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National Aeronautics and Space Administration fundamental research program. Information utilization and evaluation, appendices

Important points presented and recommendations made at an information and decision processes workshop held in Asilomar, California; at a data and information performance workshop held in Houston, Texas; and at a data base use and management workshop held near San Jose, California are summarized. Issues raised at a special session of the Soil Conservation Society of America's remote sensing for resource management conference in Kansas City, Missouri are also highlighted. The goals, status and activities of the NASA program definition study of basic research requirements, the necessity of making the computer science community aware of user needs with respect to information related to renewable resources, performance parameters and criteria for judging federal information systems, and the requirements and characteristics of scientific data bases are among the topics reported.

Estes, J. E.↗

Microwave soil moisture measurements and analysis

An effort to develop a model that simulates the distribution of water content and of temperature in bare soil is documented. The field experimental set up designed to acquire the data to test this model is described. The microwave signature acquisition system (MSAS) field measurements acquired in Colby, Kansas during the summer of 1978 are pesented.

Newton, R. W.↗

Crop classification using multidate/multifrequency radar data

Both C- and L-band radar data acquired over a test site near Colby, Kansas during the summer of 1978 were used to identify three types of vegetation cover and bare soil. The effects of frequency, polarization, and the look angle on the overall accuracy of recognizing the four types of ground cover were analyzed. In addition, multidate data were used to study the improvement in recognition accuracy possible with the addition of temporal information. The soil moisture conditions had changed considerably during the temporal sequence of the data; hence, the effects of soil moisture on the ability to discriminate between cover types were also analyzed. The results provide useful information needed for selecting the parameters of a radar system for monitoring crops.

Ulaby, F. T.↗

Evaluation of the soil moisture prediction accuracy of a space radar using simulation techniques

Image simulation techniques were employed to generate synthetic aperture radar images of a 17.7 km x 19.3 km test site located east of Lawrence, Kansas. The simulations were performed for a space SAR at an orbital altitude of 600 km, with the following sensor parameters: frequency = 4.75 GHz, polarization = HH, and angle of incidence range = 7 deg to 22 deg from nadir. Three sets of images were produced corresponding to three different spatial resolutions; 20 m x 20 m with 12 looks, 100 m x 100 m with 23 looks, and 1 km x 1 km with 1000 looks. Each set consisted of images for four different soil moisture distributions across the test site. Results indicate that, for the agricultural portion of the test site, the soil moisture in about 90% of the pixels can be predicted with an accuracy of = + or - 20% of field capacity. Among the three spatial resolutions, the 1 km x 1 km resolution gave the best results for most cases, however, for very dry soil conditions, the 100 m x 100 m resolution was slightly superior.

Ulaby, F. T.↗

Aircraft radar response to soil moisture

An analysis is presented of aircraft response to soil moisture in the upper surface layer of agricultural fields. Measurements (taken at 1.6 GHz and 4.75 GHz using HH and HV polarizations, and at 13.3 GHz using VV polarization from an experiment conducted in 1978 at Colby, Kansas) are used to derive the radar soil moisture sensitivities and correlations. It is shown that the aircraft response to soil moisture is optimum at C-band frequencies and incidence angles of 10-20 deg. confirming previous truck-radar results. Like-polarization radar response is unaffected by vegetation but is dependent on row-tillage patterns; cross-polarization response also is unaffected by vegetation but is approximately independent of tillage patterns. These results show that remote sensing radars can be used effectively for the detection and estimation of near-surface soil moisture in agricultural fields.

Bradley, G. A.↗

A synoptic analysis of the first AVE-SESAME '79 period

Key features of a severe convection observed during April 10-11, 1979 as part of the Atmospheric Variability Experiment-Severe Environmental Storms and Mesoscale Experiment (AVE-SESAME) are examined. Three-hourly rawinsonde readings from 23 stations were taken, and vertical motion and divergence parameters are considered. The data were converted into a 127 km grid at the surface, and at 50 mb intervals from 900 mb to 100 mb by an objective analysis scheme, while a kinematic method was used to compute vertical motion. A weak upper tropospheric short wave trough was found to propagate from New Mexico into the Texas panhandle, while a jet maximum propagated eastward. The development of a strong wind maximum over Oklahoma and Kansas was associated with a rapid increase in upper-level divergence and the development of a small-scale pressure perturbation in the Texas panhandle, as well as a low-level jet and convergence, which led to rapid changes over the Red River Valley, where stability was decreased.

Moore, J. T.↗

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.↗

Verification testing of the PKI collector at Sandia National Laboratories, Albuquerque, New Mexico

Verification testing of a solar collector was undertaken prior to its operation as part of an industrial process heat plant at Capitol Concrete Products in Topeka, Kansas. Testing was performed at a control plant installed at Sandia National Laboratory, Albuquerque, New Mexico (SNLA). Early results show that plant performance is even better than anticipated and far in excess of test criteria. Overall plant efficiencies of 65 to 80 percent were typical during hours of good insolation. A number of flaws and imperfections were detected during operability testing, the most important being a problem in elevation drive alignment due to a manufacturing error. All problems were corrected as they occurred and the plant, with over 40 hours of operation, is currently continuing operability testing in a wholly-automatic mode.

Hauger, J. S.↗

Physical and chemical characteristics of Mount St. Helens airborne debris

Tephra and aerosols from the May 18, 1980 eruption of Mount St. Helens, Washington were sampled in the lower stratosphere with a WB-57F aircraft. The main body of the plume was intercepted over western Kansas on May 20, 48 hours after the eruption, at an altitude of 15.2 km. Concentrations on filter samples were 26 ng of SO4(-2) of air and 579 ng of ash/g of air. Angular glass pyroclasts ranged in size from 0.5 to 10 microns, with a mean grain of 2 microns. Samples collected at altitudes of 16.7 and 12.5 km had only traces of SO4(-2) and ash. A second flight was flown, 72 hours after the eruption, on May 21. From north Texas to central Wyoming, at an altitude of 15.2 km less than 0.5 to 38 ng of ash/g of air and 1.0 to 2.2 ng of SO4(-2)/g of air were sampled. At an altitude of 18.3 km, from central Wyoming to NW New Mexico, the plume density and character were variable.

Sedlacek, W. A.↗

Assessment of radar resolution requirements for soil moisture estimation from simulated satellite imagery

Radar simulations were performed at five-day intervals over a twenty-day period and used to estimate soil moisture from a generalized algorithm requiring only received power and the mean elevation of a test site near Lawrence, Kansas. The results demonstrate that the soil moisture of about 90% of the 20-m by 20-m pixel elements can be predicted with an accuracy of + or - 20% of field capacity within relatively flat agricultural portions of the test site. Radar resolutions of 93 m by 100 m with 23 looks or coarser gave the best results, largely because of the effects of signal fading. For the distribution of land cover categories, soils, and elevation in the test site, very coarse radar resolutions of 1 km by 1 km and 2.6 km by 3.1 km gave the best results for wet moisture conditions while a finer resolution of 93 m by 100 m was found to yield superior results for dry to moist soil conditions.

Ulaby, F. T.↗

Four frequency ground scatterometer

The FM-CW Radar, used as a microwave scatterometer is described. Scatterometer system design, scatterometer system calibration, parameter calculation and correction for data acquisition, ground scatterometer data acquistion at Jornada Experimental Range, and Kansas radar cross-calibration test are discussed.

Dickerson, E. T.↗

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.↗

Development of an early warning system of crop moisture conditions using passive microwave

Emissivities were calculated from the Nimbus 5 electrically scanning microwave radiometer (ESMR) over 25 km grid cells for the southern Great Plains includin the western two-thirds of Kansas and Oklahoma and northwest Texas. These emissivities, normalized for seasonal temperature changes, were in excellent agreement with theory and measurements made from aircraft and truck sensors at the 1.55 cm wavelength of ESMR. These emissivities were related to crop moisture conditions of the winter wheat in the major wheat producing counties of the three states. High correlations were noted between emissitivity and an antecedent precipitation index (API) used to infer soil moisture for periods when the soils were essentially bare. The emissivities from ESMR were related through API and actual crop condition reports to progress of fall planting, adequacy of crop moisture for stand establishment, and periods of excessive moisture that necessitated replanting. Periods of prolonged frozen soil in the winter were observable at several grid points. The average emissivities of the canopy/soil surface during the maximum canopy development times in the spring showed a good agreement with moisture stress inferred from rainfall and yield data.

Mcfarland, M. J.↗

Crop classification using airborne radar and LANDSAT data

Airborne radar data acquired with a 13.3 GHz scatterometer over a test-site near Colby, Kansas were used to investigate the statistical properties of the scattering coefficient of three types of vegetation cover and of bare soil. A statistical model for radar data was developed that incorporates signal-fading and natural within-field variabilities. Estimates of the within-field and between-field coefficients of variation were obtained for each cover-type and compared with similar quantities derived from LANDSAT images of the same fields. The classification accuracy provided by LANDSAT alone, radar alone, and both sensors combined was investigated. The results indicate that the addition of radar to LANDSAT improves the classification accuracy by about 10; percentage-points when the classification is performed on a pixel basis and by about 15 points when performed on a field-average basis.

Ulaby, F. T.↗

Sampling for area estimation: A comparison of full-frame sampling with the sample segment approach

The effect of sampling on the accuracy (precision and bias) of crop area estimates made from classifications of LANDSAT MSS data was investigated. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plants. Four sampling schemes involving different numbers of samples and different size sampling units were evaluated. The precision of the wheat area estimates increased as the segment size decreased and the number of segments was increased. Although the average bias associated with the various sampling schemes was not significantly different, the maximum absolute bias was directly related to sampling unit size.

Hixson, M. M.↗

Radar spectral observations of snow

Radar remote sensing experiments have been conducted at test sites in Kansas, Colorado, and South Dakota over the last six years to examine backscatter coefficient response to snowcovered terrain. Truck-mounted 1-35 GHz scatterometers were employed in conjunction with detailed ground-truth measurements. From these experiments and associated modeling efforts, most of the fundamental questions concerning backscatter behavior in response to important snow parameters have been, at least qualitatively, answered. The optimum angular range seems to be between 20 and 50 deg and, for these angles, the results indicate that the radar backscatter generally: (1) increases with increasing water equivalent, (2) decreases with increasing liquid water, (3) increases with increasing crystal size, (4) is insensitive to surface roughness for dry snow conditions, and (5) can be sensitive to soil state if the snowcover is dry. This paper gives a summary of these results, along with empirical and theoretical models for describing the backscatter from snow.

Stiles, W. H.↗

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.↗

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.↗