IN43B-01
Hydrocarbon microseepage detection based on normalized ferric and ferrous indices of Landsat imagery
Ferric index (TM 3/1) (Fe3), ferrous index (TM 5/4) (Fe2), and clay and/or carbonate index (TM 5/7) have been successfully applied in mapping hydrothermal-alteration minerals, soil types, organics abundance, and mine waste. However, the ferric/ferrous indices do not work well when they are applied to detect relative oxidation/reduction area in hydrocarbon microseepage regions where the total iron and iron ion types are different in background rocks or soils. For example, there is relative high ferrous in organic-rich sediments and basic igneous rock, such as in coal-bearing beds. Clearly, the high ferrous concentration is not resulted from exotic reduction. Usually, under a homogeneous exotic reduced condition, the higher the total iron in rock or soil, the more the transferred ferrous iron produced. In order to remove the effects of total iron difference in rocks and soils on hydrocarbon microseepage detection, a new method, referred to as normalized ferric and ferrous index, is developed in this study, i.e. the normalized ferric index (NFe3) = Fe3 / (Fe3 + Fe2) and the normalized ferrous index (NFe2) = Fe2 / (Fe3 + Fe2). The NFe3 and NFe2 are successfully applied and tested in two sites for hydrocarbon microseepage detection in oil/gas-bearing Ordos Basin and Eren Basin, China. The NFe3 and NFe2 index images can preserve not only the major information of the ratio 3/1 and 5/4 images, but also remove the effects of total iron in background. Comparing to the mineral composite image (TM 3/1, 5/4, and 5/7 in RGB), the normalized indices color composite image (NFe3, NFe2, and TM5/7 in RGB) shows hydrocarbon microseepage areas clearly in green color. In addition, the composite images of normalized index also remove the vegetation effect to some degree in the test sites.
IN43B-02
An Integrated Environment for Geospatial Web Service Composition
Assembling individual geospatial web services into more complex and more useful web processes to achieve desired results proves to be essential for complex geospatial applications. As geospatial web services embed lots of geospatial information and knowledge, the geospatial domain-specific tools are needed to help users discover, retrieve and integrate these services. We have developed an integrated environment that allows users in the semi-automatic and dynamic composition of geospatial web services. This paper illustrates the whole life cycle of a web service composition: 1) discover services in OGC Catalog Service for Web (CSW), 2) present and select matching service at each step of a composition with the assistance of intelligent autonomous interface agent, 3) compose a service chain based on domain knowledge, and 4) execute the composed service chain automatically through its BPEL and WSDL scripts. The environment has been used to demonstrate practical benefits in the context of OGC Web services for Earth science research and applications.
IN43B-03
3D Visualization of Space Weather Model Output at the Community Coordinated Modeling Center
As space weather models become more advanced and complex, effective visualizations of the output become more important and necessary. The CCMC is actively exploring new tools for visualizing the output; one of these tools is Space Weather Explorer (SWX). In this presentation, we discuss SWX, a collection of OpenDX macros, modules, and programs used to visualize the model output at the CCMC, as well as the future goals of the project. We will also discuss the available visualization features and the advantage of the approach taken by SWX: utilization of a standardized access and interpolation library, and use of free and open source utilities.
<a href='http://ccmc.gsfc.nasa.gov'>http://ccmc.gsfc.nasa.gov</a>
IN43B-04
Viewpoints: Interactive Exploration of Large Multivariate Earth and Space Science Data Sets
Analysis and visualization of extremely large and complex data sets may be one of the most significant challenges facing earth and space science investigators in the forthcoming decades. While advances in hardware speed and storage technology have roughly kept up with (indeed, have driven) increases in database size, the same is not of our abilities to manage the complexity of these data. Current missions, instruments, and simulations produce so much data of such high dimensionality that they outstrip the capabilities of traditional visualization and analysis software. This problem can only be expected to get worse as data volumes increase by orders of magnitude in future missions and in ever-larger supercomputer simulations. For large multivariate data (more than 10$^{5}$ samples or records with more than 5 variables per sample) the interactive graphics response of most existing statistical analysis, machine learning, exploratory data analysis, and/or visualization tools such as Torch, MLC++, Matlab, S++/R, and IDL stutters, stalls, or stops working altogether. Fortunately, the graphics processing units (GPUs) built in to all professional desktop and laptop computers currently on the market are capable of transforming, filtering, and rendering hundreds of millions of points per second. We present a prototype open-source cross-platform application which leverages much of the power latent in the GPU to enable smooth interactive exploration and analysis of large high- dimensional data using a variety of classical and recent techniques. The targeted application is the interactive analysis of large, complex, multivariate data sets, with dimensionalities that may surpass 100 and sample sizes that may exceed 10$^{6}$-10$^{}8$.
IN43B-05
EOSDIS Customer Support Challenges
The Earth Observation System Data and Information System (EOSDIS) is a large, complex data system currently supporting over 18 operational NASA satellite missions including the flagship EOS missions: Terra, Aqua, and Aura. The observations collected by these missions are kept at geographically distributed data centers. EOSDIS manages over four petabytes of data accessed by over 200,000 distinct users last year. The data centers distributed more than 37 million Earth science data products during 2005 to a diverse customer community. An important goal for these data centers is to provide an adequate service at a uniform level for the user community to ensure we get the most benefit from our investment in space resources. This paper discusses the challenges, the ways the data centers coordinate among themselves to provide service, and recent results of measuring customer satisfaction with this service.
IN43B-06
Applications of the LBA-ECO Metadata Warehouse
The LBA-ECO Project Office has developed a system to harvest and warehouse metadata resulting from the Large-Scale Biosphere Atmosphere Experiment in Amazonia. The harvested metadata is used to create dynamically generated reports, available at www.lbaeco.org, which facilitate access to LBA-ECO datasets. The reports are generated for specific controlled vocabulary terms (such as an investigation team or a geospatial region), and are cross-linked with one another via these terms. This approach creates a rich contextual framework enabling researchers to find datasets relevant to their research. It maximizes data discovery by association and provides a greater understanding of the scientific and social context of each dataset. For example, our website provides a profile (e.g. participants, abstract(s), study sites, and publications) for each LBA-ECO investigation. Linked from each profile is a list of associated registered dataset titles, each of which link to a dataset profile that describes the metadata in a user-friendly way. The dataset profiles are generated from the harvested metadata, and are cross-linked with associated reports via controlled vocabulary terms such as geospatial region. The region name appears on the dataset profile as a hyperlinked term. When researchers click on this link, they find a list of reports relevant to that region, including a list of dataset titles associated with that region. Each dataset title in this list is hyperlinked to its corresponding dataset profile. Moreover, each dataset profile contains hyperlinks to each associated data file at its home data repository and to publications that have used the dataset. We also use the harvested metadata in administrative applications to assist quality assurance efforts. These include processes to check for broken hyperlinks to data files, automated emails that inform our administrators when critical metadata fields are updated, dynamically generated reports of metadata records that link to datasets with questionable file formats, and dynamically generated region/site coordinate quality assurance reports. These applications are as important as those that facilitate access to information because they help ensure a high standard of quality for the information. This presentation will discuss reports currently in use, provide a technical overview of the system, and discuss plans to extend this system to harvest metadata resulting from the North American Carbon Program by drawing on datasets in many different formats, residing in many thematic data centers and also distributed among hundreds of investigators.
IN43B-07
A Flexible Data-Describing Metadata Format for Earth, Lunar, Planetary and Astronomical Sciences
NASA's GCMD is the one of the most comprehensive metadata directories for locating and accessing Earth Science data. The GCMD focuses on providing direct access to scientific data and related services that can be used to visualize and analyze relevant data. The metadata format for describing Earth Science data, and the software behind the search and retrieval, is remarkably flexible and can be adapted for describing lunar, planetary, and astronomical data and subsequently linking these to related services. Central to the GCMD are robust hierarchies of controlled Earth Science keywords for search and retrieval. Targeted controlled vocabularies can be created or adopted for use in searching for lunar, planetary, and astronomical data sets in keeping with NASA's strategic goals.
<a href='http://gcmd.nasa.gov'>http://gcmd.nasa.gov</a>
IN43B-08
A Capability Vision for Earth Science Information Systems
The strategy for developing Earth science data systems has shifted from rigid, top-down development of centralized systems via large contracts to a more dynamic evolution of existing distributed community capabilities via small competitive solicitations. To meet the growing expectations of researchers, decision makers, and educators, future Earth science data systems will need to offer increasingly sophisticated data analysis and decision support capabilities, improved visualization techniques, greater integration of diverse data sources and improvements in precision, quality, and system performance. This can only be achieved through the adoption of new and emerging technologies. NASA's Earth Science Data Systems Technology Infusion Working Group has developed a Capability Vision for Earth science information systems that explores the capabilities needed by future data systems, the benefits they provide, and the technologies that will be needed to realize them. The vision identifies four key capabilities needed by researchers to realize NASA's Earth science goals: Scalable Analysis Portals, Community Modeling Frameworks, Assisted Data \& Service Discovery, and Assisted Knowledge Building. These four top-level capabilities are supported by six additional capabilities: Interactive Data Analysis, Seamless Data Access, Interoperable Information Services, Responsive Information Delivery, Verifiable Information Quality, and Evolvable Technical Infrastructure. The presentation uses a real-world science scenario, based on severe weather prediction, to illustrate how these capabilities could serve Earth science researchers and the broader Earth science community and stakeholders. By sharing this vision, the science community will be better able to focus resources on those capabilities needed to make substantial progress toward science goals of national priority.
IN43B-09
Application of OGC Specifications to Air Quality Information Systems
Interoperability among data sources and data applications is a fundamental principle in developing networked, reconfigurable environmental information systems, such as GEOSS. Air quality information systems provide a particularly good test environment for data interoperability standards because they involve observations from surface, air, and space-borne sensors, and models for multidimensional data analysis and forecasting. We assess and implement Open Geospatial Consortium (OGC) standards for fostering air quality data access and analysis. Some of the key standards implemented include the Web Map Server (WMS) for exchanging map images, the Web Feature Server (WFS) for accessing air quality monitors, and the Web Coverage Server (WCS) for multi-dimensional access to air quality data. Emerging specifications, particularly the Sensor Web Enablement suite, are evaluated to support the description of air quality monitors and access of their observations. We propose extensions to support non-traditional geospatial applications of the OGC specifications, such as the access of point monitoring data through the WCS interface which has only supported grids to this point. We also explore the relationships among specifications. Achieving complete data interoperability among air quality information systems will require a combination of standards that cross reference one another.