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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Prediction of directional reflectance of a corn field under stress

A vegetative canopy model concept is developed and used to calculate the directional spectral reflectance of a corn field under stress. The problem has been idealized by assuming that the canopy is represented in several layers of uniform but randomly distributed biological components; horizontal and vertical projection of leaves, for example, replaces the actual leaf. An accumulative horizontal projection leads to a quantitative horizontal leaf area index while accumulated vertical projections provide the vertical leaf index area for each layer. The spectral properties of the projections are obtained from the spectral properties of the biological components. These techniques together with soil reflectance data provide a physical description for the vegetative canopy and adequately interprete multispectral scanning data.

Suits, G. H.↗
NASA NTRS1989

A global climatology of albedo, roughness length and stomatal resistance for atmospheric general circulation models as represented by the Simple Biosphere Model (SiB)

Components of the Simple Biosphere Model (SiB) of Sellers et al. (1986) were used to generate global monthly fields of surface albedo (0.4-4.0 microns), roughness length and minimum surface (stomatal) resistance. SiB consists of three submodels which describe the roles of radiative transfer, turbulent transfer and surface resistance in determining the energy balance of the vegetated land surface. These three submodels were detached from SiB and used on the SiB parameter set (total and green leaf area index, leaf angle orientation, canopy dimensions, etc.) to calculate global monthly fields of albedo, roughness length and minimum stomatal resistance at 1 x 1 deg resolution. Time series of various parameters are also displayed for each vegetation type for specified grid points. The SiB results compare reasonably well with appropriate measurements obtained from the literature and have the additional merit of being mutually consistent; the three submodels use many common parameters, which ensures that, for each grid area, the calculated surface properties are closely interrelated as is the case in nature. The derived fields provide a check on the operation of the submodels and the correctness of the parameter set. They can also be used as prescribed fields for GCMs that do not have biophysically based land surface parameterizations.

Dorman, J. L.↗
NASA NTRS1984

Inversion of vegetation canopy reflectance models for estimating agronomic variables. II - Use of angle transforms and error analysis as illustrated by Suits' model

The technique for inverting a vegetation canopy reflectance model described earlier (Goel and Strebel, 1983) is investigated further. The novel concept of an 'angle transform' is introduced. This concept allows the formation of functions of reflectances at different view zenith and azimuth angles, which are either sensitive or insensitive to a certain agronomic parameter. A proper combination of these functions can allow determination of all the important agronomic and spectral parameters from measured canopy reflectance data. The technique is demonstrated using Suits' (1972) model for homogeneous canopies. It is shown that leaf area index, leaf reflectance and transmittance, and average leaf angle all can be determined from the canopy reflectance at a set of selected view zenith and azimuth angles. A sensitivity analysis of the calculated values to the errors in the data is also carried out. Guidelines are formulated for the number and types of observations required to obtain the values of a particular canopy variable to within a given degree of accuracy for a given level of error in the measurement of canopy reflectance.

Goel, N. S.↗
NASA NTRS1985

Inclusion of specular reflectance in vegetative canopy models

A detailed comparison of the observed soybeans and corn canopy reflectance with that calculated from three vegetative canopy reflectance models have shown systematic angular deviations. A likely cause of these effects is noninclusion of leaf specular reflectance. In this paper a formulation to calculate the component of canopy specular reflectance as a function of incident solar and view zenith angles, leaf area index, leaf angle distribution, and leaf specular reflectance has been developed. The SAIL model has been modified to include this component and the results are compared with an extensive observational data set on soybeans. It is shown that the systematic differences between the SAIL model and observations dependent on scattering azimuth are removed. An analysis of variance shows model improvement of 30 percent over the uncorrected SAIL model.

Reyna, E.↗
NASA NTRS1985

Modeling canopy reflectance and microwave backscattering coefficient

Various approaches to model canopy reflectance (CR) in the visible/infrared region and backscattering coefficient (BSC) in the microwave region are compared and contrasted. It is noted that BSC can be related to CR in the source direction (the 'hot spot' direction). By assuming a frequency dependent leaf reflectance and transmittance it is shown that the observed dependence of BSC on leaf area index, leaf angle distribution, angle of incidence, soil moisture content, and frequency can be simulated by a CR model. Thus both BSC and CR can, in principle, be calculated using a single model which has essentially the same parameters as many CR models do.

Goel, N. S.↗
NASA NTRS1987

Hemispherical reflectance variations of vegetation canopies and implications for global and regional budget studies

The hemispherical reflectance (HR) variations of vegetation canopies are studied as a function of solar zenith angle, wavelength, and canopy characteristics (leaf area index, leaf orientation distribution, and leaf and soil optical properties). The radiative transfer model of Kimes (1984) is used to explain the radiative transfers that give rise to variations in the HR for various vegetation canopies as a function of sun angle. The results of this model are compared with those calculated from Sellers' (1985) analytical two-stream approximation. It is noted that the findings have significant implications for a wide range of global and regional energy budget studies.

Kimes, D. S.↗
NASA NTRS2004

Hyperion Studies Of Crop Stress In Mexico

Satellite-based measurements of crop stress could provide much needed information for cropland management, especially in developing countries where other precision agriculture technologies are too expensive (Pierce and Nowak 1999; Robert 2002). For example, detection of areas that are nitrogen deficient or water stressed could guide fertilizer and water management decisions for all farmers within the swath of the satellite. Several approaches have been proposed to quantify canopy nutrient or water content based on spectral reflectance, most of which involve combinations of reflectance in the form of vegetation indices. While these indices are designed to maximize sensitivity to leaf chemistry, variations in other aspects of plant canopies may significantly impact remotely sensed reflectance. These confounding factors include variations in canopy structural properties (e.g., leaf area index, leaf angle distribution) as well as the extent of canopy cover, which determines the amount of exposed bare soil within a single pixel. In order to assess the utility of spectral indices for monitoring crop stress, it is therefore not only necessary to establish relationships at the leaf level, but also to test the relative importance of variations in other canopy attributes at the spatial scale of the remote sensing measurement. In this context, the relative importance of a given attribute will depend on (1) the sensitivity of the reflectance index to variation in the attribute and (2) the degree to which the attribute varies spatially and temporally.

Lobell, David B.↗
NASA NTRS2012

Measuring Gap Fraction, Element Clumping Index and LAI in Sierra Forest Stands Using a Full-Waveform Ground-Based Lidar

The Echidna Validation Instrument (EVI), a ground-based, near-infrared (1064 nm) scanning lidar, provides gap fraction measurements, element clumping index measurements, effective leaf area index (LAIe) and leaf area index (LAI) measurements that are statistically similar to those from hemispherical photos. In this research, a new method integrating the range dimension is presented for retrieving element clumping index using a unique series of images of gap probability (Pgap) with range from EVI. From these images, we identified connected gap components and found the approximate physical, rather than angular, size of connected gap component. We conducted trials at 30 plots within six conifer stands of varying height and stocking densities in the Sierra National Forest, CA, in August 2008. The element clumping index measurements retrieved from EVI Pgap image series for the hinge angle region are highly consistent (R2=0.866) with those of hemispherical photos. Furthermore, the information contained in connected gap component size profiles does account for the difference between our method and gap-size distribution theory based method, suggesting a new perspective to measure element clumping index with EVI Pgap image series and also a potential advantage of three dimensional Lidar data for element clumping index retrieval. Therefore further exploration is required for better characterization of clumped condition from EVI Pgap image series.

Zhao, Feng↗
NASA NTRS1986

Spectral radiance estimates of leaf area and leaf phytomass of small grains and native vegetation

Similarities and/or dissimilarities in radiance characteristics were studied among barley (Hordeum vulgare L.), oats (Avena fatua L.), spring and winter wheat (Triticum aestivum L.), and short-grass prairie vegetation. The site was a Williams loam soil (fine-loamy mixed, Typic Argiborolls) near Sidney, Montana. Radiances were measured with a truck-mounted radiometer. The radiometer was equipped with four wavelength bands: 0.45 to 0.52, 0.52 to 0.60, 0.63 to 0.69, and 0.76 to 0.90 micron. Airborne scanner measurements were made at an altitude of 600 m four times during the season under clear sky conditions. The airborne scanner was equipped with the same four bands as the truck-mounted radiometer plus the following: 1.00 to 1.30, 1.55 to 1.75, 2.08 to 2.35, and 10.4 to 12.5 microns. Comparisons using individual wave bands, the near IR/red, (0.76 to 0.90 micron)/(0.63 to 0.69 micron) ratio and the normalized difference vegetation index, ND = (IR - red)/(IR + red), showed that only during limited times during the growing season were some of the small grains distinguishable from one another and from native rangeland vegetation. There was a common relation for all small grains between leaf area index and green leaf phytomass and between leaf area index or green leaf phytomass and the IR/red ratio.

Aase, J. K.↗
NASA NTRS1974

Wheat - Its growth and disease severity as deduced from ERTS-1

The spectral reflectance of a cropped surface changes as the plant develops. An indicator of crop growth is leaf area index (ratio of green leaf area to soil area). The leaf area index, disease severity, and yield were determined for several winter wheat fields in Kansas during the 1973 growing season. Multispectral scanner (MSS) data from Earth Resources Technology Satellite-1 (ERTS-1) showed a high correlation (r greater than or equal to 0.90) between crop growth and MSS4/MSS5, and crop growth and MSS5/MSS6. Wheat disease severity and yields were significantly correlated at the 5% level with MSS4/MSS6 and with MSS4/MSS7. Further investigation is required before ERTS imagery can be routinely used detecting and estimating disease severity and yield reduction.

Kanemasu, E. T.↗
NASA NTRS1981

Temporal relationships between spectral response and agronomic variables of a corn canopy

Attention is given to an experiment in which spectral radiance data collected in three spectral regions are related to corn canopy variables. The study extends the work of Tucker et al. (1979) in that more detailed measurements of corn canopy variables were made using quantitative techniques. Wet and dry green leaf biomass is considered along with the green leaf area index, chlorotic leaf biomass, chlorotic leaf area, and leaf water content. In addition, spectral data were collected with a hand-held radiometer having Landsat-D Thematic Mapper (TM) bands TM3 (0.63-0.69 micrometers), TM4 (0.76-0.90 micrometers), and TM5 (1.55-1.75 micrometers). TM3, TM4, and TM5 seem to be well situated spectrally for making remotely sensed measurements related to chlorophyll concentration, leaf density, and leaf water content.

Kimes, D. S.↗
NASA NTRS1972

Determining density of maize canopy. 1: Digitized photography

The relationship between different densities of maize (Zea mays L.) canopies and the energy reflected by these canopies was studied. Field plots were laid out, representing four growth stages of maize, on a dark soil and on a very light colored surface soil. Spectral and spatial data were obtained from color and color infrared photography taken from a vertical distance of 10 m above the maize canopies. Estimates of ground cover were related to field measurements of leaf area index. Ground cover was predicted from leaf area index measurements by a second order equation. Color infrared photography proved helpful in determining the density of maize canopy on dark soils. Color photography was useful for determining canopy density on light colored soils. The near infrared dye layer is the most valuable in canopy density determinations.

Stoner, E. R.↗
NASA NTRS1972

Multispectral determination of vegetative cover in corn crop canopy

The relationship between different amounts of vegetative ground cover and the energy reflected by corn canopies was investigated. Low altitude photography and an airborne multispectral scanner were used to measure this reflected energy. Field plots were laid out, representing four growth stages of corn. Two plot locations were chosen-on a very dark and a very light surface soil. Color and color infrared photographs were taken from a vertical distance of 10 m. Estimates of ground cover were made from these photographs and were related to field measurements of leaf area index. Ground cover could be predicted from leaf area index measurements by a second order equation. Microdensitometry and digitzation of the three separated dye layers of color infrared film showed that the near infrared dye layer is most valuable in ground cover determinations. Computer analysis of the digitized photography provided an accurate method of determining precent ground cover.

Stoner, E. R.↗
NASA NTRS1976

Extracting scene feature vectors through modeling, volume 3

The remote estimation of the leaf area index of winter wheat at Finney County, Kansas was studied. The procedure developed consists of three activities: (1) field measurements; (2) model simulations; and (3) response classifications. The first activity is designed to identify model input parameters and develop a model evaluation data set. A stochastic plant canopy reflectance model is employed to simulate reflectance in the LANDSAT bands as a function of leaf area index for two phenological stages. An atmospheric model is used to translate these surface reflectances into simulated satellite radiance. A divergence classifier determines the relative similarity between model derived spectral responses and those of areas with unknown leaf area index. The unknown areas are assigned the index associated with the closest model response. This research demonstrated that the SRVC canopy reflectance model is appropriate for wheat scenes and that broad categories of leaf area index can be inferred from the procedure developed.

Berry, J. K.↗
NASA NTRS1977

Using Landsat data to estimate evapotranspiration of winter wheat

Results obtained from an evapotranspiration model as applied to Kansas winter wheatfields were compared with results determined by a weighing lysimeter, and the standard deviation was found to be less than 0.5 mm/day (however, the 95% confidence interval was between plus and minus 0.2 mm/day). Model inputs are solar radiation, temperature, precipitation, and leaf area index; an equation was developed to estimate the leaf area index from Landsat data. The model provides estimates of transpiration, evaporation, and soil moisture.

Kanemasu, E. T.↗
NASA NTRS1982

Portable Radiometer Monitors Plant Growth

Three-band hand-held spectral radiometer measures electromagnetic energy reflected from plant canopies in the visible and infrared portions of the spectrum. It is mobile and easy to use for rapid, repeated measurements. Radiometer probe is held level over plant canopy, readout range switches are set and measurements are recorded. Chlorophyll content, leaf area index and leaf water content can be quickly and easily measured.

Tucker, C. J., III↗
NASA NTRS1981

Effects of nitrogen nutrition on the growth, yield and reflectance characteristics of corn canopies

Spectral and agronomic measurements were collected from corn (Zea mays L.) canopies under four nitrogen treatment levels (0, 67, 134, and 202 kg/ha) on 11 dates during 1978 and 12 dates during 1979. Data were analyzed to determine the relationship between the spectral responses of canopies and their argonomic characteristics as well as the spectral separability of the four treatments. Red reflectance was increased, while the near infrared reflectance was decreased for canopies under nitrogen deprivation. Spectral differences between treatments were seen throughout each growing season. The near infrared/red reflectance ratio increased spectral treatment differences over those shown by single band reflectance measures. Of the spectral variables examined, the near infrared/red reflectance ratio most effectively separated the treatments. Differences in spectral response between treatments were attributed to varying soil cover, leaf area index, and leaf pigmentation values, all of which changed with N treatment.

Bauer, M. E.↗
NASA NTRS1984

Inversion of vegetation canopy reflectance models for estimating agronomic variables. III - Estimation using only canopy reflectance data as illustrated by the suits model. IV - Total inversion of the SAIL model

The possibility of estimating agronomic and spectral parameters for a vegetation canopy from the canopy reflectance (CR) data in the infrared region is investigated for a set of solar/view directions. It is shown that such an estimation is possible, in principle, for the Suits (1972) model for a homogeneous canopy. The technique is then applied to a more complex model, the SAIL (scattering by arbitrarily inclined leaves) model which explicitly includes the leaf angle distribution in the computation of the canopy reflectance. It is concluded that, given the expected accuracy of CR measurements and the accuracy of the SAIL model in representing CR in the infrared region, the agronomic parameters, leaf area index, and leaf angle distribution can be estimated fairly accurately using ancillary data on spectral parameters.

Goel, N. S.↗