Search NASA⌕ Search

Engineering topics

Cipra, J. E.

Publications and source records attributed to Cipra, J. E..

9 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Identification and area estimation of agricultural crops by computer classification of Landsat MSS data

Landsat Multispectral Scanner (MSS) data covering a three-county area in northern Illinois were classified using computer-aided techniques as corn, soybeans, or 'other.' Recognition of test fields was 80% accurate. County estimates of the area of corn and soybeans agreed closely with those made by the USDA. Results of the use of a priori information in classification, techniques to produce unbiased area estimates, and the use of temporal and spatial features for classification are discussed. The extendability, variability, and size of training sets, wavelength band selection, and spectral characteristics of crops were also investigated.

Bauer, M. E.↗
NASA NTRS1973

An interpretation of a geologic map of Fannin County, Texas, prepared by ADP techniques from ERTS MSS data

Multispectral scanner data, collected by ERTS-1 from an area in northeast Texas underlain by structurally simple cretaceous sedimentary rocks, were analyzed using several automatic data processing techniques. Training areas for the computer analysis were selected in three ways using: (1) an unsupervised classifier, (2) the unsupervised classifier to further refine training areas, and (3) available ground information. The first two methods utilize the capability of the unsupervised classifier to the unsupervised classifier to group resolution elements with similar spectral properties. With the imagery produced by these procedures, several geologic features can be identified. The most easily recognizable features are streams and other water bodies. The approximate location of contacts between several rock units can be mapped.

Henderson, J. A., Jr.↗
NASA NTRS1973

Identification of agricultural crops by computer processing of ERTS MSS data

Quantitative evaluation of computer-processed ERTS MSS data classifications has shown that major crop species (corn and soybeans) can be accurately identified. The classifications of satellite data over a 2000 square mile area not only covered more than 100 times the area previously covered using aircraft, but also yielded improved results through the use of temporal and spatial data in addition to the spectral information. Furthermore, training sets could be extended over far larger areas than was ever possible with aircraft scanner data. And, preliminary comparisons of acreage estimates from ERTS data and ground-based systems agreed well. The results demonstrate the potential utility of this technology for obtaining crop production information.

Bauer, M. E.↗
NASA NTRS1972

Determining density of maize canopy. 3: Temporal considerations

Multispectral scanner data were collected in two flights over ground cover plots at an altitude of 305 m. Eight ground reflectance panels in close proximity to the ground cover plots were used to normalize the scanner data obtained on different dates. Separate prediction equations were obtained for both flight dates for all eleven reflective wavelength bands of the multispectral scanner. Ratios of normalized scanner data were related to leaf area index over time. Normalized scanner data were used to plot relative reflectance versus wavelength for the ground cover plots. Spectral response curves were similar to those for bare soil and green vegetation as determined by laboratory measurements. The spectral response curves from the normalized scanner data indicated that reflectance in the 0.72 to 1.3 micron wavelength range increased as leaf area index increased. A decrease in reflectance was observed in the 0.65 micron chlorophyll absorption band as leaf area index increased.

Stoner, E. R.↗
NASA NTRS1972

Application of multispectral remote sensing to soil survey research in Indiana

Computer-implemented mappings based on spectral properties of bare soil surfaces were compared with mapping units of interest to soil surveyors. Some soil types could be differentiated by their spectral properties. In other cases, soils with similar surface colors and textures could not be distinguished spectrally. The spectral maps seemed useful for delineating boundaries between soils in many cases.

Zachary, A. L.↗
NASA NTRS1972

Definition of spectrally separable classes for soil survey research

A procedure is outlined for defining spectral classes such that the differences between classes can be quantified. It also facilitates determination of a number of classes such that the classes are spectrally discriminable. This is accomplished by partitioning the data into many classes and then combining similar spectral classes on the basis of appropriate criteria. Multispectral data were collected over a 12-mile flightline in White County, Indiana, in connection with the 1971 Corn Blight Watch Experiment. Data were collected in May by the University of Michigan airborne scanning spectrometer at an altitude of 5000 feet. Spectral maps resulting from the analysis were compared to existing soil surveys of the National Cooperative Soil Survey. The method should help determine the extent to which spectral properties of soil surfaces can be associated with morphologic and topographic differences of interest to soil surveyors engaged in operational soil mapping.

Cipra, J. E.↗
NASA NTRS1971

Determining density of maize canopy. 2: Airborne multispectral scanner data

Multispectral scanner data were collected in two flights over a light colored soil background cover plot at an altitude of 305 m. Energy in eleven reflective wavelength band from 0.45 to 2.6 microns was recorded. Four growth stages of maize (Zea mays L.) gave a wide range of canopy densities for each flight date. Leaf area index measurements were taken from the twelve subplots and were used as a measure of canopy density. Ratio techniques were used to relate uncalibrated scanner response to leaf area index. The ratios of scanner data values for the 0.72 to 0.92 micron wavelength band over the 0.61 to 0.70 micron wavelength band were calculated for each plot. The ratios related very well to leaf area index for a given flight date. The results indicated that spectral data from maize canopies could be of value in determining canopy density.

Stoner, E. R.↗