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Nalepka, R. F.

Publications and source records attributed to Nalepka, R. F..

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Investigation of thematic mapper spatial, radiometric, and spectral resolution

Low-altitude aircraft scanner data were employed in simulating the spatial resolution, radiometric sensitivity and spectral bandwidth parameters of the proposed Landsat Thematic Mapper (TM). The 30 to 40 m resolution of the TM was found to provide significant improvement over current Landsat resolution (50 to 60 m) in crop mensuration, especially for Western Europe and India where field sizes average from one to four hectares. In terms of radiometric sensitivity, a noise equivalent reflectance value of 0.5% was held to be necessary for discrimination of spectrally similar data; in addition, all of the six proposed TM spectral bands were shown to be necessary for monitoring at some point during the growing season.

Morgenstern, J. P.↗
NASA NTRS1977

Wheat yield forecasts using Landsat data

Leaf area index and percentage of vegetative cover, two indices of crop yield developed from Landsat multispectral scanning data, are discussed. Studies demonstrate that the Landsat indicators may be as highly correlated with winter wheat yield as estimates based on traditional field sampling methods; in addition, the Landsat indicators may account for variations in individual field yield which are not explainable by meteorological data. A simple technique employing early-season Landsat data to make wheat yield predictions is also considered.

Colwell, J. E.↗
NASA NTRS1976

Wheat productivity estimates using LANDSAT data

The author has identified the following significant results. Objective measurements of percent green wheat cover on May 21 were significantly correlated with yield, as were measurements of green LAI and LANDSAT data. Three data sets from the Finney test site were analyzed from LANDSAT passes on 22 November 1974, 15 April 1975, and 21 May 1975. After mean signal values in each band were computed for each sufficiently large wheat field, the mean values were correlated with the farmer estimates of wheat grain yield in order to assess relative information content. It is clear that the single best spectral temporal band for predicting yield is the 15 April red band (0.6-0.7 microns, band 5), with the 15 April green band (0.5-0.6 microns, band 4) a close second.

Nalepka, R. F.↗
NASA NTRS1976

Forest Classification Accuracy as Influenced by Multispectral Scanner Spatial Resolution

The author has identified the following significant results. A supervised classification within two separate ground areas of the Sam Houston National Forest was carried out for two sq meters spatial resolution MSS data. Data were progressively coarsened to simulate five additional cases of spatial resolution ranging up to 64 sq meters. Similar processing and analysis of all spatial resolutions enabled evaluations of the effect of spatial resolution on classification accuracy for various levels of detail and the effects on area proportion estimation for very general forest features. For very coarse resolutions, a subset of spectral channels which simulated the proposed thematic mapper channels was used to study classification accuracy.

Nalepka, R. F.↗
NASA NTRS1976

Investigation of spatial misregistration effects in multispectral scanner data

The author has identified the following significant results. A model for estimating the expected proportion of multiclass pixels in a scene was generalized and extended to include misregistration effects. Another substantial effort was the development of a simulation model to generate signatures to represent the distributions of signals from misregistered multiclass pixels, based on single class signatures. Spatial misregistration causes an increase in the proportion of multiclass pixels in a scene and a decorrelation between signals in misregistered data channels. The multiclass pixel proportion estimation model indicated that this proportion is strongly dependent on the pixel perimeter and on the ratio of the total perimeter of the fields in the scene to the area of the scene. Test results indicated that expected values computed with this model were similar to empirical measurements made of this proportion in four LACIE data segments.

Nalepka, R. F.↗
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

System for analysis of LANDSAT agricultural data: Automatic computer-assisted proportion estimation of local areas

The author has identified the following significant results. A conceptual man machine system framework was created for a large scale agricultural remote sensing system. The system is based on and can grow out of the local recognition mode of LACIE, through a gradual transition wherein computer support functions supplement and replace AI functions. Local proportion estimation functions are broken into two broad classes: (1) organization of the data within the sample segment; and (2) identification of the fields or groups of fields in the sample segment.

Nalepka, R. F.↗
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 NTRS1976

Investigation of LANDSAT follow-on thematic mapper spatial, radiometric and spectral resolution

The author has identified the following significant results. Fine resolution M7 multispectral scanner data collected during the Corn Blight Watch Experiment in 1971 served as the basis for this study. Different locations and times of year were studied. Definite improvement using 30-40 meter spatial resolution over present LANDSAT 1 resolution and over 50-60 meter resolution was observed, using crop area mensuration as the measure. Simulation studies carried out to extrapolate the empirical results to a range of field size distributions confirmed this effect, showing the improvement to be most pronounced for field sizes of 1-4 hectares. Radiometric sensitivity study showed significant degradation of crop classification accuracy immediately upon relaxation from the nominally specified values of 0.5% noise equivalent reflectance. This was especially the case for data which were spectrally similar such as that collected early in the growing season and also when attempting to accomplish crop stress detection.

Nalepka, R. F.↗
NASA NTRS1976

Economic evaluation of crop acreage estimation by multispectral remote sensing

The author has identified the following significant results. Photointerpretation of S190A and S190B imagery showed significantly better resolution with the S190B system. A small tendancy to underestimate acreage was observed. This averaged 6 percent and varied with field size. The S190B system had adequate resolution for acreage measurement but the color film did not provide adequate contrast to allow detailed classification of ground cover from imagery of a single date. In total 78 percent of the fields were correctly classified but with 56 percent correct for the major crop, corn.

Manderscheid, L. V.↗
NASA NTRS1976

PROCAMS - A second generation multispectral-multitemporal data processing system for agricultural mensuration

PROCAMS (Prototype Classification and Mensuration System) has been designed for the classification and mensuration of agricultural crops (specifically small grains including wheat, rye, oats, and barley) through the use of data provided by Landsat. The system includes signature extension as a major feature and incorporates multitemporal as well as early season unitemporal approaches for using multiple training sites. Also addressed are partial cloud cover and cloud shadows, bad data points and lines, as well as changing sun angle and atmospheric state variations.

Erickson, J. D.↗
NASA NTRS1976

Effects of misregistration on multispectral recognition

Spatial misregistration of multispectral scanner data occurs when two or more spectral band signals supposedly representing the same location are in fact data values generated from two or more overlapping or entirely different ground locations. A study was performed at the Environmental Research Institute of Michigan to determine what effect spatial misregistration may have on the accuracy of recognition processing of agriculturally oriented scanner data. It was found that misregistration severely reduces the availability of field center pixels and introduces significant errors in the classification accuracy and correct proportion estimation of a scene containing an inflated number of mixture pixels.

Cicone, R. C.↗
NASA NTRS1975

Wheat Productivity Estimates Using LANDSAT Data

The author has identified the following significant results. The biological leaf area index data show that there can be large variations in field vegetative condition from point to point. This is especially true in flood-irrigated fields, in which plant density (and development) varies drastically between rows that are in channels vs. those that are in raised areas. Considerable care must be used in interpreting the significance of isolated leaf area index measurements made from a single wheat row.

Nalepka, R. F.↗