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Thesis - University Access Only
Master of Science (MS)
H. L. Hutcheson
Double sampling procedures (visual and spectral reflectance estimate versus actual biomass) were used to monitor the production and utilization of vegetation on two different-range sites in three range condition classes during the growing seasons of 1986 and 1987. Field data were collected from six experimental pastures at the South Dakota State University Cottonwood Range and Livestock Research Station. A Landsat ground truth radiometer, a hand-held, four channel radiometer, was used to record spectral reflectance data. Three sampling periods (early, mid and late season) were selected to collect vegetation and spectral reflectance data. A multiple regression analysis was made to investigate the relationships between vegetation variables and spectral reflectance. Several multiple regression models adjusted for incoming sun angle and percent bare ground were also tested. Statistical results indicated that the variation of rangeland vegetation depended upon range condition, range site and growing season. Forage utilization was influenced by the same factors. A relatively strong relationship was found between green biomass and spectral reflectance value with adjustment. The highest coefficient of determination for total green biomass was r2 = 0.83. There seemed to be a potential to predict western wheatgrass up to 50% of accuracy in mid-June. Results also indicated that adjustment for sun angle improve the prediction of vegetation biomass. Soil moisture was found to have a great effect on spectral reflectance values. To establish signatures with single plant species was very difficult because of the close spectral reflectance values of individual plant species on rangeland.
Library of Congress Subject Headings
Rangelands -- South Dakota
Vegetation surveys -- South Dakota
Range management -- South Dakota
Number of Pages
South Dakota State University
Kanoute, Assetou, "Use of a Landsat Ground Truth Radiometer to Estimate Rangeland Vegetation in West Central South Dakota" (1989). Electronic Theses and Dissertations. 4587.