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<br />" -,". -. r\6 <br />'J ,} :.. .J lJ <br /> <br />process, because few landmarks were visible on the Landsat image in areas of <br />snow cover. ~ith the basin-boundary data, the areas of snow cover within the <br />western part of the Yampa River basin included in the Landsat image (fig. 2) <br />could be determined (fig. 16). The computer sums the pixels in each class <br />and calculates the area included in each class. The following arbitrary <br />snow-depth categories were determined for the western part of the basin <br />If ig. 16): <br /> <br />Category <br /> <br />CoLor code <br /> <br />Thick snow--------------------------- <br /> <br />Red. <br /> <br />Thin snow or partly shadowed snow---- <br /> <br />Yellow. <br /> <br />Very thin or shadowed snow----------- <br /> <br />Blue. <br /> <br />In summary, results from this preliminary investigation indicate that <br />Landsat imagery in some instances can provide timely information on areal <br />snow extent over large regions. Snow in open areas generally is easily <br />defined; however, snow under densely forested areas may be difficult to map <br />using Landsat imagery alone. Also, cloud cover can cause problems in mis- <br />classification when using digital-analysis techniques or when it obscures <br />surface areas preventing effective classification of those segments on the <br />image when using photographic-interpretation techniques. <br /> <br />Although digital analysis was investigated in this study, other studies <br />(Barnes and Bowley, 1974) indicate that, for many areas, mapping of snow-area <br />perimeters by manual (photographic-interpretation) means may provide the <br />desired information on areal snow extent while allowing subjective decisions <br />on cloud-obscured areas and snow contained under dense conifer stands. The <br />photographic-interpretation method generally would be available to more <br />agencies, because less sophisticated equipment is required. Also, <br />photographs of Landsat images can be obtained mOre rapidly subsequent to <br />acquisition than the computer-compatible digital tapes required for digital <br />analysis. <br /> <br />Turbidity Estimation <br /> <br />Expansion of surface-mining, construction, and dry1and-agricultural <br />activities is increasing the potential for greater turbidity and sediment <br />levels in the basin's streams. Aerial photography used in conjunction with a <br />few ground-control data points may prove to be a rapid alternative to time- <br />consuming extensive ground surveys required for assessing turbidity in <br />streams over large areas of the basin (Ritchie and others, 1976). <br />Photographic coverage of streams encompassing a large area could be obtained <br />in a very short time period relative to the time required for ground sampling <br />of the same areas with limited manpower. In theory, changes in turbidity in <br />a water body should cause changes in reflected energy recorded on <br />photographs. This change in reflectance is clearly visible on photographs <br />for extreme variations in turbidity. This investigation was designed to <br /> <br />33 <br />