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All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Cassini Orbit Determination Performance during Saturn Satellite Tour: August 2005 - January 2006

During the period spanning the second Enceladus flyby in July 2005 through the eleventh Titan encounter in January 2006, the Cassini spacecraft was successfully navigated through eight close-targeted satellite encounters. Three of these encounters included the 500 km flybys of the icy satellites Hyperion, Dione and Rhea and five targeted flybys of Saturn's largest moon, Titan. This paper will show how our refinements to Saturn's satellite ephemerides have improved orbit determination predictions. These refinements include the mass estimates of Saturn and its satellites by better than 0.5%. Also, it will be shown how this better orbit determination performance has helped to eliminate several statistical maneuvers that were scheduled to clean-up orbit determination and/or maneuver-execution errors.

Rhea↗
NASA NTRS2004

Assessment of AVIRIS Laboratory and In-Flight Uniformity

An assessment of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) laboratory and in-flight uniformity is presented in this Slide presentation. The ideal uniform system is described, being a system where every spectrum is intercomparable to every other spectrum. Two types of failures to achieve this uniformity are described. Graphs showing measured spectral upwelling radiance, the expanded spectral convolution, the radiometric error from spectral error, the results from the hyperion Arizaro calibration experiment and a AVIRIS cross-track uniformity are among those presented. The reasons why uniformity matters are presented.

imaging spectroscopy↗
NASA NTRS2008

Onboard Detection of Active Canadian Sulfur Springs: A Europa Analogue

We discuss a current, ongoing demonstration of insitu onboard detection in which the Earth Observing-1 spacecraft detects surface sulfur deposits that originate from underlying springs by distinguishing the sulfur from the ice-rich glacial background, a good analogue for the Europan surface. In this paper, we describe the process of developing the onboard classifier for detecting the presence of sulfur in a hyperspectral scene, including the use of a training/testing set that is not exhaustively labeled, i.e.not all true positives are marked, and the selection of 12, out of 242, Hyperion instrument wavelength bands to use in the onboard detector. This study aims to demonstrate the potential for future missions to capture short-lived science events, make decisions onboard, identify high priority data for downlink and perform onboard change detection. In the future, such capability could help maximize the science return of downlink bandwidth-limited missions, addressing a significant constraint in all deep-space missions.

autonomy↗
NASA NTRS2010

Computation of Earth Science Products on Spaceborne Platforms

Spaceborne sensors like NASA's Hyperion hyperspectral imager generate huge data volumes, and several near-term trends indicate that data volumes will only increase. Next-generation hyperspectral missions, such as NASA's Hyperspectral Infrared Imager (HyspIRI), will operate at higher duty cycles and higher data rates, and their users will expect products to be generated from the data in near real time [1]. Barring a sudden advance in satellite downlink capacity, these trends point to a need to process data and generate products onboard the spacecraft. Rather than downlink an entire hyperspectral image cube, onboard processing enables satellites to downlink partial or completed scientific data products, which are often one to two orders of magnitude smaller than the original image. In addition, a satellite with onboard data processing resources and direct broadcast transmission equipment could send data products directly to first responders, research scientists or other users on the ground. Next-generation space-capable data processors will have a combination of reconfigurable gate arrays, digital signal processors and general-purpose CPUs. Correctly programmed and configured, these resources are sufficient to run sophisticated data analysis programs, including hyperspectral image processing algorithms that commonly run on desktop computers [2]. This paper describes how we implemented one such program, the HSEG hierarchical image segmentation algorithm, software commonly used on desktop and parallel processors, on a hardware platform designed to mimic a next-generation space-capable data processor [3]. We also describe our approach to porting the algorithm to and optimizing it for the new platform, and determine the expected performance gains enabled by our design. This extended abstract will describe the HSEG algorithm and hardware platform in greater detail, provide an analysis of the key function within the algorithm that required hardware acceleration, and describe our implementation of that function in hardware.

Fisher, Kevin↗
NASA NTRS2010

Hyperspectral Systems Increase Imaging Capabilities

In 1983, NASA started developing hyperspectral systems to image in the ultraviolet and infrared wavelengths. In 2001, the first on-orbit hyperspectral imager, Hyperion, was launched aboard the Earth Observing-1 spacecraft. Based on the hyperspectral imaging sensors used in Earth observation satellites, Stennis Space Center engineers and Institute for Technology Development researchers collaborated on a new design that was smaller and used an improved scanner. Featured in Spinoff 2007, the technology is now exclusively licensed by Themis Vision Systems LLC, of Richmond, Virginia, and is widely used in medical and life sciences, defense and security, forensics, and microscopy.

Source record↗
NASA NTRS2011

Forty-Year Calibrated Record of Earth-Surface Reflected Radiance from Landsat: A Review

Sensors on Landsat satellites have been collecting images of the Earth's surface for nearly 40 years. These images have been invaluable for characterizing and detecting changes in the land cover and land use of the world. Although initially conceived as primarily picture generating sensors, even the early sensors were radiometrically calibrated and spectrally characterized prior to launch and incorporated some capabilities to monitor their radiometric calibration once on orbit. Recently, as the focus of studies has shifted to monitoring Earth surface parameters over significant periods of time, serious attention has been focused toward bringing the data from all these sensors onto a common radiometric scale over this 40-year period. This effort started with the most recent systems and then was extended back in time. Landsat-7 ETM+, the best-characterized sensor of the series prior to launch and once on orbit, and the most stable system to date, was chosen to serve as the reference. The Landsat-7 project was the first of the series to build an image assessment system into its ground system, allowing systematic characterization of its sensors and data. Second, the Landsat-5 TM (still operating at the time of the Landsat-7 launch and continues to operate) calibration history was reconstructed based on its internal calibrator, vicarious calibrations, pseudo-invariant sites and a tie to Landsat-7 ETM+ at the time of the commissioning of Landsat-7. This process was performed in two iterations: the earlier one relied primarily on the TM internal calibrator. When this was found to have some deficiencies, a revised calibration was based more on pseudo-invariant sites, though the internal calibrator was still used to establish the short-term variations in response due to icing build up on the cold focal plane. As time progressed, a capability to monitor the Landsat-5 TM was added to the image assessment system. The Landsat-4 TM, which operated from 1982-1992, was the third system to which the radiometric scale was extended. The limited and broken use of the Landsat-4 TM made this analysis more difficult. Eight-day separated image pairs from Landsat-5 combined with analysis of pseudo invariant sites established this history. The fourth and most challenging effort was making the Landsat-1 to -5 MSS sensors' data internally radiometrically consistent. This effort was particularly complicated by the age of the MSS data, varying formats and processing levels in the archive, limited datasets, and limited documentation available. Ultimately, pseudo-invariant sites were identified in North America and used for this effort. Note that most of the Landsat-MSS archived data had already been calibrated using the MSS internal calibrators, so this processing was imbedded in the result. The final effort was developing an absolute scale for Landsat MSS similar to what was already established for the "TM" sensors. This was accomplished by using simultaneous data from Landsat-5 MSS and Landsat-5 TM, accounting for spectral differences between the sensors using EO-1 Hyperion data. The recalibrated history of the Landsat data and implications to users are discussed. The key result from this work is a consistently calibrated Landsat data archive that spans nearly 40 years with total uncertainties on the order of 10% or less for most sensors and bands.

Markham, Brian↗
NASA NTRS2010

Spectral Indices to Monitor Nitrogen-Driven Carbon Uptake in Field Corn

Climate change is heavily impacted by changing vegetation cover and productivity with large scale monitoring of vegetation only possible with remote sensing techniques. The goal of this effort was to evaluate existing reflectance (R) spectroscopic methods for determining vegetation parameters related to photosynthetic function and carbon (C) dynamics in plants. Since nitrogen (N) is a key constituent of photosynthetic pigments and C fixing enzymes, biological C sequestration is regulated in part by N availability. Spectral R information was obtained from field corn grown at four N application rates (0, 70, 140, 280 kg N/ha). A hierarchy of spectral observations were obtained: leaf and canopy with a spectral radiometer; aircraft with the AISA sensor; and satellite with EO-1 Hyperion. A number of spectral R indices were calculated from these hyperspectral observations and compared to geo-located biophysical measures of plant growth and physiological condition. Top performing indices included the R derivative index D730/D705 and the normalized difference of R750 vs. R705 (ND705), both of which differentiated three of the four N fertilization rates at multiple observation levels and yielded high correlations to these carbon parameters: light use efficiency (LUE); C:N ratio; and crop grain yield. These results advocate the use of hyperspectral sensors for remotely monitoring carbon cycle dynamics in managed terrestrial ecosystems.

Corp, Lawrence A.↗
NASA NTRS2011

Constraints on Determining the Eruption Style and Composition of Terrestrial Lavas from Space

The surface temperatures of active lavas relate to cooling rates, chemistry, and eruption style. We analyzed 61 hyperspectral satellite images acquired by the National Aeronautics and Space Administration s Earth Observing-1 (EO-1) Hyperion imaging spectrometer to document the surface temperature distributions of active lavas erupted at 13 volcanoes. Images were selected to encompass the range of common lava eruption styles, specifically, lava fountains, flows, lakes, and domes. Our results reveal temperature distributions for terrestrial lavas that correlate with composition (i.e., a statistically significant difference in the highest temperatures retrieved for mafic lavas and intermediate and felsic lavas) and eruption style. Maximum temperatures observed for mafi c lavas are approx.200 C higher than for intermediate and felsic lavas. All eruption styles exhibit a low-temperature mode at approx.300 C; lava fountains and 'a' a flows also exhibit a higher-temperature mode at approx.700 C. The observed differences between the temperatures are consistent with the contrasting rates at which the lava surfaces are thermally renewed. Eruption styles that allow persistent and pervasive thermal renewal of the lava surface (e.g., fractured crusts on channel-fed 'a' a flows) exhibit a bimodal temperature distribution; eruption styles that do not (e.g., the continuous skin of pahoehoe lavas) exhibit a single mode. We conclude that insights into composition and eruption style can only be gained remotely by analyzing a large spatio-temporal sample of data. This has implications for determining composition and eruption style at the Jovian moon Io, for which no in situ validation is available.

Wright, Robert↗
NASA NTRS2012

Craters Without Ejecta

A significant portion of the Solar System's population of minor bodies may be quite porous. A unique aspect of crater formation in porous bodies is that large craters may form without the ejecta deposits that are associated with craters on less porous bodies. In this paper. laboratory experiments and scaling theories are used to identify the conditions under which ejecta deposits are suppressed. The results are consistent with the interpretation that large craters on asteroid Mathilde (porosity approx. 50%) and Saturn's moon Hyperion (porosity >40%) apparently formed without producing Significant ejecta deposits. while smaller bodies do have notable regoliths.

Housen, Kevin R.↗
NASA NTRS2012

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

Climate change in tundra regions may alter vegetation species composition and ecosystem carbon balance. Remote sensing provides critical tools for monitoring these changes as optical signals provide a way to scale from plot measurements to regional patterns. Gas exchange measurements of pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow AK, show three significantly different values of light use efficiency (LUE) with values of 0.013+/-0.001, 0.0018+/-0.0002, and 0.0012 0.0001 mol C/mol absorbed quanta for vascular plants, mosses and lichens, respectively. Further, discriminant analysis of patch reflectance identifies five spectral bands that can separate each vegetation functional type as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. Patch-level statistical discriminant functions applied to in situ hyperspectral reflectance successfully unmixed cover fractions of the vegetation functional types. These functions, developed from the tram data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine regional variability in distribution of the vegetation functional types and from those distributions, the variability of LUE. Across the landscape, there was a fivefold variation in tundra LUE that was correlated to a spectral vegetation index developed to detect vegetation chlorophyll content.

Huemmrich, Karl F.↗
NASA NTRS2012

NASA IMAGESEER: NASA IMAGEs for Science, Education, Experimentation and Research

A number of web-accessible databases, including medical, military or other image data, offer universities and other users the ability to teach or research new Image Processing techniques on relevant and well-documented data. However, NASA images have traditionally been difficult for researchers to find, are often only available in hard-to-use formats, and do not always provide sufficient context and background for a non-NASA Scientist user to understand their content. The new IMAGESEER (IMAGEs for Science, Education, Experimentation and Research) database seeks to address these issues. Through a graphically-rich web site for browsing and downloading all of the selected datasets, benchmarks, and tutorials, IMAGESEER provides a widely accessible database of NASA-centric, easy to read, image data for teaching or validating new Image Processing algorithms. As such, IMAGESEER fosters collaboration between NASA and research organizations while simultaneously encouraging development of new and enhanced Image Processing algorithms. The first prototype includes a representative sampling of NASA multispectral and hyperspectral images from several Earth Science instruments, along with a few small tutorials. Image processing techniques are currently represented with cloud detection, image registration, and map cover/classification. For each technique, corresponding data are selected from four different geographic regions, i.e., mountains, urban, water coastal, and agriculture areas. Satellite images have been collected from several instruments - Landsat-5 and -7 Thematic Mappers, Earth Observing-1 (EO-1) Advanced Land Imager (ALI) and Hyperion, and the Moderate Resolution Imaging Spectroradiometer (MODIS). After geo-registration, these images are available in simple common formats such as GeoTIFF and raw formats, along with associated benchmark data.

Le Moigne, Jacqueline↗
NASA NTRS2011

Hyperspectral Biofilm Classification Analysis for Carrying Capacity of Migratory Birds in the South Bay Salt Ponds

Tidal marshes are highly productive ecosystems that support migratory birds as roosting and over-wintering habitats on the Pacific Flyway. Microphytobenthos, or more commonly 'biofilms' contribute significantly to the primary productivity of wetland ecosystems, and provide a substantial food source for macroinvertebrates and avian communities. In this study, biofilms were characterized based on taxonomic classification, density differences, and spectral signatures. These techniques were then applied to remotely sensed images to map biofilm densities and distributions in the South Bay Salt Ponds and predict the carrying capacity of these newly restored ponds for migratory birds. The GER-1500 spectroradiometer was used to obtain in situ spectral signatures for each density-class of biofilm. The spectral variation and taxonomic classification between high, medium, and low density biofilm cover types was mapped using in-situ spectral measurements and classification of EO-1 Hyperion and Landsat TM 5 images. Biofilm samples were also collected in the field to perform laboratory analyses including chlorophyll-a, taxonomic classification, and energy content. Comparison of the spectral signatures between the three density groups shows distinct variations useful for classification. Also, analysis of chlorophyll-a concentrations show statistically significant differences between each density group, using the Tukey-Kramer test at an alpha level of 0.05. The potential carrying capacity in South Bay Salt Ponds is estimated to be 250,000 birds.

Hsu, Wei-Chen↗
NASA NTRS2012

Middle East Health and Air Quality Utilizing NASA EOS in the Saharan and Arabian Deserts to Examine Dust Particle Size and Mineralogy of Aerosols

Ground-based studies conducted in Iraq have revealed the presence of potential human pathogens in airborne dust. According to the Environmental Protection Agency (EPA), airborne particulate matter below 2.5micron (PM2.5) can cause long-term damage to the human respiratory system. NASA fs Earth Observing System (EOS) can be used to determine spectral characteristics of dust particles and dust particle sizes. Comparing dust particle size from the Sahara and Arabian Deserts gives insight into the composition and atmospheric transport characteristics of dust from each desert. With the use of NASA SeaWiFS DeepBlue Aerosol, dust particle sizes were estimated using Angstrom Exponent. Brightness Temperature Difference (BTD) equation was used to determine the area of the dust storm. The Moderate-resolution Imaging Spectroradiometer (MODIS) on Terra satellite was utilized in calculating BTD. Mineral composition of a dust storm that occurred 17 April 2008 near Baghdad was determined using imaging spectrometer data from the JPL Spectral Library and EO-1 Hyperion data. Mineralogy of this dust storm was subsequently compared to that of a dust storm that occurred over the Bodele Depression in the Sahara Desert on 7 June 2003.

Keeton, Tiffany↗
NASA NTRS2013

Erosion, Transportation, and Deposition on Outer Solar System Satellites: Landform Evolution Modeling Studies

Mass movement and landform degradation reduces topographic relief by moving surface materials to a lower gravitational potential. In addition to the obvious role of gravity, abrasive mechanical erosion plays a role, often in combination with the lowering of cohesion, which allows disaggregation of the relief-forming material. The identification of specific landform types associated with mass movement and landform degradation provides information about local sediment particle size and abundance and transportation processes. Generally, mass movements can be classified in terms of the particle sizes of the transported material and the speed the material moved during transport. Most degradation on outer planet satellites appears consistent with sliding or slumping, impact erosion, and regolith evolution. Some satellites, such as Callisto and perhaps Hyperion and Iapetus, have an appearance that implies that some additional process is at work, most likely sublimation-driven landform modification and mass wasting. A variant on this process is thermally driven frost segregation as seen on all three icy Galilean satellites and perhaps elsewhere. Titan is unique among outer planet satellites in that Aeolian and fluvial processes also operate to erode, transport, and deposit material. We will evaluate the sequence and extent of various landform-modifying erosional and volatile redistribution processes that have shaped these icy satellites using a 3-D model that simulates the following surface and subsurface processes: 1) sublimation and re-condensation of volatiles; 2) development of refractory lag deposits; 3) disaggregation and downward sloughing of surficial material; 4) radiative heating/cooling of the surface (including reflection, emission, and shadowing by other surface elements); 5) thermal diffusion; and 6) vapor diffusion. The model will provide explicit simulations of landform development and thusly predicts the topographic and volatile evolution of the surface and final landscape form as constrained by DEMs. We have also simulated fluvial and lacustrine modification of icy satellites landscapes to evaluate the degree to which fluvial erosion of representative initial landscapes can replicate the present Titan landscape.

erosion↗
NASA NTRS2014

Interstellar Organics, the Solar Nebula, and Saturn's Satellite Phoebe

The diffuse interstellar medium inventory of organic material (Pendleton et al. 1994, Pe 2002) was likely incorporated into the molecular cloud in which the solar nebula condensed. This provided the feedstock for the fo planets, and the smaller icy bodies in the region outside Neptune's orbit (transneptunian objects, or TNOs). Saturn's satellites Phoeb open a window to the composition of one class of TNO as revealed by the near-infrared mapping spectrometer (VIMS) on the Cass Phoebe (mean diameter 213 km) is a former TNO now orbiting Saturn. VIMS spectral maps of Phoebe's surface reveal a complex consisting of prominent aromatic (CH) and aliphatic hydrocarbon (CH2, CH3) absorption bands (3.2-3.6 μm). Phoebe is the source encircling Saturn, and from which particles (~5-20 μm size) spiral inward toward Saturn. They encounter Iapetus and Hyperion wh blanket the native H2O ice of those two bodies. Quantitative analysis of the hydrocarbon bands on Iapetus demonstrates that aroma abundant as aliphatic CH2+CH3, significantly exceeding the strength of the aromatic signature in interplanetary dust particles, com carbonaceous meteorites (Cruikshank et al. 2013). A similar excess of aromatics over aliphatics is seen in the qualitative analysis o itself (Dalle Ore et al. 2012). The Iapetus aliphatic hydrocarbons show CH2/CH3 ~4, which is larger than the value found in the di as Phoebe is a primitive body that formed in the outer regions of the solar nebula and has preserved some of the original nebula inv understanding the content and degree of processing of that nebular material. There are other Phoebe-like TNOs that are presently b in the organic spectral region, but JWST will open that possibility for a number of objects. We now need to explore and understand organic-bearing Solar System material to the solar nebula and the inventory of ISM materials incorporated therein.

Interstellar↗
NASA NTRS2013

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

Non-vascular plants (lichens and mosses) are significant components of tundra landscapes and may respond to climate change differently from vascular plants affecting ecosystem carbon balance. Remote sensing provides critical tools for monitoring plant cover types, as optical signals provide a way to scale from plot measurements to regional estimates of biophysical properties, for which spatial-temporal patterns may be analyzed. Gas exchange measurements were collected for pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow, AK. These functional types were found to have three significantly different values of light use efficiency (LUE) with values of 0.013 plus or minus 0.0002, 0.0018 plus or minus 0.0002, and 0.0012 plus or minus 0.0001 mol C mol (exp -1) absorbed quanta for vascular plants, mosses and lichens, respectively. Discriminant analysis of the spectra reflectance of these patches identified five spectral bands that separated each of these vegetation functional types as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Along the transect, area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. The patch-level statistical discriminant functions applied to in situ hyperspectral reflectance data collected along the transect successfully unmixed cover fractions of the vegetation functional types. The unmixing functions, developed from the transect data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine variability in distribution of the vegetation functional types for an area near Barrow, AK. Spatial variability of LUE was derived from the observed functional type distributions. Across this landscape, a fivefold variation in tundra LUE was observed. LUE calculated from the functional type cover fractions was also correlated to a spectral vegetation index developed to detect vegetation chlorophyll content. The concurrence of these alternate methods suggest that hyperspectral remote sensing can distinguish functionally distinct vegetation types and can be used to develop regional estimates of photosynthetic LUE in tundra landscapes.

VEGETATION↗
NASA NTRS2009

Onboard Classification of Hyperspectral Data on the Earth Observing One Mission

Remote-sensed hyperspectral data represents significant challenges in downlink due to its large data volumes. This paper describes a research program designed to process hyperspectral data products onboard spacecraft to (a) reduce data downlink volumes and (b) decrease latency to provide key data products (often by enabling use of lower data rate communications systems). We describe efforts to develop onboard processing to study volcanoes, floods, and cryosphere, using the Hyperion hyperspectral imager and onboard processing for the Earth Observing One (EO-1) mission as well as preliminary work targeting the Hyperspectral Infrared Imager (HyspIRI) mission.

cryosphere↗
NASA NTRS2011

Hyperspectral Mapping of the Invasive Species Pepperweed and the Development of a Habitat Suitability Model

Mapping and predicting the spatial distribution of invasive plant species is central to habitat management, however difficult to implement at landscape and regional scales. Remote sensing techniques can reduce the impact field campaigns have on these ecologically sensitive areas and can provide a regional and multi-temporal view of invasive species spread. Invasive perennial pepperweed (Lepidium latifolium) is now widespread in fragmented estuaries of the South San Francisco Bay, and is shown to degrade native vegetation in estuaries and adjacent habitats, thereby reducing forage and shelter for wildlife. The purpose of this study is to map the present distribution of pepperweed in estuarine areas of the South San Francisco Bay Salt Pond Restoration Project (Alviso, CA), and create a habitat suitability model to predict future spread. Pepperweed reflectance data were collected in-situ with a GER 1500 spectroradiometer along with 88 corresponding pepperweed presence and absence points used for building the statistical models. The spectral angle mapper (SAM) classification algorithm was used to distinguish the reflectance spectrum of pepperweed and map its distribution using an image from EO-1 Hyperion. To map pepperweed, we performed a supervised classification on an ASTER image with a resulting classification accuracy of 71.8%. We generated a weighted overlay analysis model within a geographic information system (GIS) framework to predict areas in the study site most susceptible to pepperweed colonization. Variables for the model included propensity for disturbance, status of pond restoration, proximity to water channels, and terrain curvature. A Generalized Additive Model (GAM) was also used to generate a probability map and investigate the statistical probability that each variable contributed to predict pepperweed spread. Results from the GAM revealed distance to channels, distance to ponds and curvature were statistically significant (p < 0.01) in determining the locations of suitable pepperweed habitats.

Pepperweed↗