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At least 55 records · Page 3

Development of WMS Capabilities to Support NASA Disasters Applications and App Development

During the last year several significant disasters have occurred such as Superstorm Sandy on the East coast of the United States, and Typhoon Bopha in the Phillipines, along with several others. In support of these disasters NASA's Short‐term Prediction Research and Transition (SPoRT) Center delivered various products derived from satellite imagery to help in the assessment of damage and recovery of the affected areas. To better support the decision makers responding to the disasters SPoRT quickly developed several solutions to provide the data using open Geographical Information Service (GIS) formats. Providing the data in open GIS standard formats allowed the end user to easily integrate the data into existing Decision Support Systems (DSS). Both Tile Mapping Service (TMS) and Web Mapping Service (WMS) were leveraged to quickly provide the data to the end‐user. Development of the deliver methodology allowed quick response to rapidly developing disasters and enabled NASA SPoRT to bring science data to decision makers in a successful research to operations transition.

Bell, Jordan R.↗

Development of WMS Capabilities to Support NASA Disasters Applications and App Development

During the last year several significant disasters have occurred such as Superstorm Sandy on the East coast of the United States, and Typhoon Bopha in the Phillipines, along with several others. In support of these disasters NASA's Short‐term Prediction Research and Transition (SPoRT) Center delivered various products derived from satellite imagery to help in the assessment of damage and recovery of the affected areas. To better support the decision makers responding to the disasters SPoRT quickly developed several solutions to provide the data using open Geographical Information Service (GIS) formats. Providing the data in open GIS standard formats allowed the end user to easily integrate the data into existing Decision Support Systems (DSS). Both Tile Mapping Service (TMS) and Web Mapping Service (WMS) were leveraged to quickly provide the data to the end‐user. Development of the deliver methodology allowed quick response to rapidly developing disasters and enabled NASA SPoRT to bring science data to decision makers in a successful research to operations transition.

Bell, Jordan R.↗

DIP for Service Providers

The second DIP workshop’s topic is DIP for Service Providers. The workshop presentation covers topics such as DIP onboarding process, service authentication, catalog service capabilities, API requirements, NASA services and their access points, and data requirements for service providers. The Onboarding Process describes the required documentation that enables to collaborate with NASA as well as other industry partners through DIP. Also, step by step approach for the partner to take to register services or consme services through the DIP platform. The Catalog Service describes the different ways for the users to search for services that are of interest as well as registering services to the platform, so other users can search and discover. The API Requirements and Service Specifications describes the benefits of DIP's API management approach via API Gateway where services are managed centrally but ownership is decentralized and partners completely own the administration of their own services. NASA Services and Data Access Points topic describes the services, both data access service and machine learning prediction service, that NASA provides via the DIP platform in near time and post operations via REST API endpoints defined on the API Gateway. Also, NASA's approach for data storage process is explained. The Data Requirements for service providers describes the requirements for storing and exposing to support the performance of services that are provided by the service providers. Lastly, NASA's technology development plan with preliminary scheduler will be presented. There will be a Q&A session at the end of each segment of the presentation to solicit feedback from the participants.

ATM-X↗

Linear Regression Model for Predictive Service Provider Selection

The increasing number of satellites in orbit has led to a growing reliance on third-party service providers for data transfer between Earth and space. Traditional approaches to managing satellite communications require human intervention, which becomes more burdensome with the escalating number of satellites. This research addresses the need for an efficient and automated system to optimize service provider selection for NASA space communication. Previous research has utilized human-operated approaches for service provider management. Our study fills a gap by developing a cognitive algorithm that automates and optimizes the selection process based on various parameters, such as data volume, priority, quality of service and cost. This novel solution reduces user burden, facilitates service management, and contributes to the development of cognitive spaceflight missions, ultimately supporting NASA’s research into Cognitive Communications technology. The algorithm design consists of three major steps: modeling data, developing a Link Selection Algorithm (LSA) based on a grading system, and applying machine learning using linear regression. The LSA evaluates providers based on user-defined constraints, considering factors such as delivery time, cost, and quality of service. We define a suitability metric which allows our algorithm to make a recommendation to a user regarding which commercial service providers to select. The addition of Linear Regression predicts the future suitability value. Our main findings demonstrate that the resulting algorithm can autonomously manage connections between satellites and providers, maximizing communication channel efficiency. This research has significant implications, as it not only addresses a pressing issue in satellite communication management but also advances the field of cognitive spaceflight missions.

Linear regression↗

PBL Height from AIRS, GPS RO, and MERRA-2 Products in NASA GES DISC and Their 10 Year Seasonal Mean Intercomparison

Within the planetary boundary layer (PBL), surface forcing response, drag, turbulence, and vertical mixing are important processes and play a more critical role here than in the overlying “free atmosphere”. The PBL Height (PBLH) is an important parameter in climate models, weather forecasts, and air quality prediction. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides data processing, archiving, and distribution services for numerous Earth science products. PBLH is a parameter in three products served by GES DISC, which are from the Atmospheric Infrared Sounder (AIRS), the Global Positioning System (GPS) radio occultation (RO) experiment, and the NASA reanalysis product Modern-Era Retrospective analysis for Research and Applications – 2 (MERRA-2). These products have different spatial and temporal resolutions and coverages, and their PBLH definitions are also different. To better serve the PBL research community, we have summarized the specifications of these products. A ten-year seasonal mean intercomparison is also conducted to provide further guidance to users. The intercomparison results show that MERRA-2 has a much shallower PBL than AIRS and GPS RO. An experimental study indicates the different PBLH definition in MERRA-2 caused smaller values of PBLH. The improvement of the water vapor retrieval in AIRS version 7 over version 6 results in the version 7 PBLH agreeing better with GPS RO and MERRA-2 than version 6, especially near the equator and low latitudes.

Feng Ding↗

Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (LDAS) and Other Assimilated Hydrological Data at NASA GES DISC

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides science support for several data sets relevant to agriculture and food security, including the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (LDAS), or FLDAS data set. The GES DISC is one of twelve NASA Earth Observing System (EOS) data centers that process, archive, document, and distribute data from Earth science missions and related projects. The GES DISC hosts a wide range of remote sensing and model data, and provides reliable and robust data access and other services to users worldwide. Beyond data archive and access, the GES DISC offers many services to visualize and analyze the data. This presentation provides a summary of the hydrological data available at the GES DISC, along with an overview of related data services. Specifically, the FLDAS data set has been adapted to work with domains, data streams, and monitoring and forecast requirements associated with food security assessment in data-sparse, developing country settings. The FLDAS global monthly data have a 0.1 x 0.1 degree spatial resolution covering the period from January 1982 to present. Global FLDAS monthly anomaly and monthly climatology data are also available at the GES DISC to evaluate how current conditions compare to averages over the FLDAS 35-year period. Several case studies using the FLDAS soil moisture, evapotranspiration, rainfall, runoff, and surface temperature data will be presented.

Loeser, Carlee↗

Data Quality Challenges for Analysis Ready Data (ARD)

Data quality plays a critical role in research and applications. The Earth Science Information Partners (ESIP) Information Quality Cluster (IQC) defines four aspects of information quality: Science, Product, Stewardship, and Services. The ESIP IQC has become internationally recognized as an authoritative and responsive resource of information and guidance to data producers and distributors on how to implement data quality standards and best practices for their science data systems, datasets, and data/metadata dissemination services. In recent years, cloud computing environments have provided scale-up capabilities such as data archives and services, enabling interdisciplinary science and applications. More value-added products are expected from data service providers, including Analysis Ready Data (ARD). ARD refers to data that has been preprocessed into a form that allows immediate analysis by the end user, processed to a minimum set of requirements and provides interoperability over time and across multiple datasets. Once a dataset has been developed from its original form to produce ARD, what quality characteristics should the derived dataset or ARD possess? Also, is it safe to assume that the quality of the ARD is consistent with the quality of the source data, or are there special attributes to an ARD that would warrant a secondary, independent quality assessment? What provenance (also called “data lineage”) information needs to be included in ARD? It is important to answer these questions, especially given the ease of use of ARD, and the consequent temptation by users to trust ARD without understanding the limitations or possible variations in quality compared to the source data. In this presentation, we will discuss data quality challenges for ARD products and services and introduce IQC for participation.

data quality↗

The EOSDIS Version 0 Distributed Active Archive Center for physical oceanography and air-sea interaction

The Distributed Active Archive Center (DAAC) at the Jet Propulsion Laboratory will support scientists specializing in physical oceanography and air-sea interaction. As part of the NASA Earth Observing System Data and Information System Version 0 the DAAC will build on existing capabilities to provide services for data product generation, archiving, distribution and management of information about data. To meet scientist's immediate needs for data, existing data sets from missions such as Seasat, Geosat, the NOAA series of satellites and the Global Positioning Satellite system will be distributed to investigators upon request. In 1992, ocean topography, wave and surface roughness data from the Topex/Poseidon radar altimeter mission will be archived and distributed. New data products will be derived from Topex/Poseidon and other sensor systems based on recommendations of the science community. In 1995, ocean wind field measurements from the NASA Scatterometer will be supported by the DAAC.

Hilland, Jeffrey E.↗

Mobile satellite regulation in the United States

During the last decade, the U.S. FCC has developed the regulatory structure for the provision of mobile services via satellite. In May 1989, the FCC awarded American Mobile Satellite Corporation (AMSC) a license to provide the full range of domestic mobile satellite services in the U.S. At that time, the FCC reaffirmed the U.S. mobile satellite industry structure and spectrum allocations that had been adopted previously. Also in May 1989, the FCC authorized the Communications Satellite Corporation (COMSAT), the U.S. Signatory to Inmarsat, to provide international aeronautical satellite service via the Inmarsat system. Earlier in 1989, the FCC permitted the use of Ku-band satellites to provide messaging and tracking services. In the mid-1980's, the FCC established the Radiodetermination Satellite Service and awarded licenses. Among the mobile satellite matters currently facing the FCC are whether additional spectrum should be allocated for domestic 'generic' mobile satellite services, the regulatory structure for the provision of mobile satellite service on an interim basis before AMSC launches its dedicated satellites, and whether to authorize a low earth orbit satellite system to provide mobile data service.

Levin, Lon C.↗

GHRC: NASAs Hazardous Weather Distributed Active Archive Center

The Global Hydrology Resource Center (GHRC; ghrc.nsstc.nasa.gov) is one of NASA's twelve Distributed Active Archive Centers responsible for providing access to NASA's Earth science data to users worldwide. Each of NASA's twelve DAACs focuses on a specific science discipline within Earth science, provides data stewardship services and supports its research community's needs. Established in 1991 as the Marshall Space Flight Center DAAC and renamed GHRC in 1997, the data center's original mission focused on the global hydrologic cycle. However, over the years, data holdings, tools and expertise of GHRC have gradually shifted. In 2014, a User Working Group (UWG) was established to review GHRC capabilities and provide recommendations to make GHRC more responsive to the research community's evolving needs. The UWG recommended an update to the GHRC mission, as well as a strategic plan to move in the new direction. After a careful and detailed analysis of GHRC's capabilities, research community needs and the existing data landscape, a new mission statement for GHRC has been crafted: to provide a comprehensive active archive of both data and knowledge augmentation services with a focus on hazardous weather, its governing dynamical and physical processes, and associated applications. Within this broad mandate, GHRC will focus on lightning, tropical cyclones and storm-induced hazards through integrated collections of satellite, airborne, and in-situ data sets. The new mission was adopted at the recent 2015 UWG meeting. GHRC will retain its current name until such time as it has built substantial data holdings aligned with the new mission.

Data Archive↗

Data Quality Screening Service

A report describes the Data Quality Screening Service (DQSS), which is designed to help automate the filtering of remote sensing data on behalf of science users. Whereas this process often involves much research through quality documents followed by laborious coding, the DQSS is a Web Service that provides data users with data pre-filtered to their particular criteria, while at the same time guiding the user with filtering recommendations of the cognizant data experts. The DQSS design is based on a formal semantic Web ontology that describes data fields and the quality fields for applying quality control within a data product. The accompanying code base handles several remote sensing datasets and quality control schemes for data products stored in Hierarchical Data Format (HDF), a common format for NASA remote sensing data. Together, the ontology and code support a variety of quality control schemes through the implementation of the Boolean expression with simple, reusable conditional expressions as operands. Additional datasets are added to the DQSS simply by registering instances in the ontology if they follow a quality scheme that is already modeled in the ontology. New quality schemes are added by extending the ontology and adding code for each new scheme.

Strub, Richard↗

Grid Enabled Geospatial Catalogue Web Service

Geospatial Catalogue Web Service is a vital service for sharing and interoperating volumes of distributed heterogeneous geospatial resources, such as data, services, applications, and their replicas over the web. Based on the Grid technology and the Open Geospatial Consortium (0GC) s Catalogue Service - Web Information Model, this paper proposes a new information model for Geospatial Catalogue Web Service, named as GCWS which can securely provides Grid-based publishing, managing and querying geospatial data and services, and the transparent access to the replica data and related services under the Grid environment. This information model integrates the information model of the Grid Replica Location Service (RLS)/Monitoring & Discovery Service (MDS) with the information model of OGC Catalogue Service (CSW), and refers to the geospatial data metadata standards from IS0 19115, FGDC and NASA EOS Core System and service metadata standards from IS0 191 19 to extend itself for expressing geospatial resources. Using GCWS, any valid geospatial user, who belongs to an authorized Virtual Organization (VO), can securely publish and manage geospatial resources, especially query on-demand data in the virtual community and get back it through the data-related services which provide functions such as subsetting, reformatting, reprojection etc. This work facilitates the geospatial resources sharing and interoperating under the Grid environment, and implements geospatial resources Grid enabled and Grid technologies geospatial enabled. It 2!so makes researcher to focus on science, 2nd not cn issues with computing ability, data locztic~, processir,g and management. GCWS also is a key component for workflow-based virtual geospatial data producing.

Chen, Ai-Jun↗

Developing a Dashboard Interface to Display Assessment of Hazards and Risks to sUAS Flights

The Supplemental Data Services Provider-Consolidated Dashboard (SDSP-CD) is a graphical user interface (GUI) that displays the results of predictive tools in a single location. It is intended to be used in the preflight planning phase of an operation to allow users to proactively assess predicted flight hazards off-line; expanding an operator’s overall situational awareness of a flight plan and providing an opportunity for decision making and assessing the associated risks prior to flight. Hazard data and risk predictions are informative but can be complex to read and understand. However, presented visually and in relation to flight parameters (such as flight path), the nature and significance of hazards become much more evident. The SDSP-Consolidation Dashboard interface was designed to offer a means to present the results of hazard services in an easy to-use format. Two usability studies were run to explore what features might make a suite of hazard assessment services easy to use, and to assess the SDSP-CD interface. The first study evaluated the presentation of information on the GUI and the second evaluated users’ ability to understand and use the information. The studies gathered valuable information about how users approach a hazard assessment task and interpret information from the interface. Many suggestions were given for improving the interface’s information display, to allow users to more quickly understand and interpret the information being presented.

UAV display↗

Developing a Dashboard Interface to Display Assessment of Hazards and Risks to sUAS Flights

The Supplemental Data Services Provider-Consolidated Dashboard (SDSP-CD) is a graphical user interface (GUI) that displays the results of predictive tools in a single location. It is intended to be used in the prefight planning phase of an operation to allow users to proactively assess predicted flight hazards off-line; expanding an operator’s overall situational awareness of a flight plan and providing an opportunity for decision making and assessing the associated risks prior to flight. Hazard data and risk predictions are informative but can be complex to read and understand. However, presented visually and in relation to flight parameters (such as flight path), the nature and significance of hazards become much more evident. The SDSP-Consolidation Dashboard interface was designed to offer a means to present the results of hazard services in an easy to-use format. Two usability studies were run to explore what features might make a suite of hazard assessment services easy to use, and to assess the SDSP-CD interface. The first study evaluated the presentation of information on the GUI and the second evaluated users’ ability to understand and use the information. The studies gathered valuable information about how users approach a hazard assessment task and interpret information from the interface. Many suggestions were given for improving the interface’s information display, to allow users to more quickly understand and interpret the information being presented

UAV display↗

Climate Analytics as a Service

Exascale computing, big data, and cloud computing are driving the evolution of large-scale information systems toward a model of data-proximal analysis. In response, we are developing a concept of climate analytics as a service (CAaaS) that represents a convergence of data analytics and archive management. With this approach, high-performance compute-storage implemented as an analytic system is part of a dynamic archive comprising both static and computationally realized objects. It is a system whose capabilities are framed as behaviors over a static data collection, but where queries cause results to be created, not found and retrieved. Those results can be the product of a complex analysis, but, importantly, they also can be tailored responses to the simplest of requests. NASA's MERRA Analytic Service and associated Climate Data Services API provide a real-world example of climate analytics delivered as a service in this way. Our experiences reveal several advantages to this approach, not the least of which is orders-of-magnitude time reduction in the data assembly task common to many scientific workflows.

big data↗

Atmospheric Composition Data and Information Services Center (ACDISC)

NASA's GSFC Earth Sciences (GES) Data and Information and Data Services Center (DISC) manages the archive, distribution and data access for atmospheric composition data from AURA'S OMI, MLS, and hopefully one day, HIRDLS instruments, as well as heritage datasets from TOMS, UARS, MODIS, and AIRS. This data is currently archived in the GES Distributed Active Archive Center (DAAC). The GES DISC has begun the development of a community driven data management system that's sole purpose is to manage and provide value added services to NASA's Atmospheric Composition (AC) Data. This system, called the Atmospheric Composition Data and Information Services Center (ACDISC) will provide access all AC datasets from the above mentioned instruments, as well as AC datasets residing at remote archive sites (e.g, LaRC DAAC) The goals of the ACDISC are to: 1) Provide a data center for Atmospheric Scientists, guided by Atmospheric Scientists; 2) Be absolutely responsive to the data and data service needs of the Atmospheric Composition (AC) community; 3) Provide services (i.e., expertise) that will facilitate the effortless access to and usage of AC data; 4) Collaborate with AC scientists to facilitate the use of data from multiple sensors for long term atmospheric research. The ACDISC is an AC specific, user driven, multi-sensor, on-line, easy access archive and distribution system employing data analysis and visualization, data mining, and other user requested techniques that facilitate science data usage. The purpose of this presentation is to provide the evolution path that the GES DISC in order to better serve AC data, and also to receive continued community feedback and further foster collaboration with AC data users and providers.

Kempler, S.↗

Mature data transport and command management services for the Space Station

The duplex space/ground/space data services for the Space Station are described. The need to separate the uplink data service functions from the command functions is discussed. Command management is a process shared by an operation control center and a command management system and consists of four functions: (1) uplink data communications, (2) management of the on-board computer, (3) flight resource allocation and management, and (4) real command management. The new data service capabilities provided by microprocessors, ground and flight nodes, and closed loop and open loop capabilities are studied. The need for and functions of a flight resource allocation management service are examined. The system is designed so only users can access the system; the problems encountered with open loop uplink access are analyzed. The procedures for delivery of operational, verification, computer, and surveillance and monitoring data directly to users are reviewed.

Carper, R. D.↗

Space Station Information System integrated communications concept

This paper presents a model for integrated communications within the Space Station Information System (SSIS). The SSIS is generally defined as the integrated set of space and ground information systems and networks which will provide required data services to the Space Station flight crew, ground operations personnel, and customer communities. This model is based on the International Standards Organization (ISO) layered model for Open Systems Interconnection (OSI). The requirements used to develop the model are presented, and the various elements of the model described.

Muratore, J.↗