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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Radiometric Characterization of Hyperspectral Imagers using Multispectral Sensors

The Remote Sensing Group (RSG) at the University of Arizona has a long history of using ground-based test sites for the calibration of airborne and satellite based sensors. Often, ground-truth measurements at these test sites are not always successful due to weather and funding availability. Therefore, RSG has also automated ground instrument approaches and cross-calibration methods to verify the radiometric calibration of a sensor. The goal in the cross-calibration method is to transfer the calibration of a well-known sensor to that of a different sensor, This work studies the feasibility of determining the radiometric calibration of a hyperspectral imager using multispectral a imagery. The work relies on the Moderate Resolution Imaging Spectroradiometer (M0DIS) as a reference for the hyperspectral sensor Hyperion. Test sites used for comparisons are Railroad Valley in Nevada and a portion of the Libyan Desert in North Africa. Hyperion bands are compared to MODIS by band averaging Hyperion's high spectral resolution data with the relative spectral response of M0DlS. The results compare cross-calibration scenarios that differ in image acquisition coincidence, test site used for the calibration, and reference sensor. Cross-calibration results are presented that show agreement between the use of coincident and non-coincident image pairs within 2% in most brands as well as similar agreement between results that employ the different MODIS sensors as a reference.

McCorkel, Joel↗
NASA NTRSDate not supplied

Lunar Explorer Instrument for space biology Applications (LEIA): An overview of planned science concept of operations

Radiation and reduced gravity pose biological risks to crewed deep space exploration. To better understand deep space radiation biology, the LEIA mission will measure charged particles and fast neutrons as well as yeast growth, metabolic rate, and bioengineered production of carotenoids at the lunar surface. LEIA will be delivered to the south polar region of the Moon by the Commercial Lunar Payload Services (CLPS) program. The LEIA science concept of operations was developed to isolate radiation and partial gravity from other environmental conditions experienced by the payload. Due to CLPS integration requirements, there will be at least eight months from loading yeast into the payload until activation on the lunar surface. Replicate yeast strains will be loaded in a randomized complete block design to minimize batch differences in desiccation tolerance and positional effects in the microfluidics culture system. Temperature and relative humidity will be controlled throughout integration and flight to maintain yeast viability and to enable measurement of yeast growth parameters within the lunar surface operations timeframe, with the ground control matching environmental conditions where possible. LEIA is co-manifested with the European Space Agency’s PROSPECT mission, which will be operating a drill during yeast growth. Vibration translated through the lunar lander will be mitigated and quantified to account for potential impacts on LEIA optical measurements and yeast growth rate. Total space radiation dose, including the transit exposure from Earth to the Moon, will be measured to obtain more accurate charged particle and fast neutron dose rates on the lunar surface. These radiation data will also yield ground truth radiation dose experienced by the yeast during the mission. Quantifying these environmental factors impacting the LEIA payload will allow more accurate ground control experiments to better isolate the biological responses to radiation and reduced gravity at the lunar surface.

Lunar Surface Mission↗
NASA NTRS1973

Evaluation of ERTS data for certain hydrological uses

The author has identified the following significant results. Melting ice has been detected in Lake Erie by comparison of visible and near infrared differential reflectance. This melting condition is confirmed by meteorological ground truth data and concurrent NOAA-2 thermal infrared data. Using near-synchronous ERTS-1 data, it was possible to determine the approximate ground resolution of NOAA-2 very high resolution radiometer by comparing the smallest identifiable ice crack in the imagery and measuring the same crack on the ERTS-1 image. It was determined that photointerpretation and analysis of a single Lake Erie image can, under certain conditions, provide meaningful data on ice dynamics. ERTS-1 imagery is effective for icepack monitoring of the Great Lakes, but the sampling interval of 18 days imposes a severe limitation. Maps of the snow cover in the American River basin for 16 March 1973 have been prepared using all four bands.

Wiesnet, D. R.↗
NASA NTRS2008

Using AIRS and IASI Data to Evaluate Absolute Radiometric Accuracy and Stability for Climate Applications

The creation of multi-decadal data sets for climate research requires better than 100 mK absolute calibration accuracy for the full range of spectral temperatures encountered under global conditions. Validation that this accuracy is achieved by the operational hyperspectral sounders from polar orbit is facilitated by comparing data from two instruments. Extreme radiometric calibration stability is critical to allow a long time series of noisy, but presumably long-term accurate truth measurements to be used for the validation of absolute accuracy at the 100 mK level. We use the RTGSST in the tropical oceans as ground truth. The difference between the AIRS derived sst2616 and the RTGSST based on six years of data shows a systematic cold bias of about 250 mK, but better than 4 mK/year stability. The double difference between AIRS and the RTGSST and IASI and the RTGSST with less than one year of data already allows statements at the 100 mK absolute level. It shows a 60 mK difference between the AIRS and the IASI calibration at 2616 cm-(sup 1) and 300 K, with a statistically insignificant 20 mK shift in six months.

EOS Aqua↗
DOE OSTI2022

Numerical simulations of noisy quantum circuits for computational chemistry

The opportunities afforded by near-term quantum computers to calculate the ground-state properties of small molecules depend on the structure of the computational ansatz as well as the errors induced by device noise. Here we investigate the behavior of these noisy quantum circuits using numerical simulations to estimate the accuracy and fidelity of the prepared quantum states relative to the ground truth obtained by conventional means. We implement several different types of ansatz circuits derived from unitary coupled cluster theory for the purposes of estimating the ground-state energy of sodium hydride using the variational quantum eigensolver algorithm. We show how relative error in the energy and the fidelity scale with the levels of gate-based noise, the internuclear configuration, the ansatz circuit depth, and the parameter optimization methods.

36 MATERIALS SCIENCE↗
NASA NTRS1973

Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation

The author has identified the following significant results. Preliminary evaluation of autumnal phase ground truth data suggests that the sampling procedures at the Great Plains Corridor network test sites are adequate to show relatively small temporal changes in above-ground vegetation biomass and vegetation condition. Vegetation changes measured August through December, reflect grazing intensity and environmental conditions at the test sites. Preliminary analysis of black and white imagery suggests that detail in vegetation patterns is much greater than originally anticipated. A first look analysis of single band imagery and digital data at two locations shows that woodland, grassland, and cropland areas are easily delineated. Computer derived grey-scale maps from MSS digital data were shown to be useful in identifying the location of small fields and features of the natural and cultivated lands. Single band imagery and digital data are believed to have important application for synoptic land use mapping and inventory. Initial ratio analysis, using band 5 and 7 data, suggests the applicability in the greenness of a vegetative scene.

Rouse, J. W., Jr.↗
DOE OSTI2020

Image Collection Simulation Using High-Resolution Atmospheric Modeling

A new method is described for simulating the passive remote sensing image collection of ground targets that includes effects from atmospheric physics and dynamics at fine spatial and temporal scales. The innovation in this research is the process of combining a high-resolution weather model with image collection simulation to attempt to account for heterogeneous and high-resolution atmospheric effects on image products. The atmosphere was modeled on a 3D voxel grid by a Large-Eddy Simulation (LES) driven by forcing data constrained by local ground-based and air-based observations. The spatial scale of the atmospheric model (10–100 m) came closer than conventional weather forecast scales (10–100 km) to approaching the scale of typical commercial multispectral imagery (2 m). This approach was demonstrated through a ground truth experiment conducted at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. In this experiment, calibrated targets (colored spectral tarps) were placed on the ground, and the scene was imaged with WorldView-3 multispectral imagery at a resolution enabling the tarps to be visible in at least 9–12 image pixels. The image collection was simulated with Digital Imaging and Remote Sensing Image Generation (DIRSIG) software, using the 3D atmosphere from the LES model to generate a high-resolution cloud mask. The high-resolution atmospheric model-predicted cloud coverage was usually within 23% of the measured cloud cover. The simulated image products were comparable to the WorldView-3 satellite imagery in terms of the variations of cloud distributions and spectral properties of the ground targets in clear-sky regions, suggesting the potential utility of the proposed modeling framework in improving simulation capabilities, as well as testing and improving the operation of image collection processes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Soil moisture variation patterns observed in Hand County, South Dakota

Soil moisture data were taken during 1976 (April, June, October), 1977 (April, May, June), and 1978 (May, June, July) Hand County, South Dakota as part of the ground truth used in NASA's aircraft experiments to study the use of microwave radiometers for the remote sensing of soil moisture. The spatial variability observed on the ground during each of the sampling events was studied. The data reported are the mean gravimetric soil moisture contained in three surface horizon depths: 0 to 2.5, 0 to 5 and 0 to 10 cm. The overall moisture levels ranged from extremely dry conditions in June 1976 to very wet in May 1978, with a relatively even distribution of values within that range. It is indicated that well drained sites have to be partitioned from imperfectly drained areas when attempting to characterize the general moisture profile throughout an area of varying soil and cover type conditions. It is also found that the variability in moisture content is greatest in the 0 to 2.5 cm measurements and decreases as the measurements are integrated over a greater depth. It is also determined that the sampling intensity of 10 measurements per km is adequate to estimate the mean moisture with an uncertainty of + or - 3 percent under average moisture conditions in areas of moderate to good drainage.

Jones, E. B.↗
NASA NTRS2020

SMAP Validation Experiment 2019-2020 (SMAPVEX19/20): Detection of Soil Moisture Under Forest Canopy

The retrieval of soil moisture under forest canopy has long been an important goal for low frequency remote sensing. The NASA mission started a dedicated field experiment in May 2019 by deploying two temporary soil moisture networks in northeast US that cover two separate SMAP pixels with variable degree of forest cover. The measurements will run through 2020 and they will be augmented with two intensive observation periods (IOP). The first IOP will be conducted in June-July 2020 and the other one in October 2020. The IOPs will see deployment of the airborne PALS (Passive Active L-band sensor) instrument, which is similar to the SMAP instrument, and intensive manual measurements of soil moisture and vegetation. The measurements also include tower-based radiometer observations with ground truth measurements within the instrument footprint. The early results have shown that the SMAP measurement signal at L-band is sensitive to soil moisture changes observed on the ground.

Andreas Colliander↗
NASA NTRS2021

SMAP Validation Experiment 2019-2021 (SMAPVEX19-21): Detection of Soil Moisture Under Temperate Forest Canopy

The retrieval of soil moisture under forest canopy has long been an important goal for low frequency remote sensing. The NASA mission started a dedicated field experiment in May 2019 by deploying two temporary soil moisture networks in northeast US that cover two separate SMAP pixels with variable degree of forest cover. The measurements will be augmented with two intensive observation periods (IOP). The first IOP is planned for July and the other one for October. The IOPs will see deployment of the airborne PALS (Passive Active L-band sensor) instrument, which is similar to the SMAP instrument, and intensive manual measurements of soil moisture and vegetation. The measurements also include tower-based radiometer observations with ground truth measurements within the instrument footprint. The early results have shown that the SMAP measurement signal at L-band is sensitive to soil moisture changes observed on the ground.

Yueh, Simon H.↗
NASA NTRS1978

The Kenya rangeland ecological monitoring unit

The author has identified the following significant results. Methodology for aerial surveys and ground truth studies was developed, tested, and revised several times to produce reasonably firm methods of procedure. Computer programs were adapted or developed to analyze, store, and recall data from the ground and air monitoring surveys.

Stevens, W. E.↗
NASA NTRS1997

Retrieval of Soil Moisture and Roughness from the Polarimetric Radar Response

The main objective of this investigation was the characterization of soil moisture using imaging radars. In order to accomplish this task, a number of intermediate steps had to be undertaken. In this proposal, the theoretical, numerical, and experimental aspects of electromagnetic scattering from natural surfaces was considered with emphasis on remote sensing of soil moisture. In the general case, the microwave backscatter from natural surfaces is mainly influenced by three major factors: (1) the roughness statistics of the soil surface, (2) soil moisture content, and (3) soil surface cover. First the scattering problem from bare-soil surfaces was considered and a hybrid model that relates the radar backscattering coefficient to soil moisture and surface roughness was developed. This model is based on extensive experimental measurements of the radar polarimetric backscatter response of bare soil surfaces at microwave frequencies over a wide range of moisture conditions and roughness scales in conjunction with existing theoretical surface scattering models in limiting cases (small perturbation, physical optics, and geometrical optics models). Also a simple inversion algorithm capable of providing accurate estimates of soil moisture content and surface rms height from single-frequency multi-polarization radar observations was developed. The accuracy of the model and its inversion algorithm is demonstrated using independent data sets. Next the hybrid model for bare-soil surfaces is made fully polarimetric by incorporating the parameters of the co- and cross-polarized phase difference into the model. Experimental data in conjunction with numerical simulations are used to relate the soil moisture content and surface roughness to the phase difference statistics. For this purpose, a novel numerical scattering simulation for inhomogeneous dielectric random surfaces was developed. Finally the scattering problem of short vegetation cover above a rough soil surface was considered. A general scattering model for grass-blades of arbitrary cross section was developed and incorporated in a first order random media model. The vegetation model and the bare-soil model are combined and the accuracy of the combined model is evaluated against experimental observations from a wheat field over the entire growing season. A complete set of ground-truth data and polarimetric backscatter data were collected. Also an inversion algorithm for estimating soil moisture and surface roughness from multi-polarized multi-frequency observations of vegetation-covered ground is developed.

Sarabandi, Kamal↗
NASA NTRS1974

Contribution of space platforms to a ground and airborne remote-sensing programme over active Italian volcanoes

ERTS-1 imagery of the volcanic areas of southern Italy was used primarily for the evaluation of space platform capabilties in the domains of regional geology, soil and rock-type classification and, more generally, to study the environment of active volcanoes. The test sites were selected and equipped primarily to monitor thermal emission, but ground truth data was also collected in other domains (reflectance of rocks, soils and vegetation). The test areas were overflown with a two channel thermal scanner, while a thermo camera was used on the ground to monitor the hot spots. The primary goal of this survey was to plot the changes in thermal emission with time in the framework of a research program for the surveillance of active volcanoes. However, another task was an evaluation of emissivity changes by comparing the outputs of the two thermal channels. These results were compared with the reflectance changes observed on multispectral ERTS-1 imagery.

Cassinis, R.↗
NASA NTRS1977

Use of Landsat multispectral imagery in estimating snow areal extent and snow water content cost-effectively

Landsat color composites are used in conjunction with a limited amount of aerial survey data and ground-truth measurements in order to estimate snow areal extent and snow water content. The snow water content estimations are based on the inexpensive Landsat data and the much more expensively obtained information on ground snow courses. A cost-effectiveness analysis of the procedures showed the expenses involved in obtaining confidence intervals of 80, 90, 95 and 99% for the estimates.

Khorram, S.↗
NASA NTRS2018

Volatiles Loss from Water Bearing Regolith Simulant at Lunar Environments

Permanently shadowed craters at the lunar poles contain water, ~5 wt% according to LCROSS. Interest in water for ISRU applications. Desire to 'ground truth' water using surface prospecting; e.g. Resource Prospector (RP) & RESOLVE. How to access subsurface water resources and accurately measure quantity; Excavation operations and exposure to lunar environment may affect the results A series a ground based dirty thermal vacuum tests are being conducted to better understand the subsurface sampling operations: Sample removal and transfer, Volatiles loss during sampling operations, Concept of operations, Instrumentation. This presentation covers: The capabilities of the VF-13 Thermal Vacuum Chamber (Tvac). The Resource Prospector TVAC hardware. The summary and results of 5 years of RP volatiles tests; 43 viable samples

In-situ Resource Utilization↗
NASA NTRS2017

Validation of High-Resolution MAIAC Aerosol Product over South America

Multiangle Implementation of Atmospheric Correction (MAIAC) is a new Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm that combines time series approach and image processing to derive surface reflectance and atmosphere products, such as aerosol optical depth (AOD) and columnar water vapor (CWV). The quality assessment of MAIAC AOD at 1 km resolution is still lacking across South America. In the present study, critical assessment of MAIAC AOD(sub 550) was performed using ground-truth data from 19 Aerosol Robotic Network (AERONET) sites over South America. Additionally, we validated the MAIAC CWV retrievals using the same AERONET sites. In general, MAIAC AOD Terra/Aqua retrievals show high agreement with ground-based measurements, with a correlation coefficient (R) close to unity (R(sub Terra):0.956 and R(sub Aqua):0.949). MAIAC accuracy depends on the surface properties and comparisons revealed high confidence retrievals over cropland, forest, savanna, and grassland covers, where more than 2/3 (approximately 66%) of retrievals are within the expected error (EE = +/-(0.05 + 0.05 × AOD)) and R exceeding 0.86. However, AOD retrievals over bright surfaces show lower correlation than those over vegetated areas. Both MAIAC Terra and Aqua retrievals are similarly comparable to AERONET AOD over the MODIS lifetime (small bias offset approximately 0.006). Additionally, MAIAC CWV presents quantitative information with R approximatley 0.97 and more than 70% of retrievals within error (+/-15%). Nonetheless, the time series validation shows an upward bias trend in CWV Terra retrievals and systematic negative bias for CWV Aqua. These results contribute to a comprehensive evaluation of MAIAC AOD retrievals as a new atmospheric product for future aerosol studies over South America.

Martins, V. S.↗
NASA NTRS1997

Advanced Algorithms and High-Performance Testbed for Large-Scale Site Characterization and Subsurface Target Detecting Using Airborne Ground Penetrating SAR

A team of US Army Corps of Engineers, Omaha District and Engineering and Support Center, Huntsville, let Propulsion Laboratory (JPL), Stanford Research Institute (SRI), and Montgomery Watson is currently in the process of planning and conducting the largest ever survey at the Former Buckley Field (60,000 acres), in Colorado, by using SRI airborne, ground penetrating, Synthetic Aperture Radar (SAR). The purpose of this survey is the detection of surface and subsurface Unexploded Ordnance (UXO) and in a broader sense the site characterization for identification of contaminated as well as clear areas. In preparation for such a large-scale survey, JPL has been developing advanced algorithms and a high-performance restbed for processing of massive amount of expected SAR data from this site. Two key requirements of this project are the accuracy (in terms of UXO detection) and speed of SAR data processing. The first key feature of this testbed is a large degree of automation and a minimum degree of the need for human perception in the processing to achieve an acceptable processing rate of several hundred acres per day. For accurate UXO detection, novel algorithms have been developed and implemented. These algorithms analyze dual polarized (HH and VV) SAR data. They are based on the correlation of HH and VV SAR data and involve a rather large set of parameters for accurate detection of UXO. For each specific site, this set of parameters can be optimized by using ground truth data (i.e., known surface and subsurface UXOs). In this paper, we discuss these algorithms and their successful application for detection of surface and subsurface anti-tank mines by using a data set from Yuma proving Ground, A7, acquired by SRI SAR.

Fijany, Amir↗
NASA NTRS2016

Regolith Volatile Recovery at Simulated Lunar Environments

Lunar Polar Volatiles: Permanently shadowed craters at the lunar poles contain water, 5 wt according to LCROSS. Interest in water for ISRU applications. Desire to ground truth water using surface prospecting e.g. Resource Prospector and RESOLVE. How to access subsurface water resources and accurately measure quantity. Excavation operations and exposure to lunar environment may affect the results. Volatile capture tests: A series a ground based dirty thermal vacuum tests are being conducted to better understand the subsurface sampling operations. Sample removal and transfer. Volatiles loss during sampling operations. Concept of operations, Instrumentation. This presentation is a progress report on volatiles capture results from these tests with lunar polar drill prototype hardware.

thermal vacuum tests↗