andproperly accounts for uncertainty in the final Rule of Thumbpercentages and predictions. We describe the mathematicalmodel and provides snippets of R code utilizing the brms(Bayesian Regression Models using Stan) package. To illustratethis model, we generate a Bayesian Level 2 WBS Cost Rule ofThumb for MIDEX (Medium-Class Explorers) missions withdata extracted from NASA’s CADRe. We then compare thismethod’s performance with the classical Rule of Thumb method.

Hooke, Melissa A↗

Geographic information system for fusion and analysis of high-resolution remote sensing and ground truth data

We seek to combine high-resolution remotely sensed data with models and ground truth measurements, in the context of a Geographical Information System, integrated with specialized image processing software. We will use this integrated system to analyze the data from two Case Studies, one at a bore Al forest site, the other a tropical forest site. We will assess the information content of the different components of the data, determine the optimum data combinations to study biogeophysical changes in the forest, assess the best way to visualize the results, and validate the models for the forest response to different radar wavelengths/polarizations. During the 1990's, unprecedented amounts of high-resolution images from space of the Earth's surface will become available to the applications scientist from the LANDSAT/TM series, European and Japanese ERS-1 satellites, RADARSAT and SIR-C missions. When the Earth Observation Systems (EOS) program is operational, the amount of data available for a particular site can only increase. The interdisciplinary scientist, seeking to use data from various sensors to study his site of interest, may be faced with massive difficulties in manipulating such large data sets, assessing their information content, determining the optimum combinations of data to study a particular parameter, visualizing his results and validating his model of the surface. The techniques to deal with these problems are also needed to support the analysis of data from NASA's current program of Multi-sensor Airborne Campaigns, which will also generate large volumes of data. In the Case Studies outlined in this proposal, we will have somewhat unique data sets. For the Bonanza Creek Experimental Forest (Case I) calibrated DC-8 SAR data and extensive ground truth measurement are already at our disposal. The data set shows documented evidence to temporal change. The Belize Forest Experiment (Case II) will produce calibrated DC-8 SAR and AVIRIS data, together with extensive measurements on the tropical rain forest itself. The extreme range of these sites, one an Arctic forest, the other a tropical rain forest, has been deliberately chosen to find common problems which can lead to generalized observations and unique problems with data which raise issues for the EOS System.

Freeman, Anthony↗

Data Model Management for Space Information Systems

The Reference Architecture for Space Information Management (RASIM) suggests the separation of the data model from software components to promote the development of flexible information management systems. RASIM allows the data model to evolve independently from the software components and results in a robust implementation that remains viable as the domain changes. However, the development and management of data models within RASIM are difficult and time consuming tasks involving the choice of a notation, the capture of the model, its validation for consistency, and the export of the model for implementation. Current limitations to this approach include the lack of ability to capture comprehensive domain knowledge, the loss of significant modeling information during implementation, the lack of model visualization and documentation capabilities, and exports being limited to one or two schema types. The advent of the Semantic Web and its demand for sophisticated data models has addressed this situation by providing a new level of data model management in the form of ontology tools. In this paper we describe the use of a representative ontology tool to capture and manage a data model for a space information system. The resulting ontology is implementation independent. Novel on-line visualization and documentation capabilities are available automatically, and the ability to export to various schemas can be added through tool plug-ins. In addition, the ingestion of data instances into the ontology allows validation of the ontology and results in a domain knowledge base. Semantic browsers are easily configured for the knowledge base. For example the export of the knowledge base to RDF/XML and RDFS/XML and the use of open source metadata browsers provide ready-made user interfaces that support both text- and facet-based search. This paper will present the Planetary Data System (PDS) data model as a use case and describe the import of the data model into an ontology tool. We will also describe the current effort to provide interoperability with the European Space Agency (ESA)/Planetary Science Archive (PSA) which is critically dependent on a common data model.

RDF↗

Geospatial Modeling of Asthma Population in Relation to Air Pollution

Current observations indicate that asthma is growing every year in the United States, specific reasons for this are not well understood. This study stems from an ongoing research effort to investigate the spatio-temporal behavior of asthma and its relatedness to air pollution. The association between environmental variables such as air quality and asthma related health issues over Mississippi State are investigated using Geographic Information Systems (GIS) tools and applications. Health data concerning asthma obtained from Mississippi State Department of Health (MSDH) for 9-year period of 2003-2011, and data of air pollutant concentrations (PM2.5) collected from USEPA web resources, and are analyzed geospatially to establish the impacts of air quality on human health specifically related to asthma. Disease mapping using geospatial techniques provides valuable insights into the spatial nature, variability, and association of asthma to air pollution. Asthma patient hospitalization data of Mississippi has been analyzed and mapped using quantitative Choropleth techniques in ArcGIS. Patients have been geocoded to their respective zip codes. Potential air pollutant sources of Interstate highways, Industries, and other land use data have been integrated in common geospatial platform to understand their adverse contribution on human health. Existing hospitals and emergency clinics are being injected into analysis to further understand their proximity and easy access to patient locations. At the current level of analysis and understanding, spatial distribution of Asthma is observed in the populations of Zip code regions in gulf coast, along the interstates of south, and in counties of Northeast Mississippi. It is also found that asthma is prevalent in most of the urban population. This GIS based project would be useful to make health risk assessment and provide information support to the administrators and decision makers for establishing satellite clinics in future.

Kethireddy, Swatantra R.↗