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Mroczynski, R. P.

Publications and source records attributed to Mroczynski, R. P..

23 records · Page 2

The application of remote sensing technology to the solution of problems in the management of resources in Indiana

The author has identified the following significant results. The Lydich quadrangle area was successfully classified into seven cover types: (1) trees, (2) poorly drained soil and water, (3) pasture land, (4) well drained brown soil, (5) moderately well drained dark brown soil, (6) moderately drained soil, and (7) medium to poorly drained soil. Measurements of the percent of mapping unit represented by a named soil series range from 44 to 55 percent. If the class identified as vegetation is combined with the named unit, the range increases from 54 to 64 percent. The Xenia mapping unit was the only unit represented by less than 50 percent of the named unit. Results from the intensive tent moth study in Owensburg and Williams were interpreted from 70 mm color infrared and visually transferred to maps. A correction factor was necessary, because the date the sample photography was taken was a month later than the intensive site data (CF x acres defoliated in each level = expanded defoliated acres).

Weismiller, R. A.

Detection of southern corn leaf blight by remote sensing techniques.

Multispectral photographic and scanner data were collected over western Indiana in August and September 1970, to determine the detectability of southern corn leaf blight by remote sensing. Measurements were made at altitudes of 3000 to 7000 ft. Color, color IR, and multiband black and white photography were collected at altitudes from 3000 to 60,000 ft. Six levels of infection based on the amount of leaf damage were identified in the fields. Three levels of infection were detected with color IR photography by standard photo-interpretive techniques. Up to five levels of infection were distinguished by applying automatic pattern recognition techniques to the multispectral scanner data. The results illustrate the potential of remote sensing techniques in the detection of crop diseases.

Bauer, M. E.