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All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

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.↗
NASA NTRS2013

A Web-Based Search Service to Support Imaging Spectrometer Instrument Operations

Imaging spectrometers yield rich and informative data products, but interpreting them demands time and expertise. There is a continual need for new algorithms and methods for rapid first-draft analyses to assist analysts during instrument opera-tions. Intelligent data analyses can summarize scenes to draft geologic maps, searching images to direct op-erator attention to key features. This validates data quality while facilitating rapid tactical decision making to select followup targets. Ideally these algorithms would operate in seconds, never grow bored, and be free from observation bias about the kinds of mineral-ogy that will be found.

hyperspectral imagery↗
NASA NTRS2012

Integrating NASA Satellite Data Into USDA World Agricultural Outlook Board Decision Making Environment To Improve Agricultural Estimates

The USDA World Agricultural Outlook Board (WAOB) is responsible for monitoring weather and climate impacts on domestic and foreign crop development. One of WAOB's primary goals is to determine the net cumulative effect of weather and climate anomalies on final crop yields. To this end, a broad array of information is consulted. The resulting agricultural weather assessments are published in the Weekly Weather and Crop Bulletin, to keep farmers, policy makers, and commercial agricultural interests informed of weather and climate impacts on agriculture. The goal of the current project is to improve WAOB estimates by integrating NASA satellite precipitation and soil moisture observations into WAOB's decision making environment. Precipitation (Level 3 gridded) is from the TRMM Multi-satellite Precipitation Analysis (TMPA). Soil moisture (Level 2 swath and Level 3 gridded) is generated by the Land Parameter Retrieval Model (LPRM) and operationally produced by the NASA Goddard Earth Sciences Data and Information Services Center (GBS DISC). A root zone soil moisture (RZSM) product is also generated, via assimilation of the Level 3 LPRM data by a land surface model (part of a related project). Data services to be available for these products include GeoTIFF, GDS (GrADS Data Server), WMS (Web Map Service), WCS (Web Coverage Service), and NASA Giovanni. Project benchmarking is based on retrospective analyses of WAOB analog year comparisons. The latter are between a given year and historical years with similar weather patterns and estimated crop yields. An analog index (AI) was developed to introduce a more rigorous, statistical approach for identifying analog years. Results thus far show that crop yield estimates derived from TMPA precipitation data are closer to measured yields than are estimates derived from surface-based precipitation measurements. Work is continuing to include LPRM surface soil moisture data and model-assimilated RZSM.

Teng, William↗
NASA NTRS2016

Web Map Apps using NASA's Earth Observing Fleet

Through the miracle of open web mapping services for satellite imagery, a garden of new applications has sprouted to monitor the planet across a variety of domains. The Global Imagery Browse Services (GIBS) provide free and open access to full resolution imagery captured by NASAs Earth observing fleet. Spanning 15+ years and running through as recently as a few hours ago, GIBS aims to provide a general-purpose window into NASA's vast archive of the planet. While the vast nature of this archive can be daunting, many domain-specific applications have been built to meet the needs of their respective communities. This presentation will demonstrate a diverse set of these new applications which can take planetarium visitors into (virtual) orbit, guide fire resource managers to hotspots, help anglers find their next catch, illustrate global air quality patterns to local regulators, and even spur a friendly competition to find clouds which are shaped the most like cats. We hope this garden will continue to grow and will illustrate upcoming upgrades to GIBS which may open new pathways for development. data visualization, web services, open access

data visualization↗
NASA NTRS2017

Challenges in Obtaining and Visualizing Satellite Level 2 Data in GIS

Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted. Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. One way to help users better understand the satellite data is to provide data along with Images, including accurate pixel coverage area delineation, and science team recommended quality screening for individual geophysical parameters. However, there are challenges of visualizing remote sensed non-gridded products: (1) different geodetics of space-borne instruments (2) data often arranged in a long-track and a cross-track axes (3) spatially and temporally continuous data chunked into granule files: data for a portion (or all) of a satellite orbit (4) no general rule of resampling or interpolations to a grid (5) geophysical retrieval only based on pixel center location without shape information. In this presentation, we will unravel a new Goddard Earth Sciences Data and Information Services Center (GES DISC) Level 2 (L2) visualization on-demand service. The service's front end provides various visualization and data accessing capabilities, such as overlay and swipe of multiply variables and subset and download of data in different formats. The backend of the service consists of Open Geospatial Consortium (OGC) standard-compliant Web Mapping Service (WMS) and Web Coverage Service. The infrastructure allows inclusion of outside data sources served in OGC compliant protocols and allows other interoperable clients, such as ArcGIS clients, to connect to our L2 WCS/WMS.

GI↗
NASA NTRS2018

Serving NASA GES DISC Multi-Spatiotemporal Earth Science Data to the GIS community

NASA Earth Science (ES) data is essential to a wide range of GIS research and applications. However, for many GIS users, searching, accessing, using and analyzing NASA ES data can be of a great challenge- ranging from the sheer data volumes, types of science parameters, and to the complexity of data encoding formats. As one of the twelve NASA Science Mission Directorate (SMD) Data Centers, Goddard Earth Sciences (GES) Data and Information Services Center (DISC) archives and distributes petabytes of ES parameters covering atmosphere, land, and ocean fields. Most data are multidimensional and multi-spatiotemporal in nature and are encoded in different science data formats (e.g, HDF, HDF-EOS, netCDF, GRIB, binary), which usually contain multiple variables and different metadata information. By far, GES DISC has been developing a number of services and online tools to help GIS users to easily explore our data products. In this presentation, we will describe our ArcGIS-based data accessing and visualization services and portals, which allow users directly exploring the multi-spatiotemporal ES data in ArcGIS clients without having to pre-download/import the data. The ArcGIS services are also compliant with the Open Geospatial Consortium (OGC) Web Coverage Service (WCS) and Web Map Service (WMS) protocols and can be accessed by any other WCS/WMS clients to get customized GES DISC EO data on-the-fly from such services.

Wei, Jennifer↗
NASA NTRS2007

Sensor Webs with a Service-Oriented Architecture for On-demand Science Products

This paper describes the work being managed by the NASA Goddard Space Flight Center (GSFC) Information System Division (ISD) under a NASA Earth Science Technology Ofice (ESTO) Advanced Information System Technology (AIST) grant to develop a modular sensor web architecture which enables discovery of sensors and workflows that can create customized science via a high-level service-oriented architecture based on Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) web service standards. These capabilities serve as a prototype to a user-centric architecture for Global Earth Observing System of Systems (GEOSS). This work builds and extends previous sensor web efforts conducted at NASA/GSFC using the Earth Observing 1 (EO-1) satellite and other low-earth orbiting satellites.

Mandl, Daniel↗
NASA NTRS2014

Exploring NASA OMI Level 2 Data With Visualization

Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted, such as model inputs from satellite, or extreme events (such as volcano eruptions, dust storms, etc.).Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. Such obstacles may be avoided by allowing users to visualize satellite data as images, with accurate pixel-level (Level-2) information, including pixel coverage area delineation and science team recommended quality screening for individual geophysical parameters. We present a prototype service from the Goddard Earth Sciences Data and Information Services Center (GES DISC) supporting Aura OMI Level-2 Data with GIS-like capabilities. Functionality includes selecting data sources (e.g., multiple parameters under the same scene, like NO2 and SO2, or the same parameter with different aggregation methods, like NO2 in OMNO2G and OMNO2D products), user-defined area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting, reformatting, and reprojection. The system will allow any user-defined portal interface (front-end) to connect to our backend server with OGC standard-compliant Web Mapping Service (WMS) and Web Coverage Service (WCS) calls. This back-end service should greatly enhance its expandability to integrate additional outside data-map sources.

Level 2↗
NASA NTRS2014

Exploring NASA OMI Level 2 Data With Visualization

Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted, such as model inputs from satellite, or extreme events (such as volcano eruptions, dust storms,... etc.). Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. Such obstacles may be avoided by allowing users to visualize satellite data as "images", with accurate pixel-level (Level-2) information, including pixel coverage area delineation and science team recommended quality screening for individual geophysical parameters. We present a prototype service from the Goddard Earth Sciences Data and Information Services Center (GES DISC) supporting Aura OMI Level-2 Data with GIS-like capabilities. Functionality includes selecting data sources (e.g., multiple parameters under the same scene, like NO2 and SO2, or the same parameter with different aggregation methods, like NO2 in OMNO2G and OMNO2D products), user-defined area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting, reformatting, and reprojection. The system will allow any user-defined portal interface (front-end) to connect to our backend server with OGC standard-compliant Web Mapping Service (WMS) and Web Coverage Service (WCS) calls. This back-end service should greatly enhance its expandability to integrate additional outside data/map sources.

Aura↗
NASA NTRS2002

Implementing Production Grids

We have presented the essence of experience gained in building two production Grids, and provided some of the global context for this work. As the reader might imagine, there were a lot of false starts, refinements to the approaches and to the software, and several substantial integration projects (SRB and Condor integrated with Globus) to get where we are today. However, the point of this paper is to try and make it substantially easier for others to get to the point where Information Power Grids (IPG) and the DOE Science Grids are today. This is what is needed in order to move us toward the vision of a common cyber infrastructure for science. The author would also like to remind the readers that this paper primarily represents the actual experiences that resulted from specific architectural and software choices during the design and implementation of these two Grids. The choices made were dictated by the criteria laid out in section 1. There is a lot more Grid software available today that there was four years ago, and various of these packages are being integrated into IPG and the DOE Grids. However, the foundation choices of Globus, SRB, and Condor would not be significantly different today than they were four years ago. Nonetheless, if the GGF is successful in its work - and we have every reason to believe that it will be - then in a few years we will see that the 28 functions provided by these packages will be defined in terms of protocols and MIS, and there will be several robust implementations available for each of the basic components, especially the Grid Common Services. The impact of the emerging Web Grid Services work is not yet clear. It will likely have a substantial impact on building higher level services, however it is the opinion of the author that this will in no way obviate the need for the Grid Common Services. These are the foundation of Grids, and the focus of almost all of the operational and persistent infrastructure aspects of Grids.

Johnston, William E.↗
NASA NTRS2003

IT Middleware Services for an 'Exploration Web'

This slide presentation reviews the application of middleware in space exploration, and satellite communications. The aim of the use of Space middleware is ot use remote sensors and other resources more efficiently.

middleware↗
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 NTRS2019

A Web of Data Analytics Services

Cloud Computing has become the ubiquitous approach to our Big Data challenge. However, one will quickly discover that moving (a.k.a. forklifting) existing on-premise data analytics solutions to the Cloud doesn’t always translate to costing saving and performance boost. The Cloud’s elasticity, its availability, and its wide selection of computing options and selections of costing models making Cloud an attractive environment to tackle our Big Data challenge. The fact is Cloud, on its own, is not the silver bullet to our daunting challenge need for analyze and derive scientific inferences through vast collections of multi-sensor measurements. We would like to have all scientific data in one easy to access environment, but getting the world of scientific data in one analytic system is immensely difficult to achieve. This paper describes the data analytics web architecture NASA is developing by infusing instances of Integrated Data Analytics systems next to the data. The goal is to minimize unnecessary data movement through collection of data access and analytics webservices for researchers to interact with and analyze measurements without have to download data to their local computer. These services are RESTful and provisioned by the data centers with the help from subject matter and science experts. These services encapsulate the physical computing infrastructure, which could local computing cluster, on-premise or public Cloud environment.

Huang, Thomas↗
NASA NTRS2018

The Next Generation of NASA Rapid Response: Worldview Snapshots

The NASA Rapid Response system started in 2001 by serving static subsets of Near Real Time MODIS (Moderate Resolution Imaging Spectroradiometer) imagery acquired from the Terra satellite. Over this time, Rapid Response has been used to support near real time applications such as wildfire and sea ice mapping for hundreds of thousands of users. In 2011, the toolset expanded to include GIBS, the Global Imagery Browse Services, which provides a web map tiling service of over 700 imagery products, and Worldview (https://worldview.earthdata.nasa.gov/), an interactive web application that showcases the products available in GIBS. This year a new application, Worldview Snapshots, has been added to complete the toolset by providing a flexible, low bandwidth method to download personalized subsets for those who do not need or cannot use a fully featured web mapping application. The original Rapid Response subset tool has been retired and we thank it for its seventeen years of service. Stop by to learn more about the next generation of NASA Rapid Response.

Rapid response system↗
NASA NTRS2010

SensorWeb 3G: Extending On-Orbit Sensor Capabilities to Enable Near Realtime User Configurability

This research effort prototypes an implementation of a standard interface, Web Coverage Processing Service (WCPS), which is an Open Geospatial Consortium(OGC) standard, to enable users to define, test, upload and execute algorithms for on-orbit sensor systems. The user is able to customize on-orbit data products that result from raw data streaming from an instrument. This extends the SensorWeb 2.0 concept that was developed under a previous Advanced Information System Technology (AIST) effort in which web services wrap sensors and a standardized Extensible Markup Language (XML) based scripting workflow language orchestrates processing steps across multiple domains. SensorWeb 3G extends the concept by providing the user controls into the flight software modules associated with on-orbit sensor and thus provides a degree of flexibility which does not presently exist. The successful demonstrations to date will be presented, which includes a realistic HyspIRI decadal mission testbed. Furthermore, benchmarks that were run will also be presented along with future demonstration and benchmark tests planned. Finally, we conclude with implications for the future and how this concept dovetails into efforts to develop "cloud computing" methods and standards.

Mandl, Daniel↗