Search NASA⌕ Search

SEARCH · Search NASA

Results for “Spectral discrimination”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Radiobrightness of diurnally heated, freezing soil

Freezing and thawing soils exhibit unique radiometric characteristics. To examine these characteristics, diurnal insolation is modeled as one-dimensional heating of a moist soil half-space during a typical fall at a northern Great Plains site. The one-dimensional heat flow equation is nonlinear because both the enthalpy (the change in internal energy with temperature at constant pressure) and the thermal conductivity of freezing soils are nonlinear functions of temperature. The problem is particularly difficult because phase boundaries propagate in time, and because soils, particularly clay-rich soils, freeze over a range of temperatures rather than at 0 C. Diurnal radiobrightness curves at 10.7, 18.0, and 37.0-GHz were computed for each month. The 37.0-GHz radiobrightness best tracks soil surface temperature; the 10.7-37.0-GHz spectral gradient of thawed soils is strongly positive; the spectral gradient of frozen soils is slightly negative; and the midnight-to-noon spectral gradient is shifted by approximately +0.1 K/GHz by diurnal changes in the surface temperature and the thermal gradient. These observations support the use of the scanning multichannel microwave radiometer 37.0-GHz radiobrightness and its 10.7-37.0-GHz spectral gradient as discriminants in a frozen soil classifier for high-latitude prairie.

England, Anthony W.↗
NASA NTRS1985

Remote sensing of wetland biomass and productivity for global biosystem research

The study of ecosystem function and the contributions of particular ecosystems to global elemental cycling will require data collection from orbital platforms. Presently used ground sampling techniques are not adequate for large area vegetation assessments. The research was directed toward an understanding of the relationship between spectral radiance and plant canopy biomass. Changes in the architecture of the canopy alters the observed spectral radiance patterns. The green components of a plant canopy interacts most strongly with incident radiation and usually reflect edaphic conditions as they relate to plant vigor. Plant biomass serves as an excellent integrator of the environmental factors encountered by the plant and can be used as an indicator for predicting soil redox, nutrient status, microbial activity, etc. The use was examined of TM spectral data to discriminate biomass classes and, in turn, to relate the biomass classes to the chemical status of the soil. Several preliminary studies have indicated that solar angle can be used to improve biomass predictions. This important observation also suggests that latitudinal extrapolation of the biomass predicting models will be possible if selected characteristics of the incident radiation are known.

Hardisky, M. A.↗
NASA NTRS1980

Development of a universal water signature for the LANDSAT-3 Multispectral Scanner, part 1

A generalized four channel hyperplane to discriminate water from nonwater was developed using LANDSAT-3 multispectral scaner (MSS) scenes and matching same/next day color infrared aerial photography. The MSS scenes varied in sun elevation angle from 40 to 58 deg. The 28 matching air photo frames contained over 1400 water bodies larger than one surface acre. A preliminary water discriminant, was used to screen the data and eliminate from further consideration all pixels distant from water in MSS spectral space. A linear discriminant was iteratively fitted to the labelled pixels. This discriminant correctly classified 98.7% of the water pixels and 98.6% of the nonwater pixels. The discriminant detected 91.3% of the 414 water bodies over 10 acres in surface area, and misclassified as water 36 groups of contiguous nonwater pixels.

Schlosser, E. H.↗
NASA NTRS1991

Inferring vegetation characteristics using a knowledge-based system

A knowledge-based system for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input is developed. A portion of this system has been developed to discriminate between user-defined vegetation classes using spectral and directional reflectance relationships. This discrimination program was used to classify targets into user-defined ground cover and plant height classes. The program learns class descriptors from samples (both positive and negative) of spectral, directional reflectance data of natural surfaces (bare soils, natural vegetation, and agricultural vegetation). The system is designed to handle any combination of directional view angles. The explicit relationships used in the class descriptions include greater-than relationships between combinations of two view angles and maximum and minimum value relationships. The class descriptions are used to classify an unknown target using the same directional views. The program was tested by learning class descriptions of various categories of percent ground cover and vegetation height.

Kimes, D. S.↗
NASA NTRS1972

Multispectral discrimination of possible Martian surface constituents.

In the 1970s attempts will be made to soft-land scientific instruments on the surface of Mars. The question of the employment of several spectral bands to improve discrimination is investigated. The studies conducted are concerned with the development of a technique for selecting color bands for a lander imaging system. Other study objects include the investigation of certain solid state detectors and the determination of the feasibility of minimizing the total number of telemetry bits from the lander by various means.

Klemas, V.↗
NASA NTRS1991

Discrimination of active and inactive sand from remote sensing - Kelso dunes, Mojave Desert, California

Landsat TM images, field data, and laboratoray reflectance spectra were examined for the Kelso dunes, Mojave Desert, California to assess the use of visible and near-infrared (VNIR) remote sensing data to discriminate aeolian sand populations on the basis of spectral brightness. Results show that areas of inactive sand have a larger percentage of dark, fine-grained materials compared to those composed of active sand, which contain less dark fines and a higher percentage of quartz sand-size grains. Both areas are spectrally distinct in the VNIR, suggesting that VNIR spectral data can be used to discriminate active and inactive sand populations in the Mojave Desert. Analysis of laboratory spectra was complicated by the presence of magnetite in the active sands, which decreases their laboratory reflectance values to those of inactive sands. For this application, comparison of TM and laboratory spectra suggests that less than 35 percent vegetation cover does not influence the TM spectra.

Paisley, Elizabeth C. I.↗
NASA NTRS1993

The red edge in arid region vegetation: 340-1060 nm spectra

The remote sensing study of vegetated regions of the world has typically been focused on the use of broad-band vegetation indices such as NDVI. Various modifications of these indices have been developed in attempts to minimize the effect of soil background, e.g., SAVI, or to reduce the effect of the atmosphere, e.g., ARVI. Most of these indices depend on the so-called 'red edge,' the sharp transition between the strong absorption of chlorophyll pigment in visible wavelengths and the strong scattering in the near-infrared from the cellular structure of leaves. These broadband indices tend to become highly inaccurate as the green canopy cover becomes sparse. The advent of high spectral resolution remote sensing instrument such as the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) has allowed the detection of narrow spectral features in vegetation and there are reports of detection of the red edge even for pixels with very low levels of green vegetation cover by Vane et al. and Elvidge et al., and to characterize algal biomass in coastal areas. Spectral mixing approaches similar to those of Smith et al. can be extended into the high spectral resolution domain allowing for the analysis of more endmembers, and potentially, discrimination between material with narrow spectral differences. Vegetation in arid regions tends to be sparse, often with small leaves such as the creosote bush. Many types of arid region vegetation spend much of the year with their leaves in a senescent state, i.e., yellow, with lowered chlorophyll pigmentation. The sparseness of the leaves of many arid region plants has the dual effect of lowering the green leaf area which can be observed and of allowing more of the sub-shrub soil to be visible which further complicates the spectrum of a region covered with arid region vegetation. Elvidge examined the spectral characteristics of dry plant materials showing significant differences in the region of the red edge and the diagnostic ligno-cellulose absorptions at 2090 nm and 2300 nm. Ray et al. detected absorption at 2100 nm in AVIRIS spectra of an abandoned field known to be covered by a great deal of dead plant litter. In order to better study arid region vegetation remote sensing data, it is necessary to better characterize the reflectance spectra of in situ, living, arid region plants.

Ray, Terrill W.↗
NASA NTRS1986

Discrimination of lithologic units using geobotanical and LANDSAT TM spectral data

Thematic Mapper (TM) spectral data were correlated with lithologic units, geobotanical forest associations, and geomorphic site parameters in the Ridge and Valley Province of Pennsylvania. Both the TM and forest association data can be divided into four groups based on their lithology (sandstone or shale) and geomorphic aspect (north or south facing). In this clastic sedimentary terrane, geobotanical associations are useful indicators of lithology and these different geobotanical associations are detectable in LANDSAT TM data.

Birnie, R. W.↗
NASA NTRS1986

Discrimination of natural and cultivated vegetation using Thematic Mapper spectral data

The availability of high quality spectral data from the current suite of earth observation satellite systems offers significant improvements in the ability to survey and monitor food and fiber production on both a local and global basis. Current research results indicate that Landsat TM data when used in either digital or analog formats achieve higher land-cover classification accuracies than MSS data using either comparable or improved spectral bands and spatial resolution. A review of these quantitative results is presented for both natural and cultivated vegetation.

Degloria, Stephen D.↗
NASA NTRS1992

Discrimination among semi-arid landscape endmembers using the Spectral Angle Mapper (SAM) algorithm

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were acquired during three consecutive seasons of the year (26 Sep. 1989, 22 Mar. 1990, and 7 Aug. 1990) over an area of the High Plains east of Greeley, Colorado. This region contains extensive eolian deposits in the form of stabilized dune complexes (small scale parabolic dunes superimposed on large scale longitudinal and parabolic dunes). Due to the dunes' large scale (2-10 km) and low relief (1-5 m), the scaling relationships that contribute to the evolution of this landscape are nearly impossible to understand without the use of remote sensing. Additionally, climate models indicate that the High Plains could be one of the first areas to experience changes in climate caused by either global warming or cooling. During the past 10,000 years there were at least three periods of extensive sand activity, followed by periods of landscape stability, as shown in the stratigraphic record of this area. Therefore, if the past is an indication of the future, the monitoring of this landscape and its sensitive ecosystem is important for early detection of regional and global climate change.

Yuhas, Roberta H.↗
NASA NTRS1979

An evaluation of Landsat 3 RBV imagery for an area of complex terrain in Southern Italy

Return Beam Videcon imagery from Landsat 3 was obtained in August, 1978 for part of Southern Italy in the regions of Basilicata and Apulia. The resolution of this imagery for medium contrast objects is approximately 40 meters and is shown to provide significant information concerning land cover and fluvial morphometry. Because of the wide spectral band width which is sensed (0.505-0.750 microns) by the RBV cameras, discrimination is only possible for spectrally distinct cover types, especially oak woodland. Fluvial morphometry can be readily described using the imagery. Because of the intense dissection of the area, the lowest order streams cannot be consistently mapped, but the rank order of the measured values of properties such as drainage density and link frequency for different lithologies corresponds closely to the actual ranking.

Townshend, J. R. G.↗
NASA NTRS2011

Performance of the QWIP Focal Plane Arrays for NASA's Landsat Data Continuity Mission

The focal plane assembly for the Thermal Infrared Sensor (TIRS) instrument on NASA's Landsat Data Continuity Mission (LDCM) consists of three 512 x 640 GaAs Quantum Well Infrared Photodetector (QWIP) arrays. The three arrays are precisely mounted and aligned on a silicon carrier substrate to provide a continuous viewing swath of 1850 pixels in two spectral bands defined by filters placed in close proximity to the detector surfaces. The QWIP arrays are hybridized to Indigo ISC9803 readout integrated circuits (ROICs). QWIP arrays were evaluated from four laboratories; QmagiQ, (Nashua, NH), Army Research Laboratory, (Adelphi, MD}, NASA/ Goddard Space Flight Center, (Greenbelt, MD) and Thales, (Palaiseau, France). All were found to be suitable. The final discriminating parameter was the spectral uniformity of individual pixels relative to each other. The performance of the QWIP arrays and the fully assembled, NASA flight-qualified, focal plane assembly will be reviewed. An overview of the focal plane assembly including the construction and test requirements of the focal plane will also be described.

Jhabvala, M.↗
NASA NTRS1985

Thermal Infrared Geologic Remote Sensing Research at the Jet Propulsion Laboratory

Remotely sensed thermal infrared spectral data have great potential to improve rock type discrimination if the factors that control thermal infrared spectral reflection and emission can be better understood. Improved rock type discrimination in turn leads to better and more efficient geologic mapping which is carried out in the exploration, assessment and documentation of mineral resources and geologic hazards. Geologic maps also contribute significantly to the understanding of the natural history of the Earth and neighboring planetary bodies.

Bartholomew, M. J.↗
NASA NTRS1997

Development and Operation of a Material Identification and Discrimination Imaging Spectroradiometer

Many imaging applications require quantitative determination of a scene's spectral radiance. This paper describes a new system capable of real-time spectroradiometric imagery. Operating at a full-spectrum update rate of 30Hz, this imager is capable of collecting a 30 point spectrum from each of three imaging heads: the first operates from 400 nm to 950 nm, with a 2% bandwidth; the second operates from 1.5 micro-m to 5.5 micro-m with a 1.5% bandwidth; the third operates from 5 micro-m to 12 micro-m, also at a 1.5% bandwidth. Standard image format is 256 x 256, with 512 x 512 possible in the VIS/NIR head. Spectra of up to 256 points are available at proportionately lower frame rates. In order to make such a tremendous amount of data more manageable, internal processing electronics perform four important operations on the spectral imagery data in real-time. First, all data in the spatial/spectral cube of data is spectro-radiometrically calibrated as it is collected. Second, to allow the imager to simulate sensors with arbitrary spectral response, any set of three spectral response functions may be loaded into the imager including delta functions to allow single wavelength viewing; the instrument then evaluates the integral of the product of the scene spectral radiances and the response function. Third, more powerful exploitation of the gathered spectral radiances can be effected by application of various spectral-matched filtering algorithms to identify pixels whose relative spectral radiance distribution matches a sought-after spectral radiance distribution, allowing materials-based identification and discrimination. Fourth, the instrument allows determination of spectral reflectance, surface temperature, and spectral emissivity, also in real-time. The spectral imaging technique used in the instrument allows tailoring of the frame rate and/or the spectral bandwidth to suit the scene radiance levels, i.e., frame rate can be reduced, or bandwidth increased to improve SNR when viewing low radiance scenes. The unique challenges of design and calibration are described. Pixel readout rates of 160 MHz, for full frame readout rates of 1000 Hz (512 x 512 image) present the first challenge; processing rates of nearly 600 million integer operations per second for sensor emulation, or over 2 billion per second for matched filtering, present the second. Spatial and spectral calibration of 66,536 pixels (262,144 for the 512 x 512 version) and up to 1,000 spectral positions mandate novel decoupling methods to keep the required calibration memory to a reasonable size. Large radiometric dynamic range also requires care to maintain precision operation with minimum memory size.

Dombrowski, Mark↗
NASA NTRS1972

Near infrared iron absorption bands: Applications to geologic mapping and mineral exploration

A spectroscopic analysis of the difference in reflectance of iron-rich and iron-poor minerals was made. Attempts were made to use these minima contrast in geological mapping and metallic mineral exploration of large areas from near infrared and visible satellite images. Data cover pertinent laboratory spectroscopic investigations, applications of spectral differences to the discrimination of two important metamorphic rock types, and mineral exploration by aircraft in Beartooth Mountains, Montana.

Rowan, L. C.↗
NASA NTRS2018

Compensation of Oxygen Transmittance Effects for Proximal Sensing Retrieval of Canopy-Leaving Sun-Induced Chlorophyll Fluorescence

Estimates of Sun-Induced vegetation chlorophyll Fluorescence (SIF) using remote sensing techniques are commonly determined by exploiting solar and/or telluric absorption features. When SIF is retrieved in the strong oxygen (O2) absorption features, atmospheric effects must always be compensated. Whereas correction of atmospheric effects is a standard airborne or satellite data processing step, there is no consensus regarding whether it is required for SIF proximal-sensing measurements nor what is the best strategy to be followed. Thus, by using simulated data, this work provides a comprehensive analysis about how atmospheric effects impact SIF estimations on proximal sensing, regarding: (1) the sensor height above the vegetated canopy; (2) the SIF retrieval technique used, e.g., Fraunhofer Line Discriminator (FLD) family or Spectral Fitting Methods (SFM); and (3) the instrument's spectral resolution. We demonstrate that for proximal-sensing scenarios compensating for atmospheric effects by simply introducing the O2 transmittance function into the FLD or SFM formulations improves SIF estimations. However, these simplistic corrections still lead to inaccurate SIF estimations due to the multiplication of spectrally convolved atmospheric transfer functions with absorption features. Consequently, a more rigorous oxygen compensation strategy is proposed and assessed by following a classic airborne atmospheric correction scheme adapted to proximal sensing. This approach allows compensating for the O2 absorption effects and, at the same time, convolving the high spectral resolution data according to the corresponding Instrumental Spectral Response Function (ISRF) through the use of an atmospheric radiative transfer model. Finally, due to the key role of O2 absorption on the evaluated proximal-sensing SIF retrieval strategies, its dependency on surface pressure (p) and air temperature (T) was also assessed. we combined simulated spectral data with p and T measurements obtained for a one-year period in the Hyytiala Forestry Field Station in Finland. Of importance hereby is that seasonal dynamics in terms of T and p, if not appropriately considered as part of the retrieval strategy, can result in erroneous SIF seasonal trends that mimic those of known dynamics for temperature-dependent physiological responses of vegetation.

"sun–induced chlorophyll fluorescence (SIF); pro↗