Graduate Thesis Or Dissertation


Quantitative shape analysis of soil map delineations in Benton County, Oregon Public Deposited

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  • Soils are 3-dimensional bodies that make up natural landscapes. In addition to the morphological properties used to characterize soils, soil bodies also have the properties of size and shape. Soil maps are made in an effort to provide information on the spatial distribution of different kinds of soils. Soil mappers draw to scale, as accurately as possible, the sizes and shapes of the different kinds of soil bodies they observe in the landscape. Beyond that, however, very little quantitative information relative to size and shape is provided to soil map users. Quantitative shape characterization presents several opportunities to learn about soil genesis and soil interpretations for land use. Intriguing questions include "Why does a soil body have the particular shape it has?", "Does each map unit possess an intrinsic shape or range of shapes?", "Do existing map unit interpretations apply equally to delineations of different size and shape?", "How can shape data for individual delineations be aggregated into an overall description of soil patterns in different geographic areas?", "What effects do soil patterns have on land use?". None of these questions can be answered without first having an appropriate technique for characterizing the shapes of individual delineations. The objective of this research, therefore, was to examine several possible shape indexes and isolate those few which had the greatest utility for characterizing shape. These few were then used to examine shape distributions within a few selected map units and compare shapes between map units. Data were collected by digitizing 452 delineations sampled from 13 different kinds of soil bodies identified in the soil survey of Benton County. For each delineation, 43 potential indexes were calculated. These included primary measurements, such as area and perimeter, and figure attribute ratios such as Horton's form ratio, Miller's circularity index, Schumm's elongation ratio, and Fridland's coefficient of dissection. A convex hull was circumscribed around each delineation, and the same primary measurements and attribute ratios were calculated for the convex hull. Additional indexes were calculated by comparing values determined for a delineation and corresponding values for it's convex hull. One additional technique used was to fit each polygon and convex hull with a 22-sided vertex lag polygon. Calculation of distances between vertices of this polygon leads to the derivation of a vertex lag index of shape. Variations on the vertex lag theme provided several additional indexes. Correlation analysis showed that the set of 43 indexes was highly intercorrelated. In order to reduce this set to a smaller set of minimally correlated indexes, the entire data set was subjected to a factor analysis. The result was a set of three dominant factors, which together accounted for 86.1% of the total variance in the data set. Each factor was interpreted by considering the nature of the shape indexes that loaded heavily on it, and a single index was selected to represent each factor on the basis of maximum interpretability. The first factor was interpreted as a measure of the complexity, or irregularity, of a delineation. The vertex lag index for the delineation was selected as the best single index to represent this attribute of shape. The second factor included all of the primary measurements. Though not a measure of shape per se, primary measurement data were viewed as significant elements in the spatial description of soil map delineations. Polygon area was taken as the best index to represent the effects of primary measurements. The third factor was interpreted as a measure of form. In this case, Schumm's elongation ratio, as measured on the convex hull, was found to be the most interpretable index of form. These three attributes, size, form, and complexity, provided the best quantitative description of shape. The indexes that represent them were found to be minimally correlated and maximally interpretable. Each of the 13 kinds of soil bodies sampled was characterized in terms of the three aspects of shape using descriptive statistics and frequency histograms. Comparisons between samples were evaluated using the Mann-Whitney U test. The data suggested that delineations belonging to a single soil mapping unit do have distinctive distributions of size, form, and complexity. Shape differences between mapping units were most evident when comparing soils on different landforms, parent materials, and slope gradients.
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