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At least 145 records · Page 8

BOREAS RSS-1 PARABOLA SSA Surface Reflectance and Transmittance Data

The BOREAS RSS-1 team collected surface reflectance and transmittance data from three forested sites in the SSA. This data set contains averaged reflectance factors and transmitted radiances measured by the PARABOLA instrument at selected sites in the BOREAS SSA at different view angles and at three wavelength bands throughout the day. PARABOLA measurements were made during each of the three BOREAS IFCs during the growing season of 1994 at three SSA tower flux sites as well as during the FFC-T. Additional measurements were made in early and mid-1996 during the FFC-W and during IFC-2. The data are stored in tabular ASCII files.

Hall, Forrest G.↗

Understanding the Radiant Scattering Behavior of Vegetated Scenes

Knowledge of the physics of the scattering behavior of vegetation will ultimately serve the remote sensing and earth science community in many ways. For example, it will provide: (1) insight and guidance in developing new extraction techniques of canopy characteristics, (2) a basis for better interpretation of off-nadir satellite and aircraft data, (3) a basis for defining specifications of future earth observing sensor systems, and (4) a basis for defining important aspects of physical and biological processes of the plant system. The overall objective of the three-year study is to improve our fundamental understanding of the dynamics of directional scattering properties of vegetation canopies through analysis of field data and model simulation data. The specific objectives are to: (1) collect directional reflectance data covering the entire exitance hemisphere for several common vegetation canopies with various geometric structure (both homogeneous and row crop structures), (2) develop a scene radiation model with a general mathematical framework which will treat 3-D variability in heterogeneous scenes and account for 3-D radiant interactions within the scene, (3) conduct validations of the model on collected data sets, and (4) test and expand proposed physical scattering mechanisms involved in reflectance distribution dynamics by analyzing both field and modeling data.

Kimes, D. S.↗

Abundance and distribution of ultramafic microbreccia in Moses Rock Dike: Quantitative application of AIS data

Moses Rock dike is a Tertiary diatreme containing serpentinized ultramafic microbreccia (SUM). Field evidence indicates the SUM was emplaced first followed by breccias derived from the Permian strata exposed in the walls of the diatreme and finally by complex breccias containing basement and mantle derived rocks. SUM is found primarily dispersed throughout the matrix of the diatreme. Moses Rock dike was examined with Airborne Imaging Spectrometer (AIS) to map the distribution and excess of SUM in the matrix and to better understand the nature of the eruption which formed this explosive volcanic feature. AIS data was calibrated by dividing the suite of AIS data by data from an internal standard area and then multiplying this relative reflectance data by the absolute bidirectional reflectance of a selected sample from the standard area which was measured in the lab. From the calibrated AIS data the minerals serpentine, gypsum, and illite as well as desert varnish and the lithologies SUM and other sandstones were identified. SUM distribution and abundance in the matrix of the diatreme were examined in detail and two distinct styles of SUM dispersion were observed. The two styles are discussed in detail.

Mustard, John F.↗

Removing Atmospheric Effects From AVIRIS Data for Surface Reflectance Retrievals

Analysis of high resolution imaging spectrometer data requires a thorough compensation for atmospheric absorption and scattering. A method for retrieving surface reflectances from spectral data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) is being developed. In this method, the integrated water vapor amount on a pixel by pixel basis is derived from the 0.94- and 1.14-micrometer water vapor features. The water vapor, carbon dioxide (CO2), oxygen (O2) and methane (CH4) transmission spectrum in the 0.4-2.5 micrometer region is calculated. The derived water vapor value and the solar and observational geometry are used in the spectral calculation. The AVIRIS spectrum is ratioed against the transmission spectrum to obtain the surface reflectance spectrum. Major mineral absorption features near 2.2 micrometer in retrieved reflectance spectra can be identified. Different vegetation absorption characteristics are observed. At present, the method is most useful for deriving surface reflectances from AVIRIS data measured on clear days with high visibilities. Atmospheric scattering effects will be included in our spectral calculations in the near future.

Gao, Bo-Cai↗

The violet absorber on Io: Disulfur monoxide derivatives

Following the Voyager flybys of Jupiter it was generally accepted that the surface of Io is covered with SO2 frost and elemental sulfur. However, several difficulties have recently become apparent with this hypothesis. The S2O, which is readily formed under a variety of conditions from the dissociation of SO2, may be an important compound on Io, but at that time no reflectance data on the frost was available. The reflectance spectra of S2O/SO2 mixtures as low temperature frosts and their derivatives, polysulfur oxides, were measured at a variety of temperatures. Specific features possessed by these frosts and identified on Io are bands at 340 nm and 440 nm and a maximum at 800 nm, with decreasing IR reflectance. Thus, this material can account for many of the features in the spectrum of Io. So S2O rather than elemental S is probably the reddening agent on Io, and there is presently no good evidence for S on the surface.

Hapke, B.↗

Use of near infrared correlation spectroscopy for quantitation of surface iron, absorbed water and stored electronic energy in a suite of Mars soil analog materials

A number of questions concerning the surface mineralogy and the history of water on Mars remain unresolved using the Viking analyses and Earth-based telescopic data. Identification and quantitation of iron-bearing clays on Mars would elucidate these outstanding issues. Near infrared correlation analysis, a method typically applied to qualitative and quantitative analysis of individual constituents of multicomponent mixtures, is adapted here to selection of distinctive features of a small, highly homologous series of Fe/Ca-exchanged montmorillonites and several kalinites. Independently determined measures of surface iron, relative humidity and stored electronic energy were used as constituent data for linear regression of the constituent vs. reflectance data throughout the spectral region 0.68 to 2.5 micrometers. High correlations were found in appropriate regions for all three constituents, though that with stored energy is still considered tenuous. Quantitation was improved using 1st and 2nd derivative spectra. High resolution data over a broad spectral range would be required to quantitatively identify iron-bearing clays by remotely sensed reflectance.

Coyne, Lelia M.↗

Development of a digital data base for reflectance-related soil information

A digital soils data base established for inclusion of soil reflectance data, physical, chemical, and engineering measurements, and site information is discussed. Initial data are taken from 500 soil samples covering the spectral range of 0.5 to 2.3 microns. Information obtained from each observation includes spectral data, and identification records with the soil and spectral observation parameters. The LARSPEC software system is available to retrieve and manipulate information, and scattergrams of identification and spectral data allow the initiation of statistical analyses of soil data. In addition, soil characteristics, graphical displays of reflectance spectra, and identification information examples are given.

Stoner, E. R.↗

Validation of S-NPP VIIRS Day-Night Band and M Bands Performance Using Ground Reference Targets of Libya 4 and Dome C

This paper provides methodologies developed and implemented by the NASA VIIRS Calibration Support Team (VCST) to validate the S-NPP VIIRS Day-Night band (DNB) and M bands calibration performance. The Sensor Data Records produced by the Interface Data Processing Segment (IDPS) and NASA Land Product Evaluation and Algorithm Testing Element (PEATE) are acquired nearly nadir overpass for Libya 4 desert and Dome C snow surfaces. In the past 3.5 years, the modulated relative spectral responses (RSR) change with time and lead to 3.8% increase on the DNB sensed solar irradiance and 0.1% or less increases on the M4-M7 bands. After excluding data before April 5th, 2013, IDPS DNB radiance and reflectance data are consistent with Land PEATE data with 0.6% or less difference for Libya 4 site and 2% or less difference for Dome C site. These difference are caused by inconsistent LUTs and algorithms used in calibration. In Libya 4 site, the SCIAMACHY spectral and modulated RSR derived top of atmosphere (TOA) reflectance are compared with Land PEATE TOA reflectance and they indicate a decrease of 1.2% and 1.3%, respectively. The radiance of Land PEATE DNB are compared with the simulated radiance from aggregated M bands (M4, M5, and M7). These data trends match well with 2% or less difference for Libya 4 site and 4% or less difference for Dome C. This study demonstrate the consistent quality of DNB and M bands calibration for Land PEATE products during operational period and for IDPS products after April 5th, 2013.

radiance↗

Infrared Telescope Facility's Spectrograph Observations of Human-Made Space Objects

Presented here are the results of the Infrared Telescope Facility (IRTF) spectral observations of human-made space objects taken from 2006 to 2008. The data collected using the SpeX infrared spectrograph cover the wavelength range 0.7-2.5 micrometers. Overall, data were collected on 20 different orbiting objects at or near the geosynchronous (GEO) regime. Four of the objects were controlled spacecraft, seven were non-controlled spacecraft, five were rocket bodies, and the final four were cataloged as debris pieces. The remotely collected data are compared to the laboratory-collected reflectance data on typical spacecraft materials, thereby general materials are identified but not specific types. These results highlight the usefulness of observations in the infrared by focusing on features from hydrocarbons, silicon, and thermal emission. The spacecraft, both the controlled and non-controlled, show distinct features due to the presence of solar panels, whereas the rocket bodies do not. Signature variations between rocket bodies, due to the presence of various metals and paints on their surfaces, show a clear distinction from those objects with solar panels, demonstrating that one can distinguish most spacecraft from rocket bodies through infrared spectrum analysis. Finally, the debris pieces tend to show featureless, dark spectra. These results show that the laboratory data in its current state give excellent indications as to the nature of the surface materials on the objects. Further telescopic data collection and model updates to include noise, surface roughness, and material degradation are necessary to make better assessments of orbital object material types. However, based on the current state of the comparison between the observations and the laboratory data, infrared spectroscopic data are adequate to classify objects in GEO as spacecraft, rocket bodies, or debris.

Abercromby, K.↗

United Kingdom Infrared Telescope's Spectrograph Observations of Human-Made Space Objects

Presented here are the results of the United Kingdom Infrared Telescope (UKIRT) spectral observations of human-made space objects taken from 2014 to 2015. The data collected using the UKIRT 1-5 micron Imager Spectrometer (UIST) cover the wavelength range 0.7-2.5 micrometers. Overall, data were collected on 18 different orbiting objects at or near geosynchronous orbit (GEO). Two of the objects are controlled spacecraft, twelve are non-controlled spacecraft, one is a rocket body, and three are cataloged as debris. The remotely collected data are compared to the laboratory-collected reflectance data on typical spacecraft materials; thereby general materials are identified but not specific types. These results highlight the usefulness of observations in the infrared by focusing on features from hydrocarbons and silicon. The spacecraft, both the controlled and non-controlled, show distinct features due to the presence of solar panels whereas the rocket bodies do not. Signature variations between rocket bodies, due to the presence of various metals and paints on their surfaces, show a clear distinction from those objects with solar panels, demonstrating that one can distinguish most spacecraft from rocket bodies through infrared spectrum analysis. Finally, the debris pieces tend to show featureless, dark spectra. These results show that the laboratory data in its current state give well-correlated indications as to the nature of the surface materials on the objects. Further telescopic data collection and model updates to include noise, surface roughness, and material degradation are necessary to make better assessments of orbital object material types. A comparison conducted between objects observed previously with the NASA Infrared Telescope Facility (IRTF) shows similar materials and trends from the two telescopes and different times. However, based on the current state of the model, infrared spectroscopic data are adequate to classify objects in GEO as spacecraft, rocket bodies, or debris.

Buckalew, Brent↗

United Kingdom Infrared Telescope's Spectrograph Observations of Human-Made Space Objects

Presented here are the results of the United Kingdom Infrared Telescope (UKIRT) spectral observations of human-made space objects taken from 2014 to 2015. The data collected using the UIST infrared spectrograph cover the wavelength range 0.7-2.5 micrometers. Overall, data were collected on 18 different orbiting objects at or near the geosynchronous (GEO) regime. Thirteen of the objects are spacecraft, one is a rocket body, and four are cataloged as debris pieces. The remotely collected data are compared to the laboratory-collected reflectance data on typical spacecraft materials; thereby general materials are identified but not specific types. These results highlight the usefulness of observations in the infrared by focusing on features from hydrocarbons and silicon. The spacecraft show distinct features due to the presence of solar panels. Signature variations between rocket bodies, due to the presence of various metals and paints on their surfaces, show a clear distinction from those objects with solar panels, demonstrating that one can distinguish most spacecraft from rocket bodies through infrared spectrum analysis. Finally, the debris pieces tend to show featureless, dark spectra. These results show that the laboratory data in its current state give excellent indications as to the nature of the surface materials on the objects. Further telescopic data collection and model updates to include more materials, noise, surface roughness, and material degradation are necessary to make better assessments of orbital object material types. A comparison conducted between objects observed previously with the NASA Infrared Telescope Facility (IRTF) shows similar materials and trends from the two telescopes and from the two distinct data sets. However, based on the current state of the model, infrared spectroscopic data are adequate to classify objects in GEO as spacecraft, rocket bodies, or debris.

Buckalew, Brent↗

Multiangle Observations of Directional Reflectances of Snow Fields

Accurate measurements of snow areas and surface albedo are crucial to advancing our understanding of the global climate system. This is because of the highly reflective nature of snow combined with its large surface coverage (snow can cover up to 40 % of the Earth's land surface during the Northern Hemisphere winter). The reflectance of snow varies with both solar incidence angle and the viewing angle. Visible sensors with different spatial resolutions have been used to infer the snow parameters. Currently, only nadir-viewing directional reflectance data are available from satellite observations. Observations at multiple angles are needed to infer the hemispheric reflectance albedo of snow fields. We propose to study the directional reflectance of snow fields using POLDER data, which contains information from different viewing angles and polarization. POLDER was successfully launched an the ADEOS-1 satellite in August, 1996, however, because POLDER data are not yet available, data from ASAS, a pointable, airborne spectroradiometer, were used in this study. Data collected over Glacier National Park of Montana show strong angular dependence. Preliminary results confirm the anisotropic nature of the snow reflectance. Knowledge of the bi-directional reflectance function(BDRF) of snow -covered surfaces is the key to developing a true albedo model in the future.

Chang, A.T.C.↗

Kinematics of a large-scale intraplate extending lithosphere: The Basin-Range

Upper lithospheric structure of the Cordilleran Basin Range (B-R) is characterised by an E-W symmetry of velocity layering. The crust is 25 km thick on its eastern active margin, thickening to 30 km within the central portion and thinning to approx. 25 km on the west. Pn velocities of 7.8 to 7.9 km/s characterize the upper mantle low velocity cushion, 7.4 km/s to 7.5 km/s, occurs at a depth of approx. 25 km in the eastern B-R and underlies the area of active extension. An upper-crustal low-velocity zone in the eastern B-R shows a marked P-wave velocity inversion of 7% at depths of 7 to 10 km also in the area of greatest extension. The seismic velocity models for this region of intraplate extension suggest major differences from that of a normal, thermally underformed continental lithosphere. Interpretations of seismic reflection data demonstrate the presence of extensive low-angle reflections in the upper-crust of the eastern B-R at depths from near-surface to 7 to 10 km. These reflections have been interpreted to represent low-angle normal fault detachments or reactivated thrusts. Seismic profiles across steeply-dipping normal faults in unconsolidated sediments show reflections from both planar to downward flatening (listric) faults that in most cases do not penetrate the low-angle detachments. These faults are interpreted as late Cenozoic and cataclastic mylonitic zones of shear displacement.

Smith, R. B.↗

Fusion of AIRSAR and TM Data for Parameter Classification and Estimation in Dense and Hilly Forests

The expanded remotely sensed data space consisting of coincident radar backscatter and optical reflectance data provides for a more complete description of the Earth surface. This is especially useful where many parameters are needed to describe a certain scene, such as in the presence of dense and complex-structured vegetation or where there is considerable underlying topography. The goal of this paper is to use a combination of radar and optical data to develop a methodology for parameter classification for dense and hilly forests, and further, class-specific parameter estimation. The area to be used in this study is the H. J. Andrews Forest in Oregon, one of the Long-Term Ecological Research (LTER) sites in the US. This area consists of various dense old-growth conifer stands, and contains significant topographic relief. The Andrews forest has been the subject of many ecological studies over several decades, resulting in an abundance of ground measurements. Recently, biomass and leaf-area index (LAI) values for approximately 30 reference stands have also become available which span a large range of those parameters. The remote sensing data types to be used are the C-, L-, and P-band polarimetric radar data from the JPL airborne SAR (AIRSAR), the C-band single-polarization data from the JPL topographic SAR (TOPSAR), and the Thematic Mapper (TM) data from Landsat, all acquired in late April 1998. The total number of useful independent data channels from the AIRSAR is 15 (three frequencies, each with three unique polarizations and amplitude and phase of the like-polarized correlation), from the TOPSAR is 2 (amplitude and phase of the interferometric correlation), and from the TM is 6 (the thermal band is not used). The range pixel spacing of the AIRSAR is 3.3m for C- and L-bands and 6.6m for P-band. The TOPSAR pixel spacing is 10m, and the TM pixel size is 30m. To achieve parameter classification, first a number of parameters are defined which are of interest to ecologists for forest process modeling. These parameters include total biomass, leaf biomass, LAI, and tree height. The remote sensing data from radar and TM are used to formulate a multivariate analysis problem given the ground measurements of the parameters. Each class of each parameter is defined by a probability density function (pdf), the spread of which defines the range of that class. High classification accuracy results from situations in which little overlap occurs between pdfs. Classification results provide the basis for the future work of class-specific parameter estimation using radar and optical data. This work was performed in part by the Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, and in part by the NASA Ames Research Center, Moffett Field, CA, both under contract from the National Aeronautics and Space Administration.

Moghaddam, Mahta↗

Algorithm for Automated Detection of Edges of Clouds

An algorithm processes cloud-physics data gathered in situ by an aircraft, along with reflectivity data gathered by ground-based radar, to determine whether the aircraft is inside or outside a cloud at a given time. A cloud edge is deemed to be detected when the in/out state changes, subject to a hysteresis constraint. Such determinations are important in continuing research on relationships among lightning, electric charges in clouds, and decay of electric fields with distance from cloud edges.

Ward, Jennifer G.↗

Evaluation and Validation of a High Spatial Resolution Satellite Soil Moisture Product over the Continental United States

The soil moisture (SM) data retrieved from the Soil Moisture Active and Passive (SMAP) satellite are available at a 9 km grid spacing since April 2015. This product can provide valuable information for research and applications in hydrology and other related fields. However, the resolution may be too coarse for applications at catchment or field scale. In this study, an established downscaling methodology, which had a major modification regarding its application on the SMAP 33 km domain, was implemented to develop a 1 km soil moisture product based on the SMAP 9 km data. The algorithm proposed here is based on the thermal inertia principle and developed by modeling the relationship between surface temperature difference and SM for different Normalized Difference Vegetation Index (NDVI) classes. The model functions were established and tuned using data from the NASA’s Land Information System (LIS) North America Land Data Assimilation System (NLDAS) and remotely sensed VISible/InfRared (VIS/IR) reflectance data from Long Term Data Record (LTDR) AVHRR (Advanced Very High Resolution Radiometer) for the growing season months of April-September 1981–2018. These were then implemented using the MODIS (Moderate Resolution Imaging Spectroradiometer) data over the Continental United States (CONUS) domain. Validation activities were carried out using in situ measurements distributed through the International Soil Moisture Network (ISMN). The validation results computed using the 1 km SM data showed that the R2, unbiased RMSE (root mean square error) and bias were improved relative to the 9 km SMAP product by 0.045, 0.018m3/m3 and 0.001m3/m3, respectively. The 1 km SM also exhibited a strong time-series autocorrelation. Further accuracy assessment analyses indicated that precipitation might contribute to the uncertainties in both the 9 km SMAP and 1 km downscaled SMAP SM products.

SMAP↗