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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Temporal spectral response of a corn canopy

Techniques developed for the prediction of winter wheat yields from remotely sensed data indicating crop status over the growing season are tested for their applicability to corn. Ground-based spectral measurements in the Landsat Thematic Mapper bands 3 (0.62-0.69 microns), 4 (0.76-0.90 microns) and 5 (1.55-1.75 microns) were performed at one-week intervals throughout the growing season for 24 plots of corn, and analyzed to derive spectral ratios and normalized spectral differences of the IR and shortwave IR bands with the red. The ratios of the near IR and shortwave IR bands are found to provide the highest and most consistent correlations with corn yield and dry matter accumulation, however the value of band 5 could not be tested due to the absence of water stress conditions. Integration of spectral ratios over several dates improved the correlations over those of any single date by achieving a seasonal, rather than instantaneous, estimate of crop status. Results point to the desirability of further tests under other growth conditions to determine whether satellite-derived data will be useful in providing corn yield information.

Markham, B. L.↗
NASA NTRS1980

Field size, length, and width distributions based on LACIE ground truth data

The development of agricultural remote sensing systems requires knowledge of agricultural field size distributions so that the sensors, sampling frames, image interpretation schemes, registration systems, and classification systems can be properly designed. Malila et al. (1976) studied the field size distribution for wheat and all other crops in two Kansas LACIE (Large Area Crop Inventory Experiment) intensive test sites using ground observations of the crops and measurements of their field areas based on current year rectified aerial photomaps. The field area and size distributions reported in the present investigation are derived from a representative subset of a stratified random sample of LACIE sample segments. In contrast to previous work, the obtained results indicate that most field-size distributions are not log-normally distributed. The most common field size observed in this study was 10 acres for most crops studied.

Pitts, D. E.↗
NASA NTRS1980

View angle effects in the radiometric measurement of plant canopy temperatures

The thermal infrared sensor response from a wheat canopy was extremely non-Lambertian because of spatial variations in energy flow processes; the effective radiant temperature of the sensor varied as much as 13 C with changing view angle. This variation of sensor response was accurately quantified (root-mean-square of deviations between theoretical and measured responses reduced to 1.1 C) as a function of vegetation canopy geometry, vertical temperature distribution of canopy components, and sensor view angle. The results have important implications for optimizing sensor view angles for remote sensing missions.

Kimes, D. S.↗
NASA NTRS1982

Evaluation of NOAA-AVHRR data for crop assessment

A study has been carried out in order to determine the angular limits which should be imposed upon NOAA06 and -7 satellite advanced very high-resolution radiometer (AVHRR) data used in vegetation assessment. The study involved simulations of anticipated sensor output over a wheat crop and empirical investigation of sensor data over vegetated areas. The conclusion drawn from both approaches is that less than 10% variation in the simulated vegetative index may be anticipated across the swath of imagery used if only the central 512 pixels are utilized.

Duggin, M. J.↗
NASA NTRS1982

Effects of varying soil moisture contents and vegetation canopies on microwave emissions

Results of NASA airborne passive microwave scans of bare and vegetated fields for comparison with ground truth tests are discussed and a model for atmospheric scattering of radiation by vegetation is detailed. On-board radiometers obtained data at 21, 2.8, and 1.67 cm during three passes over each of 46 fields, 28 of which were bare and the others having wheat or alfalfa. Ground-based sampling included moisture in five layers down to 15 cm in addition to soil temperature. The relationships among the brightness temperature and soil moisture, as well as the surface roughness and the vegetation canopy were examined. A model was developed for the dielectric coefficient and volume scattering for a vegetation medium. L- to C-band data were found useful for retrieving soil information directly. A surface moisture content of 5-35% yielded an emissivity of 0.9-0.7. The data agreed well with a combined multilayer radiative transfer model with simple roughness correction.

Burke, H.-H. K.↗
NASA NTRS1982

Polyamines and plant stress - Activation of putrescine biosynthesis by osmotic shock

The putrescine content of oat leaf cells and protoplasts increases up to 60-fold within 6 hours of exposure to osmotic stress (0.4 to 0.6 molar sorbitol). Barley, corn, wheat, and wild oat leaves show a similar response. Increased arginine decarboxylase activity parallels the rise in putrescine, whereas ornithine decarboxylase remains unchanged. DL-alpha-Difluoromethylarginine, a specific irreversible inhibitor of arginine decarboxylase, prevents the stress-induced rise in increase in arginine decarboxylase activity and putrescine synthesis, indicating the preferential activation of this pathway.

Flores, H. E.↗
NASA NTRS1982

Data documentation for the 1981 summer vegetation experiment

The mobile agricultural radar sensor was used to collect data from 31 fields in the floodplain of the Kansas River east of Lawrence, Kansas during the summer of 1981. Corn, soybeans, and wheat crops were observed from May 1 to November 11. Radar backscattering measurements were acquired at 10.2 GHz for VV and VH polarizations at 50 deg incidence angles for all fields and at 30 deg, 40 deg, 50 deg, 60 deg, and 70 deg for nine of the 31 fields. Target parameters describing the vegatation and soil characteristics, such as plant moisture, plant height, soil moisture, etc., were also measured. The methodology, radar backscatter data and associated ground-truth data obtained during this experiment are documented.

Ulaby, F. T.↗
NASA NTRS1982

Comparison of the CEAS and Williams-type barley yield models for North Dakota and Minnesota

The CEAS and Williams type models were compared based on specified selection criteria which includes a ten year bootstrap test (1970-1979). Based on this, the models were quite comparable; however, the CEAS model was slightly better overall. The Williams type model seemed better for the 1974 estimates. Because that year spring wheat yield was particularly low, the Williams type model should not be excluded from further consideration.

Leduc, S.↗
NASA NTRS1977

Development of techniques for producing static strata maps and development of photointerpretive methods based on multitemporal LANDSAT data

Progress in the evaluation of the static stratification procedure and the development of alternative photointerpretive techniques to the present LACIE procedure for the identification of training fields is reported. Statistically significant signature controlling variables were defined for use in refining the stratification procedure. A subset of the 1973-74 Kansas LACIE segments for wheat was analyzed.

Colwell, R. N.↗
NASA NTRS1982

Yield model development project implementation plan

Tasks remaining to be completed are summarized for the following major project elements: (1) evaluation of crop yield models; (2) crop yield model research and development; (3) data acquisition processing, and storage; (4) related yield research: defining spectral and/or remote sensing data requirements; developing input for driving and testing crop growth/yield models; real time testing of wheat plant process models) and (5) project management and support.

Ambroziak, R. A.↗
NASA NTRS1983

Relating the radar backscattering coefficient to leaf-area index

The relationship between the radar backscattering coefficient of a vegetation canopy, sigma(0) sub can, and the canopy's leaf area index (LAI) is examined. The relationship is established through the development of a model for corn and sorghum and another for wheat. Both models are extensions of the cloud model of Attema and Ulaby (1978). Analysis of experimental data measured at 8.6, 13.0, 17.0, and 35.6 GHz indicates that most of the temporal variations of sigma(0) sub can can be accounted for through variations in green LAI alone, if the latter is greater than 0.5.

Ulaby, F. T.↗
NASA NTRS1983

Effects of vegetation cover on the microwave radiometric sensitivity to soil moisture

The reduction in sensitivity of the microwave brightness temperature to soil moisture content due to vegetation cover is analyzed using airborne observations made at 1.4 and 5 GHz. The data were acquired during six flights in 1978 over a test site near Colby, Kansas. The test site consisted of bare soil, wheat stubble, and fully mature corn fields. The results for corn indicate that the radiometric sensitivity to soil moisture S decreases in magnitude with increasing frequency and with increasing angle of incidence (relative to nadir). The sensitivity reduction factor, defined in terms of the radiometric sensitivities for bare soil and canopy-covered conditions Y = 1 - Scan/Ss was found to be equal to 0.65 for normal incidence at 1.4 GHz, and increases to 0.89 at 5 GHz. These results confirm previous conclusions that the presence of vegetation cover may pose a serious problem for soil moisture detection with passive microwave sensors.

Ulaby, F. T.↗
NASA NTRS1983

Extension of a uniform canopy reflectance model to include row effects

The reflectance model for a uniform crop canopy is extended to include the effects of crops planted in rows. The effect of row structure is assumed to be caused by the variation in density of vegetation across rows rather than to a profile in canopy height. The calculation of crop reflectance using vegetation density modulation across rows follows a parallel procedure to that for a uniform canopy. Predictions using the row model for wheat show that the effect of changes in sun to row azimuth are greatest in Landsat Band 5 (red band) and can result in underestimation of crop biomass.

Suits, G. H.↗
NASA NTRS1983

Identification of corn fields using multidate radar data

Airborne C- and L-band radar data acquired over a test site in western kansas were analyzed to determine corn-field identification accuracies obtainable using single-channel, multichannel, and multidate radar data. An automated pattern-recognition procedure was used to classify 144 fields into three categories: corn, pasture land, and bare soil (including wheat stubble and fallow). Corn fields were identified with accuracies ranging from 85 percent for single channel, single-date data to 100 percent for single-channel, multidate data. The effects of radar parameters such as frequency, polarization, and look angle as well as the effects of soil moisture on the classification accuracy are also presented.

Shanmugan, K. S.↗
NASA NTRS1983

Scattering from randomly oriented circular discs with application to vegetation

A vegetation layer is modeled by a collection of randomly oriented circular discs over a half space. The backscattering coefficient from such a half space is computed using the radiative transfer theory. It is shown that significantly different results are obtained from this theory as compared with some earlier investigations using the same modeling approach but with restricted disc orientations. In particular, the backscattered cross-polarized returns cannot have a fast increasing angular trend which is inconsistent with measurements. By setting the appropriate angle of orientation to zero the theory reduces to previously published results. Comparisons are shown with measurements taken from milo, corn and wheat and good agreements are obtained for both polarized and cross-polarized returns.

Karam, M. A.↗
NASA NTRS1983

Radar remote sensing for crop classification and canopy condition assessment: Ground-data documentation

A vegetation and soil-moisture experiment was conducted in order to examine the microwave emission and backscattering from vegetation canopies and soils. The data-acquisition methodology used in conjunction with the mobile radar scatterometer (MRS) systems is described and associated ground-truth data are documented. Test fields were located in the Kansas River floodplain north of Lawrence, Kansas. Ten fields each of wheat, corn, and soybeans were monitored over the greater part of their growing seasons. The tabulated data summarize measurements made by the sensor systems and represent target characteristics. Target parameters describing the vegetation and soil characteristics include plant moisture, density, height, and growth stage, as well as soil moisture and soil-bulk density. Complete listings of pertinent crop-canopy and soil measurements are given.

Ulaby, F. T.↗
NASA NTRS1984

A Study of the Relation Between Crop Growth and Spectra Reflectance Parameters

A differential equation describing the temporal behavior of greenness, G(t), with time was developed. The basic equation, dG(t)/dt=k(t)(1-G/G sub m) where G sub m is the saturation value of greenness at time, t sub p. It demonstrated that k(t) is linearly proportional to the rate of change of leaf area index. It was also demonstrated that G sub m, t sub p and profile width, are the key to vegetation identification and that the inflection points of the profile are related to the ontogenic state of the plant. These profile features were shown to hold not only throughout the United States corn/soybean growing area, but for the first time in Argentina. A mathematical technique that maximizes the sensitivity of spectral transformation to Leaf Area Index and simultaneously minimizes the sensitivity to all other variables was formulated. Initial results on corn and wheat were obtained.

Badhwar, G.↗