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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Association of spectral development patterns with development stages of corn

Association is made between the development stages of corn as defined by Hanway and the temporal-spectral development pattern of corn in a transformed data space derived from Landsat-MSS band reflectance values, using field-collected reflectance and associated data. Results indicate that the spectral vegetation index used (a reflectance equivalent of Tasseled Cap Greenness) reaches a maximum well before the stage at which corn is expected to achieve its peak leaf area index. Possible physiological and canopy geometry related causes for this and other results are presented.

Crist, E. P.↗
NASA NTRS1983

Evaluation of spatial, radiometric and spectral thematic mapper performance for coastal studies

An area along the southeastern shore of the Chesapeake Bay was subsetted from TM imagery. The subsetted image was then enhanced and classified using an ERDAS 400 system. Results obtained were compared with a chart showing the distribution of both Zolsters marina and Rupplia martime in the Vaucluse Shores and which supports a large community of SAV. Radiative transfer models describing the irradiance reflectance of a water column containing SAV are being refined. Radiative transfer theory was used to model upwelling radiance for an orbiting sensor viewing an estuarine environment. Upwelling radiance was calculated for a clear maritime atmosphere, an optically shallow estuary of either clear or turbid water, and one of three bottom types: vegetation, sand, or mud using TM bands 1, 2, and 3 and MSS bands 4 and 5. A spectral quality index was defined similar to the equation for apparent contrast and used to evaluate the relative effectiveness of TM and MSS bands in detecting submerged vegetation.

Klemas, V.↗
NASA NTRS1985

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

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

Goward, S. N.↗
NASA NTRS1985

Analysis of Terrestrial Conditions and Dynamics

An ecological model is developed to estimate annual net primary productivity of vegetation in twelve major North American biomes. Three models are adapted and combined, each addressing a different factor known to govern primary productivity, i.e., photosynthesis, respiration, and moisture availability. Measures of intercepted photosynthetically active radiation (1PAR) for input to the photosynthesis model are derived from spectral vegetation index data. Normalized Difference Vegetation Index (NDVI) data are produced from NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) observations for April 1982 through March 1983. NDVI values are sampled from within the biomes at locations for which climatological data are available. Monthly estimates of Net Primary Productivity (NPP) for each sample location are generated and summed over the twelve month period. These monthly estimates are averaged to produce a single annual estimated NPP value for each biomes. Comparison of estimated NPP values with figures reported in the literature produces a correlation coefficient of 85.

Goward, S. N.↗
NASA NTRS1987

Evaluating North American net primary productivity with satellite observations

An ecological model is developed to estimate annual net primary productivity (NPP) in 12 North American biomes. The model combines existing models which address canopy photosynthesis in response to light, temperature, and moisture availability, and account for respiration. Climate data, solar radiation data, and spectral vegetation index data are utilized. Estimates of NPP from the model compare well with data in the literature, but a systematic error is suspected. Difficulties encountered in specifying certain model parameters are discussed as possible sources of this error. The results of this study suggest the promise of remotely sensed measurements for macroscale evaluation and modeling of NPP.

Goward, Samuel N.↗
NASA NTRS1985

The relationship of global green leaf biomass to atmospheric CO2 concentrations

Advanced very high resolution radiometer data from NOAA's polar orbiting meteorological satellite have been obtained globally for a 21 month period, processed to produce a green leaf biomass spectral vegetative index for the entire terrestrial surface by month, zonally aggregated by latitude, and compared to atmospheric CO2 concentrations from observing stations. A strong inverse association was found between the monthly Pt. Barrow CO2 concentrations and the vegetation index measurements from 50 deg N to 80 deg N, between the monthly Mauna Loa CO2 concentrations and the vegetation index measurements from 10 deg N to 30 deg N, 10 deg N to 80 deg N, and the global total, and between the globally averaged CO2 concentrations and the globally averaged vegetation index. No relationships between atmospheric CO2 concentrations and the vegetative index measurements from any latitude zone or combinations of zones were found for the South Pole station.

Tucker, C. J.↗
NASA NTRS1997

Surface Energy Heat Fluxes Using Remotely Sensed Parameters

Realistic estimates of surface energy heat fluxes are needed for the study of water and energy interactions between the land and atmosphere. The primary objective of this work is to study the estimation of surface heat energy fluxes using remote sensing derived parameters under different spatial and temporal conditions. Surface energy fluxes and remote sensing derived data from two sources were analyzed. First, we used surface heat flux, remote sensing, and ancillary data from the International Satellite Land Surface Climatology Project (ISLSCP), mapped at a 1 deg. x 1 deg. grid. Second, we used NOAA AVHRR (1 km), weather station, and ancillary data to derive estimates of surface latent and sensible heat energy fluxes over a 100 sq kilometers area for three test sites: 1) First ISLSCP Field Experiment (FIFE) grassland site, Konza Prairie, Kansas; 2) Howland, Maine Forest Ecosystem Dynamics Site; and 3) Walnut Gulch, scrubland site, surrounding Tombstone, Arizona. Satellite derived estimates of land surface temperature, surface albedo, and spectral vegetation index are used in selected models to provide estimates of surface heat fluxes. Analysis of results from the 1 deg. x 1 deg. grid for North America indicated there were similar, overall correlations between sensible and latent heat energy fluxes versus remotely sensed vegetation index and ground temperature during dry and wet year conditions. However, there were significant differences in correlations between years when stratified by land cover class. Analysis of 100 km x 100 km data (1 km resolution) indicated partitioning the areas in to primary versus secondary cover, with the secondary cover comprising less than 5% of the area, significantly improved surface heat energy flux estimates.

Toll, David L.↗
NASA NTRS1995

Preliminary Results of the Analysis

The preliminary results of the photometry of CaII K spectroheliograms taken at the NationalSolar Observatory at Sacramento peak are presented in this paper. We have digitizedspectroheliograms for 1980 (maximum of SC21), 1985 (minimum of SC21), 1987 (beginning of theascending phase of SC22), 1988 and 1989 (ascending phase and maximum of SC22), and 1992(declining phase of SC22). We have analyzed images for 1992 and separated the plages, the magneticnetwork, internetwork elements and the chromospheric background using histogram method. Wehave derived the intensity and area of these features as well as the full disk intensity (Spatial KIndex). The Spatial K Index has been compared to the spectral Ca K index derived from the lineprofiles and total solar and UV irradiance measured by the UARS and NOAA9 satellites. Thecontribution of plages, the magnetic network and internetwork element to the changes observed intotal solar and UV irradiances are also estimated.

CaII K Spectroheliograms↗
NASA NTRS2007

Assessing North American Forest Disturbance from the Landsat Archive

Forest disturbances are thought to play a major role in controlling land-atmosphere fluxes of carbon. Under the auspices of the North American Carbon Program, the LEDAPS (Landsat Ecosystem Disturbance Adaptive Processing System) and NACP-FIA projects have been analyzing the Landsat satellite record to assess rates of forest disturbance across North America. In the LEDAPS project, wall-to-wall Landsat imagery for the period 1975-2000 has been converted to surface reflectance and analyzed for decadal losses (disturbance) or gains (regrowth) in biomass using a spectral "disturbance index". The NACP-FIA project relies on a geographic sample of dense Landsat image time series, allowing both disturbance rates and recovery trends to be characterized. Preliminary results for the 1990's indicate high rates of harvest within the southeastern US, Eastern Canada, and the Pacific Northwest, with spatially averaged (approx.50x50 km) turnover periods as low as 25-40 years. Lower rates of disturbance are found in the Rockies and Northeastern US.

Masek, Jeffrey G.↗
NASA NTRS2009

90 GHz and 150 GHz Observations of the Orion M42 Region. A Submillimeter to Radio Analysis

We have used the new 90GHz MUSTANG camera on the Robert C. Green Bank Telescope (GBT)to map the bright Huygens region of the star-forming region M42 with a resolution of 9" and a sensitivity of 2.8 mJy/beam. Ninety GHz is an interesting transition frequency, as MUSTANG detects both the free-free emission characteristic of the H II region created by the Trapezium stars, normally seen at lower frequencies, and thermal dust emission from the background OMCI molecular cloud, normally mapped at higher frequencies. We also present similar data from the 150 GHz GISMO camera taken on the IRAM 30 m telescope. This map has 15" resolution. By combining the MUSTANG data with 1.4, 8. and 31 GHz radio data from the VLA and GBT, we derive a new estimate of the emission measure averaged electron temperature of T(sub e) = 11376+/-1050 K by an original method relating free-free emission intensities at optically thin and optically thick frequencies. Combining Infrared Space Observatory-long wavelength spectrometer (ISO-LWS) data with our data, we derive a new estimate of the dust temperature and spectral emissivity index within the 80" ISO-LWS beam toward Orion KL/BN, T(sub d) = 42+/-3 K and Beta(sub d) = 1.3+/-0.1. We show that both T(sub d) and Beta(sub d) decrease when going from the H II region and excited OMCI interface to the denser UV shielded part OMCI (Orion KL/BN, Orion S). With a model consisting of only free-free and thermal dust emission, we are able to fit data taken at frequencies from 1.5 GHz to 854 GHz (350 micrometers).

Dicker, S. 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 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↗
DOE OSTI2023

Elastomeric reflection suppressor

Various embodiments of the present technology generally relate to reflection suppressors. More specifically, some embodiments use elastomeric materials doped with optical absorbers for temporary suppression of Fresnel reflections for multiple substrates spanning wide spectral and angular bandwidth. The refractive index of the elastomer can be tuned to match a substrate and thereby minimize reflection. Some embodiments can use the addition of different absorptive dopants to allow for either broadband or wavelength-selective reflection suppression. As performance is limited only by index mismatch, both spectral and angular performance significantly exceed that of anti-reflection coatings. After use, these light traps may be removed and reused without damaging the substrate. These films have uses in spectroscopic ellipsometry, holography, and lithography.

Miller, David↗
NASA NTRS2011

The Solar Spectral Irradiance as a Function of the Mg II Index for Atmosphere and Climate Modelling

In this paper we present a new method to reconstruct the solar spectrum irradiance in the Ly alpha-400 nm region, and its variability, based on the Mg II index and neutron monitor. Measurements of the solar spectral irradiance available in the literature have been made with different instruments at different times and different spectral ranges. However, climate studies require harmonized data sets. This new approach has the advantage of being independent of the absolute calibration and aging of the instruments. First, the Mg II index is derived using solar spectra from Ly alpha (121 nm) to 410 nm measured from 1978 to 2010 by several space missions. The variability of the spectra with respect to a chosen reference spectrum as a function of time and wavelength is scaled to the derived Mg II index. The set of coefficients expressing the spectral variability can be applied to the chosen reference spectrum to reconstruct the solar spectra within a given time frame or Mg II index values. The accuracy of this method is estimated using two approaches: by direct comparison with particular cases where solar spectra are available from independent measurements, and by calculating the standard deviation between the measured spectra and their reconstruction. From direct comparisons with measurements we obtain an accuracy of about 1 to 2 %, which degrades towards Ly alpha. In a further step, we extend our solar spectral irradiance reconstruction back to the Maunder Minimum introducing the relationship between the Mg II index and the neutron monitor data. Consistent measurements of the Mg II index are not available prior to 1978. However, we observe that over the last three solar cycles, the Mg II index shows strong correlation with the modulation potential determined from the neutron monitor data. Assuming that this correlation can be applied to the past, we reconstruct the Mg II index from the modulation potential back to the Maunder Minimum, and obtain the corresponding solar spectral irradiance reconstruction back to that period. As there is no direct measurement of the spectral irradiance for this period we discuss this methodology in light of the other proposed approaches available in the literature. The use of the cosmogenic isotope data provides a major advantage: it provides information about the solar activity over several thousands years. Using technology of today we can calibrate the solar irradiance against the activity and thus reconstruct it for the times when cosmogenic isotope data are available. This calibration can be re-accessed at any time, if necessary.

Thuillier, Gerard↗
NASA NTRS1978

Retrieving the complex refractive index of atmospheric aerosols from ratios of solar spectral extinction measurements

The technique proposed by Fymat (1976) for retrieving the complex refractive index of atmospheric aerosols using narrowband spectral transmission ratios, taken within an overall narrow spectral interval, is investigated in the case of modelled polydispersions of rural, maritime-continental, maritime-sea spray and meteoric dust aerosols. It is confirmed that for not too broad size distributions most of the information comes from a narrow size range of 'active' aerosols so that, under these circumstances, the refractive index components can indeed be retrieved essentially independently of the size distribution. For 0.1% accurate data in three colors, the technique can provide the real and imaginary components of the index respectively within 0.07% and 0.3% accuracy.

Fymat, A. L.↗
NASA NTRS1995

Is walking a random walk? Evidence for long-range correlations in stride interval of human gait

Complex fluctuation of unknown origin appear in the normal gait pattern. These fluctuations might be described as being (1) uncorrelated white noise, (2) short-range correlations, or (3) long-range correlations with power-law scaling. To test these possibilities, the stride interval of 10 healthy young men was measured as they walked for 9 min at their usual rate. From these time series we calculated scaling indexes by using a modified random walk analysis and power spectral analysis. Both indexes indicated the presence of long-range self-similar correlations extending over hundreds of steps; the stride interval at any time depended on the stride interval at remote previous times, and this dependence decayed in a scale-free (fractallike) power-law fashion. These scaling indexes were significantly different from those obtained after random shuffling of the original time series, indicating the importance of the sequential ordering of the stride interval. We demonstrate that conventional models of gait generation fail to reproduce the observed scaling behavior and introduce a new type of central pattern generator model that sucessfully accounts for the experimentally observed long-range correlations.

Hausdorff, Jeffrey M.↗
NASA NTRS1985

Spectral estimation of green leaf area index of oats

Green leaf area index (LAI) is a measure of vegetative growth and development and is frequently used as an input parameter in yield estimation and evapotranspiration models. Extensive destructive sampling is usually required to achieve accurate estimates of green LAI in natural situations. In this investigation, a statistical modeling approach was used to predict the green LAI of oats from bidirectional reflectance data collected with multiband radiometers. Stepwise multiple regression models based on two sets of spectral reflectance factors accounted for 73 percent and 65 percent of the variance in green LAI of oats. Exponential models of spectral data transformations of greenness, normalized difference, and near-infrared/red ratio accounted for more of the variance in green LAI than the multiple regression models.

Best, R. G.↗