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Morgenstern, J. P.

Publications and source records attributed to Morgenstern, J. P..

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Investigation of thematic mapper spatial, radiometric, and spectral resolution

Empirical evidence was provided for the definition of system specifications for the LANDSAT Follow-On Thematic Mapper (TM) and other future space Multispectral Sensor (MSS) systems. Specific sensor parameters addressed were spatial resolution, radiometric sensitivity, and to a lesser degree spectral bandwidths and locations. The study used selected available aircraft MSS data, characterized by narrow spectral bands, fine spatial resolution, and high signal-to-noise, as the basis for simulating spacecraft TM data of various spatial resolutions, radiometric sensitivities, and sets of spectral bands. The primary measure used in evaluating the effects of varying spatial and radiometric resolutions was agricultural crop mensuration accuracy using automatic (computer) information extraction techniques.

Morgenstern, J. P.↗
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 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 NTRS1975

Developing processing techniques for Skylab data

The author has identified the following significant results. The effects of misregistration and the scan-line-straightening algorithm on multispectral data were found to be: (1) there is greatly increased misregistration in scan-line-straightening data over conic data; (2) scanner caused misregistration between any pairs of channels may not be corrected for in scan-line-straightened data; and (3) this data will have few pure field center pixels than will conic data. A program SIMSIG was developed implementing the signature simulation model. Data processing stages of the experiment were carried out, and an analysis was made of the effects of spatial misregistration on field center classification accuracy. Fifteen signatures originally used for classifying the data were analyzed, showing the following breakdown: corn (4 signatures), trees (2), brush (1), grasses, weeds, etc. (5), bare soil (1), soybeans (1), and alfalfa (1).

Nalepka, R. F.↗