A program for the rapid screening of multivariate data from the earth sciences and remote sensing
Computer program for rapid screening of multivariate data from earth sciences and remote sensing
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Computer program for rapid screening of multivariate data from earth sciences and remote sensing
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.
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.
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.
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.
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.
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.
This will be presented at the Earth Science Constellation Mission Operations Working Group meeting June 13-15, 2017 to discuss EOS Aura.
The purpose of the workshop was to further explore and define the earth sciences requirements for the Information Sciences Experiment System (ISES), a proposed onboard data processor with real-time communications capability intended to support the Earth Observing System (Eos). A review of representative Eos instrument types is given and a preliminary set of real-time data needs has been established. An executive summary is included.
The following is a technical report of the progress made under Cooperative Agreement NCC5494, the Goddard Earth Sciences and Technology Center (GEST). The period covered by this report is October 1, 2001 through December 31, 2001. GEST is a consortium of scientists and engineers, led by the University of Maryland, Baltimore County (UMBC), to conduct scientific research in Earth and information sciences and related technologies in collaboration with the NASA Goddard Space Flight Center (GSFC). GEST was established through a cooperative agreement signed May 11, 2000, following a competitive procurement process initiated by GSFC.
It is suggested that the science requirements for passive geostationary microwave observations be met by near- and far-term sensors for each of two overlapping bands, with each band covering no more than a decade in frequency. The low-frequency band includes channels near 6, 10, 18, 22, 31 to 37, and possibly 50 to 60 GHz. The high-frequency band includes channels near 220 to 230, 183, 166, 118, 90 to 110, and possibly 50 to 60 and 31 to 37 GHz. The precise channel specifications will have to comply with international frequency allocations. The near-term goal is a high-frequency sensor based on a filled-aperture solid reflector antenna, which should rely on currently existing technology. The most critical issues for the near-term sensor are momentum compensation and the design of the feed assembly; these issues are coupled through the desired scan rate. The successful demonstration of the near-term (high-frequency) sensor will be essential for the continued development of far-term sensors satisfying the ideal science requirements. The far-term goal includes both a high-frequency sensor which meets the ideal science requirements, and a low-frequency sensor whose design will depend on advances in large antenna technology. The low-frequency (far-term) sensor might be based on one of several concepts: a deployable mesh reflector antenna of diameter at least 20 m, which shows promise for use at frequencies up to 30-GHz, a synthetic aperture interferometer of maximum baseline from 100 to 300 m, or a deployable phased-array bootlace lens, of diameter from 100 to 300 m. The first of these, a deployable mesh reflector antenna, will satisfy only the adequate spatial resolution requirements. The last two concepts meet the ideal spatial resolution science requirements, although they present significant structural and meteorological challenges.
Space science is science carried out in space. There is much that is exciting, but nothing mysterious about it. Space science calls upon physics, chemistry, astronomy, biosciences, and other scientific disciplines to attack some of the most important and challenging scientific problems of today. Among these problems are the investigation of the Earth and Sun, Moon and planets, stars and galaxies, and life in space from the vantage point provided by the orbiting satellite or the dep space probe.
This paper describes an experiment to prototype a new way of conducting science by applying networking and distributed computing technologies to an Earth Science application. A combination of satellite, wireless, and terrestrial networking provided geologists at a remote field site with interactive access to supercomputer facilities at two NASA centers, thus enabling them to validate and calibrate remotely sensed geological data in near-real time. This represents a fundamental shift in the way that Earth scientists analyze remotely sensed data. In this paper we describe the experiment and the network infrastructure that enabled it, analyze the data flow during the experiment, and discuss the scientific impact of the results.
The purpose of this workshop was to hold interactive discussions where providers, users, and other stakeholders could explore the convergence of three main elements in the rapidly developing world of technology: Big Data, Cloud Computing, and Analytics, [for earth science data].
New antenna technologies have unlocked a new class of missions using CubeSats for Earth Science or Deep Space operations. This class of small satellites have historically been mostly used as teaching tools allowing students to design and test small satellites and develop space experiments. With the rise of new game-changing antenna technologies, overcoming their small size and need for high gain, they can now be used beyond Low Earth Orbit (LEO). Over the past 5 years, technologists at the Jet Propulsion Laboratory have designed, tested and successfully flown these innovative Smallsat antennas, enabling new telecommunication and science achievements.
A users guide for teaching activities in planetary geology, and for physical and earth sciences is presented. The following topics are discussed: cratering; aeolian processes; planetary atmospheres, in particular the Coriolis Effect and storm systems; photogeologic mapping of other planets, Moon provinces and stratigraphy, planets in stereo, land form mapping of Moon, Mercury and Mars, and geologic features of Mars.
Functionality of a geostationary spacecraft to support Earth science regional process research is identified. Most regional process studies require high spatial and temporal resolution. These high temporal resolutions are on the order of 30 minutes and may be achievable with instruments positioned in a geostationary orbit. A complement of typical existing or near term instruments are identified to take advantage of this altitude. This set of instruments is listed, and the requirements these instruments impose on a spacecraft are discussed. A brief description of the geostationary spacecraft concepts which support these instruments is presented.
Viewgraphs on grid analysis and display system (GrADS): a practical tool for earth science visualization are presented. Topics covered include: GrADS design goals; data sets; and temperature profiles.