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At least 487 records · Page 27

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NASA NTRS1999

GPS Ocean Reflection Experiment on Spartan 251

It has recently been demonstrated that the GPS signal which has reflected from the ocean surface contains useful geophysical data from which the sea surface wind speed and other parameters can be extracted. This can be used for remote sensing, similar to present day use of radar altimeters or scatterometers, but with significantly smaller instrumentation because of the utilization of the existing GPS broadcast signal for illumination. Several campaigns of aircraft experimentation have been completed demonstrating this technique and reflected GPS data has been reliably collected from 25 km altitude on a balloon. However, there has not yet been a demonstration that the reflected GPS signal can be detected from orbit with sufficient signal to noise ratio (SNR) to make useful remote sensing measurements. A technology demonstration experiment was planned for a Space Shuttle flight in the late 2000 using the Spartan 251 recoverable carrier. This experiment would also have been the first flight validation of the PiVoT GPS receiver developed in house at the Goddard Space Flight Center. The "open-architecture" design of this receiver would allow the software modifications to be made which control code-correlator spacing to map out the shape of the reflected signal waveform, which is the most basic data product generated by this instrumentation. A moderate gain left-hand circularly polarized antenna, constructed from an array of off-the-shelf hemispherical antennas was to be used to give approximately 3 to 6 dB of additional gain. Preliminary SNR predictions have been done indicating that this antenna would offer sufficient gain to record waveform measurements. A system level description of the experiment instrumentation, including the receiver, antenna and data storage and retrieval will be given. The visibility of GPS reflections over the mission duration of several hours will be studied, including the effects of the limited beamwidth of the antenna. Spartan 251 has now been postponed with the earliest opportunity in the year 2002. The results of this study however, have been 2 used to further the define the requirements and expected performance of reflected GPS receivers in orbit. Several other space flight opportunities are being considered based upon this new information.

Garrison, James L↗

NASA NTRS1975

Investigation of remote sensing to detect near-surface groundwater on irrigated lands

The application of remote sensing techniques was studied for detecting areas with high water tables in irrigated agricultural lands. Aerial data were collected by the LANDSAT-1 satellite and aircraft over the Kansas/Bostwick Irrigation District in Republic and Jewell Counties, Kansas. LANDSAT-1 data for May 12 and August 10, 1973, and aircraft flights (midday and predawn) on August 10 and 11, 1973, and June 25 and 26, 1974, were obtained. Surface and water table contour maps and active observation well hydrographs were obtained from the Bureau of Reclamation for use in the analysis. Results of the study reveal that LANDSAT-1 data (May MSS band 6 and August MSS band 7) correlate significantly (0.01 level) with water table depth for 144 active observation wells located throughout the Kansas/Bostwick Irrigation District. However, a map of water table depths of less than 1.83 meters prepared from the LANDSAT-1 data did not compare favorably with a map of seeped lands of less than 1.22 m (4 feet) to the water table. Field evaluation of the map is necessary for a complete analysis. Analysis of three fields on a within or single-field basis for the 1973 LANDSAT-1 data also showed significant correlation results.

Ryland, D. W.↗

NASA NTRS1992

On the use of stochastic process-based methods for the analysis of hyperspectral data

Further development in remote sensing technology requires refinement of information system design aspects, i.e., the ability to specify precisely the data to collect and the means to extract increasing amounts of information from the increasingly rich and complex data stream created. One of the principal directions of advance is that data from much larger numbers of spectral bands can be collected, but with significantly increased signal-to-noise ratio. The theory of stochastic or random processes may be applied to the modeling of second-order variations. A multispectral data set with a large number of spectral bands is analyzed using standard pattern recognition techniques. The data were classified using first a single spectral feature, then two, and continuing on with greater and greater numbers of features. Three different classification schemes are used: a standard maximum likelihood Gaussian scheme; the same approach with the mean values of all classes adjusted to be the same; and the use of a minimum distance to means scheme such that mean differences are used.

Landgrebe, David A.↗

NASA NTRS1996

Assessment of Climate Variability of the Greenland Ice Sheet: Integration of In Situ and Satellite Data

The proposed research involves the application of multispectral satellite data in combination with ground truth measurements to monitor surface properties of the Greenland Ice Sheet which are essential for describing the energy and mass of the ice sheet. Several key components of the energy balance are parameterized using satellite data and in situ measurements. The analysis has been done for a 6 to 17 year time period in order to analyze the seasonal and interannual variations of the surface processes and the climatology. Our goal was to investigate to what accuracy and over what geographic areas large scale snow properties and radiative fluxes can be derived based upon a combination of available remote sensing and meteorological data sets. For the understanding of the surface processes a field program was designed to collect information on spectral albedo, specular reflectance, soot content, grain size and the physical properties of different snow types. Further, the radiative and turbulent fluxes at the ice/snow surface were monitored for the parameterization and interpretation of the satellite data. Highlights include AVHRR time series and surface based radiation measurements, passive microwave time series, and geodetic results from the ETH/CU camp.

Steffen, K.↗

NASA NTRS2020

Space Flight LiDARs, Navigation & Science Instrument Implementations: Lasers, Optoelectronics, Integrated Photonics, Fiber Optic Subsystems and Components

For the past 25 years, the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center's Photonics Group in the Engineering Directorate has been substantially contributing to the flight design, development, production, testing and integration of many science and navigational instruments. The Moon to Mars initiative will rely heavily upon utilizing commercial technologies for instrumentation with aggressive schedule deadlines. The group has an extensive background in screening, qualifying, development and integration of commercial components for spaceflight applications. By remaining adaptable and employing a rigorous approach to component and instrument development, they have forged and fostered relationships with industry partners. They have been willing to communicate lessons learned in packaging, part construction, materials selection, testing, and other facets of the design and production process critical to implementation for high-reliability systems. As a result, this successful collaboration with industry vendors and component suppliers has enabled a history of mission success from the Moon to Mars (and beyond) while balancing cost, schedule, and risk postures. In cases where no commercial components exist, the group works closely with other teams at Goddard Space Flight Center and other NASA field centers to fabricate and produce flight hardware for science, remote sensing, and navigation applications. Summarized here is the last ten years of instrumentation development lessons learned and data collected from the subsystems down to the optoelectronic component level.

Detectors↗

NASA NTRS1984

Remote detection of geobotanical anomalies associated with hydrocarbon microseepage using thematic mapper simulator (TMS) and airborne imaging spectrometer (AIS) data

An interpretation of TMS and AIS data sets collected from Lost River, West Virginia, are presented, along with a brief review of the supervised vegetation classification approach to vegetation mapping used at Lost River. A preliminary study of AIS data suggests that contiguous high-spectral resolution data from a very limited portion of the spectrum (1.2-1.5 micron) provide a greater discriminatory capability than do broad-band sensors such as the TMS covering of wider spectral range (0.45-2.35 microns).

Rock, B. N.↗

NASA NTRS2016

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters : Aerosols - Part 2

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

aerosol retrieval↗

NASA NTRS2017

Image Detective 2.0: Engaging Citizen Scientists with NASA Astronaut Photography

Image Detective 2.0 engages citizen scientists with NASA astronaut photography of the Earth obtained by crew members on the International Space Station (ISS). Engaged citizen scientists are helping to build a more comprehensive and searchable database by geolocating this imagery and contributing to new imagery collections. Image Detective 2.0 is the newest addition to the suite of citizen scientist projects available through CosmoQuest, an effort led by the Astronomical Society of the Pacific (ASP) and supported through a NASA Science Mission Directorate Cooperative Agreement Notice award. CosmoQuest hosts a number of citizen science projects enabling individuals from around the world to engage in authentic NASA science. Image Detective 2.0, an effort that focuses on imagery acquired by astronauts on the International Space Station, builds on work initiated in 2012 by scientists and education specialists at the NASA Johnson Space Center. Through the many lessons learned, Image Detective 2.0 enhances the original project by offering new and improved options for participation. Existing users, as well as new Image Detective participants joining through the CosmoQuest platform, gain first-hand experience working with astronaut photography and become more engaged with this valuable data being obtained from the International Space Station. Citizens around the world are captivated by astronauts living and working in space. As crew members have a unique vantage point from which to view our Earth, the Crew Earth Observations (CEO) online database, referred to as the Gateway to Astronaut Photography of Earth (https://eol.jsc.nasa.gov/), provides a means for crew members to share their unique views of our home planet from the ISS with the scientific community and the public. Astronaut photography supports multiple uses including scientific investigations, visualizations, education, and outreach. These astronaut images record how the planet is changing over time, from human-made changes like urban growth and agriculture, to natural features and landforms such as tropical cyclones, aurora, coastlines, volcanoes and more. This imagery provides researchers on Earth with data to understand the planet from the perspective of the ISS, and is a useful complement to other remotely sensed datasets collected from robotic satellite platforms.

Higgins, Melissa↗

NASA NTRS2013

Aerosol Remote Sensing from Space - Where We Stand, Where We're Heading

The MISR and MODIS instruments aboard the NASA Earth Observing System's Terra Satellite have been collecting data containing information about the state of Earth's atmosphere and surface for over eleven years. Among the retrieved quantities are amount and type of wildfire smoke, desert dust, volcanic effluent, urban and industrial pollution particles, and other aerosols. However, the broad scientific challenges of understanding aerosol impacts on climate and health place different, and very exacting demands on our measurement capabilities. And these data sets, though much more advanced in many respects than previous aerosol data records, are imperfect. In this presentation, I will summarize current understanding of MISR and MODIS aerosol product strengths and limitations, discuss how they relate to the bigger aerosol science questions we must address, and give my view of the way forward.

MISR↗

NASA NTRSDate not supplied

MPATH (Measuring Performance for Autonomy Teaming with Humans) Ground Control Station: Design Approach and Initial Usability Results

Envisioned future Advanced Air Mobility (AAM) operations will require a transition of aircraft command and control from onboard pilots to remote operators. The National Aeronautics and Space Administration (NASA) has developed a research ground control station (GCS) software called MPATH (Measuring Performance for Autonomy Teaming with Humans) to study the human factors of remote operators in a representative AAM environment, where small uncrewed aerial systems (sUAS; simulated or real) act as surrogates for larger AAM aircraft. A primary focus of the research being conducted with the MPATH GCS is scalability (i.e., one human managing multiple vehicles). MPATH has demonstrated to be a useful capability for human factors research and remote operations. Two initial usability studies and a multi-vehicle control assessment were recently conducted, and usability data and operator feedback were collected. Generally, participants rated MPATH high on usability and interface quality, whereas information quality was rated slightly lower. These results were supported by specific feedback. Several generalized GCS design recommendations are proposed based on the results and feedback from these flight activities. Future updates to MPATH will incorporate the proposed recommendations. In practice, these recommendations could be used by any GCS software designer or developer to promote usability and safety.

Advanced Air Mobility↗

NASA NTRS1975

Soil moisture detection from Skylab

An investigation was designed for the Skylab satellite to determine the feasibility of remote sensing of the soil moisture content of the surface from various microwave sensors. Skylab data for the experiment were collected during passes 5, 10, 16, and 38 across the two test sites selected in eastern Kansas and western Texas. Pass 38 covered both test sites giving five data sets for the analysis. As Skylab data were being taken the moisture content of the soil was sampled by ground crews for each 2.5 centimeter depth from the surface to 15 centimeters at interval of about six kilometers along two different routes along the test sites. This resulted in a total of 2250 soil moisture samples corresponding to different locations and six different depths. Skylab data were collected by passive microwave radiometers at wavelengths of 2.1 and 21 centimeters by the S193 and S194 microwave sensors. An active microwave system also collected scatterometer data at a wavelength of 2.1 centimeters. The analysis of microwave data has revealed that the longer wavelength L-Band passive radiometer gives the best correlation with soil moisture content of the upper 2.5 centimeter depth of soil.

Eagleman, J. R.↗

NASA NTRS1977

Remote beacon location from a single satellite pass

This paper describes the techniques and associated dedicated hardware utilized in locating remote beacons via satellites. Applications include those associated with a 'distress' situation or for monitoring the location of floating data collection platforms. Results obtained from experiments involving the NASA Nimbus-6 and the Amateur Satellite Corporation (AMSAT) OSCAR spacecrafts indicate position accuracies on the order of one and two kilometers are possible. The geographical location of a low power VHF transmitter is determined from Doppler data collected during a single satellite pass. A dedicated microcomputer utilizes an efficient algorithm to provide beacon position coordinates within a minute after the end of the satellite pass.

Lynn, J. J.↗

NASA NTRS1984

Geometry Software Common to All Experiments

All imaging, remote sensing, and in situ experiments require information about the geometry and location of observations. An alterntive to collecting geometry data with a supplementary experiment data record is proposed. The new method involves identifying the fundamental information, that is, the geometric state upon which geometry calculations are based, and maintaining or delivering these calculations in separate packages which are easily replaced when improved information is available. Implementation of this method in spacecraft navigation is discussed along with software system requirements.

Source record↗

NASA NTRS1990

Test images for the maximum entropy image restoration method

One of the major activities of any experimentalist is data analysis and reduction. In solar physics, remote observations are made of the sun in a variety of wavelengths and circumstances. In no case is the data collected free from the influence of the design and operation of the data gathering instrument as well as the ever present problem of noise. The presence of significant noise invalidates the simple inversion procedure regardless of the range of known correlation functions. The Maximum Entropy Method (MEM) attempts to perform this inversion by making minimal assumptions about the data. To provide a means of testing the MEM and characterizing its sensitivity to noise, choice of point spread function, type of data, etc., one would like to have test images of known characteristics that can represent the type of data being analyzed. A means of reconstructing these images is presented.

Mackey, James E.↗

NASA NTRS2007

Automating CapCom Using Mobile Agents and Robotic Assistants

Mobile Agents (MA) is an advanced Extra-Vehicular Activity (EVA) communications and computing system to increase astronaut self-reliance and safety, reducing dependence on continuous monitoring and advising from mission control on Earth. MA is voice controlled and provides information verbally to the astronauts through programs called "personal agents." The system partly automates the role of CapCom in Apollo-including monitoring and managing navigation, scheduling, equipment deployment, telemetry, health tracking, and scientific data collection. Data are stored automatically in a shared database in the habitat/vehicle and mirrored to a site accessible by a remote science team. The program has been developed iteratively in authentic work contexts, including six years of ethnographic observation of field geology. Analog field experiments in Utah enabled empirically discovering requirements and testing alternative technologies and protocols. We report on the 2004 system configuration, experiments, and results, in which an EVA robotic assistant (ERA) followed geologists approximately 150 m through a winding, narrow canyon. On voice command, the ERA took photographs and panoramas and was directed to serve as a relay on the wireless network.

Clancey, William J.↗

NASA NTRS2009

Winter Camp: A Blog from the Greenland Summit, Part II

An earlier issue presents the first half of the author's experience living and working at the National Science Foundation's (NSF) Greenland Summit Camp. The author is a remote-sensing glaciologist at NASA s Goddard Space Flight Center. She took measurements that will be used to validate data collected by NASA s Aqua, Terra, and Ice, Clouds, and land Elevation Satellite (ICESat) satellites with ground-truth measurements of the Greenland Ice Sheet she made at Summit Camp from November 2008-February 2009. This article presents excerpts from the second half of her stay and work at the Greenland Summit.

Koenig, Lora↗

NASA NTRS2009

Winter Camp: A Blog from the Greenland Summit

This article presents the first half of the author's experience living and working at the National Science Foundation's (NSF) Greenland Summit Camp. The author is a remote-sensing glaciologist at NASA's Goddard Space Flight Center. She took measurements that will be used to validate data collected by NASA s Aqua, Terra, and Ice, Clouds, and land Elevation Satellite (ICESat) satellites with ground-truth measurements of the Greenland Ice Sheet she made at Summit Camp from November 2008-February 2009. This article presents excerpts from the second half of her stay and work at the Greenland Summit. The second half of the story is presented in another issue of this journal

Koenig, Lora↗

NASA NTRS2019

Past and Future Operations Concepts of NASA's Earth Science Data and Information System

NASA committed to support the collection and distribution of Earth science data to study global change in the 1990's. A series of Earth science remote sensing satellites, the Earth Observing System (EOS), was to be the centerpiece. The concept for the science data system, the EOS Data and Information System (EOSDIS), created new challenges in the data processing of multiple satellite instrument observations for climate research and in the distribution of global-coverage remote sensor products to a large and growing science research community. EOSDIS was conceived to facilitate easy access to EOS science data for a wide heterogeneous national and international community of users. EOSDIS was to provide a spectrum of services designed for research scientists working on NASA focus areas but open to the general public and international science community. EOSDIS would give researchers tools and assistance in searching, selecting and acquiring data, allowing them to focus on Earth science climate research rather than complex product generation. Goals were to promote exchange of data and research results and expedite development of new geophysical algorithms. The system architecture had to accommodate a diversity of data types, data acquisition and product generation operations, data access requirements and different centers of science discipline expertise. Steps were taken early to make EOSDIS flexible by distributing responsibility for basic services. Many of the system operations concept decisions made in the 90s continued to this day. Once implemented, concepts such as the EOSDIS data model played a critical role developing effective data services, now a hallmark of EOSDIS. In other cases, EOSDIS architecture has evolved to enable more efficient operations, taking advantage of new technology and thereby shifting more resources on data services and less on operating and maintaining infrastructure. In looking to the future, EOSDIS may be able to take advantage of commercial compute environments for infrastructure and further enable large scale climate research. In this presentation, we will discuss key EOSDIS operations concepts from the 1990's, how they were implemented and evolved in the architecture, and look at concepts and architectural challenges for EOSDIS operations utilizing commercial cloud services.

Moses, John F.↗