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At least 235 records · Page 13

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.↗

Progress In The Scene-To-Map Registration Investigation

The geometric accuracy of the scene-to-map registration process for P-format LANDSAT MSS data for scenes from Kansas and Louisiana/Mississippi is discussed. Large scale row and column bias values and row and column standard deviation values were measured for the P-format data sets indicating a poor georegistration accuracy for these geometrically corrected LANDSAT MSS scenes. Experimental work is underway with A-format LANDSAT MSS scenes from the same locations to examine the influence of the number of ground control points and the spatial distribution of ground control points on geometric registration accuracy. An early conclusion from this work is that the root mean square approach for assessing how well the ground control points fit the mapping equations measures a different aspect of georegistration accuracy than does the approach of evaluating the bias (offset) and standard deviation using independently chosen ground reference points.

Dow, D. D.↗

A simulation study of scene confusion factors in sensing soil moisture from orbital radar

Simulated C-band radar imagery for a 124-km by 108-km test site in eastern Kansas is used to classify soil moisture. Simulated radar resolutions are 100 m by 100 m, 1 km by 1km, and 3 km by 3 km. Distributions of actual near-surface soil moisture are established daily for a 23-day accounting period using a water budget model. Within the 23-day period, three orbital radar overpasses are simulated roughly corresponding to generally moist, wet, and dry soil moisture conditions. The radar simulations are performed by a target/sensor interaction model dependent upon a terrain model, land-use classification, and near-surface soil moisture distribution. The accuracy of soil-moisture classification is evaluated for each single-date radar observation and also for multi-date detection of relative soil moisture change. In general, the results for single-date moisture detection show that 70% to 90% of cropland can be correctly classified to within +/- 20% of the true percent of field capacity. For a given radar resolution, the expected classification accuracy is shown to be dependent upon both the general soil moisture condition and also the geographical distribution of land-use and topographic relief. An analysis of cropland, urban, pasture/rangeland, and woodland subregions within the test site indicates that multi-temporal detection of relative soil moisture change is least sensitive to classification error resulting from scene complexity and topographic effects.

Ulaby, F. T.↗

Accomplishments of the NASA Johnson Space Center portion of the soil moisture project in fiscal year 1981

The NASA/JSC ground scatterometer system was used in a row structure and row direction effects experiment to understand these effects on radar remote sensing of soil moisture. Also, a modification of the scatterometer system was begun and is continuing, to allow cross-polarization experiments to be conducted in fiscal years 1982 and 1983. Preprocessing of the 1978 agricultural soil moisture experiment (ASME) data was completed. Preparations for analysis of the ASME data is fiscal year 1982 were completed. A radar image simulation procedure developed by the University of Kansas is being improved. Profile soil moisture model outputs were compared quantitatively for the same soil and climate conditions. A new model was developed and tested to predict the soil moisture characteristic (water tension versus volumetric soil moisture content) from particle-size distribution and bulk density data. Relationships between surface-zone soil moisture, surface flux, and subsurface moisture conditions are being studied as well as the ways in which measured soil moisture (as obtained from remote sensing) can be used for agricultural applications.

Paris, J. F.↗

Effects of Vegetation Canopy Structure on Microwave Scattering

The role of canopy structure on microwave backscattering is studied. Structure refers to the size, orientation, and vertical placement of scatterers in the canopy. Models to predict the backscattering coefficient, SIGMAO, of vegetation with explicit biophysical and explicit polarization-dependent parameters were developed. Preparation for field measurements with radar scatterometers was completed. Technical progress included: (1) the modification of the Attema and Ulaby (1977) model and its multilayer variation by Hoekman et al. (1983) to include polarization explicitly (i.e., to allow for separate backscattering cross sections, SIGMA, and extinction cross sections, Q, for each polarization), (2) the investigation of the modified model to isolate canopy element orientation parameters by the rationing of SIGMAO measurements for different polarization combinations, (3) the development of expressions for bistatic scattering and canopy-substrate scattering to supplement the models, (4) the performance of sensitivity analyses on these models, (5) the modification of the Attema and Ulaby model to alloy for changes, (6) the use of the modified model with a seasonal corn data set from Kansas (Eger et al., 1983), and (7) the initiation of preparations for empirical measurements with radar spectrometer and the Mobile Radar Scatterometer in irrigated cropland to test the models.

Paris, J. F.↗

Study of Thematic Mapper and Multispectral Scanner Data Applications

The U.S. Geological Survey EROS Data Center evaluated the utility of LANDSAT multispectral scanner (MSS) and Thematic Mapper (TM) data for natural resource assessment and land cover information, emphasizing manual interpretation and digital classification of the data for U.S. Department of the Interior applications. In most cases, substantially more information was derived from TM data than from MSS data. The test areas included Washington, D.C. and prairie regions of South Dakota and Kansas.

Sadowski, F. G.↗

The influence of the number of ground control points on the scene-to-map registration accuracy

The optimum number of ground control points required to rectify a full scene or a portion of a LANDSAT MSS scene was investigated using data from southeastern Louisiana/southwestern Mississippi and eastern Kansas. The ground control points utilized were randomly distributed across the partial or full scene. This work suggest that 24 round control points are more than adequate to rectify a partial or full scene of LANDSAT MSS data. The error incurred in choosing ground control points representing artificial versus natural features was also studied.

Dow, D. D.↗

Test and evaluation plan for the Centralized Storm Information System

The installation of the Centralized Storm Information System (CSIS) at the NOAA operational complex in Kansas City, Missouri is described. This complex includes the National Severe Storms Forecast center and a Satellite Field Service Station which is denoted in this research plan as NSSFC. CSIS computers will act in concert to merge analyze the many data sets needed to forecast severe convective storms. Specific aspects of CSIS are evaluated against the CSIS objectives. The functions to be evaluated characterize the attributes of a generalized interactive computer system. A major development in the CSIS program will allow communication between CSIS and the NSSFC Eclipse computer.

Source record↗

Potentials for change detection using Seasat synthetic aperture radar data

The use of synthetic aperture radar (SAR) images for detecting change on the earth's surface is highly dependent on target orientation, azimuth angle, and sensor depression angle. SAR data can be used for change detection when consistency is maintained in radar wavelength, polarization, azimuth directions, and off-nadir depression angle. The interaction of these parameters and the imaged surface for change detection are shown in examples drawn from (1) Los Angeles, CA, (2) southern Florida, (3) Imperial Valley, CA, (4) a desert region west of Tucson, AZ, and (5) western Kansas. SAR imagery is used to emphasize the geometric form, and roughness, of the earth's surface. As changes in the roughness of the surface occur over time, temporal SAR images will indicate those differences. Several guidelines for change detection studies using imaging radar are derived from the examples.

Bryan, M. L.↗

A simulation study of the effects of land cover and crop type on sensing soil moisture with an orbital C-band radar

Simulated C-band radar imagery for a 124-km by 108-km test site in eastern Kansas is used to classify soil moisture. Simulated radar resolutions are 100 m by 100 m, 1 km by 1 km, and 3 km by 3 km, and each is processed using more than 23 independent samples. Moisture classification errors are examined as a function of land-cover distribution, field-size distribution, and local topographic relief for the full test site and also for subregions of cropland, urban areas, woodland, and pasture/rangeland. Results show that a radar resolution of 100 m by 100 m yields the most robust classification accuracies.

Dobson, M. C.↗

The role of an apparent mesoscale frontogenetic circulation in squall line initiation

The present investigation is concerned with the nature and apparent origin of a mesoscale clear zone and associated frontal line convection (a line of cumulus congestus clouds along an intensifying cold front) which appeared just prior to the explosive development of a line of severe thunderstorms at the cold front. It is pointed out that the clear zone formed immediately behind the cold front in southeastern Kansas and northeastern Oklahoma during the afternoon of April 16, 1982. Sequential displays of GOES-East satellite imagery are considered. The mechanism which seems to explain best the observations is a thermally direct frontogenetic circulation resulting from the combined effects of the synoptic-scale wind deformation field and mesoscale differential sensible heating.

Koch, S. E.↗

An observational study of a mesoscale area of convection under weak synoptic-scale forcing

This is a case study of a mesoscale area of convection which began at night over western Kansas on September 2, 1982 and lasted until the afternoon of September 3. Evidence from analyses of surface, upper-air radar, and satellite observations suggests that the thunderstorms probably formed in response to the lifting of an elevated layer of conditional instability. The lifting can be attributed qualitatively to quasi-geostrophic ascending motion resulting from a shallow layer of warm advection near 60 kPa. Two possible sources of moisture were midlevel moisture which had been advected around an upstream ridge and a localized area of turbulent transport of water vapor from below. The convective event could not have been forecast with synoptic-scale, mandatory-level analyses alone; it was difficult to explain even with detailed analyses at other levels.

Bluestein, H. B.↗