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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 379 records · Page 21
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NASA NTRS1977

Further tests of the suits reflectance model

Experiments performed by stacking cotton leaves in the port of a spectroradiometer indicate that single leaf reflectance ceases to vary with more than two leaves in the visible region and eight leaves in the infrared region. Chance and LeMaster have shown that the Suits spectral reflectance model predicts an asymptotic dependence of crop reflectance on leaf area index (LAI) with crop reflectance static for leaf area indices in excess of two in the visible regions and six in the infrared regions of the spectrum. These results are experimentally verified in the field for Milam and Penjamo spring wheat, and a theoretical relationship is discussed that relates crop reflectance at 650 nm to crop canopy LAI. Experimental data are given that relate observer zenith angle to crop reflectance for wheat. The Suits reflectance model calculations for wheat fail to agree with this data.

Lemaster, E. W.↗
NASA NTRS1977

Pattern recognition of Landsat data based upon temporal trend analysis

The Delta Classifier defined as an agricultural crop classification scheme employing a temporal trend procedure is applied to more than 100 different Landsat data sets collected during the 1974-1975 growing season throughout the major wheat-producing regions of the United States. The classification approach stresses examination of temporal trends of the Landsat mean vectors of crops in the absence of corresponding ground truth information. It is shown that the resulting classifications compare favorably to ground truth estimates for wheat proportion in those cases where ground truth is available, and that the temporal trend procedure yields estimates of the wheat proportion that are comparable to the best results from maximum likelihood classification with photointerpreter-defined training fields.

Engvall, J. L.↗
NASA NTRS1978

LACIE: An experiment in global crop forecasting

The author has identified the following significant results. Both the accuracy and efficiency with which LACIE crop survey estimates were made have shown significant improvement in three years. In the U.S. and U.S.S.R. winter wheat regions, the original accuracy goals were met or exceeded, with 90/90 estimates achieved in the United States 1.5 to 2 months before harvest. Additionally, all available accuracy parameters indicate 90/90 estimates for the U.S.S.R. total crop. Key technology problems were identified during phase 2 with spring wheat in the United States and Canada which prevented the attainment of 90/90 accuracies in these regions. Technology solutions developed and tested in phase 3 partly resolved these issues with a significant improvement realized in the accuracy of the spring wheat area estimates.

Macdonald, R. B.↗
NASA NTRS1976

Large Area Crop Inventory Experiment (LACIE). Accuracy assessment report phase 1A, November - December 1974

The author has identified the following significant results. Results of the accuracy assessment activity for Phase IA of LACIE indicated that (1) The 90/90 criteria could be reached if the degree of accuracy of the LACIE performance in Kansas could be equaled in other areas. (2) The classification of both wheat and nonwheat fields was significantly accurate for the three ITS segments analyzed. The wheat field classification accuracy varied for the segments. However, this was not so with respect to nonwheat fields. (3) Biophase as well as its interaction with segment location turned out to be an important factor for the classification performance. Analyst interpretation of segments for training the classifier was a significant error-contributing factor in the estimation of wheat acreage at both the field and the segment levels.

Source record↗
NASA NTRS1979

A study of the tolerance block approach to special stratification

The author has identified the following significant results. Twelve winter wheat LACIE segments in Kansas were used to compare the performance of three clustering methods: (1) BCLUST, which uses a spectral distance function to accumulate clusters; (2) blocks-alone, which divides spectral space into equally populated blocks; and (3) block-seeds, which uses spectral means of blocks-alone as seeds for accumulating distance-type clusters. Both BCLUST and block-seeds performed equally well and outperformed blocks-alone significantly. Their average variance ratio of about 0.5 showed imperfect separation of wheat from non-wheat. This result points to the need to explore the achievable crop separability in the spectral/temporal domain, and suggest evaluating derived features rather than data channels as a means to achieve purer spectral strata.

Richardson, W.↗
NASA NTRS1979

LACIE sampling design

The sampling design in LACIE consisted of two major components, one for wheat acreage estimation and one for wheat yield prediction. The acreage design was basically a classical survey for which the sampling unit was a 5- by 6-nautical mile segment; however, there were complications caused by measurement errors and loss of data. Yield was predicted by sampling meteorological data from weather stations within a region and then using those data as input to previously fitted regression equations. Wheat production was not estimated directly, but was computed by multiplying yield and acreage estimates. The allocation of samples to countries is discussed as well as the allocation and selection of segments in strata/substrata.

Feiveson, A. H.↗
NASA NTRS1979

LACIE large area acreage estimation

A sample wheat acreage for a large area is obtained by multiplying its small grains acreage estimate as computed by the classification and mensuration subsystem by the best available ratio of wheat to small grains acreages obtained from historical data. In the United States, as in other countries with detailed historical data, an additional level of aggregation was required because sample allocation was made at the substratum level. The essential features of the estimation procedure for LACIE countries are included along with procedures for estimating wheat acreage in the United States.

Chhikara, R. S.↗
NASA NTRS1979

Development of LACIE CCEA-1 weather/wheat yield models

The advantages and disadvantages of the casual (phenological, dynamic, physiological), statistical regression, and analog approaches to modeling for grain yield are examined. Given LACIE's primary goal of estimating wheat production for the large areas of eight major wheat-growing regions, the statistical regression approach of correlating historical yield and climate data offered the Center for Climatic and Environmental Assessment the greatest potential return within the constraints of time and data sources. The basic equation for the first generation wheat-yield model is given. Topics discussed include truncation, trend variable, selection of weather variables, episodic events, strata selection, operational data flow, weighting, and model results.

Strommen, N. D.↗
NASA NTRS1979

Accuracy and performance of LACIE crop development models

Of the three principal phenological crop calendar models evaluated for LACIE, Robertson's triquadratic model which predicts the rate of progression of wheat through its biological development, was selected. Daily maximum and minimum temperatures and day length are the input variables, and the principal output is a daily increment of development through six physiological growth stages. Because wheat corresponds differently to the environment during each growth stage, five different equations are required. The estimated and observed crop development data were compared in order to establish a measure of confidence in the model and to identify consistent discrepancies that would adversely affect LACIE operation. Although the model provided reliable estimates for various wheat growing regions of the world, it was found that there are still areas in need of further model improvement or development.

Woolley, S. K.↗
NASA NTRS1979

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

The author has identified the following significant results. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plans. Evaluation of four sampling schemes involving different numbers of samples and different size sampling units shows that the precision of the wheat 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 size unit.

Hixson, M.↗
NASA NTRS1979

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

The objective of this investigation was to evaluate the effect of sampling on the accuracy (precision and bias) of crop area estimates made from classifications of Landsat MSS data. Full-frame classifications of wheat and non-wheat for eighty counties in Kansas were repetitively sampled to simulate alternative sampling plans. 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.↗
NASA NTRS1980

Relationship of spectral data to grain yield variation

Two-band hand-held radiometer data from a winter wheat field, collected on 21 dates during the spring growing season, were correlated with within-field final grain yield. Significant linear relationships were found between various combinations of the red and photographic infrared radiance data collected and the grain yield. The spectral data explained about 64 percent of the within-field grain yield variation. This variation in grain yield could not be explained using meteorological data as these were similar for all areas of the wheat field. Most importantly, data collected early in the spring were highly correlated with grain yield, a five-week time window existed from stem elongation through anthesis in which the spectral data were most highly correlated with grain yield, and manifestations of wheat canopy water stress were readily apparent in the spectral data.

Tucker, C. J.↗
NASA NTRS1980

Dryland pasture and crop conditions as seen by HCMM

Ground truth, aircraft, and satellite data were examined in order to: (1) assess the capability for determining wheat and pasture canopy temperatures in a dryland farming region from HCMM data; (2) assess the capability for determining soil moisture from HCMM data in dryland crops (winter wheat) from adjacent range lands; and (3) determine the relationship of HCMM-derived soil moisture and canopy temperature values with the condition of winter wheat and dryland farming areas during the principal growth stages. The IR data were screened to include areas having greater than 60% pasture and surface temperatures were recalculated using the atmospheric correction factor calculated by the modified RADTRA model, and the July 29, 1978 IR data were analyzed. Screening the IR data improved the relationship for July 24/July 13 and October 7/August 31 temperature/API relationship. However the coefficient of determination was not improved in the July 29/July 13 relationship.

Rosenthal, W. D.↗
NASA NTRS1981

Correlation of spacecraft passive microwave system data with soil moisture indices (API)

Electrical scanning microwave radiometer brightness temperature, meteorological data, climatological data, and winter wheat crop information were used to estimate that soil moisture content in the Great Plains region. Results over the predominant winter wheat areas indicate that the best potential to infer soil moisture occurs during fall and spring. These periods encompass the growth stages when soil moisture is most important to winter wheat yield. Other significant results are reported.

Blanchard, B. J.↗
NASA NTRS1982

Selection of USSR foreign similarity regions

The similarity regions in the United States and Canada were selected to parallel the conditions that affect labeling and classification accuracies in the U.S.S.R. indicator regions. In addition to climate, a significant condition that affects labeling and classification accuracies in the U.S.S.R. is the proportion of barley and wheat grown in a given region (based on sown areas). The following regions in the United States and Canada were determined to be similar to the U.S.S.R. indicator regions: (1) Montana agrophysical unit (APU) 104 corresponds to the Belorussia high barley region; (2) North Dakota and Minnesota APU 20 and secondary region southern Manitoba and Saskatchewan correspond to the Ural RSFSR barley and spring wheat region; (3) Montana APU 23 corresponds to he North Caucasus barley and winter wheat region. Selection criteria included climates, crop type, crop distribution, growth cycles, field sizes, and field shapes.

Disler, J. M.↗
NASA NTRS1979

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.↗
NASA NTRS1984

Measurement and Modeling of the Optical Scattering Properties of Crop Canopies

Progress and results in the measurement and scattering properties of crop canopies was examined. The following accomplishments are reported: (1) analysis of inhouse polarization, Sun/view angle data set of wheat was completed; (2) polarization photometer instrument system was completed; (3) light polarization properties (measured with polarization photometer) of individual plant leaves initiated, and twenty two species/varieties were measured before frost; (4) light polarizing properties of both moisture-stressed corn leaves and diseased wheat leaves were measured; (5) Sun/view angle data and ancillary data were acquired on two wheat canopies on two dates and on one sorghum canopy on two adjacent days.

Vanderbilt, V. C.↗
NASA NTRS1983

Shuttle Imaging Radar-A (SIR-A) data as a complement to Landsat Multispectral Scanner (MSS) data

Principal components analysis and supervised classifications were performed on two dates of Landsat multispectral scanner (MSS) data registered to one date of Shuttle Imaging Radar-A (SIR-A) data in a wheat-growing area of New South Wales, Australia. The purpose was to evaluate SIR-A data as a complement to Landsat MSS data in an agricultural environment. The SIR-A data was filtered using a 7 x 7 pixel moving window median filter. Principal components analysis indicated the SIR-A data were discriminating between trees and agricultural fields. Supervised classifications using wheat, pasture, trees, and idle classes resulted in increased accuracies for wheat and pasture and slightly decreased accuracies for trees and idle for the Landsat MSS/SIR-A registered data sets over the Landsat MSS alone. Overall classification accuracies were unchanged for one date and substantially increased for the other when the SIR-A data were added to the Landsat MSS data.

Henninger, D. L.↗