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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Remote sensing of soil moisture by a 21-cm passive radiometer

Microwave sensors on Skylab collected data as part of the Earth Resources Experiment Package. An investigation was designed to obtain field observations of soil moisture content for comparison with data from Skylab. The 21-cm radiometer has been shown to be highly responsive to the moisture content of the upper 2.5-cm layer of soil. A composite relationship between the radiometric temperature and soil moisture content has been determined from five data sets obtained over Kansas and Texas. This relationship, having a correlation index of -0.96, has been used as a basis for calculating the soil moisture content of large areas across the United States.

Eagleman, J. R.↗
NASA NTRS1976

Evaluation of algorithms for estimating wheat acreage from multispectral scanner data

The author has identified the following significant results. Fourteen different classification algorithms were tested for their ability to estimate the proportion of wheat in an area. For some algorithms, accuracy of classification in field centers was observed. The data base consisted of ground truth and LANDSAT data from 55 sections (1 x 1 mile) from five LACIE intensive test sites in Kansas and Texas. Signatures obtained from training fields selected at random from the ground truth were generally representative of the data distribution patterns. LIMMIX, an algorithm that chooses a pure signature when the data point is close enough to a signature mean and otherwise chooses the best mixture of a pair of signatures, reduced the average absolute error to 6.1% and the bias to 1.0%. QRULE run with a null test achieved a similar reduction.

Nalepka, R. F.↗
NASA NTRS1976

Signature extension for spectral variation in soils, volume 4

The reduced 1975-1976 field data at Garden City, Kansas are presented. These data are being used to evaluate the SRVC model predictions, to compare the ERIM-SUITS model with both the SRVC results and field data, and finally, to provide a data base for reviewing multitemporal trajectories. In particular, the applicability of the tasselled cap transformation is reviewed. The first detailed verification of this approach utilizing actual field measured data from the LACIE field measurement program, rather than LANDSAT data, is given.

Berry, J. K.↗
NASA NTRS1977

Crop identification and area estimation over large geographic areas using LANDSAT MSS data

The author has identified the following significant results. LANDSAT MSS data was adequate to accurately identify wheat in Kansas; corn and soybean estimates in Indiana were less accurate. Computer-aided analysis techniques were effectively used to extract crop identification information from LANDSAT data. Systematic sampling of entire counties made possible by computer classification methods resulted in very precise area estimates at county, district, and state levels. Training statistics were successfully extended from one county to other counties having similar crops and soils if the training areas sampled the total variation of the area to be classified.

Bauer, M. E.↗
NASA NTRS1976

Wheat signature modeling and analysis for improved training statistics

The author has identified the following significant results. The spectral, spatial, and temporal characteristics of wheat and other signatures in LANDSAT multispectral scanner data were examined through empirical analysis and simulation. Irrigation patterns varied widely within Kansas; 88 percent of wheat acreage in Finney was irrigated and 24 percent in Morton, as opposed to less than 3 percent for western 2/3's of the State. The irrigation practice was definitely correlated with the observed spectral response; wheat variety differences produced observable spectral differences due to leaf coloration and different dates of maturation. Between-field differences were generally greater than within-field differences, and boundary pixels produced spectral features distinct from those within field centers. Multiclass boundary pixels contributed much of the observed bias in proportion estimates. The variability between signatures obtained by different draws of training data decreased as the sample size became larger; also, the resulting signatures became more robust and the particular decision threshold value became less important.

Nalepka, R. F.↗
NASA NTRS1977

Applications of remote sensing, volume 2

The author has identified the following significant results. The overall spectral response of the strata measured by a mean vector and covariance matrix for each stratum did not show differences among the LACIE phase 3 strata using the machine clustering procedures. This was expected since the large strata gave rise to broad normal distributions with a great deal of overlap. The static stratification of Kansas contains strata which are small in size. The distributions for these strata are not as broad as those based on the LACIE phase 3 partitions, but there is still some confusion since strata from different categories are not spectrally distinct.

Landgrebe, D. A.↗
NASA NTRS1976

Selecting class weights to minimize classification bias in acreage estimation

Preliminary results of experiments being performed to select optimal class weights for use with the maximum likelihood classifier in acreage estimation using remote sensor imagery are presented. These weights will be optimal in the sense that the bias will be minimized in the proportion estimate obtained from the classification results by sample counting. The procedure was tested using Landsat MSS data from an 8 by 9.6 km area of ground truth in Finney County, Kansas.

Belcher, W. M.↗
NASA NTRS1976

Satellite cloud climatology of summertime cumulus research areas

Defense Meteorological Satellite Program data available for the summer of 1974 was used to construct a cloud climatology of areas where weather modification experiments are currently being conducted or planned; the three High Plains Experiment sites at Colby, Kansas, Big Springs, Texas, and Miles City, Montana; South Park, Colorado, where the South Park Area Cumulus Experiment is being conducted; and the National Hail Research Experiment area in northeastern Colorado. Digital data tapes were produced from the transparencies, obtained from the sun-synchronous polar-orbiting satellite passing over the study areas at about 1200 local time, and a computer analysis was carried out, producing areas and numbers of clouds for each area and day as well as providing data for cumulative averages over selected time periods for each study area.

Stodt, R. W.↗
NASA NTRS1977

Ground truth management system to support multispectral scanner /MSS/ digital analysis

A computerized geographic information system for management of ground truth has been designed and implemented to relate MSS classification results to in situ observations. The ground truth system transforms, generalizes and rectifies ground observations to conform to the pixel size and shape of high resolution MSS aircraft data. These observations can then be aggregated for comparison to lower resolution sensor data. Construction of a digital ground truth array allows direct pixel by pixel comparison between classification results of MSS data and ground truth. By making comparisons, analysts can identify spatial distribution of error within the MSS data as well as usual figures of merit for the classifications. Use of the ground truth system permits investigators to compare a variety of environmental or anthropogenic data, such as soil color or tillage patterns, with classification results and allows direct inclusion of such data into classification operations. To illustrate the system, examples from classification of simulated Thematic Mapper data for agricultural test sites in North Dakota and Kansas are provided.

Coiner, J. C.↗
NASA NTRS1977

Wheat productivity estimates using LANDSAT data

The author has identified the following significant results. Large area LANDSAT yield estimates were generated. These results were compared with estimates computed using a meteorological yield model (CCEA). Both of these estimates were compared with Kansas Crop and Livestock Reporting Service (KCLRS) estimates of yield, in an attempt to assess the relative and absolute accuracy of the LANDSAT and CCEA estimates. Results were inconclusive. A large area direct wheat prediction procedure was implemented. Initial results have produced a wheat production estimate comparable with the KCLRS estimate.

Nalepka, R. F.↗
NASA NTRS1977

Planting data and wheat yield models

The author has identified the following significant results. A variable date starter model for spring wheat depending on temperature was more precise than a fixed date model. The same conclusions for fall-planted wheat were not reached. If the largest and smallest of eight temperatures were used to estimate daily maximum and minimum temperatures; respectively, a 1-4 F bias would be introduced into these extremes. For Kansas, a reduction of 0.5 bushels/acre in the root-mean-square-error between model and SRS yields was achieved by a six fold increase (7 to 42) in the density of weather stations. An additional reduction of 0.3 b/A was achieved by incorporating losses due to rusts in the model.

Feyerherm, A. M.↗
NASA NTRS1977

Investigations of spectral separability of small grains, early season wheat detection, and multicrop inventory planning

The author has identified the following significant results. LANDSAT data from seven 5 by 6 segments having crop type information were analyzed to determine the potential for spectral separation of spring wheat from other small grains as an alternative to the primary LACIE procedure for estimating spring wheat acreage. Within segment field-center, classification accuracies for spring wheat vs. barley tended to be best in mid-July when crop color changes were in progress. When correlations were made for differences in atmospheric haze, data from several segments could be aggregated, and results that approached within segment accuracies were obtained for selected dates. LACIE field measurement spectral reflectance data provided information on both wheat development patterns and the importance of various agronomic factors on wheat reflectance, the most important being availability of soil moisture. To investigate early season detection for winter wheat, reflectance of developing wheat patterns was simulated through reflectance modeling and was analyzed along with field measured reflectance from a Kansas site. The green component development of the wheat field was analyzed as a function of data throughout the season. A selected threshold was not crossed by all fields until mid-April. These reflectance data were shown to be consistent actual LANDSAT data.

Nalepka, R. F.↗
NASA NTRS1977

Two phase sampling for wheat acreage estimation

A two phase LANDSAT-based sample allocation and wheat proportion estimation method was developed. This technique employs manual, LANDSAT full frame-based wheat or cultivated land proportion estimates from a large number of segments comprising a first sample phase to optimally allocate a smaller phase two sample of computer or manually processed segments. Application to the Kansas Southwest CRD for 1974 produced a wheat acreage estimate for that CRD within 2.42 percent of the USDA SRS-based estimate using a lower CRD inventory budget than for a simulated reference LACIE system. Factor of 2 or greater cost or precision improvements relative to the reference system were obtained.

Thomas, R. W.↗
NASA NTRS1978

Experimental and theoretical sound transmission

The capabilities of the Kansas University- Flight Research Center for investigating panel sound transmission as a step toward the reduction of interior noise in general aviation aircraft were discussed. Data obtained on panels with holes, on honeycomb panels, and on various panel treatments at normal incidence were documented. The design of equipment for panel transmission loss tests at nonnormal (slanted) sound incidence was described. A comprehensive theory-based prediction method was developed and shows good agreement with experimental observations of the stiffness controlled, the region, the resonance controlled region, and the mass-law region of panel vibration.

Roskam, J.↗
NASA NTRS1978

Solar heating and cooling system design and development

The progress of the program during the sixth program quarter is reported. The program calls for the development and delivery of eight prototype solar heating and cooling systems for installation and operational test. The William O'Brien single-family heating system was installed and is operational. The New Castle single-family heating residence is under construction. The Kansas University (KU) system is in the final design stages. The 25 ton cooling subsystem for KU is the debugging stage. Pressure drops that were greater than anticipated were encountered. The 3 ton simulation work is being finalized and the design parameters for the Rankine system were determined from simulation output.

Source record↗
NASA NTRS1977

Two phase sampling for wheat acreage estimation

A two-phase Landsat-based sample allocation and wheat proportion estimation method was developed. The technique employs manual, Landsat full frame-based wheat or cultivated land proportion estimates from a large number of segments comprising a first sample phase to optimally allocate a small phase-two sample of computer or manually processed segments. Proportion estimates from each phase are then linked by regression or probability proportional to estimated size estimators to provide wheat proportion estimates and standard errors by reporting unit. Application to the Kansas Southwest CRD (Crop Reporting District) for 1974 produced a wheat acreage estimate for that CRD within 2.42% of the USDA SRS-based estimate using a lower CRD inventory budget than for a simulated reference LACIE (Large Area Crop Inventory Experiment) system.

Thomas, R. W.↗
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 NTRS1977

Evaluating soil moisture and yield of winter wheat in the Great Plains using Landsat data

Locating areas where soil moisture is limiting to crop growth is important for estimating winter-wheat yields on a regional basis. In the 1975-76 growing season, we evaluated soil-moisture conditions and winter-wheat yields for a five-state region of the Great Plains using Landsat estimates of leaf area index (LAI) and an evapotranspiration (ET) model described by Kanemasu et al (1977). Because LAI was used as an input, the ET model responded to changes in crop growth. Estimated soil-water depletions were high for the Nebraska Panhandle, southwestern Kansas, southeastern Colorado, and the Texas Panhandle. Estimated yields in five-state region ranged from 1.0 to 2.9 metric ton/ha.

Heilman, J. L.↗