Engineering topics

Wharton, Stephen W.

Publications and source records attributed to Wharton, Stephen W..

16 records

NASA NTRS2006

Data Integration Support for Data Served in the OPeNDAP and OGC Environments

NASA is coordinating a technology development project to construct a gateway between system components built upon the Open-source Project for a Network Data AcceSs Protocol (OPeNDAP) and those made available made available via interfaces specified by the Open Geospatial Consortium (OGC). This project is funded though the Advanced Collaborative Connections for Earth-Sun System Science (ACCESS) Program and is a NASA contribution to the Committee on Earth Satellites (CEOS) Working Group on Information Systems and Services (WGISS). The motivation for the project is the set of data integration needs that have been expressed by the Coordinated Enhanced Observing Period (CEOP), an international program that is addressing the study of the global water cycle. CEOP is assembling a large collection in situ and satellite data and mode1 results from a wide variety of sources covering 35 sites around the globe. The data are provided by systems based on either the OPeNDAP or OGC protocols but the research community desires access to the full range of data and associated services from a single client. This presentation will discuss the current status of the OPeNDAP/OGC Gateway Project. The project is building upon an early prototype that illustrated the feasibility of such a gateway and which was demonstrated to the CEOP science community. In its first year as an ACCESS project, the effort has been has focused on the design of the catalog and data services that will be provided by the gateway and the mappings between the metadata and services provided in the two environments.

McDonald, Kenneth R.↗

NASA NTRS2002

Global Change Data Center: Mission, Organization, Major Activities, and 2001 Highlights

Rapid efficient access to Earth sciences data is fundamental to the Nation's efforts to understand the effects of global environmental changes and their implications for public policy. It becomes a bigger challenge in the future when data volumes increase further and missions with constellations of satellites start to appear. Demands on data storage, data access, network throughput, processing power, and database and information management are increased by orders of magnitude, while budgets remain constant and even shrink. The Global Change Data Center's (GCDC) mission is to provide systems, data products, and information management services to maximize the availability and utility of NASA's Earth science data. The specific objectives are (1) support Earth science missions be developing and operating systems to generate, archive, and distribute data products and information; (2) develop innovative information systems for processing, archiving, accessing, visualizing, and communicating Earth science data; and (3) develop value-added products and services to promote broader utilization of NASA Earth Sciences Enterprise (ESE) data and information. The ultimate product of GCDC activities is access to data and information to support research, education, and public policy.

Wharton, Stephen W.↗

NASA NTRS2001

Gridded Hourly Text Products: A TRMM Data Reduction Approach

The quantity of precipitation data from satellite-based observations is a blessing and a curse. The sheer volume of the data makes it difficult for many researchers to use in targeted applications. This volume increases further as algorithm improvements lead to the reprocessing of mission data. In addition to the overall volume of data, the size and format complexity of orbital granules contribute to the difficulty in using all the available data. Finally, the number of different instruments available to measure rainfall and related parameters further contributes to the volume concerns. In summary, we have an embarrassment of riches. The science team of the Tropical Rainfall Measuring Mission (TRMM) recognized this dilemma and has developed a strategy to address it. The TRMM Science Data and Information System (TSDIS) produces, at the direction of the Joint TRMM Science Team, a number of instantaneous rainfall products. The TRMM Microwave Imager (TMI), the Precipitation Radar and a Combined TMI/PR are the key "instruments" used in this production. Each of these products contains an entire orbit of data. The algorithm code computes not just rain rates but a large number of other physical parameters as well as information needed for monitoring algorithm performance. That makes these products very large. For example, a single orbit of TMI rain rate product is 99 MB, a single orbit of the combined product yields a granule that is 158 MB, while the 80 vertical levels of rain information from the PR yields an orbital product of 253 MB. These are large products that are often difficult for science users to electronically transfer to their sites especially if they want a large period of time. Level 3 gridded products are much smaller, but their 5 or 30 day temporal resolution is insufficient for many researchers. In addition, TRMM standard products are produced in the HDF format. While a large number of user-friendly tools are available to hide the details of the format (including a toolkit developed at TSDIS for the TRMM science team), many potential users shy away

Stocker, Erich↗

NASA NTRS2001

Syntactic and Semantic Validation without a Metadata Management System

The ability to maintain quality information is essential to securing the confidence in any system for which the information serves as a data source. NASA's Global Change Master Directory (GCMD), an online Earth science data locator, holds over 9000 data set descriptions and is in a constant state of flux as metadata are created and updated on a daily basis. In such a system, the importance of maintaining the consistency and integrity of these-metadata is crucial. The GCMD has developed a metadata management system utilizing XML, controlled vocabulary, and Java technologies to ensure the metadata not only adhere to valid syntax, but also exhibit proper semantics.

Pollack, Janine↗

NASA NTRS2001

Simple, Scalable, Script-Based Science Processor (S4P)

The development and deployment of data processing systems to process Earth Observing System (EOS) data has proven to be costly and prone to technical and schedule risk. Integration of science algorithms into a robust operational system has been difficult. The core processing system, based on commercial tools, has demonstrated limitations at the rates needed to produce the several terabytes per day for EOS, primarily due to job management overhead. This has motivated an evolution in the EOS Data Information System toward a more distributed one incorporating Science Investigator-led Processing Systems (SIPS). As part of this evolution, the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC) has developed a simplified processing system to accommodate the increased load expected with the advent of reprocessing and launch of a second satellite. This system, the Simple, Scalable, Script-based Science Processor (S42) may also serve as a resource for future SIPS. The current EOSDIS Core System was designed to be general, resulting in a large, complex mix of commercial and custom software. In contrast, many simpler systems, such as the EROS Data Center AVHRR IKM system, rely on a simple directory structure to drive processing, with directories representing different stages of production. The system passes input data to a directory, and the output data is placed in a "downstream" directory. The GES DAAC's Simple Scalable Script-based Science Processing System is based on the latter concept, but with modifications to allow varied science algorithms and improve portability. It uses a factory assembly-line paradigm: when work orders arrive at a station, an executable is run, and output work orders are sent to downstream stations. The stations are implemented as UNIX directories, while work orders are simple ASCII files. The core S4P infrastructure consists of a Perl program called stationmaster, which detects newly arrived work orders and forks a job to run the appropriate executable (registered in a configuration file for that station). Although S4P is written in Perl, the executables associated with a station can be any program that can be run from the command line, i.e., non-interactively. An S4P instance is typically monitored using a simple Graphical User Interface. However, the reliance of S4P on UNIX files and directories also allows visibility into the state of stations and jobs using standard operating system commands, permitting remote monitor/control over low-bandwidth connections. S4P is being used as the foundation for several small- to medium-size systems for data mining, on-demand subsetting, processing of direct broadcast Moderate Resolution Imaging Spectroradiometer (MODIS) data, and Quick-Response MODIS processing. It has also been used to implement a large-scale system to process MODIS Level 1 and Level 2 Standard Products, which will ultimately process close to 2 TB/day.

Lynnes, Christopher↗

NASA NTRS2001

Controlling Malaria and Other Diseases Using Remote Sensing

Remote sensing offers the vantage of monitoring a vast area of the Earth continuously. Once developed and launched, a satellite gives years of service in collecting data from the land, the oceans, and the atmosphere. Since the 1980s, attempts have been made to relate disease occurrence with remotely sensed environmental and geophysical parameters, using data from Landsat, SPOT, AVHRR, and other satellites. With higher spatial resolution, the recent satellite sensors provide a new outlook for disease control. At sub-meter to I 10m resolution, surface types associated with disease carriers can be identified more accurately. The Ikonos panchromatic sensor with I m resolution, and the Advanced Land Imager with 1 Om resolution on the newly launched Earth Observing-1, both have displayed remarkable mapping capabilities. In addition, an entire array of geophysical parameters can now be measured or inferred from various satellites. Airborne remote sensing, with less concerns on instrument weight, size, and power consumption, also offers a low-cost alternative for regional applications. NASA/GSFC began to collaborate with the Mahidol University on malaria and filariasis control using remote sensing in late 2000. The objectives are: (1) To map the breeding sites for the major vector species; (2) To identify the potential sites for larvicide and insecticide applications; (3) To explore the linkage of vector population and transmission intensity to environmental variables; (4) To monitor the impact of climate change and human activities on vector population and transmission; and (5) To develop a predictive model for disease distribution. Field studies are being conducted in several provinces in Thailand. Data analyses will soon begin. Malaria data in South Korea are being used as surrogates for developing classification techniques. GIS has been shown to be invaluable in making the voluminous remote sensing data more readily understandable. It will be used throughout this study to clearly demonstrate the spatial relationship between the disease intensities, geophysical variables, and socioeconomic parameters. Asides from malaria and filariasis, application of remote sensing to the control of other diseases have been vigorously pursued by NASA's Environment and Health Initiative. The current program includes projects on Rift Valley fever, St. Louis encephalitis, dengue fever, ebola, African dust and diseases, meningitis, asthma, bartonellosis, cholera, and urban health concerns. Results from these projects indicate that remote sensing will play an increasingly important role in disease control in the future.

Kiang, Richard K.↗

NASA NTRS2001

In Interactive, Web-Based Approach to Metadata Authoring

NASA's Global Change Master Directory (GCMD) serves a growing number of users by assisting the scientific community in the discovery of and linkage to Earth science data sets and related services. The GCMD holds over 8000 data set descriptions in Directory Interchange Format (DIF) and 200 data service descriptions in Service Entry Resource Format (SERF), encompassing the disciplines of geology, hydrology, oceanography, meteorology, and ecology. Data descriptions also contain geographic coverage information, thus allowing researchers to discover data pertaining to a particular geographic location, as well as subject of interest. The GCMD strives to be the preeminent data locator for world-wide directory level metadata. In this vein, scientists and data providers must have access to intuitive and efficient metadata authoring tools. Existing GCMD tools are not currently attracting. widespread usage. With usage being the prime indicator of utility, it has become apparent that current tools must be improved. As a result, the GCMD has released a new suite of web-based authoring tools that enable a user to create new data and service entries, as well as modify existing data entries. With these tools, a more interactive approach to metadata authoring is taken, as they feature a visual "checklist" of data/service fields that automatically update when a field is completed. In this way, the user can quickly gauge which of the required and optional fields have not been populated. With the release of these tools, the Earth science community will be further assisted in efficiently creating quality data and services metadata. Keywords: metadata, Earth science, metadata authoring tools

Pollack, Janine↗

NASA NTRS2001

An Approach to Data Center-Based KDD of Remote Sensing Datasets

The data explosion in remote sensing is straining the ability of data centers to deliver the data to the user community, yet many large-volume users actually seek a relatively small information component within the data, which they extract at their sites using Knowledge Discovery in Databases (KDD) techniques. To improve the efficiency of this process, the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC) has implemented a KDD subsystem that supports execution of the user's KDD algorithm at the data center, dramatically reducing the volume that is sent to the user. The data are extracted from the archive in a planned, organized "campaign"; the algorithms are executed, and the output products sent to the users over the network. The first campaign, now complete, has resulted in overall reductions in shipped volume from 3.3 TB to 0.4 TB.

Lynnes, Christopher↗

NASA NTRS2001

A Time-Frequency Analysis of the Effects of Solar Activities on Tropospheric Thermodynamics

Whether the Sun has significantly influenced the climate during the last century has been under extensive debates for almost two decades. Since the solar irradiance varies very little in a solar cycle, it is puzzling that some geophysical parameters show proportionally large variations which appear to be responding to the solar cycles. For example, variation in low altitude clouds is shown correlated with solar cycle, and the onset of Forbush decrease is shown correlated with the reduction of the vorticity area index. A possible sun-climate connection is that galactic cosmic rays modulated by solar activities influence cloud formation. In this paper, we apply wavelet transform to satellite and surface data to examine this hypothesis. Data analyzed include the time series for solar irradiance, sunspots, UV index, temperature, cloud coverage, and neutron counter measurements. The interactions among the elements in the Earth System under the external and internal forcings give out very complex signals.The periodicity of the forcings or signals could range widely. Since wavelet transforms can analyze multi-scale phenomena that are both localized in frequency and time, it is a very useful technique for detecting, understanding and monitoring climate changes.

Kiang, Richard K.↗

NASA NTRS2000

KDD Services at the Goddard Earth Sciences Distributed Active Archive Center

NASA's Goddard Earth Sciences Distributed Active Archive Center (GES DAAC) processes, stores and distributes earth science data from a variety of remote sensing satellites. End users of the data range from instrument scientists to global change and climate researchers to federal agencies and foreign governments. Many of these users apply data mining techniques to large volumes of data (up to 1 TB) received from the GES DAAC. However, rapid advances in processing power are enabling increases in data processing that are outpacing tape drive performance and network capacity. As a result, the proportion of data that can be distributed to users continues to decrease. As mitigation, we are migrating more data mining and mining preparation activities into the data center in order to reduce the data volume that needs to be distributed and to offer the users a more useful and manageable product. This migration of activities faces a number of technical and human-factor challenges. As data reduction and mining algorithms are normally quite specific to the user's research needs, the user's algorithm must be integrated virtually unchanged into the archive environment. Also, the archive itself is busy with everyday data archive and distribution activities and cannot be dedicated to, or even impacted by, the mining activities. Therefore, we schedule KDD 'campaigns' (similar to reprocessing campaigns), during which we schedule a wholesale retrieval of specific data products, offering users the opportunity to extract information from the data being retrieved during the campaign.

Lynnes, Christopher↗

NASA NTRS1991

Sizing the science data processing requirements for EOS

The methodology used in the compilation and synthesis of baseline science requirements associated with the 30 + EOS (Earth Observing System) instruments and over 2,400 EOS data products (both output and required input) proposed by EOS investigators is discussed. A brief background on EOS and the EOS Data and Information System (EOSDIS) is presented, and the approach is outlined in terms of a multilayer model. The methodology used to compile, synthesize, and tabulate requirements within the model is described. The principal benefit of this approach is the reduction of effort needed to update the analysis and maintain the accuracy of the science data processing requirements in response to changes in EOS platforms, instruments, data products, processing center allocations, or other model input parameters. The spreadsheets used in the model provide a compact representation, thereby facilitating review and presentation of the information content.

Wharton, Stephen W.↗

NASA NTRS1989

Land image data processing requirements for the EOS era

Requirements are proposed for a hybrid approach to image analysis that combines the functionality of a general-purpose image processing system with the knowledge representation and manipulation capabilities associated with expert systems to improve the productivity of scientists in extracting information from remotely sensed image data. The overall functional objectives of the proposed system are to: (1) reduce the level of human interaction required on a scene-by-scene basis to perform repetitive image processing tasks; (2) allow the user to experiment with ad hoc rules and procedures for the extraction, description, and identification of the features of interest; and (3) facilitate the derivation, application, and dissemination of expert knowledge for target recognition whose scope of application is not necessarily limited to the image(s) from which it was derived.

Wharton, Stephen W.↗

NASA NTRS1988

An interactive testbed for development of expert tools for pattern recognition

The initial implementation of an interactive testbed for development of expert system applications in image processing, i.e., a toolbox of procedures designed to facilitate the capture of expert knowledge for region grouping and analysis is described. The user can elect to interactively enter commands (via a command interpreter) for region manipulation to, in effect, simulate the actions of a hypothetical expert system. The user can then incorporate any rules and procedures as derived from interactive experimentation into customized region processing procedures using the library of utility functions. An iterative technique based on image pyramids is used to compute the initial region segmentation without the use of process parameters. These regions can then be interactively examined and manipulated using the command interpreter.

Wharton, Stephen W.↗

NASA NTRS1987

A methodology for evaluation of an interactive multispectral image processing system

Because of the considerable cost of an interactive multispectral image processing system, an evaluation of a prospective system should be performed to ascertain if it will be acceptable to the anticipated users. Evaluation of a developmental system indicated that the important system elements include documentation, user friendliness, image processing capabilities, and system services. The criteria and evaluation procedures for these elements are described herein. The following factors contributed to the success of the evaluation of the developmental system: (1) careful review of documentation prior to program development, (2) construction and testing of macromodules representing typical processing scenarios, (3) availability of other image processing systems for referral and verification, and (4) use of testing personnel with an applications perspective and experience with other systems. This evaluation was done in addition to and independently of program testing by the software developers of the system.

Kovalick, William M.↗

NASA NTRS1987

A spectral-knowledge-based approach for urban land-cover discrimination

A prototype expert system was developed to demonstrate the feasibility of classifying multispectral remotely sensed data on the basis of spectral knowledge. The spectral expert was developed and tested with Thematic Mapper Simulator (TMS) data having eight spectral bands and a spatial resolution of 5 m. A knowledge base was developed that describes the target categories in terms of characteristic spectral relationships. The knowledge base was developed under the following assumptions: the data are calibrated to ground reflectance, the area is well illuminated, the pixels are dominated by a single category, and the target categories can be recognized without the use of spatial knowledge. Classification decisions are made on the basis of convergent evidence as derived from applying the spectral rules to a multiple spatial resolution representation of the image. The spectral expert achieved an accuracy of 80-percent correct or higher in recognizing 11 spectral categories in TMS data for the washington, DC, area. Classification performance can be expected to decrease for data that do not satisfy the above assumptions as illustrated by the 63-percent accuracy for 30-m resolution Thematic Mapper data.

Wharton, Stephen W.↗

NASA NTRS1987

The Land Analysis System (LAS) - A general purpose system for multispectral image processing

The present, general-purpose Land Analysis System (LAS) for image processing furnishes a comprehensive set of functions for the manipulation of MSS data; the initial version has more than 240 functions and utilities ranging from pixel manipulation to complex classification. A LAS user's guide describes each such function in terms of purpose, input parameters, illustrative examples, algorithms, error messages, and user codes. The LAS source code is so distributed as to simplify system maintenance; the Transportable Application Executive is employed as the user interface, thereby accommodating both expert and novice users by means of menus and tutored prompting.

Wharton, Stephen W.↗