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<br />20. Soil strength, however, is quite variable and changes with changes <br />in water content of the soil. Thus, the cone index values of all soils not <br />continually saturated (such as those on the bottoms of nonperennially wet <br />gaps) change with seasonal fluctuations of moisture content. TIley change <br />with any moisture. conte.nt change., of course, and so react to rainfall at <br />any time of the year. However, the only available data were the cone index <br />values obtained at each field site and these represented the condition only <br />at the moment of measurement. While there are methods of relating cone index <br />value, soil type (USeS or USDA), and moisture content, they are not very <br />reliable and, at best, depend upon highly accurate determinations of soil <br />moisture. Since soil moisture could not be reliably estimated, it was de- <br />cided to record the measured cone index values and not to attempt to pre- <br />dict seasonal values. There were, of course, neither soil type nor cone <br />index data for the literature sites and, indeed, no reliable method for <br />estimating them. <br /> <br />21. The cone index values were problems only for the top-of-bank <br />positions; soils were assumed to be perennially saturated in the bottoms <br />of wet gaps as well as the water level locations, and therefore the <br />measured values at those points remained valid for all seasons. <br /> <br />Areal distribution of the factors <br /> <br />22. The areal distributions of the factors were mapped by photo <br />interpretation. First, the locations of the sample sites were plotted on <br />the topographic maps and aerial photography, and all of the gap profiles <br />were drawn to a common scale and grouped into classes on the basis of <br />visual similari ty to the "type classes." Since the sample si tes were <br />deliberately scattered across the entire study area, this provided a rea- <br />sonably uniform coverage of all variations in the region. <br /> <br />23. Next, every gap which could be recognized on the aerial photog- <br />raphy was traced and classified according to the factor classes defined <br />in Table 2. This process involved the development of a set of recognition <br />criteria for each factor or factor set, using the sample sites as ground <br />truth. To the extent possible, each factor was mapped individually, but <br />there were exceptions. For example, all vegetation factors were mapped <br />simultaneously so that in that instance the gap segments were assigned a <br />two-part code, one digit of which represented the stem diameter/stem <br />spacing category, and the other the vegetation band width. <br /> <br />24. <br />array of <br /> <br />Upon completion of the photo interpretation, <br />planimetrically accurate factor maps covering <br /> <br />the product was an <br />the area of interest. <br /> <br />19 <br />