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At least 307 records · Page 17

Goddard Visiting Scientist Program for the Space and Earth Sciences Directorate

A visiting scientist program was conducted in the space and earth sciences at GSFC. Research was performed in the following areas: astronomical observations; broadband x-ray spectral variability; ground-based spectroscopic and photometric studies; Seyfert galaxies; active galactic nuclei (AGN); massive stellar black holes; the differential microwave radiometer (DMR) onboard the cosmic background explorer (COBE); atmospheric models; and airborne and ground based radar observations. The specific research efforts are detailed by tasks.

Kerr, Frank↗

ODISEES: Ontology-Driven Interactive Search Environment for Earth Sciences

This paper discusses the Ontology-driven Interactive Search Environment for Earth Sciences (ODISEES) project currently being developed to aid researchers attempting to find usable data among an overabundance of closely related data. ODISEES' ontological structure relies on a modular, adaptable concept modeling approach, which allows the domain to be modeled more or less as it is without worrying about terminology or external requirements. In the model, variables are individually assigned semantic content based on the characteristics of the measurements they represent, allowing intuitive discovery and comparison of data without requiring the user to sift through large numbers of data sets and variables to find the desired information.

Rutherford, Matthew T.↗

Web Coverage Service Challenges for NASA's Earth Science Data

In an effort to ensure that data in NASA's Earth Observing System Data and Information System (EOSDIS) is available to a wide variety of users through the tools of their choice, NASA continues to focus on exposing data and services using standards based protocols. Specifically, this work has focused recently on the Web Coverage Service (WCS). Experience has been gained in data delivery via GetCoverage requests, starting out with WCS v1.1.1. The pros and cons of both the version itself and different implementation approaches will be shared during this session. Additionally, due to limitations with WCS v1.1.1 ability to work with NASA's Earth science data, this session will also discuss the benefit of migrating to WCS 2.0.1 with EO-x to enrich this capability to meet a wide range of anticipated user's needs This will enable subsetting and various types of data transformations to be performed on a variety of EOS data sets.

Web Coverage Services↗

International Earth Science Constellation (ESC)

This presentation will introduce topics of note for the Earth Science Constellation (ESC) Mission Operations Working Group (MOWG) meeting Gilbert AZ, December 3-5, 2019

Machado, Michael J.↗

Remote Access to Earth Science Data by Content, Space and Time

This demo presents the combination on an http-based client/server application that facilitates internet access to Earth science data coupled with a Java applet GUI that allows the user to graphically select data based on spatial and temporal coverage plots and scientific parameters.

Data and Information System (EOSDIS) remote access↗

Collaborations and Partnerships in NASA’s Earth Science Data Systems

NASA has been collecting Earth observation data from spaceborne instruments since 1960. Today, there are tens of satellites orbiting the Earth and collecting frequent global observations for the benefit of mankind. Collaboration between NASA and organizations in the US and other countries has been extremely important in maintaining the Earth observation capabilities as well as collecting, organizing and managing the data. These collaborations have occurred in the form of: 1. NASA’s developing and launching spacecraft and instruments for operation by other agencies; 2. Instruments from collaborating organizations being flown on NASA satellites; and 3. Instruments from NASA being flown on satellites from collaborating organizations. In addition, there are collaborations such as joint science teams, data exchanges, and participation in international organizations to promote interoperability of various data systems. The purpose of this paper is to describe some of the Earth science data-related collaborative efforts in which NASA participates, and highlight a few results relevant to Earth system science research obtained through such collaborations.

Ramapriyan, Hampapuram K.↗

Automated Collection of Scientific Publications Linked to NASA Earth Science Datasets

NASA's Earth Observing System Data and Information System (EOSDIS) began dataset Digital Object Identifier (DOI) registration in 2012. The number of dataset DOIs registered as of January of 2023 exceeds 11,000. As the research community becomes aware of the importance of sharing data through Open Science and optimizing data reuse through Findability, Accessibility, Interoperability, and Reuse (FAIR) data management principles, datasets are increasingly being cited in scientific publications. When datasets are cited explicitly by DOI within published works, automated methods can be developed for collecting these published works from a variety of bibliometric sources. The coverage of the sources varies, so each source can collect citations that are only available within it. Using major citation databases such as Scopus and Web of Science, the Google Scholar search engine, the CrossRef Open Citation Index, and the dataset DOI registry DataCite, we present an automated workflow for dataset citation collection. By harvesting citations automatically, a citation library is created explicitly linking EOSDIS datasets to publications that cite them. Using Zotero, a free and open-source citation manager, we demonstrate how to access and browse this library by the tags indicating bibliometric sources, dataset DOI, and the dataset archive center. We also demonstrate temporary trends in the number of publications harvested from bibliometric sources.

Infometrics↗

Goddard Earth Science Data and Information Center (GES DISC)

The GES DIS is one of 12 NASA Earth science data centers. The GES DISC vision is to enable researchers and educators maximize knowledge of the Earth by engaging in understanding their goals, and by leading the advancement of remote sensing information services in response to satisfying their goals. This presentation will describe the GES DISC approach, successes, challenges, and best practices.

data management↗

A strategy for Earth science from space in the 1980s. Part 1: Solid earth and oceans

The report develops a ten-year science strategy for investigating the solid earth and dynamics of world oceans from Earth orbit. The strategy begins from the premise that earth studies have proceeded to the point where further advances in understanding Earth processes must be based on a global perspective and that the U.S. is technically ready to begin a global study approach from Earth orbit. The major areas of study and their fundamental problems are identified. The strategy defines the primary science objectives to be addressed and the essential measurements and precision to achieve them.

Source record↗

Applications of the massively parallel machine, the MasPar MP-1, to Earth sciences

The computational workload of upcoming NASA science missions, especially the ground data processing for the Earth Observing System, is projected to be quite large (in the 50 to 100 gigaFLOPS range) and corespondingly very expensive to perform using conventional supercomputer systems. High performance, general purpose massively parallel computer systems such as the MasPar MP-1 are being investigated by NASA as a more cost effective alternative. Massively parallel systems are targeted for accelerated development and maturation by NASA's upcoming five-year High Performance Computing and Communications Program. A summary of the broad range of applications currently running on the MP-1 at NASA/Goddard are presented in this paper along with descriptions of the parallel algorithmic techniques employed in five applications that have bearing on Earth sciences.

Fischer, James R.↗

Earth Sciences Data and Information System (ESDIS) program planning and evaluation methodology development

An Earth Sciences Data and Information System (ESDIS) Project Management Plan (PMP) is prepared. An ESDIS Project Systems Engineering Management Plan (SEMP) consistent with the developed PMP is also prepared. ESDIS and related EOS program requirements developments, management and analysis processes are evaluated. Opportunities to improve the effectiveness of these processes and program/project responsiveness to requirements are identified. Overall ESDIS cost estimation processes are evaluated, and recommendations to improve cost estimating and modeling techniques are developed. ESDIS schedules and scheduling tools are evaluated. Risk assessment, risk mitigation strategies and approaches, and use of risk information in management decision-making are addressed.

Dickinson, William B.↗

NASA's Earth Science Enterprise: 1998 Education Catalog

This catalog presents a reference guide to NASA Earth science education programs and products. The topics include: 1) Student Support (Elementary and Secondary, Undergraduate and Graduate, Postgraduate, and Postdoctorate); 2) Teacher/Faculty Preparation and Enhancement; 3) Systemic Change; 4) Curriculum Support; and 5) Resources.

Source record↗

Goddard Earth Sciences and Technology Center (GEST)

This document summarizes the activities of the Goddard Earth Sciences and Technology Center (GEST), a consortium of scientists and engineers led by the University of Maryland, Baltimore County (UMBC), during the contract reporting period. Topics covered include: new programs, eligibility and selection criteria, Goddard Coastal Research Graduate Fellowship Program and staffing changes.

Source record↗

Close Approach Prediction Analysis of the Earth Science Constellation with the Fengyun-1C Debris

Routine satellite operations for the Earth Science Constellation (ESC) include collision risk assessment between members of the constellation and other orbiting space objects. Each day, close approach predictions are generated by a U.S. Department of Defense Joint Space Operations Center Orbital Safety Analyst using the high accuracy Space Object Catalog maintained by the Air Force's 1" Space Control Squadron. Prediction results and other ancillary data such as state vector information are sent to NASAJGoddard Space Flight Center's (GSFC's) Collision Risk Assessment analysis team for review. Collision analysis is performed and the GSFC team works with the ESC member missions to develop risk reduction strategies as necessary. This paper presents various close approach statistics for the ESC. The ESC missions have been affected by debris from the recent anti-satellite test which destroyed the Chinese Fengyun- 1 C satellite. The paper also presents the percentage of close approach events induced by the Fengyun-1C debris, and presents analysis results which predict the future effects on the ESC caused by this event. Specifically, the Fengyun-1C debris is propagated for twenty years using high-performance computing technology and close approach predictions are generated for the ESC. The percent increase in the total number of conjunction events is considered to be an estimate of the collision risk due to the Fengyun-1C break- UP.

Duncan, Matthew↗

Image Segmentation Analysis for NASA Earth Science Applications

NASA collects large volumes of imagery data from satellite-based Earth remote sensing sensors. Nearly all of the computerized image analysis of this data is performed pixel-by-pixel, in which an algorithm is applied directly to individual image pixels. While this analysis approach is satisfactory in many cases, it is usually not fully effective in extracting the full information content from the high spatial resolution image data that s now becoming increasingly available from these sensors. The field of object-based image analysis (OBIA) has arisen in recent years to address the need to move beyond pixel-based analysis. The Recursive Hierarchical Segmentation (RHSEG) software developed by the author is being used to facilitate moving from pixel-based image analysis to OBIA. The key unique aspect of RHSEG is that it tightly intertwines region growing segmentation, which produces spatially connected region objects, with region object classification, which groups sets of region objects together into region classes. No other practical, operational image segmentation approach has this tight integration of region growing object finding with region classification This integration is made possible by the recursive, divide-and-conquer implementation utilized by RHSEG, in which the input image data is recursively subdivided until the image data sections are small enough to successfully mitigat the combinatorial explosion caused by the need to compute the dissimilarity between each pair of image pixels. RHSEG's tight integration of region growing object finding and region classification is what enables the high spatial fidelity of the image segmentations produced by RHSEG. This presentation will provide an overview of the RHSEG algorithm and describe how it is currently being used to support OBIA or Earth Science applications such as snow/ice mapping and finding archaeological sites from remotely sensed data.

Tilton, James C.↗

Earth-Science Data Co-Locating Tool

This software is used to locate Earth-science satellite data and climate-model analysis outputs in space and time. This enables the direct comparison of any set of data with different spatial and temporal resolutions. It is written in three separate modules that are clearly separated for their functionality and interface with other modules. This enables a fast development of supporting any new data set. In this updated version of the tool, several new front ends are developed for new products. This software finds co-locatable data pairs for given sets of data products and creates new data products that share the same spatial and temporal coordinates. This facilitates the direct comparison between the two heterogeneous datasets and the comprehensive and synergistic use of the datasets.

Lee, Seungwon↗