IN13A-1053
IKONOS and AIRSAR Imagery Informatics in Land Cover Classification
For earth and space sciences, one application of visible and near infrared multispectral imagery is land cover classification. For a number of studies found in the literature, inclusion of processed radar imagery with visible and near infrared imagery improved the land cover map accuracy. In this study, IKONOS multispectral imagery and NASA JPL AIRSAR imagery are utilized together in the land cover classifier. Here, the radar imagery is processed by various methods before insertion into the classifier. Classifier accuracy is investigated for efficient processing of radar imagery. This study explores a number of land cover types such as urban, residential, vegetation, and others.
IN13A-1054
Multisensor and Multispectral Approach in Documenting and Analyzing Liquefaction Hazard using Remote Sensing
Seismic liquefaction is the loss of strength of soil due to shaking that leads to various ground failures such as lateral spreading, settlements, tilting, and sand boils. It is important to document these failures after earthquakes to advance our study of when and where liquefaction occurs. The current approach of mapping these failures by field investigation teams suffers due to the inaccessibility to some of the sites immediately after the event, short life of some of these failures, difficulties in mapping the aerial extent of the failure, incomplete coverage etc. After the 2001 Bhuj earthquake (India), researchers, using the Indian remote sensing satellite, illustrated that satellite remote sensing can provide a synoptic view of the terrain and offer unbiased estimates of liquefaction failures. However, a multisensor (data from different sensors onboard of the same or different satellites) and multispectral (data collected in different spectral regions) approach is needed to efficiently document liquefaction incidences and/or its potential of occurrence due to the possibility of a particular satellite being located inappropriately to image an area shortly after an earthquake. The use of SAR satellite imagery ensures the acquisition of data in all weather conditions at day and night as well as information complimentary to the optical data sets. In this study, we analyze the applicability of the various satellites (Landsat, RADARSAT, Terra-MISR, IRS-1C, IRS-1D) in mapping liquefaction failures after the 2001 Bhuj earthquake using Support Vector Data Description (SVDD). The SVDD is a kernel based nonparametric outlier detection algorithm inspired by the Support Vector Machines (SVMs), which is a new generation learning algorithm based on the statistical learning theory. We present the applicability of SVDD for unsupervised change-detection studies (i.e. to identify post-earthquake liquefaction failures). The liquefaction occurrences identified from the different satellites using SVDD have been compared to the ground truth in terms of documented liquefaction failures by other researchers. We present the applicability and appropriateness of the various satellites and spectral regions for documenting liquefaction related failures. Results illustrate that the SVDD is a promising unsupervised change-detection algorithm, which can help in automating the documentation of earthquake induced liquefaction failures.
IN13A-1055
The Impact of Current Events on Access to EOSDIS Data Centers
The Earth Observing System Data and Information System (EOSDIS) has been collecting and analyzing information on the archiving, processing and distribution of Earth science data for over10 years. Long- standing approaches for evaluating the performance of systems managed by EOSDIS have provided insights into how system engineering requirements are being met, how user communities are being served and the levels of interest across the science data products. With data and services increasingly being made available to users via web-based applications, EOSDIS has implemented a system that collects measurements of web- based activity along with standard data system parameter counts and user access metrics. Tracking the access to Earth science data products serves as a key estimate of system utility since these products can be used for Earth science research. In today's world, system access, especially for new users, begins with the access to a web site to gain more information or understanding of the area of interest. Web based content and on-line services provide information and data directly from the web site that may satisfy the viewers' needs. The growing ability of EOSDIS to monitor this interaction provides increased understanding of user interest. And this interest may translate into access to science data products, the traditional measurement of system utility. Recent climate change predictions and the prevalence of natural disasters (flooding in Myanmar and Iowa, earthquakes in China, fires in California) have led to increased interest in Earth science data and information. These events, along with planned EOSDIS outreach activities, often show a corresponding increase in visits to EOSDIS web sites. Examination of the increased activity, e.g., number of unique visitors, their source domains, as well as the lack of activity during similar events, helps us understand what drives our users. The goal is to investigate the correlation between events, natural or man-made, that lead to a change in activity at the EOSDIS data center web sites and impact user access to science data products. We present metrics collected in response to real world events, the capabilities of our metrics collection tools to support detailed analysis, and the insights derived from this analysis.
IN13A-1056
NASA EOSDIS Data Centers - Connecting Us to a Changing Planet
NASA Earth Observing System Data and Information System (EOSDIS) data centers support over 18 operational NASA satellite missions including the flagship EOS missions: Terra, Aqua, and Aura. The EOS missions collect data for the key physical variables needed to advance understanding of the entire Earth system and develop a deeper comprehension of the components of that system and the interactions among the components. These components (the atmosphere, land, oceans, and cryosphere) are characterized by the key measurements identified by the Earth science community known as the 24 EOS measurements. The observations and data products resulting from these measurements are processed and managed at geographically distributed facilities. Processing facilities generate data products for selected mission instruments and deliver them to the data centers for archive and user distribution. The data centers serve one or more specific Earth science disciplines to provide the user community with data products, information, services, and tools unique to its particular science. In addition to data from the EOS satellites, EOSDIS data centers house socioeconomic data, data from pre-EOS missions, and data from field campaigns. With the continued growth of the data centers holdings and the addition of the Crustal Dynamics Data and Information System to EOSDIS researchers have more data and knowledge to enhance their scientific studies of global change. We describe each processing facility and data center, its expertise, and its disciplines. We indicate the physical location of the data products that are associated with the 24 science measurements. We provide a diagrammatic mapping of the components, disciplines, and measurements to the data centers to facilitate understanding of the individual centers and to show the interrelated nature of the data center holdings. We present lessons learned in developing and managing data set diversity.
IN13A-1057
The NASA EOSDIS Role in Providing Science Support for Natural Hazards
The Earth Observation System Data and Information System (EOSDIS) data centers process, archive, and distribute satellite data from Earth science missions. Although EOSDIS was designed to ensure that scientists and the public have access to data to advance scientific understanding, the data centers have done considerable work supporting the study and response to natural hazards such as floods, fires, mudslides and severe weather. Recent disasters from flooding in Burma and Iowa, earthquakes in China, fires in California, and hurricane damage in the Caribbean and southeastern US illustrate ways in which the NASA data are used to show the physical nature and geographic extent of the risks and hazards. We believe the inherent geospatial view of NASA satellite data could give response and preparedness organizers an important tool for communicating these risks and hazards to local communities. We will highlight the NASA EOSDIS sources and types of data used in recent collaborations and ongoing efforts to show the effects of natural hazards.
IN13A-1058
Discrimination of Sedimentary Lithologies Through Unmixing of EO-1 Hyperion Data: Melville Island, Canadian High Arctic
The use of remote-sensing techniques in the discrimination of rock and soil classes in northern regions can help support a diverse range of activities including environmental characterization, mineral exploration, and the study of Quaternary paleoenvironments. Images of low spectral resolution can commonly be used in the mapping of lithological classes possessing distinct spectral characteristics, but hyperspectral databases offer greater potential for discrimination of materials distinguished by more subtle reflectance properties. Orbiting sensors offer an especially flexible and cost-effective means for acquisition of data to workers unable to conduct airborne surveys. In an effort to better constrain the utility of hyperspectral datasets in northern research, this study undertook to investigate the effectiveness of EO-1 Hyperion data in the discrimination and mapping of surface classes at a study area on Melville Island, Nunavut. Bedrock units in the immediate study area consist of late-Paleozoic clastic and carbonate sequences of the Sverdrup Basin. Weathered and frost-shattered felsenmeer, predominantly taking the form of boulder- to pebble-sized clasts that have accumulated in place and that mantle parent bedrock units, is the most common surface material in the study area. Hyperion data were converted from at-sensor radiance to reflectance, and were then linearly unmixed on the basis of end-member spectra measured from field samples. Hyperion unmixing results effectively portray the general fractional cover of six end members, although the fraction images of several materials contain background values that in some areas overestimate surface exposure. The best separated end members include the snow, green vegetation, and red-weathering sandstone classes, whereas the classes most negatively affected by elevated fraction values include the mudstone, limestone, and 'other' sandstone classes. Local overestimates of fractional cover are likely related to the shared lithological and weathering characteristics of several clastic and carbonate units, and may also be related to the lower radiometric precision characteristic of Hyperion data. Despite these issues, the databases generated in this study successfully provide useful complementary information to that provided by maps of local bedrock geology.
IN13A-1059
MODIS Interactive Subsetting Tool (MIST)
In response to requests from the user community, NSIDC has teamed with the Oak Ridge National Laboratory Distributive Active Archive Center (ORNL DAAC) and the Moderate Resolution Data Center (MrDC) to provide time series subsets of satellite data covering stations in the Greenland Climate Network (GC-NET) and the International Arctic Systems for Observing the Atmosphere (IASOA) network. To serve these data NSIDC created the MODIS Interactive Subsetting Tool (MIST). MIST works with 7 km by 7 km subset time series of certain Version 5 (V005) MODIS products over GC-Net and IASOA stations. User- selected data are delivered in a text Comma Separated Value (CSV) file format. MIST also provides online analysis capabilities that include generating time series and scatter plots. Currently, MIST is a Beta prototype and NSIDC intends that user requests will drive future development of the tool. The intent of this poster is to introduce MIST to the MODIS data user audience and illustrate some of the online analysis capabilities.
IN13A-1060
A New 3D Visualization Tool for Space Weather from the Community Coordinated Modeling Center
The Community Coordinated Modeling Center (CCMC) at NASA Goddard Space Flight Center provides free access to modern space research models to the space weather community. We execute space weather model simulations for end users through our Runs-On-Request system, and provide tools to explore and analyze space weather simulation data. We currently have both 2D and 3D visualizations available through our easy-to-use web interface, and soon, a new standalone 3D visualization tool that will allow an easier, more interactive experience. Using our Kameleon library (a data format standardization and access and interpolation library), and our extension utility libraries, we can visualize data interactively that otherwise would not be possible. We present our new Java3D based visualization tool and highlight the innovative features that aid in the interactive exploration of the data, including our modern data access method.
IN13A-1061
SAFOD Brittle Microstructure and Mechanics Knowledge Base (SAFOD BM2KB)
We have developed a knowledge base to store and present the data collected by a group of investigators
studying the microstructures and mechanics of brittle faulting using core samples from the SAFOD (San
Andreas Fault Observatory at Depth) project. The investigations are carried out with a variety of analytical
and experimental methods primarily to better understand the physics of strain localization in fault gouge. The
knowledge base instantiates an specially-designed brittle rock deformation ontology developed at Georgia
State University. The inference rules embedded in the semantic web languages, such as OWL, RDF, and
RDFS, which are used in our ontology, allow the Pellet reasoner used in this application to derive additional
truths about the ontology and knowledge of this domain. Access to the knowledge base is via a public
website, which is designed to provide the knowledge acquired by all the investigators involved in the project.
The stored data will be products of studies such as: experiments (e.g., high-velocity friction experiment),
analyses (e.g., microstructural, chemical, mass transfer, mineralogical, surface, image, texture), microscopy
(optical, HRSEM, FESEM, HRTEM]), tomography, porosity measurement, microprobe, and
cathodoluminesence. Data about laboratories, experimental conditions, methods, assumptions, equipments,
and mechanical properties and lithology of the studied samples will also be presented on the website per
investigation.
The ontology was modeled applying the UML (Unified Modeling Language) in Rational Rose, and
implemented in OWL-DL (Ontology Web Language) using the Protégé ontology editor. The UML model was
converted to OWL-DL by first mapping it to Ecore (.ecore) and Generator model (.genmodel) with the help of
the EMF (Eclipse Modeling Framework) plugin in Eclipse. The Ecore model was then mapped to a .uml file,
which later was converted into an .owl file and subsequently imported into the Protégé ontology editing
environment. The web-interface was developed in java using eclipse as the IDE. The web interfaces to query
and submit data were implemented applying JSP, servlets, javascript, and AJAX. The Jena API, a Java
framework for building Semantic Web applications, was used to develop the web-interface. Jena provided a
programmatic environment for RDF, RDFS, OWL, and SPARQL query engine. Building web applications with
AJAX helps retrieving data from the server asynchronously in the background without interfering with the
display and behavior of the existing page. The application was deployed on an apache tomcat server at GSU.
The SAFOD BM2KB website provides user-friendly search, submit, feedback, and other services. The
General Search option allows users to search the knowledge base by selecting the classes (e.g., Experiment,
Surface Analysis), their respective attributes (e.g., apparatus, date performed), and the relationships to
other classes (e.g., Sample, Laboratory). The Search by Sample option allows users to search the
knowledge base based on sample number. The Search by Investigator lets users to search the knowledge
base by choosing an investigator who is involved in this project. The website also allows users to submit new
data. The Submit Data option opens a page where users can submit the SAFOD data to our knowledge
base by selecting specific classes and attributes. The submitted data then become available for query as
part of the knowledge base. The SAFOD BM2KB can be accessed from the main SAFOD website.
http://www.gsu.edu/~geohab
IN13A-1062
Online data analysis using Web GDL
The ever improving capability of modern astronomical instruments to capture data at high spatial resolution and cadence is opening up unprecedented opportunities for scientific discovery. When data sets become so large that they cannot be easily transferred over the internet, the researcher must find alternative ways to perform data analysis. One strategy is to bring the data analysis code to where the data resides. We present Web GDL, an implementation of GDL (GNU Data Language, open source incremental compiler compatible with IDL) that allows users to perform interactive data analysis within a web browser.
IN13A-1063
Effects of Indicator Transform Method of Electric Resistivity Data on Rock Mass Classification Using Multiple Indicator Kriging
This study investigates the effects of indicator transform method of electric resistivity data on rock mass classification using multiple indicator kriging. Two different approaches were designed to examine the variation of rock mass classifications according to each indicator transform method. One approach is to change fuzzy membership functions for determining the indicator values at four increasing thresholds (i.e., 20, 40, 60 and 80 which represent the boundary values of rock mass classes in RMR). The other is to reclassify indicator transform ranges of electric resistivity data by considering various classification rules such as quantile, equal interval, natural breaks, standard deviation and grade block. Two tunnelling sites in Korea were selected as study areas, and multiple indicator kriging using borehole RMR and electric resistivity data was performed to estimate RMR values along planned tunnel alignments. The results showed that rock mass classes determined by multiple indicator kriging are significantly sensitive to both the fuzzy membership functions and the transform ranges. From validation processes, it was found that combination of the indicator values derived from frequency ratio of borehole RMR values at each rock mass class and the indicator transform ranges determined by the grade block can make a more accurate result than others.
IN13A-1064
Working Process Development For Weathering Degree Mapping Of Stone Monument Using Reflectance Spectroscopy
Most stone monuments have been weathered on the field with exposure of rain and wind during hundreds or thousands years. Reflectance spectroscopy can be applied to assess weathering degree of those stone monuments composed of granite which is the most general material of stone monument in Korea. Weathering degree was analyzed by using reflected and transmitted electromagnetic energy based on the theory of reflectance spectroscopy on the surface of rock to identify rock forming minerals using their diagnostic spectral absorption features. This method could be used as an improved nondestructive assessment method compared with conventional subjective and qualitative assessment methods. We tested feasibility of this technique for actual granite stone monuments. Granite is generally composed of quartz, feldspars and micas. Feldspars are changed to clay minerals such as kaolinite and illite after weathering process. Biotite of mica produce iron oxides which induce color changes on surface of rocks. The experiments were conducted using field spectrometer FieldSpec®3 of ASD Inc. and the range of measurement was form 350µm to 2500µm wavelength. Spectral reflectance of weathering products at each measuring point was processed by removing delineated convex hull from raw reflectance curves to exclude background effects and to extract quantitative absorption depths which indicate relative distribution degree of weathering products. We produced deterioration map on the surface of the monument by interpolating absorption depth values of each point with consideration of spatial distribution of measurements. For facilitation of practical uses a chain of working process of this method was designed using whole experimental processes.
IN13A-1065
Development of a Database Program for Managing Drilling Data in the Oil and Gas Industry
This study presents a prototype of database program for managing drilling data for the oil and gas industry. The characteristics of petrophysical data from drilling cores were categorized to define the schema of database system such as data fields in tables, the relationships between those tables and key index fields to create the relationships. And many types of drilling reports and previous drilling database systems were reviewed to design of relational database program. Various algorithms of logging tool were analyzed to offer many kinds of function for user. Database program developed in this study provides well-organized graphic user interfaces for creating, editing, querying, exporting and visualizing the drilling data as well as for interchanging data with a spreadsheet such as MS-Excel.
IN13A-1066
Exploring Monte Carlo Simulation Strategies for Geoscience Applications
Computer simulations are an increasingly important area of geoscience research and development. At the core of stochastic or Monte Carlo simulations are the random number sequences that are assumed to be distributed with specific characteristics. Computer generated random numbers, uniformly distributed on [0, 1], can be very different depending on the selection of pseudo-random number (PRN), quasi-random number (QRN) or chaotic random number (CRN) generators. In the evaluation of some definite integrals, the expected error variances are generally of different orders for the same number of random numbers. A comparative analysis of these three strategies has been carried out for geodetic and related applications in planar and spherical contexts. Based on these computational experiments, conclusions and recommendations concerning their performance and error variances are included.
IN13A-1067
The Integrated Space Weather Analysis System
Space weather affects virtually all of NASA's endeavors, from robotic missions to human exploration.
Knowledge and prediction of space weather conditions is therefore essential to NASA operations. The
diverse nature of currently available space environment measurements and modeling products, along with
the lack of single-portal access, renders its practical use for space weather analysis and forecasting
unfeasible. There exists a compelling need for accurate real-time forecasting of both large-scale and local
space environments - and their probable impacts for missions.
A vital design driver for any system that is created to solve this problem lies in the fact that information needs
to be presented in a form that is useful and as such, must be both easily accessible and understandable.
The Integrated Space Weather Analysis System is a joint development project at NASA GSFC between the
Space Weather Laboratory, Community Coordinated Modeling Center, Applied Engineering & Technology
Directorate, and NASA HQ Office Of Chief Engineer. The iSWA system will be a turnkey, web-based
dissemination system for NASA-relevant space weather information that combines forecasts based on the
most advanced space weather models with concurrent space environment information. It will be customer
configurable and adaptable for use as a powerful decision making tool offering an unprecedented ability to
analyze the present and expected future space weather impacts on virtually all NASA human and robotic
missions.
We will discuss some of the key design considerations for the system and present some of the initial space
weather analysis products that have been created to date.
http://iswa.gsfc.nasa.gov
IN13A-1068
Comparison of Ontology Reasoners: Racer, Pellet, Fact++
In this paper, we examine some key aspects of three of the most popular and effective Semantic reasoning engines that have been developed: Pellet, RACER, and Fact++. While these reasonably advanced reasoners share some notable similarities, it is ultimately the creativity and unique nature of these reasoning engines that have resulted in the successes of each of these reasoners. Of the numerous dissimilarities, the most obvious example might be that while Pellet is written in Java, RACER employs the Lisp programming language and Fact++ was developed using C++. From this and many other distinctions in the system architecture, we can understand the benefits of each reasoner and potentially discover certain properties that may contribute to development of an optimal reasoner in the future. The objective of this paper is to establish a solid comparison of the reasoning engines based on their system architectures, features, and overall performances in real world application. In the end, we expect to produce a valid conclusion about the advantages and problems in each reasoner. While there may not be a decisive first place among the three reasoners, the evaluation will also provide some answers as to which of these current reasoning tools will be most effective in common, practical situations.
IN13A-1069
Substorm Classification In UVI Aurora Image Sequences Using The Fuzzy K-NN Algorithm
Auroral substorms are generally observed in the polar regions and are a well-organized pattern of auroral growth, brightening and then decay. The importance of determining substorm in aurora image sequence is that the information might be used to estimate auroral energy parameters from space-based auroral images and to determine the frequency of outbursts of substorms. Systematic investigations of the images should guide researchers to a better understanding of magnetosphere-ionosphere dynamics and insight into what physical mechanisms are involved. Some prior image-based investigations of aurora with Polar Ultraviolet Imager (UVI) images have been done, but little work toward substorm recognition has been fully investigated. Substorm recognition can be thought as a problem of classification of aurora images into two classes, one having substorm and the other without substorm. In the pattern and image classification, Bayes decision theory gives optimal error rates if the full knowledge of the underlying probabilities is known. In those cases where the underlying probabilities are not known, many algorithms use the similarity among samples as a means of classification. The technique employed for solving this substorm recognition problem is based on the fuzzy K-Nearest Neighbor (K-NN) algorithm. The fuzzy K- NN and non-fuzzy K-NN algorithms have been used in the pattern recognition problems. The first task in aurora substorm classification is to extract distinct features so that different aurora patterns and images can be easily discriminated. The wavelet transforms will be employed for features extraction. However, the salient features extracted from images may show a variety of characteristics. Therefore, we propose the fuzzy K-NN algorithm to deal with this type of image features. Experimental results will be presented.
IN13A-1070
Sea Level Rise Scenarios and Predicted Impacts on New Hampshire's Hampton-Seabrook Estuary
According to the Intergovernmental Panel on Climate Change, Environmental Protection Agency, and the Union of Concerned Scientist, coastal areas could experience a rise in sea level from 0.3m (conservative) to 6m (extreme). Due in part to global warming, over the last 100 years mid-Atlantic and Gulf Coast sea level has risen approximately 0.1m more than the average global rise. GIS models illustrating future sea level rise (SLR) projections were generated to assess the potential impact on beaches and estuaries of Hampton and Seabrook, New Hampshire (NH). Limited, but important, tidal wetlands are particularly at risk from rising sea levels. A raster unsupervised landcover classification and a Digital Elevation Model of the southeastern NH coastal region were overlain in ARC/GIS v. 9.0. Sea level rise predictions greater than 1.2m will result in the inundation of greater than 50 percent of the emergent area of the Hampton/Seabrook estuary and urban development fringing the estuary will be prone to greater flooding from storm surges and high tides. An approximate 6m rise in sea level will inundate greater than 95 percent of the Hampton-Seabrook tidal marsh and greater than 95 percent of New Hampshire's existing sand dunes.
IN13A-1071
Tools and Services at PO.DAAC
The Physical Oceanography Distributed Active Archiving Center (PO.DAAC) is the NASA data center
responsible for archiving and distributing data relevant to the physical state of the ocean.
PO.DAAC's primary role is to provide distribution and archive support for
NASA's physical oceanography missions such as Jason-1 and Seawinds on
QuikSCAT. We present several data access tools that facilitate the distribution of data available through
PO.DAAC.
The PO.DAAC Ocean ESIP TOOL (POET), a WMS-compliant web interface allowing users to subset,
download, and view PO.DAAC data, based upon parametric, spatial, temporal constraints and output format.
The PO.DAAC Event Tracker is a web portal providing access to i) near-real-time and historical hurricane
track data, ii) subsetted ocean vector wind and sea surface temperature data centered on storm tracks, and
iii) visualized storm tracks co-locating the aforementioned subsetted data to storm tracks by time.
The Southern California Coastal Ocean Observing System (SCCOOS) web interface allows one to visualize
and download near-real-time and historical data for topography, sea surface temperature, and ocean color
for the Southern California bight region.
Each of these tools provides subsetting, visualization, and related services such as format conversion to
enable PO.DAAC users to obtain data in a from most usable to their needs.
http://podaac.jpl.nasa.gov
IN13A-1072
Implementation and study of quality of compression of a non-lossy data compression technique for multi-dimensional field data
Geophysical Models and observations generate large amount of data in two or three dimensional grid most often with an additional time dimension. Most often the field variables that are stored vary slowly across each of these dimensions in comparison to the range allowed by corresponding IEEE754 format in which those are stored. The standard stream compression techniques like gzip, bzip can not exploit the full spatio-temporal correlation of these data because those techniques look for correlation along the contiguous dimension only. In our approach to this problem we hierarchically strip-off the exponent and abcissa along all the dimensions to exploit the strong correlation in values across nearby physical grid points. We implement the support for netcdf format in the sense that the software can both read and write data in netcdf format. We demonstrate the quality of compression of our implementation on some standard climate data and compare with corresponding compression ratio using bzip and gzip with highest compression quality factor turned on for those.
IN13A-1073
Geosciences Information Network (GIN): A modular, distributed, interoperable data network for the geosciences
A coalition of the state geological surveys (AASG), the U.S. Geological Survey (USGS), and partners will
receive NSF funding over 3 years under the INTEROP solicitation to start building the Geoscience
Information Network (www.geoinformatics.info/gin) a distributed, interoperable data network. The GIN project
will develop standardized services to link existing and in-progress components using a few standards and
protocols, and work with data providers to implement these services.
The key components of this network are 1) catalog system(s) for data discovery; 2) service definitions for
interfaces for searching catalogs and accessing resources; 3) shared interchange formats to encode
information for transmission (e.g. various XML markup languages); 4) data providers that publish information
using standardized services defined by the network; and 5) client applications adapted to use information
resources provided by the network. The GIN will integrate and use catalog resources that currently exist or
are in development. We are working with the USGS National Geologic Map Database's existing map catalog,
with the USGS National Geological and Geophysical Data Preservation Program, which is developing a
metadata catalog (National Digital Catalog) for geoscience information resource discovery, and with the
GEON catalog. Existing interchange formats will be used, such as GeoSciML, ChemML, and Open Geospatial
Consortium sensor, observation and measurement MLs. Client application development will be fostered by
collaboration with industry and academic partners. The GIN project will focus on the remaining aspects of the
system -- service definitions and assistance to data providers to implement the services and bring content
online - and on system integration of the modules.
Initial formal collaborators include the OneGeology-Europe consortium of 27 nations that is building a
comparable network under the EU INSPIRE initiative, GEON, Earthchem, and GIS software company ESRI.
OneGeology-Europe and GIN have agreed to integrate their networks, effectively adopting global standards
among geological surveys that are available across the entire field. ESRI is creating a Geology Data Model
for ArcGIS software to be compatible with GIN, and other companies are expressing interest in adapting their
services, applications, and clients to take advantage of the large data resources planned to become
available through GIN.
http://www.geoinformatics.info/gin
IN13A-1074
Calibration of R/V Marcus G. Langseth Seismic Sources
NSF-owned Research Vessel Marcus G. Langseth is operated by Lamont-Doherty Earth Observatory,
providing the tools for full-scale marine seismic surveys to the academic community. Since inauguration of
science operations, Langseth has successfully supported 2D and 3D seismic operations, including offshore-
onshore and OBS refraction profiling A significant component of Langseths equipage is the seismic source,
comprising four identical linear subarrays which can be combined in a number of configurations according to
the needs of each scientific mission. To ensure a full understanding of the acoustic levels of these sources
and in order to mitigate their possible impact upon marine life through accurate determination of safety radii,
an extensive program of acoustic calibration was carried out in 2007 and 2008, during Langseths shakedown
exercises. A total of 14000+ airgun array discharges were recorded in three separate locations with water
depths varying from 1750 to 45 meters and at source-receiver offsets between near-zero and 17 km. The
quantity of data recorded allows significant quantitative analysis of the sound levels produced by the
Langseth seismic sources. A variety of acoustic metrics will be presented and compared, including peak
levels and energy-based measures such as RMS, Energy Flux Density and its equivalent, Sound Exposure
Level. It is clearly seen that water depth exerts a fundamental control on received sound levels, but also that
these effects can be predicted with reasonable accuracy.
http://www.ldeo.columbia.edu/res/fac/oma/3D_Seismic/3Dcapabilitiesandcruiseplanning.html