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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Theoretical modelling and experimental data matching for active and passive microwave remote sensing of Earth terrain

Two theoretical models were developed to characterize terrain media: a random medium with a variance, a horizontal correlation length; and a homogeneous dielectric containing discrete scatterers. The earth terrain is modelled as layers of such scattering media bounded by air above and half-space below. Matching the theoretical results with experimental data collected from vegetation and snow-ice fields shows that: (1) for observation angles near nadir, rough surface effects are important; (2) for snow-ice field the horizontal correlation length is greater than the vertical correlation length whereas for vegetation field their relative sizes depend on the types of vegetation; (3) the vertically polarized backscattering cross-section is always larger than the horizontally polarized backscattering cross-section for half-space scattering media; (4) for snow field displaying diurnal change, a three-layer model including a thin top layer caused by sunlight illumination must be used; and (5) for a random medium with equal horizontal and vertical correlation lengths, the measured data can also be matched with a corresponding discrete scatterer model.

Kong, J. A.↗
NASA NTRS2007

Simulation of Malaria Transmission among Households in a Thai Village using Remotely Sensed Parameters

We have used discrete-event simulation to model the malaria transmission in a Thailand village with approximately 700 residents. Specifically, we model the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle under the explicit influences of selected extrinsic and intrinsic factors. Some of the meteorological and environmental parameters used in the simulation are derived from Tropical Rainfall Measuring Mission and the Ikonos satellite data. Parameters used in the simulations reflect the realistic condition of the village, including the locations and sizes of the households, ages and estimated immunity of the residents, presence of farm animals, and locations of larval habitats. Larval habitats include the actual locations where larvae were collected and the probable locations based on satellite data. The output of the simulation includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Simulated transmission under homogeneous environmental condition was compared with that predicted by a SEIR model. Sensitivity of the output with respect to some extrinsic and intrinsic factors was investigated. Results were compared with mosquito vector and human malaria data acquired over 4.5 years (June 1999 - January 2004) in Kong Mong Tha, a remote village in Kanchanaburi Province, western Thailand. The simulation method is useful for testing transmission hypotheses, estimating the efficacy of insecticide applications, assessing the impacts of nonimmune immigrants, and predicting the effects of socioeconomic, environmental and climatic changes.

Kiang, Richard K.↗
DOE OSTI2021

Monitoring agroecosystem productivity and phenology at a national scale: A metric assessment framework

Effective measurement of seasonal variations in the timing and amount of production is critical to managing spatially heterogeneous agroecosystems in a changing climate. Although numerous technologies for such measurements are available, their relationships to one another at a continental extent are unknown. Using data collected from across the Long-Term Agroecosystem Research (LTAR) network and other networks, we investigated correlations among key metrics representing primary production, phenology, and carbon fluxes in croplands, grazing lands, and crop-grazing integrated systems across the continental U.S. Metrics we examined included gross primary productivity (GPP) estimated from eddy covariance (EC) towers and modelled from the Landsat satellite, Landsat NDVI, and vegetation greenness (Green Chromatic Coordinate, GCC) from tower-mounted PhenoCams for 2017 and 2018. Overall, our analysis compared production dynamics estimated from three independent ground and remote platforms using data for 34 agricultural sites constituting 51 site-years of co-located time series. Pairwise sensor comparisons across all four metrics revealed stronger correlation and lower root mean square error (RMSE) between end of season (EOS) dates (Pearson R ranged from 0.6 to 0.7 and RMSE from 32.5 to 67.8) than start of season (SOS) dates (0.46 to 0.69 and 40.4 to 66.2). Overall, moderate to high correlations between SOS and EOS metrics complemented one another except at some lower productivity grazing land sites where estimating SOS can be challenging. Growing season length estimates derived from 16-day satellite GPP (179.1 days) were significantly longer than those from PhenoCam G CC (70.4 days, p adj < 0.0001) and EC GPP (79.6 days, p adj < 0.0001). Landscape heterogeneity did not explain differences in SOS and EOS estimates. Annual integrated estimates of productivity from EC GPP and PhenoCam G CC diverged from those estimated by Landsat GPP and NDVI at sites where annual production exceeds 1000 gC/m –2 yr –1 . Based on our results, we developed a “metric assessment framework” that articulates where and how metrics from satellite, eddy covariance and PhenoCams complement, diverge from, or are redundant with one another. The framework was designed to optimize instrumentation selection for monitoring, modeling, and forecasting ecosystem functioning with the ultimate goal of informing decision-making by land managers, policy-makers, and industry leaders working at multiple scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Origin and mitigation of wind noise on balloon-borne infrasound microbarometers

High-altitude monitoring of low-frequency acoustic waves (infrasound) on Earth has regained prominence in recent years, primarily driven by improvements in light-weight sensor technology and advances in scientific ballooning techniques. Balloon-borne infrasound monitoring is also being proposed as a remote sensing technique for planetary exploration. Contrary to ground-based infrasound monitoring, the infrasound noise background in the stratosphere as measured by a balloon remains uncharacterized and the efficacy of wind noise mitigation filters has not been investigated. In this study, an analysis of pressure data collected using infrasound microbarometers during the flight of a long-duration zero pressure balloon is presented. Here, a dramatic reduction of background noise in the stratosphere is demonstrated and it is shown that wind noise mitigation filters are not effective at reducing wind noise under these conditions. Results from this study demonstrate stratospheric balloons as a low-noise platform for infrasound monitoring and motivate the development of improved noise mitigation tools.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Sizing ice hydrometeor populations using the dual-wavelength radar ratio

Dual-wavelength (3.2 and 0.32 cm, i.e., X- and W-radar bands) radar ratio (DWR) measurements in ice clouds and precipitation using Canada's National Research Council Institute for Aerospace Research airborne radar are compared to closely collocated particle microphysical in situ sampling data in order to develop relations between DWR and characteristic hydrometeor size. This study uses the radar and in situ data sets collected during the In-Cloud ICing and Large-drop Experiment (ICICLE) campaign in midlatitude frontal clouds. Since atmospheric particle scattering at X band is predominantly in the Rayleigh regime and the W-band frequency is the highest frequency usually used for hydrometeor remote sensing, the X–W-band combination provides a relatively strong dual-wavelength reflectivity difference. This study considers radar and in situ measurements conducted in relatively homogeneous cloud and precipitation conditions. Measurements show that under these conditions, the difference between the X-band radar reflectivities observed with vertical and horizontal pointing of the radar beam are generally small and often negligible. However, W-band reflectivities at vertical beam pointing are, on average, larger than those for horizontal beam pointing by about 4 dB, which is a non-Rayleigh scattering effect from preferentially oriented non-spherical particles. A horizontal radar beam DWR–mean volume particle size relation, D v , provides robust estimates of this characteristic size for populations of particles with different habits. Uncertainties of D v retrievals using DWR are around 0.6 mm when D v is greater than approximately 1 mm. Size estimates using vertical radar beam DWRs have larger uncertainties due to smaller dual-wavelength signals and stronger influences of hydrometeor habits and orientations at this geometry of beam pointing. Mean relations among different characteristic sizes, which describe the entire particle size distribution (PSD), such as D v , and other sizes used in various applications (e.g., the mean, effective, and median sizes) are derived, so the results of this study can be used for estimating different PSD characteristic sizes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Aquarius Third Stokes Parameter Measurements: Initial Results

The Aquarius/SAC-D observatory was launched on June 10, 2011 and the Aquarius instrument has been collecting data continuously since late August. One of the unique features of the L-band radiometers comprising Aquarius is the presence of a polarimetric channel to measure the third Stokes parameter. The purpose is to provide a measure of Faraday rotation, which can be important for remote sensing at L-band, especially in the case of remote sensing of salinity which requires high precision. Initial results are presented here showing a reasonable agreement between retrieved and modeled Faraday rotation and also the "noisy" behavior at land-water boundaries and other mixed scenes predicted by theory.

faradayrotation↗
NASA NTRS2023

Ocean Carbon From Space: Current Status and Priorities for the Next Decade

The ocean plays a central role in modulating the Earth’s carbon cycle. Monitoring how the ocean carbon cycle is changing is fundamental to managing climate change. Satellite remote sensing is currently our best tool for viewing the ocean surface globally and systematically, at high spatial and temporal resolutions, and the past few decades have seen an exponential growth in studies utilising satellite data for ocean carbon research. Satellite-based observations must be combined with in-situ observations and models, to obtain a comprehensive view of ocean carbon pools and fluxes. To help prioritise future research in this area, a workshop was organised that assembled leading experts working on the topic, from around the world, including remote-sensing scientists, field scientists and modellers, with the goal to articulate a collective view of the current status of ocean carbon research, identify gaps in knowledge, and formulate a scientific roadmap for the next decade, with an emphasis on evaluating where satellite remote sensing may contribute. A total of 449 scientists and stakeholders participated (with balanced gender representation), from North and South America, Europe, Asia, Africa, and Oceania. Sessions targeted both inorganic and organic pools of carbon in the ocean, in both dissolved and particulate form, as well as major fluxes of carbon between reservoirs (e.g., primary production) and at interfaces (e.g., air-sea and land–ocean). Extreme events, blue carbon and carbon budgeting were also key topics discussed. Emerging priorities identified include: expanding the networks and quality of in-situ observations; improved satellite retrievals; improved uncertainty quantification; improved understanding of vertical distributions; integration with models; improved techniques to bridge spatial and temporal scales of the different data sources; and improved fundamental understanding of the ocean carbon cycle, and of the interactions among pools of carbon and light. We also report on priorities for the specific pools and fluxes studied, and highlight issues and concerns that arose during discussions, such as the need to consider the environmental impact of satellites or space activities; the role satellites can play in monitoring ocean carbon dioxide removal approaches; economic valuation of the satellite based information; to consider how satellites can contribute to monitoring cycles of other important climatically-relevant compounds and elements; to promote diversity and inclusivity in ocean carbon research; to bring together communities working on different aspects of planetary carbon; maximising use of international bodies; to follow an open science approach; to explore new and innovative ways to remotely monitor ocean carbon; and to harness quantum computing. Overall, this paper provides a comprehensive scientific roadmap for the next decade on how satellite remote sensing could help monitor the ocean carbon cycle, and its links to the other domains, such as terrestrial and atmosphere.

oceanography↗
NASA NTRS2018

Learning Model Structural Uncertainty with Gaussian Processes

The advent of commercially available quantum computers has marked the beginning of quantum computing as a reality. Both quantum gate and annealing computers have been released by major computer hardware companies. In this work, the D-Wave 2XTM quantum annealing computer housed at the NASA Advanced Systems computational facility is investigated to accelerate Machine Learning (ML) for image registration. NASA collects large amounts of images over the globe remotely using space-based monitoring. Images of a fixed areas of the land surface are taken over time. Due to the orbit of the sensors, the viewing angles deviate slightly, and it is necessary to align or register the images precisely to create image time series over the land surface. Unaligned images can lead to substantial analysis errors. These time-series are then used in modeling Earth Systems models such as hydrological, weather, and carbon monitoring models. In this work, we consider the Moderate Resolution Image Spectrometer (MODIS) data collected by the NASA's terra satellite. Artificial Neural Networks (ANNs) is a natural fit for ML modelling of images. Several successes have been reported using machine learning related to image processing. We investigate the use of ML to register MODIS images. ANNs are investigated in combination with a Restricted Boltzmann Machines (RBM) as an auto-encoder. We will present results showing the accuracy and efficiency of this approach.The D-Wave 2XTM quantum annealer samples the ground-state wave-function of a spin-Ising systems with quadratic interactions between qubits and a Chimera connectivity. The system sits in a ~15 mK thermal bath. One can think of the system as being placed in the ground state initially and subject to thermal excitations governed by Boltzmann statistics. If this is assumed true, one can use the statistics from the D-Wave 2XTM to train RBMs. Generating statistics for training Boltzmann machines is an NP-hard problem and constitutes the largest compute cost. We investigate the use of the D-Wave 2XTM to accelerate the training of the RBMs in our ANNs and report on the results.

Kouatchou, Jules↗
NASA NTRS1998

The CERES S'COOL Project: Development and Operational Phases

As part of NASA's Mission to Planet Earth, the first Clouds and the Earth's Radiant Energy System (CERES) instrument will be launched on the Tropical Rainfall Measuring Mission (TRMM) spacecraft from the Tanegashima launch site in Japan in November 1997. The instrument will measure the radiation budget incoming and outgoing radiant energy - of the Earth. The major feature of interest is clouds, which play a very strong role in regulating our climate. CERES will identify clear and cloudy regions and determine cloud physical and microphysical properties using imager data from a companion instrument. Validation efforts for the remote sensing algorithms will be intensive. As one component of the validation, the S'COOL (Students' Cloud Observations On-Line) project will involve school children around the globe in making ground truth measurements at the time of a CERES overpass. They will report cloud type, height, fraction, and opacity, as well as the local surface conditions. Their observations will be collected at the NASA Langley Distributed Active Archive Center (DAAC) and made available over the Internet for educational purposes as well as for use by the CERES Science Team in validation efforts. Pilot testing of the S'COOL project began in January 1997 with two local schools in Southeastern Virginia and one remote site in Montana. National testing in April 1997 involved 8 schools (grades 3 to high school) across the United States. Global testing will be carried out in October 1997. Details of the S'COOL project, which is mainly Internet-based, are being developed in each of these phases according to feedback received from participants. In 1998, when the CERES instrument is operational, a global observer network should be in place providing useful information to the scientists and learning opportunities to the students. Broad participation in the S'COOL project is planned, both to obtain data from a wide range of geographic areas, and to involve as many students as possible in learning about clouds and atmospheric science. This paper reports on the development phase of the S'COOL project, including the reaction of the teachers and students who have been involved. It describes the operational state of the S'COOL network, and identifies opportunities for additional participants.

Chambers, Lin H.↗
DOE OSTI2022

A multi-modal scanning system to digitize CBRNE emergency response scenes

A handheld system developed to digitize a contextual understanding of the scene at a chemical, biological, radiological, nuclear and/or explosives (CBRNE) events is described. The system uses LiDAR and cameras to create a colorized 3D model of the environment, which helps domain experts that are supporting responders in the field. To generate the digitized model, a responder scans any suspicious objects and the surroundings by carrying the system through the scene. The scanning system provides a real-time user interface to inform the user about scanning progress and to indicate any areas that may have been missed either by the LiDAR sensors or the cameras. Currently, the collected data are post-processed on a different device, building a colorized triangular mesh of the encountered scene, with the intention of moving this pipeline to the scanner at a later point. The mesh is sufficiently compressed to be sent over a reduced bandwidth connection to a remote analyst. Furthermore, the system tracks fiducial markers attached to diagnostic equipment that is placed around the suspicious object. The resulting tracking information can be transmitted to remote analysts to further facilitate their supporting efforts. The paper will discuss the system's design, software components, the user interface used for scanning a scene, the necessary procedures for calibration of the sensors, and the processing steps of the resulting data. The discussion will close by evaluating the system's performance on 11 scenes.

Salathe, Marco↗
DOE OSTI2026

Location Identifiers, Metadata, and Map for Field Measurements at the East-Taylor Watershed Community Observatory, Colorado, USA (Version 3.3)

This dataset contains identifiers, metadata, and a map of the locations where field measurements have been conducted at the East-Taylor Watershed Community Observatory located in the Upper Colorado River Basin, United States. This is version 3.3 of the dataset and replaces the prior version 3.2 (see below for details on changes between the versions). Dataset description: The East River-Taylor Watershed is the primary field site of the Watershed Function Scientific Focus Area (WFSFA) and the Rocky Mountain Biological Laboratory. Researchers from several institutions generate highly diverse hydrological, biogeochemical, climate, vegetation, geological, remote sensing, and model data at the East-Taylor Watershed in collaboration with the WFSFA. Thus, the purpose of this dataset is to maintain an inventory of the field locations and instrumentation to provide information on the field activities in the East-Taylor Watershed and coordinate data collected across different locations, researchers, and institutions. The dataset contains (1) a README file with information on the various files, (2) three csv files describing the metadata collected for each surface point location, plot and region registered with the WFSFA, (3) csv files with metadata and contact information for each surface point location registered with the WFSFA, (4) a csv file with with metadata and contact information for plots, (5) a csv file with metadata for geographic regions and sub-regions within the watershed, (6) a compiled xlsx file with all the data and metadata which can be opened in Microsoft Excel, (7) a kml map of the locations plotted in the watershed which can be opened in Google Earth, (8) a jpg image of the kml map which can be viewed in any photo viewer, and (9) a zipped file with the registration templates used by the SFA team to collect location metadata. The zipped template file contains two csv files with the blank templates (point and plot), two csv files with instructions for filling out the location templates, and one compiled xlsx file with the instructions and blank templates together. Additionally, the templates in the xlsx include drop down validation for any controlled metadata fields. Persistent location identifiers (Location_ID) are determined by the WFSFA data management team and are used to track data and samples across locations. Dataset uses: This location metadata is used to update the Watershed SFA’s publicly accessible Field Information Portal (an interactive field sampling metadata exploration tool; https://wfsfa-data.lbl.gov/watershed/), the kml map file included in this dataset, and other data management tools internal to the Watershed SFA team. Version Information: The latest version of this dataset publication is version 3.3. This version contains 167 new point locations, 1 new plot, and 2 new geographic regions. Overall, there are a total of 1439 point locations, 75 plots, and 54 geographic regions. Additionally, the kml map of locations and image now includes two boundaries (Upper Ohio Creek (UO) and Carbon Creek (CA)) outside of the East River watershed (USGS HUC-10) and accompanying stream network that represents areas of focus. Refer to methods for further details on the version history. This dataset will be updated on a periodic basis with new measurement location information. Researchers interested in having their East-Taylor Watershed measurement locations added to this list should reach out to the WFSFA data management team at wfsfa-data@googlegroups.com. Acknowledgments: Please cite this dataset if using any of the location metadata in other publications or derived products. If using the location metadata for the 2018 NEON hyperspectral campaign, additionally cite Chadwick et al. (2020). doi:10.15485/1618130. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2025

Testing, Calibration, and UxS Integration of the Kromek GR1 Plus CZT Gamma Spectrometer

Collecting radiation measurements can be a hazardous task, especially in the presence of highly active sources. Various scenarios necessitate source search, classification, and quantification, often with limited or no a priori information. Activities such as disaster mitigation, emergency response, environmental monitoring, and site remediation may involve dangerous radioactive sources. In these situations, there is a pressing need for remote monitoring capabilities that protect human operators from potential harm and enhance adherence to the principle of “As Low as Reasonably Achievable” (ALARA) for radiation doses. The first step toward achieving remote radiation measurement capabilities is the remote operation of a radiation sensor. Once this milestone is reached, the next challenge is to integrate this remote sensing capability into suitable actuation agents, collectively referred to as uncrewed systems (UxS). These systems include familiar platforms such as robotic quadrupeds, aerial multirotor vehicles, and ground vehicles, any of which may be teleoperated, act autonomously, or utilize a combination of both. A critical factor in achieving remote radiation sensing is the availability of data from the appropriate sensor. Many commercially available radiation sensors have closed-source documentation for their communication protocols. Typical end-user products are often self-contained, handheld devices designed for manual measurement scenarios. While there are commercial off-the-shelf (COTS) integrations of radiation sensors with UxS available for purchase, these solutions are typically tailored for specific use cases and may not meet the requirements of different applications. This paper discusses efforts to remotely acquire radiation measurements from a small form-factor CZT gamma spectrometer. Sandia National Laboratories has successfully demonstrated the initial capability to integrate low size, weight, and power (SWaP) gamma spectroscopy into various UxS, alongside co-located GPS data logging and sensor calibration and qualification. With remote gamma spectroscopy achieved, the stage is set for UxS integration of this capability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1972

The Nimbus 4 IRLS meteorological experiment

The Nimbus 4 interrogation, recording, and location system is designed to locate and collect measurement data of upper atmospheric parameters through the tracking of free floating, constant level balloons flying at altitudes of 20.5 and 24.1 km and carrying specially designed interrogation packages. The basic elements of the system include a ground acquisition and command station, the Nimbus satellite, and the remote sensing platforms. Addresses of platforms as they come into view are programmed into the satellite on an orbit by orbit basis from the central ground station. Sensory data are transmitted to the satellite for storage and readout from balloon interrogation units.

Cote, C. E.↗
NASA NTRS1980

HCMM satellite follow-on investigation no. 25. Soil moisture and heat budget evalution in selected European zones of agricultural and environmental interest (TELLUS project)

A simple procedure to evaluate actual evaporation was derived by linearizing the surface energy balance equation, using Taylor's expansion. The original multidimensional hypersurface could be reduced to a linear relationship between evaporation and surface temperature or to a surface relationship involving evaporation, surface temperature and albedo. This procedure permits a rapid sensitivity analysis of the surface energy balance equation as well as a speedy mapping of evaporation from remotely sensed surface temperatures and albedo. Comparison with experimental data yielded promising results. The validity of evapotranspiration and soil moisture models in semiarid conditions was tested. Wheat was the crop chosen for a continuous measurement campaign made in the south of Italy. Radiometric, micrometeorologic, agronomic and soil data were collected for processing and interpretation.

Source record↗
NASA NTRS1987

Multiplatform sampling (ship, aircraft, and satellite) of a Gulf Stream warm core ring

The purpose of this paper is to demonstrate the ability to meet the need to measure distributions of physical and biological properties of the ocean over large areas synoptically and over long time periods by means of remote sensing utilizing contemporaneous buoy, ship, aircraft, and satellite (i.e., multiplatform) sampling strategies. A mapping of sea surface temperature and chlorophyll fields in a Gulf Stream warm core ring using the multiplatform approach is described. Sampling capabilities of each sensing system are discussed as background for the data collected by means of these three dissimilar methods. Commensurate space/time sample sets from each sensing system are compared, and their relative accuracies in space and time are determined. The three-dimensional composite maps derived from the data set provide a synoptic perspective unobtainable from single platforms alone.

Smith, Raymond C.↗
NASA NTRS1987

Atmospheric correction of NS-001 data and extraction of multiple angle reflectance data sets

The percentage of incident solar flux reflected by a surface is a quantity of considerable interest in remote sensing studies. To calculate reflectance from remotely sensed radiance data some estimate of incident flux is needed. Since simultaneous ground-based radiometric measurements are often not available for observations by aircraft or satellite sensors, a procedure based on modeling atmospheric transmittance and scattering was developed. The primary application is to an aircraft data set collected with the NASA C-130 over the Superior National Forest, Minnesota. Atmospherically corrected multiple angle reflectance data sets and reflectance images are generated for areas of natural forest vegetation. These data and the technique may be useful for studies of the interactions of light with forested canopies.

Strebel, D. E.↗
NASA NTRS2009

Feature Detection Systems Enhance Satellite Imagery

In 1963, during the ninth orbit of the Faith 7 capsule, astronaut Gordon Cooper skipped his nap and took some photos of the Earth below using a Hasselblad camera. The sole flier on the Mercury-Atlas 9 mission, Cooper took 24 photos - never-before-seen images including the Tibetan plateau, the crinkled heights of the Himalayas, and the jagged coast of Burma. From his lofty perch over 100 miles above the Earth, Cooper noted villages, roads, rivers, and even, on occasion, individual houses. In 1965, encouraged by the effectiveness of NASA s orbital photography experiments during the Mercury and subsequent Gemini manned space flight missions, U.S. Geological Survey (USGS) director William Pecora put forward a plan for a remote sensing satellite program that would collect information about the planet never before attainable. By 1972, NASA had built and launched Landsat 1, the first in a series of Landsat sensors that have combined to provide the longest continuous collection of space-based Earth imagery. The archived Landsat data - 37 years worth and counting - has provided a vast library of information allowing not only the extensive mapping of Earth s surface but also the study of its environmental changes, from receding glaciers and tropical deforestation to urban growth and crop harvests. Developed and launched by NASA with data collection operated at various times by the Agency, the National Oceanic and Atmospheric Administration (NOAA), Earth Observation Satellite Company (EOSAT, a private sector partnership that became Space Imaging Corporation in 1996), and USGS, Landsat sensors have recorded flooding from Hurricane Katrina, the building boom in Dubai, and the extinction of the Aral Sea, offering scientists invaluable insights into the natural and manmade changes that shape the world. Of the seven Landsat sensors launched since 1972, Landsat 5 and Landsat 7 are still operational. Though both are in use well beyond their intended lifespans, the mid-resolution satellites, which provide the benefit of images detailed enough to reveal large features like highways while still broad enough for global coverage, continue to scan the entirety of the Earth s surface. In 2012, NASA plans to launch the Landsat Data Continuity Mission (LDCM), or Landsat 8, to extend the Landsat program s contributions to cartography, water management, natural disaster relief planning, and more.

Source record↗
NASA NTRS2013

Microchemical and Structural Evidence for Space Weathering in Soils from Asteroid Itokawa

The chemistry, microstructure and optical properties of grains on the surfaces of airless bodies are continu-ously modified due to their interactions predominantly with solar energetic ions and micrometeorite impacts. Collectively known as space weathering, this phenomenon results in a discrepancy between remotely sensed spectra from asteroids and those ac-quired directly from meteorites. The return of pristine samples from the asteroid Itokawa provides insight into surface processes on airless bodies and will help in correlating remote sensing data with laboratory analysis of meteorites. Samples and Methods: We examined Itokawa samples RA-QD02-0042-01 and RA-QD-02-0042-02, ultramicrotomed sec-tions of a singular grain prepared by the Hayabusa sample cura-tion team. We analyzed these slices using a 200 keV JEOL 2010F transmission electron microscope (TEM) at Arizona State Uni-versity and a 200 keV JEOL 2500SE TEM at NASA JSC. Both field emission TEMs are equipped with energy-dispersive X-ray spectrometers (EDS) and scanning TEM (STEM) detectors. Results and Discussion: TEM observations reveal that the sectioned grain predominantly consists of a single crystal of low-Ca orthopyroxene, with subsidiary smaller regions of olivine, Fe-Ni sulfide, and Fe-Ni metal. EDS-spectrum imaging and high-resolution TEM (HRTEM) show local, nanocrystalline regions of the outermost 2 to 5 nm of the pyroxene are composed of an Fe-Mg-S-rich and Si- and O-depleted layer that is underlain by a 2- to 5-nm thick amorphous zone enriched in Si. These layers occur in multiple microtome slices and have uniform thicknesses. We also observe localized 'islands' of material on the surface of the pyroxene which HRTEM imaging indicates are amorphous and EDS measurements show are compositionally heterogeneous. A 10- to 60-nm thick partially amorphous zone occurs below the compositionally distinct rim. While this this zone is associated with the compositionally heterogeneous outer layer, it also occurs as a local stand-alone feature on the exterior rim of the grain. Ar-eas of the pyroxene grain rim also exhibit a vesicular texture. The TEM data indicate a complex history of space weather-ing for samples RA-QD02-0042-01 and -02. The outermost layer of nanocrystalline material with varied composition is consistent with previously suggested [3-4] chemical and structural pro-cessing by solar wind ions, with a possible additional role for im-pact vapor deposition [3-4]. The amorphous and compositionally distinct islands on the surface of this grain, similar to lunar glasses, suggest formation through vapor deposition via micrometeor-ite impact events. In comparison, the amorphization and vesicula-tion textures are likely a product of radiation damage from the solar wind. The depth and degree of amorphization, in conjunction with model calculations, will help provide an upper limit on exposure time for these particles.

Thompson, M. S.↗