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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

NASA plans for future earth resources missions

Development activities underway to improve LANDSAT sensors and observing systems are reported. Data cover high resolution imagery of surface temperatures for improving crop and other vegetation and soil classifications, and heat capacity mapping for recording surface temperatures at hours of maximum and minimum heating. Automatic identification and classification methods designed to extract information such as crop and forage acreages, amounts of water run-off, and types of land use directly from the satellite observations were also studied. A number of applications verification tests were conducted, particularly in the areas of crop and land use inventory and water run-off prediction, to demonstrate the direct transfer of space acquired information to end users.

Nordberg, W.↗
NASA NTRS1984

In-flight wobble identification for Galileo

To achieve in-flight wobble compensation for Galileo, wobble identification is implemented using star scanner data or automatic gain control (AGC) signal as measurement in all-spin mode. The star scanner provides spacecraft attitude in inertial space while the AGC signal provides the spacecraft pointing relative to earth. A linear observation model is defined for each sensor which is being applied to a Kalman Estimator. It can be shown from simulation that better result can be achieved using a combined set of data than any one sensor alone due to correlation reduction among error sources.

Lai, J. Y.↗
NASA NTRS1988

Automated cataloging and characterization of space-derived data

One of the most significant technical issues that NASA must address and resolve is the problem of managing the enormous amounts of scientific and engineering data that will be generated by the next generation of remote sensing systems such as the Hubble Space Telescope (HST) and the Earth Observing System (EOS). The amount of data these sensors are expected to produce will be orders of magnitude greater than NASA has ever experienced. Consequently new solutions must be developed for managing, accessing, and automatically inputting the data into a database in some expressive fashion that will provide a meaningful understanding and effective utilization of this data in a multidisciplinary environment. Presently, scientific data provided by satellites and other sources are processed, cataloged, and archived according to narrow mission or project-specific requirements with little regard to the semantics of the overall research. Scientists therefore lack knowledge of or access to potentially valuable data outside their own field. What is needed is an innovative approach that will allow collected data to be automatically cataloged, characterized, and managed in a domain-community. A concept and design approach that employs expert system-based knowledge controllers combined with advanced spatial database systems and graphical data structures is discussed.

Campbell, William J.↗
NASA NTRS1988

Automated cataloging and characterization of space-derived data

One of the most significant technical issues that NASA must address and resolve is the problem of managing the enormous amounts of scientific and engineering data that will be generated by the next generation of remote sensing systems such as the Hubble Space Telescope (HST) and the Earth Observing System (EOS). The amount of data these sensors are expected to produce will be orders of magnitude greater than NASA has ever experienced. Consequently, new solutions must be developed for managing, accessing, and automatically inputting the data into a database in some expressive fashion that will provide a meaningful understanding and effective utilization of this data in a multidisciplinary environment. Presently, scientific data provided by satellites and other sources are processed, cataloged, and archived according to narrow mission or project-specific requirements with little regard to the semantics of the overall research. Scientists therefore lack knowledge of or access to potentially valuable data outside their own field. What is needed is an innovative approach that will allow collected data to be automatically cataloged, characterized, and managed in a domain-community. A concept and design approach that employs expert system-based knowledge controllers combined with advanced spatial database systems and graphical data structures is discussed.

Campbell, William J.↗
NASA NTRS1988

Moderate resolution imaging spectrometer-nadir (MODIS-N) - Progress 1988

The paper describes progress made through 1987 in refining the required characteristics of the MODIS-N, which is one of two MODIS sensors being planned as a facility for the earth observing system. The MODIS-N will make it possible to observe new characteristics of the land and ocean surfaces and the troposphere at least once every three days over the entire globe for a decade following launch. Spatial resolutions of 1000 m or better are expected.

Salomonson, V. V.↗
NASA NTRS1990

Eos visible imagers

Some of the proposed Earth Observing System (Eos) optical imagers are examined. These imagers include: moderate resolution imaging spectrometer (MODIS); geoscience laser ranging system (GLRS); high resolution imaging spectrometer (HIRIS); the intermediate thermal infrared spectrometer (ITIR); multi-angle imaging spectrometer (MISR); earth observing scanning polarimeter (EOSP); and the lightening imaging sensor (LIS).

Barnes, W. L.↗
NASA NTRS1991

Results of calibrations of the NOAA-11 AVHRR made by reference to calibrated SPOT imagery at White Sands, N.M

The calibration method reported here makes use of the reflectances of several large, uniform areas determined from calibrated and atmospherically corrected SPOT Haute Resolution Visible (HRV) scenes of White Sands, New Mexico. These reflectances were used to predict the radiances in the first two channels of the NOAA-11 Advanced Very High Resolution Radiometer (AVHRR). The digital counts in the AVHRR image corresponding to these known reflectance areas were determined by the use of two image registration techniques. The plots of digital counts versus pixel radiance provided the calibration gains and offsets for the AVHRR. A reduction in the gains of 4 and 13 percent in channels 1 and 2 respectively was found during the period 1988-11-19 to 1990-6-21. An error budget is presented for the method and is extended to the case of cross-calibrating sensors on the same orbital platform in the Earth Observing System (EOS) era.

Nianzeng, Che↗
NASA NTRS2008

Global Test Range: Toward Airborne Sensor Webs

This viewgraph presentation reviews the planned global sensor network that will monitor the Earth's climate, and resources using airborne sensor systems. The vision is an intelligent, affordable Earth Observation System. Global Test Range is a lab developing trustworthy services for airborne instruments - a specialized Internet Service Provider. There is discussion of several current and planned missions.

Mace, Thomas H.↗
NASA NTRS2009

Volcano Monitor: Autonomous Triggering of In-Situ Sensors

In-situ sensors near volcanoes would be alerted by the Earth Observing-1 (EO-1) craft to take more frequent data readings. This project involves developing a sulfur-dioxide-sensing volcano monitor that will be able to transmit its readings through an Iridium modem.

Behar, Alberto↗
NASA NTRS2016

Using Remotely Sensed Data for Climate Change Mitigation and Adaptation: A Collaborative Effort Between the Climate Change Adaptation Science Investigators Workgroup (CASI), NASA Johnson Space Center, and Jacobs Technology

With ever changing landscapes and environmental conditions due to human induced climate change, adaptability is imperative for the long-term success of facilities and Federal agency missions. To mitigate the effects of climate change, indicators such as above-ground biomass change must be identified to establish a comprehensive monitoring effort. Researching the varying effects of climate change on ecosystems can provide a scientific framework that will help produce informative, strategic and tactical policies for environmental adaptation. As a proactive approach to climate change mitigation, NASA tasked the Climate Change Adaptation Science Investigators Workgroup (CASI) to provide climate change expertise and data to Center facility managers and planners in order to ensure sustainability based on predictive models and current research. Generation of historical datasets that will be used in an agency-wide effort to establish strategies for climate change mitigation and adaptation at NASA facilities is part of the CASI strategy. Using time series of historical remotely sensed data is well-established means of measuring change over time. CASI investigators have acquired multispectral and hyperspectral optical and LiDAR remotely sensed datasets from NASA Earth Observation Satellites (including the International Space Station), airborne sensors, and astronaut photography using hand held digital cameras to create a historical dataset for the Johnson Space Center, as well as the Houston and Galveston area. The raster imagery within each dataset has been georectified, and the multispectral and hyperspectral imagery has been atmospherically corrected. Using ArcGIS for Server, the CASI-Regional Remote Sensing data has been published as an image service, and can be visualized through a basic web mapping application. Future work will include a customized web mapping application created using a JavaScript Application Programming Interface (API), and inclusion of the CASI data for the NASA Johnson Space Center into a NASA-Wide GIS Institutional Portal.

Jagge, Amy↗
NASA NTRS2018

An Accurate Method for Correcting Spectral Convolution Errors in Intercalibration of Broadband and Hyperspectral Sensors

The intercalibration between a broadband and a hyperspectral satellite Earth observation system requires the convolution of the hyperspectral data with the spectral response functions (SRFs) of the corresponding broadband channels. There are two potential issues associated with the convolution procedure. First, the finite resolution of a hyperspectral spectrum, that is, the deviation from the highly accurate line-by-line monochromatic radiances, will contribute to convolution errors. The magnitude of the errors depends on the spectral resolution and the SRF shape of the hyperspectral instrument. This type of the convolution error has not been well recognized, and there is a lack of corresponding discussion in most published papers. Although it is small as compared with the instrument accuracy of existing hyperspectral sounders, the error is deemed to be signicant when it is compared with the stringent calibration requirement imposed by future climate missions like the Climate Absolute Radiance and Refractivity Observatory (CLARREO). Second, some broadband channels are insufficiently covered by the hyperspectral data, causing spectral gaps that lead to convolution errors. Although several methods have been developed to fill the spectral gaps and hence compensate for the second type of convolution error, the correction accuracy may still need improvement especially when a large spectral gap needs to be lled. This paper presents a methodology to accurately quantify and compensate for both types of convolution errors. This methodology utilizes the available hyperspectral information to correct the scene-dependent convolution errors due to either the limited spectral resolution or spectral gaps. We use simulations to characterize the intercalibration errors between the Moderate resolution Imaging Spectroradiometer (MODIS) and current operational infrared sounders. We demonstrate that convolution errors can be effectively removed to meet the highly accurate intersatellite calibration requirement proposed by the Climate Absolute Radiance and Refractivity Observatory. Our methodology is also validated using real satellite data for the intercalibration between Aqua MODIS and Aqua Atmospheric Infrared Sounders (AIRS). Our study demonstrates that the accurate characterization and correction for the convolution errors greatly reduces the scene-dependent and spectrally dependent errors, being critical to the consistency check between Infrared Atmospheric Sounding Interferometer (IASI) and AIRS using the double-difference method. The convolution correction also facilitates the evaluation for other intercalibration errors (e.g., the drift of MODIS SRFs). Our derived SRF shift values from MODIS-AIRS (after convolution error corrections) and from MODIS-IASI intercalibration are consistent with each other. We further extend the methodology to study the calibration of a broadband channel which is either completely or largely uncovered bya hyperspectral measurement.The large spectral gap-filling methodology is validated by demonstrating the accurate prediction of the MODIS radiance of band 29 using the Cross-track Infrared Sounder spectra, with the real IASI spectral data being used as the reference.

Correction Method↗
NASA NTRS2000

Optical Lightning Detection From Space

Since 1995 we have had one or more optical lightning sensors in low earth orbit (LEO) providing near continuous lightning observations of the earth. The resulting data sets have enabled scientists to study global lighting distributions and their variable. Diurnal, seasonal and interannual variabilities are clearly revealed. In addition, because of the exceptionally high detection efficiency of the optical sensing technique and the high spatial resolution, it is possible to study individual clouds and cloud system despite a viewing time that is often as short as 80 seconds. These case studies have demonstrated the importance of total lightning measurements in the study of severe weather. Results from these space-based lightning measurements will be presented as well as the next logical concept - optical observations from geostationary orbit (GEO). With a Lightning Mapper Sensor (LMS) in GEO, it will be possible to monitor severe weather on a continuous basis and to disseminate the data in less than 60 seconds.

Christian, Hugh J., Jr.↗
NASA NTRSDate not supplied

Using DSCOVR EPIC as a Transfer Radiometer to Scale Multiple VIIRS Sensors Over Tropical Earth Views

The NASA CERES project provides Energy Balanced and Filled (EBAF) product climate-quality observed TOA and computed surface fluxes to the climate community. The CERES instruments are on board the Terra, Aqua, Suomi-NPP, and NOAA-20 satellites. The CERES project radiometrically scales the MODIS and VIIRS imager visible channel radiances to the Aqua- MODIS reference to retrieve consistent imager cloud properties between sensors, which are used to retrieve cloud properties required for converting CERES radiance observations into fluxes. The NPP, NOAA-20, and the future NOAA-21 VIIRS imagers will be in the same sun- synchronous orbit but spaced equally apart, which means that no simultaneous nadir overpasses (SNO) may be used to inter-calibrate the VIIRS imagers to each one another. Currently, the CERES project uses Aqua-MODIS to radiometrically scale between VIIRS imagers. Once the Terra and Aqua satellites start drifting toward the terminator, Aqua-MODIS can no longer be utilized as the transfer radiometer between VIIRS sensors and there will be no SNOs in common between either MODIS and or VIIRS imagers. The DSCOVR satellite orbits the Lagrange-1 (L1) point about 1.5 million kilometers from Earth. The Earth Polychromatic Imaging Camera (EPIC) instrument on the Earth-facing side of DSCOVR takes images ranging from the UV to the NIR of the sunlit side of the Earth. While the EPIC sensor has no onboard calibration systems, multiple inter-calibration studies have indicated that the EPIC instrument response is radiometrically stable. The stability of the EPIC instrument allows it to be used as a transfer radiometer between all MODIS and VIIRS imagers and is especially suited for drifting orbits because EPIC imager frequently samples the Earth diurnally. The study will demonstrate the use of EPIC as a transfer radiometer to radiometrically scale the NPP and NOAA-20 VIIRS imagers. The scaling factors will be compared with the scaling factors using Aqua-MODIS as the transfer radiometer.

Conor Haney↗
NASA NTRS2001

Ocean Drifters Get the Facts

With the help of Small Business Innovation Research (SBIR) funding from NASA's Goddard Space Flight Center, of Greenbelt, Maryland, Clearwater Instrumentation, of Watertown, Massachusetts, created the ClearSat-Autonomous Drifting Ocean Station (ADOS). The multi-sensor array ocean drifting station was developed to support observations of Earth by NASA satellites. It is a low-cost device for gathering an assortment of data necessary to the integration of present and future satellite measurements of biological and physical processes. Clearwater Instrumentation developed its ADOS technology based on Goddard's Sea-viewing Wide Field-of-view Sensor (SeaWiFS) project, but on a scale that is practical for commercial use. ADOS is used for the in situ measuring of ocean surface layer properties such as ocean color, surface thermal structure, and surface winds. Thus far, multiple ADOS units have been sold to The Scripps Institution of Oceanography, where they are being applied in the field of academic science research. Fisheries can also benefit, because ADOS can locate prime cultivation conditions for this fast-growing industry.

Source record↗
NASA NTRS2019

A Neural Network Correction to the Scalar Approximation in Radiative Transfer

The next generation of advanced high-resolution sensors in geostationary orbit will gather detailed information for studying the Earth system. There is an increasing desire to perform observing system simulation experiments (OSSEs) for new sensors during the development phase of the mission in order to better leverage information content from the new and existing sensors. Forward radiative transfer calculations that simulate the observing characteristics of a new instrument are the first step to an OSSE, and they are computationally intensive. The scalar approximation to the radiative transfer equation, a simplification of the vector representation, can save considerable computational cost, but produces errors in top of the atmosphere (TOA) radiance as large as 10% due to neglecting polarization effects. This article presents an artificial neural network technique to correct scalar TOA radiance over both land and ocean surfaces to within 1% of vector-calculated radiance. A neural network was trained on a database of scalar-vector TOA radiance differences at a large range of solar and viewing angles for several thousand realistic atmospheric vertical profiles that were sampled from a high resolution (7 km) global atmospheric transport model. The profiles include Rayleigh scattering and aerosol scattering and absorption. Training and validation of the neural network was demonstrated for two wavelengths in the ultraviolet-visible (US-Vis) spectral range (354 nm and 670 nm). The significant computational savings accrued from using a scalar approximation plus neural network correction approach to simulating TOA radiance will make feasible hyperspectral forward simulations of high-resolution sensors on geostationary satellites, such as TEMPO, GOES-R, GEMS, and SENTINEL-4.

TOA↗
NASA NTRS1974

Modular design of the earth observatory satellite /EOS/

The next generation of earth observation satellites are planned to carry advanced optical and microwave sensors for application studies. Design concepts have evolved to a modular spacecraft systems approach which is compatible with Delta, Titan, and Space Shuttle launches, with in-flight Shuttle maintenance, and with Shuttle retrieval. Use of this modularized spacecraft for a variety of low-earth orbiting missions can provide high reliability at reduced costs.

Fischetti, T. L.↗
NASA NTRS2013

Quantifying Uncertainties in Land-Surface Microwave Emissivity Retrievals

Uncertainties in the retrievals of microwaveland-surface emissivities are quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including the Special Sensor Microwave Imager, the Tropical Rainfall Measuring Mission Microwave Imager, and the Advanced Microwave Scanning Radiometer for Earth Observing System, are studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land-surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors inthe retrievals. Generally, these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 1%-4% (3-12 K) over desert and 1%-7% (3-20 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.5%-2% (2-6 K). In particular, at 85.5/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are most likely caused by rain/cloud contamination, which can lead to random errors up to 10-17 K under the most severe conditions.

Land-Surface↗
NASA NTRS2026

Landsat Instrument Suite (LandIS) Sensor Design for the Landsat 10 Mission

Landsat 10 will be the upcoming mission in the 50+ year Landsat series of Earth observation platforms. The centerpiece of the observatory will be a super-spectral imager known as the Landsat Instrument Suite (LandIS). The sensor will feature 26 spectral channels from the visible through near-, short-wave, and thermal infrared wavelengths with spatial resolutions of 10, 20, and 60 meters on the ground, depending on the band. These enhancements over the legacy Landsat instruments will ensure data continuity with the existing archive and will expand upon the core Landsat capabilities to enable new applications in Earth science. After a competitive procurement, NASA selected the design submitted by the Raytheon Company for the LandIS instrument. The innovative Raytheon instrument concept utilizes an advanced whiskbroom architecture to fulfill the strict radiometric, spatial, and geometric image quality requirements demanded by the Landsat 10 mission and fits within restrictive mass, volume, and power constraints. The instrument will continue the Landsat directive to image all daylit land and near-shore water areas, along with select nighttime imaging. On-board calibration source data will ensure high radiometric and geometric accuracy and stability consistent with previous missions to enable continuity in data products available to users. This paper discusses the driving requirements for LandIS and provides a description of the chosen design and operations concept of the instrument.

Requirements↗