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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

ICESat-2 Photon Classification: Finding Signal Photons in the ATL03 Geolocated Photon Data Product

ICESat-2 carries NASA's next-generation laser altimeter, ATLAS, (Advanced Topographic Laser Altimeter System), designed to measure changes in ice sheet height, sea ice freeboard, and vegetation canopy height. ATLAS contains a photon-counting lidar which transmits green (532-nm) pulses at 10kHz. Each pulse is split into 3 pairs of beams (one strong and one weak). Approximately 1014 photons per pulse travel from ATLAS through the atmosphere to reflect off the Earth's surface. Some return back into the ATLAS telescope where they are recorded. Photons from sunlight and instrument noise at the same wavelength are also recorded. The flight software time tags all photons within a 500m to 6 km range window and generates histograms. Using the histograms, it selects a telemetry window which varies from 20m over flat surfaces to hundreds of meters over rougher terrain. ATL03 contains the time, height (relative to the WGS-84 ellipsoid), latitude and longitude of every photon within the telemetry window. The basic challenge is to determine which of these photons were reflected off the surface. We have developed an algorithm that identifies these signal photons and assigns a confidence level (low, medium, or high) to each signal photon based on the signal to noise ratio. We present an overview of the signal identification algorithm and show the results on actual ICESat-2 data over ice sheet, sea ice, vegetated, and water surfaces. Higher level ATLAS products work with aggregations of the photons in order to determine the ellipsoidal height of the Earth, canopy height and structure, and other quantities of geophysical interest.

Remote Sensing↗
NASA NTRS2016

Considering Combined or Separated Roughness and Vegetation Effects in Soil Moisture Retrievals

For more than six years, the Soil Moisture and Ocean Salinity (SMOS) mission has provided multi angular and full-polarization brightness temperature (TB) measurements at L-band. Geophysical products such as soil moisture (SM) and vegetation optical depth at nadir (tau(sub nad)) are retrieved by an operational algorithm using TB observations at different angles of incidence and polarizations. However, the quality of the retrievals depends on several surface effects, such as vegetation, soil roughness and texture, etc. In the microwave forward emission model used in the retrievals (L-band Microwave Emission Model, L-MEB),soil roughness is modeled with a semi-empirical equation using four main parameters (Q(sub r), H(sub r), N(sub rp), with p = H or V polarizations). At present, these parameters are calibrated with data provided by airborne studies and in situ measurements made at a local scale that is not necessarily representative of the large SMOS footprints (43 km on average) at global scale. In this study, we evaluate the impact of the calibrated values of N(sub rp) and H(sub r) on the SM and tau(sub nad) retrievals based on SMOS TB measurements (SMOS Level 3 product) over the Soil Climate Analysis Network (SCAN) network located in North America over five years (2011-2015). In this study, Qr was set equal to zero and we assumed that N(sub rH)= N(sub rV). The retrievals were performed by varying N(sub rp) from −1 to 2 by steps of 1 and H(sub r) from 0 to 0.6 by steps of 0.1. At satellite scale, the results show that combining vegetation and roughness effects in a single parameter provides the best results in terms of soil moisture retrievals, as evaluated against the in situ SM data. Even though our retrieval approach was very simplified, as we did not account for pixel heterogeneity, the accuracy we obtained in the SM retrievals was almost systematically better than those of the Level 3 product. Improved results were also obtained in terms of optical depth retrievals. These new results may have key consequences in terms of calibration of roughness effects within the algorithms of the SMOS (ESA) and the SMAP (NASA) space missions.

full-polarization↗
NASA NTRS2014

Global and Time-Resolved Monitoring of Crop Photosynthesis with Chlorophyll Fluorescence

Photosynthesis is the process by which plants harvest sunlight to produce sugars from carbon dioxide and water. It is the primary source of energy for all life on Earth; hence it is important to understand how this process responds to climate change and human impact. However, model-based estimates of gross primary production (GPP, output from photosynthesis) are highly uncertain, in particular over heavily managed agricultural areas. Recent advances in spectroscopy enable the space-based monitoring of sun-induced chlorophyll fluorescence (SIF) from terrestrial plants. Here we demonstrate that spaceborne SIF retrievals provide a direct measure of the GPP of cropland and grassland ecosystems. Such a strong link with crop photosynthesis is not evident for traditional remotely sensed vegetation indices, nor for more complex carbon cycle models. We use SIF observations to provide a global perspective on agricultural productivity. Our SIF-based crop GPP estimates are 50-75% higher than results from state-of-the-art carbon cycle models over, for example, the US Corn Belt and the Indo-Gangetic Plain, implying that current models severely underestimate the role of management. Our results indicate that SIF data can help us improve our global models for more accurate projections of agricultural productivity and climate impact on crop yields. Extension of our approach to other ecosystems, along with increased observational capabilities for SIF in the near future, holds the prospect of reducing uncertainties in the modeling of the current and future carbon cycle.

fluorescence↗
NASA NTRS2015

Coastal and Inland Aquatic Data Products for the Hyperspectral Infrared Imager (HyspIRI)

The HyspIRI Aquatic Studies Group (HASG) has developed a conceptual list of data products for the HyspIRI mission to support aquatic remote sensing of coastal and inland waters. These data products were based on mission capabilities, characteristics, and expected performance. The topic of coastal and inland water remote sensing is very broad. Thus, this report focuses on aquatic data products to keep the scope of this document manageable. The HyspIRI mission requirements already include the global production of surface reflectance and temperature. Atmospheric correction and surface temperature algorithms, which are critical to aquatic remote sensing, are covered in other mission documents. Hence, these algorithms and their products were not evaluated in this report. In addition, terrestrial products (e.g., land use land cover, dune vegetation, and beach replenishment) were not considered. It is recognized that coastal studies are inherently interdisciplinary across aquatic and terrestrial disciplines. However, products supporting the latter are expected to already be evaluated by other components of the mission. The coastal and inland water data products that were identified by the HASG, covered six major environmental and ecological areas for scientific research and applications: wetlands, shoreline processes, the water surface, the water column, bathymetry and benthic cover types. Accordingly, each candidate product was evaluated for feasibility based on the HyspIRI mission characteristics and whether it was unique and relevant to the HyspIRI science objectives.

Infrared↗
NASA NTRSDate not supplied

Oregon Wildfires: Integrating ECOSTRESS to Map & Analyze Vegetation Moisture for Wildfire Modeling

Wildfire season in the western USA is starting earlier and gaining in intensity. The Bootleg Fire in Southern Oregon began on July 6th, 2021, and burned over 1675 km2 before it was fully contained on August 15th, 2021. Evapotranspiration (ET) is one indicator of vegetation moisture and there is interest in using high-resolution ET products from ECOsystem and Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) in future wildfire modeling. In partnership with the Pacific Northwest National Laboratory and US Forest Service, the team examined ECOSTRESS ET for the two years before the Bootleg Fire and assessed the relationship between ET, topography, and vegetation. Remotely sensed data from Shuttle Radar Topography Mission (SRTM) and Global Ecosystem Dynamics Investigation (GEDI) along with ancillary data from the National Land Cover Database (NLCD) and Landscape Fire Resource Management Planning Tools (LANDFIRE) were incorporated. The team examined data in relation to soil burn severity from the Burned Area Emergency Response (BAER) program. From ET median composites for April 1st – July 5th, 2021 and 2019, the Bootleg Fire area showed a 7 mm/day decrease in ET and a relative 75% decrease in ET between 2019 and 2021. Approximately 6% of the Bootleg Fire area was identified as having a high soil burn severity and these areas were found predominantly in the evergreen forest land cover class and northward facing slopes with a mean ET decrease of 3 mm/day between 2019 and 2021. The team also analyzed ECOSTRESS Water Use Efficiency products as an additional vegetation moisture indicator of pre-fire conditions in the study area. The end products will allow the partners to assess if higher resolution vegetation moisture datasets from ECOSTRESS will improve wildfire modeling for other susceptible areas.

Brenna Hatch↗
NASA NTRS1985

North American vegetation patterns observed with the NOAA-7 advanced very high resolution radiometer

Spectral vegetation index measurements derived from remotely sensed observations show great promise as a means to improve knowledge of land vegetation patterns. The daily, global observations acquired by the advanced very high resolution radiometer, a sensor on the current series of U.S. National Oceanic and Atmospheric Administration meteorological satellites, may be particularly well suited for global studies of vegetation. Preliminary results from analysis of North American observations, extending from April to November 1982, show that the vegetation index patterns observed correspond to the known seasonality of North American natural and cultivated vegetation. Integration of the observations over the growing season produced measurements that are related to net primary productivity patterns of the major North American natural vegetation formations. Regions of intense cultivation were observed as anomalous areas in the integrated growing season measurements. Significant information on seasonality, annual extent and interannual variability of vegetation photosynthetic activity at continental and global scales can be derived from these satellite observations.

Goward, S. N.↗
NASA NTRS2004

Use of EO-1 Hyperion Data for Inter-Sensor Calibration of Vegetation Indices

Numerous satellite sensor systems useful in terrestrial Earth observation and monitoring have recently been launched and their derived products are increasingly being used in regional and global vegetation studies. The increasing availability of multiple sensors offer much opportunity for vegetation studies aimed at understanding the terrestrial carbon cycle, climate change, and land cover conversions. Potential applications include improved multiresolution characterization of the surface (scaling); improved optical-geometric characterization of vegetation canopies; improved assessments of surface phenology and ecosystem seasonal dynamics; and improved maintenance of long-term, inter-annual, time series data records. The Landsat series of sensors represent one group of sensors that have produced a long-term, archived data set of the Earth s surface, at fine resolution and since 1972, capable of being processed into useful information for global change studies (Hall et al., 1991).

Huete, Alfredo↗
NASA NTRS2021

The NASA AfriSAR Campaign: Airborne SAR and Lidar Measurements of Tropical Forest Structure and Biomass in Support of Current and Future Space Missions

In 2015 and 2016, the AfriSAR campaign was carried out as a collaborative effort among international space and National Park agencies (ESA, NASA, ONERA, DLR, ANPN and AGEOS) in support of the upcoming ESA BIOMASS, NASA-ISRO Synthetic Aperture Radar (NISAR) and NASA Global Ecosystem Dynamics Initiative (GEDI) missions. The NASA contribution to the campaign was conducted in 2016 with the NASA LVIS (Land Vegetation and Ice Sensor) Lidar, the NASA L-band UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar). A central motivation for the AfriSAR deployment was the common AGBD estimation requirement for the three future spaceborne missions, the lack of sufficient airborne and ground calibration data covering the full range of ABGD in tropical forest systems, and the intercomparison and fusion of the technologies. During the campaign, over 7000 km2 of waveform Lidar data from LVIS and 30000 km2 of UAVSAR data were collected over 10 key sites and transects. In addition, field measurements of forest structure and biomass were collected in sixteen 1 hectare sized plots. The campaign produced gridded Lidar canopy structure products, gridded aboveground biomass and associated uncertainties, Lidar based vegetation canopy cover profile products, Polarimetric Interferometric SAR and Tomographic SAR products and field measurements. Our results showcase the types of data products and scientific results expected from the spaceborne Lidar and SAR missions; we also expect that the AfriSAR campaign data will facilitate further analysis and use of waveform Lidar and multiple baseline polarimetric SAR datasets for carbon cycle, biodiversity, water resources and more applications by the greater scientific community.

AfriSAR↗
NASA NTRS1986

Canopy reflectance modeling in a tropical wooded grassland

A study area was selected in West Africa in order to establish a relationship between rainfall and grassland productivity, and also to provide ground measurements and support for the GIMMS investigation of the use of AVHRR vegetation index data for monitoring grassland biomass and productivity. Field data collection, image and collateral data acquisition, model development, and data analysis and processing are briefly discussed.

Simonett, D.↗
NASA NTRS1985

1985 International Geoscience and Remote Sensing Symposium (IGARSS '85), University of Massachusetts, Amherst, October 7-9, 1985, Digest. Volumes 1 & 2

The present conference on remote sensing instrumentation considers topics in water resources research, planetary remote sensing and mathematical geophysics, sea ice behavior in view of the Cold Regions Research and Engineering Laboratories pond measurements, Shuttle Imaging Radar-B (SIR-B) system performance and calibration results, geological applications of remote sensing, and microwave scattering from vegetation. Further attention is given to atmospheric probing with lasers, image processing for remote sensing, forest inventory and condition assessment, atmospheric remote sensing, SIR-B geological results, the reflectance, emission, and scattering characteristics of vegetation, sea ice sensing, multipolarization SAR results, the theoretical modeling of surfaces and volumes, crop condition assessment and productivity estimates, and SIR-B results for vegetation cover. Also considered are the microwave remote sensing of soil moisture, advanced sensors, advanced information extraction, wind and wave remote observations, results from the ESA Remote Sensing satellite, large area crop and land cover statistics, SIR-B results for directional ocean wave spectra, seasonal snow cover, ice sheets, and lake ice, fundamental research in terrain remote sensing, image classification methods, vegetation stress detection, remote sensing of coastal processes, SAR systems and calibration, electromagnetic geophysical methods and signal processing, image processing techniques, and SAR internal wave measurements.

Carver, K. R.↗
NASA NTRSDate not supplied

Role of Antecedent Soil Moisture and Vegetation Stress in Lightning-Initiated Wildfires

Lightning-caused wildfires are a small percentage of all wildfire events within the Conterminous U.S. (CONUS), but they account for over 56% of the acreage burned. The atmospheric conditions favoring wildfire and rapid growth are well understood: large dewpoint depressions, unstable planetary boundary layer, strong winds, etc. However, antecedent land surface conditions affecting dead and live fuel moisture is more difficult to quantify. This study examines over 20 years of antecedent land surface, vegetation stress, and wildfire characteristic data associated with nearly 77,000 lightning-initiated wildfires from the U.S. Forest Service Wildfire Database. We will invoke two in-house databases generated by the NASA Short-term Prediction Research and Transition (SPoRT) Center: an observations-driven, climatological run of the Noah land surface model within the NASA Land Information System (i.e., SPoRT-LIS) to depict soil moisture deficits / anomalies, and a satellite-constrained Evaporative Stress Index (ESI) product to denote areas of stressed vegetation. We will mine these datasets associated with lightning-caused (and null) events to determine important relationships, distributions, and delineators that correspond to elevated threat areas for lightning-initiated wildfires.

Wildfire↗
NASA NTRS1992

Effects of management and topography on the radiometric response of a tallgrass prairie

Bidirectional reflectance measurements are obtained for grazed, burned ungrazed, and unburned ungrazed tallgrass prairie in eastern Kansas. Observations are also made on experimental plots where vegetation height and biomass were manipulated by mowing. While productivity of grazed or mowed sites was either equal to or greater than that on ungrazed or unmowed sites, individual or cumulative normalized difference vegetation index values tended to be positively correlated with biomass, not productivity.

Turner, C. L.↗
NASA NTRS1988

Comparison of simulation modeling and satellite techniques for monitoring ecological processes

In 1985 improvements were made in the world climatic data base for modeling and predictive mapping; in individual process models and the overall carbon-balance models; and in the interface software for mapping the simulation results. Statistical analysis of the data base was begun. In 1986 mapping was shifted to NASA-Goddard. The initial approach involving pattern comparisons was modified to a more statistical approach. A major accomplishment was the expansion and improvement of a global data base of measurements of biomass and primary production, to complement the simulation data. The main accomplishments during 1987 included: production of a master tape with all environmental and satellite data and model results for the 1600 sites; development of a complete mapping system used for the initial color maps comparing annual and monthly patterns of Normalized Difference Vegetation Index (NDVI), actual evapotranspiration, net primary productivity, gross primary productivity, and net ecosystem production; collection of more biosphere measurements for eventual improvement of the biological models; and development of some initial monthly models for primary productivity, based on satellite data.

Box, Elgene O.↗
NASA NTRS1990

Seed sprout production: Consumables and a foundation for higher plant growth in space

Seed sprouts can be produced as a source of fresh vegetable materials and as higher plant seedlings in space. Sprout production was undertaken to evaluate the mass accumulations possible, the technologies needed, and the reliability of the overall process. Baseline experiments corroborated the utility of sprout production protocols for a variety of seed types. The automated delivery of saturated humidity effectively supplants labor intensive manual soaking techniques. Automated humidification also lend itself to modest centrifugal sprout growth environments. A small amount of ultraviolet radiation effectively suppressed bacterial and fungal contamination, and the sprouts were suitable for consumption.

Day, Michelle↗
NASA NTRS1993

The use of a vegetation index for assessment of the urban heat island effect

A vegetation index and radiative surface temperature were derived from NOAA-11 Advanced Very High Resolution Radiometer (AVHRR) data for the Seattle, WA region from 28 June through 4 July 1991. The vegetation index and surface temperature values were computed for locations of weather observation stations within the region and compared to observed minimum air temperatures. These comparisons were used to evaluate the use of AVHRR data to assess the influence of the urban environment on observed minimum air temperatures (the urban heat island effect). AVHRR derived normalized difference vegetation index (NDVI) and radiant surface temperature data from a one week composite product were both related significantly to observed minimum temperatures, however, the vegetation index accounted for a greater amount of the spatial variation observed in mean minimum temperatures. The difference in the NDVI between urban and rural regions appears to be an indicator of the difference in surface properties (i.e., evaporation and heat storage capacity) between the two environments that are responsible for differences in urban and rural minimum temperatures.

Gallo, K. P.↗
NASA NTRS1977

Reforming of glucose and wood at the critical conditions of water

Reforming of organics in aqueous solutions is being investigated as a potential waste treatment process. Earlier studies showed that glucose in water reacts to form a gaseous mixture of CO, H2, CH4, CO2, C2H6, and C2H4 in the vicinity of the critical conditions of water (374 C, 22 MPa). The earlier work has been extended to determine the effect of variations in temperature and feed concentration on the extent of gasification. The percent gasification decreases with increasing feed concentration, indicating an overall kinetic order less than unity. Surprisingly, the percent gasification decreases with increasing temperature. A number of preliminary experiments were conducted with maple sawdust feed, which was thought to be representative of complex organic wastes from paper and vegetable matter. Once again, no solid products were found under the critical conditions; the percent gasification ranged from 16 to 88 percent, depending on the feed composition and residence time.

Modell, M.↗
NASA NTRS1981

NASA/BLM Applications Pilot Test (APT), phase 2. Volume 1: Executive summary

Data from LANDSAT, low altitude color aerial photography, and ground visits were combined and used to produce vegetation cover maps and to estimate productivity of range, woodland, and forest resources in northwestern Arizona. A planning session, two workshops, and four status reviews were held to assist technology transfer from NASA. Computer aided digital classification of LANDSAT data was selected as a major source of input data. An overview is presented of the data processing, data collection, productivity estimation, and map verification techniques used. Cost analysis and digital LANDSAT digital products are also considered.

Source record↗
NASA NTRS1988

Formic and acetic acid over the central Amazon region, Brazil. I - Dry season

The concentrations of formic and acetic acids in the gas phase, atmospheric aerosol, and rainwater samples collected in Amazonia at ground level and in the atmosphere during the Amazon Boundary Layer Experiment in July/August 1985 were analyzed by ion exchange chromatography. The diurnal behavior of both acids at ground level and their vertical distribution in the forest canopy point to the existence of vegetative sources as well as to production by chemical reactions in the atmosphere. The concentrations of formic and acetic acids in the gas phase were about 2 orders of magnitude higher than the corresponding concentrations in the atmospheric aerosol. In rainwater, the total formate and acetate represented about one half of the anion equivalents, in contrast to less than 10 percent of the soluble anionic equivalents contributed by these acids in the atmospheric aerosol. The observed levels of these ions in rainwater are considered to be the result of a combination of chemical reactions in hydrometeors and the scavenging of the gaseous acids by cloud droplets.

Andreae, M. O.↗