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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Advanced Concepts, Technologies and Flight Experiments for NASA's Earth Science Enterprise

Over the last 25 years, NASA Langley Research Center (LaRC) has established a tradition of excellence in scientific research and leading-edge system developments, which have contributed to improved scientific understanding of our Earth system. Specifically, LaRC advances knowledge of atmospheric processes to enable proactive climate prediction and, in that role, develops first-of-a-kind atmospheric sensing capabilities that permit a variety of new measurements to be made within a constrained enterprise budget. These advances are enabled by the timely development and infusion of new, state-of-the-art (SOA), active and passive instrument and sensor technologies. In addition, LaRC's center-of-excellence in structures and materials is being applied to the technological challenges of reducing measurement system size, mass, and cost through the development and use of space-durable materials; lightweight, multi-functional structures; and large deployable/inflatable structures. NASA Langley is engaged in advancing these technologies across the full range of readiness levels from concept, to components, to prototypes, to flight experiments, and on to actual science mission infusion. The purpose of this paper is to describe current activities and capabilities, recent achievements, and future plans of the integrated science, engineering, and technology team at Langley Research Center who are working to enable the future of NASA's Earth Science Enterprise.

Meredith, Barry D.↗
NASA NTRS1995

Spaceborne GPS for Earth Science

With the recent completion of the Global Positioning System (GPS) constellation and lower cost spaceborne receivers GPS usage is expanding rapidly in the area of space flight projects. Several of these are discussed, such as precise orbit determination, Earth gravity model improvement, and other global geodesy enhancements; high resolution 2D/3D ionospheric imaging; and atmospheric limb sounding.

Global↗
NASA NTRS1994

Obtaining coincident image observations for Mission to Planet Earth science data return

One objective of the Mission to Planet Earth (MTPE) program involves comparing data from various instruments on multiple spacecraft to obtain a total picture of the Earth's systems. To correlate image data from instruments on different spacecraft, these spacecraft must be able to image the same location on the Earth at approximately the same time. Depending on the orbits of the spacecraft involved, complicated operational details must be considered to obtain such observations. If the spacecraft are in similar orbits, close formation flying or synchronization techniques may be used to assure coincident observations. If the orbits are dissimilar, the launch time of the second satellite may need to be restricted in order to align its orbit with that of the first satellite launched. This paper examines strategies for obtaining coincident observations for spacecraft in both similar and dissimilar orbits. Although these calculations may be performed easily for coplanar spacecraft, the non-coplanar case involves additional considerations which are incorporated into the algorithms presented herein.

Newman, Lauri Kraft↗
NASA NTRS2010

Public Participation in Earth Science from the ISS

The Gateway to Astronaut Photography of Earth (GAPE) is an online database (http://eol.jsc.nasa.gov) of terrestrial astronaut photography that enables the public to experience the astronaut s view from orbit. This database of imagery includes all NASA human-directed missions from the Mercury program of the early 1960 s to the current International Space Station (ISS). To date, the total number of images taken by astronauts is 1,025,333. Of the total, 621,316 images have been "cataloged" (image geographic center points determined and descriptive metadata added). The remaining imagery provides an opportunity for the citizen-scientist to become directly involved with NASA through cataloging of astronaut photography, while simultaneously experiencing the wonder and majesty of our home planet as seen by astronauts on board the ISS every day. We are currently developing a public cataloging interface for the GAPE website. When complete, the citizen-scientist will be able to access a selected subset of astronaut imagery. Each candidate will be required to pass a training tutorial in order to receive certification as a cataloger. The cataloger can then choose from a selection of images with basic metadata that is sorted by difficulty levels. Some guidance will be provided (template/pull down menus) for generation of geographic metadata required from the cataloger for each photograph. Each cataloger will also be able to view other contributions and further edit that metadata if they so choose. After the public inputs their metadata the images will be posted to an internal screening site. Images with similar geographic metadata and centerpoint coordinates from multiple catalogers will be reviewed by NASA JSC Crew Earth Observations (CEO) staff. Once reviewed and verified, the metadata will be entered into the GAPE database with the contributors identified by their chosen usernames as having cataloged the frame.

Willis, Kimberly J.↗
NASA NTRS2018

A Concept of Operations for Earth Science Data Archive and Distribution in the Cloud

Science data systems can enable more comprehensive Earth system research by evolving to take advantage of advances in commercial computer technology services. Since their inception twenty five years ago, NASA's Earth Observing System Data and Information System (EOSDIS) Distributed Active Archive Centers (DAACs) have periodically evolved to utilize new technology and expand research using the exponential growth and diversity of Earth observations. Recently, with the advent of a maturing commercial compute services industry and upcoming high data volume missions such as the Surface Water and Ocean Topography (SWOT) mission and the NASA-Indian Space Research Organization Synthetic Aperture Radar (NISAR) mission, options were explored and a decision made to utilize commercial compute and storage services. This paper presents an overview of the concept of operations under development for the DAACs in the Cloud. We highlight the goals and expected advantages of utilizing Cloud services. We outline EOSDIS operations tenets and driving principles. A high-level view of EOSDIS system of systems target architecture serves as context for describing principle interactions. Concepts for key DAAC system and EOSDIS enterprise functions characterize automated end-to-end operations but mark nominal check and recovery points. Concepts are presented for managing Cloud resources, including organizational roles and responsibilities of the NASA project and DAAC personnel. Scenarios we use to further distinguish between what the system will do and what configuration and controls operators will have. Examples include interactions with data providers and data consumers with both in-cloud and on-premise facilities.

Moses, John F.↗
NASA NTRSDate not supplied

Maximizing Earth Science Observations with Data Harmonization: Harmonized Landsat/Sentinel-2

In August 2021, NASA released science quality harmonized Landsat/Sentinel-2 products for both cloud-based access and direct download from the Land Processes Distributed Active Archive Center (LP DAAC). These 30-meter products, HLSS30 (Sentinel-2 component) and HLSL30 (Landsat component) are placed on the same grid and are generated and distributed fully in the cloud. Similarly, ESA is prototyping harmonized Landsat Sentinel-2 products at 10-meter resolution. The data production and science teams from NASA and ESA will present technical details on the data production system, data product status and availability, and the benefit of harmonizing instruments with similar sensing characteristics between the agencies.

Earth Science↗
NASA NTRS2016

International Earth Science Constellations (ESC) Introduction

This presentation will discuss NASA HQ perspective, current state of the mission, Landsat 7 and Terra exit plans, long term plans for all mission, CARA updates, Spring 2016 IAM series plans and current status, CCS future release plans, and results of covariance calculation meetings.

Afternoon Constellation↗
NASA NTRS2019

The Legacy and Future of the International Earth Science Constellation (ESC)

The most recent Decadal Survey placed high value on continuing constellation science. The ESC has evolved by seeing new missions joining and old missions retiring. Most recently, GCOM-W1, Landsat-8, and OCO-2 joined during 2012-2014. Landsat-9 is set to join in 2020. Each new mission provides new and improved suite of sensors. The new sensors also benefit both from the multitude of other existing on-orbit sensors as well as from the long-term cross-calibrated climate observations from the sensors that preceded them. At the same time, existing missions leave the constellation due to low fuel reserves or aging spacecraft subsystems. For example, CloudSat and CALIPSO left the ESC orbits in 2018, although they plan to continue making coordinated science observations at their new lower altitudes. This ESC evolution is expected to continue and this paper will discuss the opportunities for other new missions to join the ESC.

afternoon constellation↗
NASA NTRSDate not supplied

Agile Satellite Planning for Multi-Payload Observations in Earth Science Models

We present the planner methods and preliminary results for a new paradigm of earth observing systems based on coordinating science observations for a constellation of agile satellites which can quickly maneuver to change viewing angles. Each satellite has multiple heterogeneous instruments.

Satellite Constellation↗
NASA NTRS1994

Automatic cataloguing and characterization of Earth science data using SE-trees

In the future, NASA's Earth Observing System (EOS) platforms will produce enormous amounts of remote sensing image data that will be stored in the EOS Data Information System. For the past several years, the Intelligent Data Management group at Goddard's Information Science and Technology Office has been researching techniques for automatically cataloguing and characterizing image data (ADCC) from EOS into a distributed database. At the core of the approach, scientists will be able to retrieve data based upon the contents of the imagery. The ability to automatically classify imagery is key to the success of contents-based search. We report results from experiments applying a novel machine learning framework, based on Set-Enumeration (SE) trees, to the ADCC domain. We experiment with two images: one taken from the Blackhills region in South Dakota; and the other from the Washington DC area. In a classical machine learning experimentation approach, an image's pixels are randomly partitioned into training (i.e. including ground truth or survey data) and testing sets. The prediction model is built using the pixels in the training set, and its performance is estimated using the testing set. With the first Blackhills image, we perform various experiments achieving an accuracy level of 83.2 percent, compared to 72.7 percent using a Back Propagation Neural Network (BPNN) and 65.3 percent using a Gaussain Maximum Likelihood Classifier (GMLC). However, with the Washington DC image, we were only able to achieve 71.4 percent, compared with 67.7 percent reported for the BPNN model and 62.3 percent for the GMLC.

Rymon, Ron↗
NASA NTRS2017

Exploiting Dark Information Resources to Create New Value Added Services to Study Earth Science Phenomena

This paper presents two research applications exploiting unused metadata resources in novel ways to aid data discovery and exploration capabilities. The results based on the experiments are encouraging and each application has the potential to serve as a useful standalone component or service in a data system. There were also some interesting lessons learned while designing the two applications and these are presented next.

Earth Science Informatics↗
NASA NTRS2007

Understanding Local Structure Globally in Earth Science Remote Sensing Data Sets

Empirical probability distributions derived from the data are the signatures of physical processes generating the data. Distributions defined on different space-time windows can be compared and differences or changes can be attributed to physical processes. This presentation discusses on ways to reduce remote sensing data in a way that preserves information, focusing on the rate-distortion theory and using the entropy-constrained vector quantization algorithm.

massive data sets↗
NASA NTRS2007

Ikhana: A NASA Unmanned Aerial System Supporting Long-Duration Earth Science Missions

This viewgraph presentation reviews Ikhana's project goals: (1) Develop an airborne platform to conduct Earth observation and atmospheric sampling science missions both nationally and internationally, (2) develop and demonstrate technologies that improve the capability of UAVs to conduct science collection missions, (3) develop technologies that improve manned and unmanned aircraft systems, and (4) support important national UAV development activities. The criteria that guided the selection of the aircraft are listed. The payload areas on Ikhana are shown and the network that connects the systems are also reviewed. The data recorder is shown. Also the diagram of the Airborne Research Test System (ARTS) is reviewed. The Mobile Ground Control Station and the Mobile Ku SatCom Antenna are also shown and described.

Cobleigh, Brent R.↗