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All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

System and method for attitude determination based on optical imaging

A method and apparatus is provide for receiving a first set of optical data from a first field of view and receiving a second set of optical data from a second field of view. A portion of the first set of optical data is communicated and a portion of the second set of optical data is reflected, both toward an optical combiner. The optical combiner then focuses the portions onto the image plane such that information at the image plane that is associated with the first and second fields of view is received by an optical detector and used to determine an attitude characteristic.

Junkins, John L.↗
NASA NTRS2010

Dual Oculometer System for Aviation Crew Assessment

Oculometers, eye trackers, are a useful tool for ascertaining the manner in which pilots deploy visual attentional resources, and for assessing the degree to which stimuli capture attention exogenously. The aim of this effort was to obtain oculometer data comfortably, unobtrusively, reliably and with good spatial resolution over a standard B757-like flight deck for both individuals in a crew. We chose to implement two remote, 5-camera Smarteye systems which were crafted for this purpose to operate harmoniously. We present here the results of validation exercises, lessons learned for improving data quality, and initial thoughts on the use of paired oculometer data to reflect crew workload, coordination, and situation awareness, in the aggregate.

Latorella, Kara↗
NASA NTRS2011

Landsat-7 ETM+: 12 years On-Orbit Reflective-Band Radiometric Performance

The Landsat-7 ETM+ sensor has been operating on orbit for more than 12 years and characterizations of its performance have been ongoing over this period. In general, the radiometric performance of the instrument has been remarkably stable: (1) Noise performance has degraded by 2% or less overall, with a few detectors displaying step changes in noise of 2% or less, (2) Coherent noise frequencies and magnitudes have generally been stable, though the within-scan amplitude variation of the 20kHz noise in bands 1 and 8 disappeared with the failure of the scan line corrector and a new similar frequency noise (now about 18kHz) has appeared in two detectors in band 5 and increased in magnitude with time, (3) Bias stability has been better than 0.25 DN out of a normal value of 15 DN in high gain, (4) Relative gains, the differences in response between the detectors in the band, have generally changed by 0.1% or less over the mission, with the exception of a few detectors with a step response change of 1% or less and (5) Gain stability averaged across all detectors in a band, which is related to the stability of the absolute calibration, has been more stable than the techniques used to measure it. Due to the inability to confirm changes in the gain (beyond a few detectors that have been corrected back to the band average), ETM+ reflective band data continues to be calibrated with the pre-launch measured gains. In the worst case some bands may have changed as much as 2% in uncompensated absolute calibration over the 12 years.

Markham, Brian L.↗
NASA NTRS2016

Characterization of Evidence for Human System Risk Assessment

Understanding the kinds of evidence available and using the best evidence to answer a question is critical to evidenced-based decision-making, and it requires synthesis of evidence from a variety of sources. Categorization of human system risks in spaceflight, in particular, focuses on how well the integration and interpretation of all available evidence informs the risk statement that describes the relationship between spaceflight hazards and an outcome of interest. A mature understanding and categorization of these risks requires: 1) sufficient characterization of risk, 2) sufficient knowledge to determine an acceptable level of risk (i.e., a standard), 3) development of mitigations to meet the acceptable level of risk, and 4) identification of factors affecting generalizability of the evidence to different design reference missions. In the medical research community, evidence is often ranked by increasing confidence in findings gleaned from observational and experimental research (e.g., "levels of evidence"). However, an approach based solely on aspects of experimental design is problematic in assessing human system risks for spaceflight. For spaceflight, the unique challenges and opportunities include: (1) The independent variables in most evidence are the hazards of spaceflight, such as space radiation or low gravity, which cannot be entirely duplicated in terrestrial (Earth-based) analogs, (2) Evidence is drawn from multiple sources including medical and mission operations, Lifetime Surveillance of Astronaut Health (LSAH), spaceflight research (LSDA), and relevant environmental & terrestrial databases, (3) Risk metrics based primarily on LSAH data are typically derived from available prevalence or incidence data, which may limit rigorous interpretation, (4) The timeframe for obtaining adequate spaceflight sample size (n) is very long, given the small population, (5) Randomized controlled trials are unattainable in spaceflight, (6) Collection of personal and environmental data on the astronaut population may create opportunities for advanced analytics and human-environment modeling that goes beyond that achieved in isolated experimental designs; and (7) Translation of relevant research to operations is a complex, transdisciplinary enterprise in which the approach must apply across the physical, biological, behavioral, and social sciences. The approach to synthesizing evidence must address both source and fidelity of data, and reflect the most general attributes of quality of evidence in science and engineering: reliability and validity. The authors are developing a two-factor approach which includes the various kinds of evidence required to understand risks and for the integrated interpretation of all evidence that is essential to develop standards and countermeasures. A unified framework for aggregating and assessing different kinds of evidence provides a consistent, traceable, evidence-based decision-making process to translate research to operations in an environment where engineers, scientists, physicians, and managers all engage in analyzing the trade space of vehicle design, standards, requirements and solutions for spaceflight.

Steinberg, S. L.↗
NASA NTRS2018

Exploration of Backscatter Methods for Wireless Avionics

This report describes and characterizes the low-power Jeeva Passive Radio systems, including Wanscatter (passive Chirp Spread Spectrum) and Passive Wi-Fi, with respect to their applicability to wireless avionics. The Wireless Avionics Intra-Communications (WAIC) objectives document, ITU-R M.2197, describes a number of applications of wireless avionics, and lists requirements specifications for each. Additionally, it describes models for compartments and areas of aircraft or vehicles in which wireless avionics would be applied. This exploratory study attempts to map Jeeva's Passive Radio technology to those scenarios outlined in the ITU-R M.2197 operational objectives document, and determine the areas and applications for which it is most suitable. Jeeva Passive Radio operates differently than conventional radios. In a conventional radio, a sensor-connected radio node must actively emit a signal in order to communicate. In a Jeeva Passive Radio system, that node instead simply reflects radio frequency energy which is emitted by another nearby device (called the Companion), which can be "plugged in" or otherwise has access to more power. Using reflections, a data packet can be generated and interpreted by a standard receiver. This method of communication inherently uses less energy, resulting in the potential for far lower power consumption and thus far longer battery life. Overall, 68.4% of use cases described by the ITU-R M.2197 operational objectives document were found to be addressable by Jeeva's Passive Radio systems (26 addressable of 38 total), with 26 of those best addressable by Wanscatter and three found to be best addressable with passive Wi-Fi. See Section 4.2 for a detailed breakdown of application suitability. The most fitting types of applications were in the LI (Low-rate Indoors) and LO (Low-rate Outdoors) categories, where lower rates were acceptable and thus Wanscatter could be applied and its much better uplink sensitivity leveraged. Jeeva has identified the Wanscatter (Chirp Spread Spectrum) system as likely holding the most promise for applications such as those outlined in the ITU-R M.2197 operational objectives document. We recommend that Wanscatter be a technology considered for adoption in wireless avionics.

Backscatter↗
NASA NTRS2022

Idaho Wildfires II: Assessing the Relationship Between Drought Indicators and Wildfire Risk to Enhance Hazard Modeling and Inform Mitigation Planning

The western United States has experienced twenty years of increased and prolonged drought which have exacerbated wildfire hazards. These jeopardize population centers through increased risks to ecosystem services, local economies, and livelihoods. The Idaho Office of Emergency Management, Water Resources, and Department of Lands are seeking methods to dynamically monitor these conditions and update models that inform hazard mitigation planning and resource allocation. Towards this, these agencies partnered with NASA DEVELOP to produce drought-enhanced wildfire hazard models. Part of a two-term project, the two teams revised the state’s static wildfire hazard model with refined data layers and remotely-sensed data to reflect dynamic ecosystem responses to drought conditions and wildfire potential. Our team distinguished between rangeland and forestland ecosystems, and investigated relationships between drought metrics and vegetation condition using TerrSet Earth Trends Modeler. This analysis determined that total precipitation at a 5-month lag interval (r 2 = 0.72) along with the Evaporative Stress Index (r 2 = 0.69); and precipitation at a 5-month interval (r 2 = 0.42) were important drivers in rangeland and forestland, respectively. These driver variables were incorporated into a temporally dynamic wildfire hazard map. Our team used linear regression to correlate hazard ratings with wildfire frequency. For the year 2020, neither the enhanced hazard model (p < 0.10, r 2 = 0.01) nor the state’s static model (p < 0.05, r 2 = 0.03) were strongly correlated with actual wildfire frequency as they expressed an inverse relationship between wildfire hazard and frequency. This suggests wildfire occurrence is complex and not necessarily driven by the variables used.

Wildfire↗
NASA NTRS2023

A GeoNEX-Based High-Spatiotemporal-Resolution Product of Land Surface Downward Shortwave Radiation and Photosynthetically Active Radiation

Surface downward shortwave radiation (DSR) and photosynthetically active radiation (PAR) play critical roles in the Earth’s surface processes. As the main inputs of various ecological, hydrological, carbon, and solar photovoltaic models, increasing requirements for high-spatiotemporal-resolution DSR and PAR es- timation with high accuracy have been observed in recent years. However, few existing products satisfy all of these requirements. This study employed a well-established physical-based lookup table (LUT) approach to the GeoNEX gridded top-of-atmosphere bidirectional reflectance factor data acquired by the Advanced Hi- mawari Imager (AHI) and Advanced Baseline Imager (ABI) sensors. It produced a data product of DSR and PAR over both AHI and ABI coverage at an hourly temporal step with a 1 km spatial resolution. GeoNEX DSR data were validated over 63 stations, and GeoNEX PAR data were validated over 27 stations. The vali- dation showed that the new GeoNEX DSR and PAR products have accuracy higher than other existing prod- ucts, with root mean square error (RMSE) of hourly GeoNEX DSR achieving 74.3Wm−2 (18.0%), daily DSR estimation achieving 18.0 W m−2 (9.2 %), hourly GeoNEX PAR achieving 34.9 W m−2 (19.6 %), and daily PAR achieving 9.5 W m−2 (10.5 %). The study also demonstrated the application of the high-spatiotemporal- resolution GeoNEX DSR product in investigating the spatial heterogeneity and temporal variability of surface solar radiation. The data product can be freely accessed through the NASA Advanced Supercomputing Division GeoNEX data portal: https://data.nas.nasa.gov/geonex/geonexdata/GOES16/GEONEX-L2/DSR-PAR/ (last ac- cess: 12 March 2023) and https://data.nas.nasa.gov/geonex/geonexdata/HIMAWARI8/GEONEX-L2/DSR-PAR/ (last access: 12 March 2023) (https://doi.org/10.5281/zenodo.7023863; Wang and Li, 2022).

Surface downward shortwave radiation (DSR)↗
DOE OSTI2018

Recognizing Amazonian tree species in the field using bark tissues spectra

The identification of tree species in the field is often a subjective process and misidentifications cause many problems for forest management in the Amazon Forest. Near infrared spectra from dried leaves of herbarium specimens are able to distinguish species in tropical forests. However, tools to improve species identification directly in the field are needed. In this study, we tested whether spectral reflectance of bark tissues (rhytidome and phloem) collected with a portable spectrometer in the field can be used for the discrimination of tree species. Spectral data was collected for 254 trees of 8 families, 10 genera and 11 species from terra firme forests in Central Amazon with an ASD field spectrometer. Data consisted of reflectance values within 350–2500 nm wavelengths. We compared the rate of correct species recognition for different datasets using linear discriminant models. The rate of correct species assignment using this technique was 98% when using spectra from the inner bark (phloem) and 94% with outer bark (rhytidome) spectra. We suggest that the application of this technique can improve the quality of species identification directly during field inventories, fostering better forest management practices.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Producing Science-Ready Radar Datasets for the Retrieval of Forest Structure Parameters from Backscatter: Correcting for Terrain Topography and Changes in Vegetation Reflectivity

Radar backscatter data contain both geometric and radiometric distortions due to underlying topography and the radar viewing geometry. Our objective is to develop a radiometric correction algorithm specific to the UAVSAR system configuration that would improve retrieval of forest structure parameters. UAVSAR is an airborne Lband radar capable of repeat?pass interferometry producing images with a spatial resolution of 5m. It is characterized by an electronically steerable antenna to compensate for aircraft attitude. Thus, the computation of viewing angles (i.e. look, incidence and projection) must include aircraft attitude angles (i.e. yaw, pitch and roll) in addition to the antenna steering angle. In this presentation, we address two components of radiometric correction: area projection and vegetation reflectivity. The first correction is applied by normalization of the radar backscatter by the local ground area illuminated by the radar beam. The second is a correction due to changes in vegetation reflectivity with viewing geometry.

polarimetry↗
NASA NTRS1982

Association of spectral development patterns with development stages of corn

Association is made between the development stages of corn as defined by Hanway and the temporal-spectral development pattern of corn in a transformed data space derived from Landsat-MSS band reflectance values, using field-collected reflectance and associated data. Results indicate that the spectral vegetation index used (a reflectance equivalent of Tasseled Cap Greenness) reaches a maximum well before the stage at which corn is expected to achieve its peak leaf area index. Possible physiological and canopy geometry related causes for this and other results are presented.

Crist, E. P.↗
NASA NTRS1985

Surface characteristics of Venus derived from Pioneer Venus altimetry, roughness, and reflectivity measurements

Pioneer Venus data sets for global topography, surface roughness, and reflectivity are analyzed, and the geological significance of some of the distinctive surface types is locally calibrated by examining high-resolution images from the Venera lander spacecraft and the Arecibo Observatory. Regional rock and bedrock surfaces are found to cover the majority of the planet. The relatively smooth rock and bedrock surfaces probably represent lava flows. Porous and unconsolidated fine materials cover less than about 27 percent of the surface. The distribution of soil surfaces indicate that they are the result of local weathering and small amounts of lateral transport. Several hypotheses for the origin of the high-dielectric materials which cover a small portion of the surface are discussed.

Head, J. W., III↗
NASA NTRS1989

Surface reflectance factor retrieval from Thematic Mapper data

Based on the absolute radiometric calibration of the TM and the use of a radiative transfer program for atmospheric correction, ground reflectances were retrieved for several fields of crops and bare soil in TM bands 1-4 for six TM scenes acquired over a 12-month period. These reflectances were compared to those measured using ground-based and low-altitude, aircraft-mounted radiometers. When, for four TM acquisitions, the comparison was made between areas that had been carefully selected for their high uniformity, the reflectance factors agreed to + or - 0.01 over the reflectance range 0.02-0.55. When the comparison was made for two of the above acquisitions and two others on different dates, for larger areas not carefully selected to be of uniform reflectance, the reflectance factors agreed to + or - 0.02 (1 sigma RMS), over same reflectance range.

Holm, Ronald G.↗
DOE OSTI2024

Canopy reflectance spectroscopy, thermal images and digital photographs, San Lorenzo, Panama, 2020

This data package comprises reflectance spectra, thermal and visible images of top of canopy tree crowns at the San Lorenzo Protected Area, Panama. Data were collected using the Smithsonian Tropical Research Institute (STRI) canopy access crane, from positions approximately 4 m above the target tree canopy. Canopy reflectance spectra were collected using an HR-1024i full range spectroradiometer (350–2500 nm, SVC, Poughkeepsie, NY, USA) with a 14-degree lens. Canopy thermal images were captured using an 8640-S series USB Calibrated Thermal Camera (ICI International, Beaumont, TX, USA). Visible images were collected using an AW130 waterproof/shockproof camera (Nikon, Tokyo, Japan). Data were collected on three days, on 16 canopies from 10 tree species. On both January 30, 2020, and February 27, 2020, we collected spectra at three time points, in the morning, midday, and afternoon. On February 18, 2020, we collected data around midday only. Due to technical issues, digital photography was collected on 30 January only. This dataset includes unprocessed data only, including spectral data (.sig or .sed), thermal images (.i16), and photographs (.raw), a detailed method description (.pdf), species information (.csv) and ESS-DIVE file-level metadata (FLMD.csv).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

Using NASA Techniques to Atmospherically Correct AWiFS Data for Carbon Sequestration Studies

Carbon dioxide is a greenhouse gas emitted in a number of ways, including the burning of fossil fuels and the conversion of forest to agriculture. Research has begun to quantify the ability of vegetative land cover and oceans to absorb and store carbon dioxide. The USDA (U.S. Department of Agriculture) Forest Service is currently evaluating a DSS (decision support system) developed by researchers at the NASA Ames Research Center called CASA-CQUEST (Carnegie-Ames-Stanford Approach-Carbon Query and Evaluation Support Tools). CASA-CQUEST is capable of estimating levels of carbon sequestration based on different land cover types and of predicting the effects of land use change on atmospheric carbon amounts to assist land use management decisions. The CASA-CQUEST DSS currently uses land cover data acquired from MODIS (the Moderate Resolution Imaging Spectroradiometer), and the CASA-CQUEST project team is involved in several projects that use moderate-resolution land cover data derived from Landsat surface reflectance. Landsat offers higher spatial resolution than MODIS, allowing for increased ability to detect land use changes and forest disturbance. However, because of the rate at which changes occur and the fact that disturbances can be hidden by regrowth, updated land cover classifications may be required before the launch of the Landsat Data Continuity Mission, and consistent classifications will be needed after that time. This candidate solution investigates the potential of using NASA atmospheric correction techniques to produce science-quality surface reflectance data from the Indian Remote Sensing Advanced Wide-Field Sensor on the RESOURCESAT-1 mission to produce land cover classification maps for the CASA-CQUEST DSS.

Holekamp, Kara L.↗
NASA NTRS1983

Stratigraphy and structural evolution of southern Mare Serenitatis - A reinterpretation based on Apollo Lunar Sounder Experiment data

Two subsurface reflecting horizons have been detected by the Apollo Lunar Sounder Experiment (ALSE) in the southern Mare Serenitatis which appear to be regolith layers more than 2 m thick, and are correlated with major stratigraphic boundaries in the southeastern Mare Serenitatis. The present stratigraphic boundaries in the southeastern Mare Serenitatis. The present analysis implies that the lower horizon represents the interface between the earliest mare unit and the modified Serenitatis basin material below. The depth of volcanic fill within Serenitatis is highly variable, with an average thickness of mare basalts under the ALSE ground track of 1.6 km. Comparisons with the Orientale basin topography suggests that a major increaae in load thickness could occur a few km basinward of the innermost extent of the traverse. The history of volcanic infilling of Mare Serenitatis was characterized by three major episodes of volcanism.

Sharpton, V. L.↗
NASA NTRS2004

Rapid Chemometric Filtering of Spectral Data

A method of rapid, programmable filtering of spectral transmittance, reflectance, or fluorescence data to measure the concentrations of chemical species has been proposed. By programmable is meant that a variety of spectral analyses can readily be performed and modified in software, firmware, and/or electronic hardware, without need to change optical filters or other optical hardware of the associated spectrometers. The method is intended to enable real-time identification of single or multiple target chemical species in applications that involve high-throughput screening of multiple samples. Examples of such applications include (but are not limited to) combinatorial chemistry, flow cytometry, bead assays, testing drugs, remote sensing, and identification of targets. The basic concept of the proposed method is to perform real-time crosscorrelations of a measured spectrum with one or more analytical function(s) of wavelength that could be, for example, the known spectra of target species. Assuming that measured spectral intensities are proportional to concentrations of target species plus background spectral intensities, then after subtraction of background levels, it should be possible to determine target species concentrations from cross-correlation values. Of course, the problem of determining the concentrations is more complex when spectra of different species overlap, but the problem can be solved by use of multiple analytical functions in combination with computational techniques that have been developed previously for analyses of this type. The method is applicable to the design and operation of a spectrometer in which spectrally dispersed light is measured by means of an active-pixel sensor (APS) array. The row or column dimension of such an array is generally chosen to be aligned along the spectral-dispersion dimension, so that each pixel intercepts light in a narrow spectral band centered on a wavelength that is a known function of the pixel position. The proposed method admits of two hardware implementations for computing cross-correlations in real time.

Beaman, Gregory↗
NASA NTRS1998

A New and Fast Method for Smoothing Spectral Imaging Data

The Airborne Visible Infrared Imaging Spectrometer (AVIRIS) acquires spectral imaging data covering the 0.4 - 2.5 micron wavelength range in 224 10-nm-wide channels from a NASA ER-2 aircraft at 20 km. More than half of the spectral region is affected by atmospheric gaseous absorption. Over the past decade, several techniques have been used to remove atmospheric effects from AVIRIS data for the derivation of surface reflectance spectra. An operational atmosphere removal algorithm (ATREM), which is based on theoretical modeling of atmospheric absorption and scattering effects, has been developed and updated for deriving surface reflectance spectra from AVIRIS data. Due to small errors in assumed wavelengths and errors in line parameters compiled on the HITRAN database, small spikes (particularly near the centers of the 0.94- and 1.14-micron water vapor bands) are present in this spectrum. Similar small spikes are systematically present in entire ATREM output cubes. These spikes have distracted geologists who are interested in studying surface mineral features. A method based on the "global" fitting of spectra with low order polynomials or other functions for removing these weak spikes has recently been developed by Boardman (this volume). In this paper, we describe another technique, which fits spectra "locally" based on cubic spline smoothing, for quick post processing of ATREM apparent reflectance spectra derived from AVIRIS data. Results from our analysis of AVIRIS data acquired over Cuprite mining district in Nevada in June of 1995 are given. Comparisons between our smoothed spectra and those derived with the empirical line method are presented.

Gao, Bo-Cai↗