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Remote sensing applications in agriculture and forestry. Applications of aerial photography and ERTS data to agricultural, forest and water resources management

Remote sensing techniques are being used in Minnesota to study: (1) forest disease detection and control; (2) water quality indicators; (3) forest vegetation classification and management; (4) detection of saline soils in the Red River Valley; (5) corn defoliation; and (6) alfalfa crop productivity. Results of progress, and plans for future work in these areas, are discussed.

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Utilizing ERTS-1 imagery for tectonic analysis through study of the Bighorn Mountains region

The author has identified the following significant results. Comparisons of imagery of three seasons, late summer-fall, winter, and spring indicate that for this region fall imagery is the best for overall geologic analysis. Winter scenes with light to moderate snow cover provide excellent topographic detail owing to snow enhancement, lower sun angle, and clarity of the atmosphere. Spring imagery has considerable reduction of tonal contrast owing to the low reflecting heavy green grass cover which subdues lithologic effects; heavy snow cover in the uplands masks topography. Mapping of geologic formations is impractical in most cases. Separation into tonal units can provide some general clues on structure. A given tonal unit can include parts of several geologic formations and different stratigraphic units can have the same tonal signature. Drainage patterns and anomalies provide the most consistent clues for detecting folds, monoclines, and homoclines. Vegetation only locally reflects lithology and structure. False color infrared 9 x 9 transparencies are the most valuable single imagery. Where these can be supplemented by U-2 color infrared for more detailed work, a tremendous amount of information is available. Adequately field checking such a large area just in one scene is the major logistic problem even in a fairly well known region.

Hoppin, R. A.↗

ERTS data user investigation to develop a multistage forest sampling inventory system

The author has identified the following significant results. A unique digital timber volume estimation system was developed for use with the MSS CCT tapes. The system was tested on a 64-square mile area in Northern California's Trinity Alps. The outcome of a systematic experiment, in which several possible combinations of bands 5 and 7 and a contrast measure were tried, showed that an estimated gain in precision of 50% can be obtained in a multistage sampling design. The difference between bands 5 and 7 proved to be of special importance for the estimation of biomass in the form of timber volume. In addition, an interpretation model for high flight U2 photographs was developed. A maximum multiple correlation coefficient of 0.74 was obtained for the regression model, explaining 55% of the variation in timber volume as estimated from aerial photos and ground measurments. An interpretation model for MSS color composites is in the testing stage.

Langley, P. G.↗

A Proposal for Precambrian Mineral Resource Evaluation in Minnesota Utilizing ERTS Imagery

An investigation was made of Minnesota. These rock units hold promise for potential mineral resources as do important ore deposits found in similar rocks to the north in Canada. The research planned involves the discrimination of rock types to show their aerial extent and an interpretation of the structural relationships between and within the various rock units.

Davidson, D., Jr.↗

ERTS-1 imagery interpretation techniques in the Tennessee Valley

The author has identified the following significant results. Significant findings are presented which demonstrate the feasibility of delineating major terrain features, land uses, and crop species through computerized analyses. Delineation of features are presently restricted to unsurveyed areas within the same scene as the test sites. Channel 6 appears to give or contain the most information for making feature separations of cropland, pasture, forest, and water.

Bodenheimer, R. E.↗