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Bauer, M. E.

Publications and source records attributed to Bauer, M. E..

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Agricultural scene understanding

The author has identified the following significant results. The LACIE field measurement data were radiometrically calibrated. Calibration enabled valid comparisons of measurements from different dates, sensors, and/or locations. Thermal band canopy results included: (1) Wind velocity had a significant influence on the overhead radiance temperature and the effect was quantized. Biomass and soil temperatures, temperature gradient, and canopy geometry were altered. (2) Temperature gradient was a function of wind velocity. (3) Temperature gradient of the wheat canopy was relatively constant during the day. (4) The laser technique provided good quality geometric characterization.

Landgrebe, D. A.↗
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 NTRS1977

A laser technique for characterizing the geometry of plant canopies

The interception of solar power by the canopy is investigated as a function of solar zenith angle (time), component of the canopy, and depth into the canopy. The projected foliage area, cumulative leaf area, and view factors within the canopy are examined as a function of the same parameters. Two systems are proposed that are capable of describing the geometrical aspects of a vegetative canopy and of operation in an automatic mode. Either system would provide sufficient data to yield a numerical map of the foliage area in the canopy. Both systems would involve the collection of large data sets in a short time period using minimal manpower.

Vanderbilt, V. C.↗
NASA NTRS1977

Crop identification and area estimation by computer-aided analysis of Landsat data

This report describes the results of a study involving the use of computer-aided analysis techniques applied to Landsat MSS data for identification and area estimation of winter wheat in Kansas and corn and soybeans in Indiana. Key elements of the approach included use of aerial photography for classifier training, stratification of Landsat data and extension of training statistics to areas without training data, and classification of a systematic sample of pixels from each county. Major results and conclusions are: (1) Landsat data was adequate for accurate identification and area estimation of winter wheat in Kansas, but corn and soybean estimates for Indiana were less accurate; (2) computer-aided analysis techniques can be effectively used to extract crop identification information from Landsat MSS data, and (3) systematic sampling of entire counties made possible by computer classification methods resulted in very precise area estimates at county as well as district and state levels.

Bauer, M. E.↗
NASA NTRS1976

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

The author has identified the following significant results. The comparison between the acreage estimates for the April LANDSAT data and the USDA Statistical Reporting Service estimates show no significant difference for the south central crop reporting district in Kansas. A paired-t test with an alpha = .05 was run comparing the percentages of wheat in each county. The results of their test showed no significant difference between the two estimates for wheat.

Bauer, M. E.↗
NASA NTRS1976

Results from the Crop Identification Technology Assessment for Remote Sensing (CITARS) project

The author has identified the following significant results. It was found that several factors had a significant effect on crop identification performance: (1) crop maturity and site characteristics, (2) which of several different single date automatic data processing procedures was used for local recognition, (3) nonlocal recognition, both with and without preprocessing for the extension of recognition signatures, and (4) use of multidate data. It also was found that classification accuracy for field center pixels was not a reliable indicator of proportion estimation performance for whole areas, that bias was present in proportion estimates, and that training data and procedures strongly influenced crop identification performance.

Bauer, M. E.↗
NASA NTRS1976

Stratification of Landsat data by clustering

Full realization of the potential advantages of the synoptic coverage provided by Landsat will require the development and use of data analysis techniques which take into account the large variation and diversity of patterns found over many Landsat scenes. Stratification of the scene into units which are internally homogeneous is recommended as a first step in the analysis of data for whole or multiple frames of Landsat data. The use of clustering as an objective and efficient method of dividing scenes into areas which are spectrally similar (strata) is discussed and initial results, including classification performances and comparisons of spectral strata with major physical factors, are presented.

Bauer, M. E.↗
NASA NTRS1975

Crop identification technology assessment for remote sensing (CITARS). Volume 10: Interpretation of results

The CITARS was an experiment designed to quantitatively evaluate crop identification performance for corn and soybeans in various environments using a well-defined set of automatic data processing (ADP) techniques. Each technique was applied to data acquired to recognize and estimate proportions of corn and soybeans. The CITARS documentation summarizes, interprets, and discusses the crop identification performances obtained using (1) different ADP procedures; (2) a linear versus a quadratic classifier; (3) prior probability information derived from historic data; (4) local versus nonlocal recognition training statistics and the associated use of preprocessing; (5) multitemporal data; (6) classification bias and mixed pixels in proportion estimation; and (7) data with differnt site characteristics, including crop, soil, atmospheric effects, and stages of crop maturity.

Bizzell, R. M.↗
NASA NTRS1975

Crop identification technology assessment for remote sensing (CITARS). Volume 6: Data processing at the laboratory for applications of remote sensing

The results of classifications and experiments for the crop identification technology assessment for remote sensing are summarized. Using two analysis procedures, 15 data sets were classified. One procedure used class weights while the other assumed equal probabilities of occurrence for all classes. Additionally, 20 data sets were classified using training statistics from another segment or date. The classification and proportion estimation results of the local and nonlocal classifications are reported. Data also describe several other experiments to provide additional understanding of the results of the crop identification technology assessment for remote sensing. These experiments investigated alternative analysis procedures, training set selection and size, effects of multitemporal registration, spectral discriminability of corn, soybeans, and other, and analyses of aircraft multispectral data.

Bauer, M. E.↗
NASA NTRS1975

Crop Identification Technology Assessment for Remote Sensing (CITARS)

The results of classifications and experiments performed for the Crop Identification Technology Assessment for Remote Sensing (CITARS) project are summarized. Fifteen data sets were classified using two analysis procedures. One procedure used class weights while the other assumed equal probabilities of occurrence for all classes. In addition, 20 data sets were classified using training statistics from another segment or date. The results of both the local and non-local classifications in terms of classification and proportion estimation are presented. Several additional experiments are described which were performed to provide additional understanding of the CITARS results. These experiments investigated alternative analysis procedures, training set selection and size, effects of multitemporal registration, the spectral discriminability of corn, soybeans, and other, and analysis of aircraft multispectral data.

Bauer, M. E.↗
NASA NTRS1975

The use of ERTS-1 multispectral imagery for crop identification in a semi-arid climate

Crop identification using multispectral satellite imagery and multivariate pattern recognition was used to identify wheat accurately in Greeley County, Kansas. A classification accuracy of 97 percent was found for wheat and the wheat estimate in hectares was within 5 percent of the USDA's Statistical Reporting Service estimate for 1973. The multispectral response of cotton and sorghum in Texas was not unique enough to distinguish between them nor to separate them from other cultivated crops.

Stockton, J. G.↗
NASA NTRS1975

Results from the crop identification technology assessment for remote sensing /CITARS/ project

The CITARS (Crop Identification Technology Assessment for Remote Sensing) task design, objectives, and results are reviewed along with relevant conclusions and recommendations. The principal assessment concern crop identification performance for corn and soybeans in six sites in Illinois and Indiana. Use of quantitative measures of classification performance and statistical evaluations of the results have been important parts of the technology assessment. Relation of crop and sensor characteristics is discussed. Factors affecting crop identification performance are identified as crop maturity and site characteristics, type of single-date automatic data processing procedure used for local recognition, nonlocal recognition with and without processing for extension of recognition signatures, and use of multidate or multitemporal data. In particular, the probability of correct classification of field center pixels is not well correlated and thus is not a reliable indicator of proportion estimation performance.

Bizzell, R. M.↗
NASA NTRS1974

First results from the crop identification technology assessment for remote sensing /CITARS/

The CITARS task design, including objectives, analysis methodology and experimental procedures, is described and first results from this effort are presented. The extensive ground truth data set acquired for the CITARS task is described and discussed in some detail. Results of the accuracy tests for the photo interpretative CITARS ground truth are given. Results of the assessment of the ERTS MSS data for cloud cover and electronic quality are presented. Some results of the geometric correction and registration of the time sequential CITARS ERTS data are given. Finally, the field boundary selection problem is addressed and the results of the use of new technology for boundary selection are presented.

Hall, F. G.↗